Service Manager 9.6x Deployment Sizing Guide Service Manager 9.6x Deployment Sizing Guide Page 7 Service Manager sizing questions The following list of questions is designed to gather

Service Manager 9.6x Deployment Sizing Guide Page 1

Technical white paper

Service Manager 9.6x Deployment Sizing Guide

Software version: 9.6x

Document release date: February 2020

Contents Introduction .............................................................................................................................................................................................. 6

Terminology ............................................................................................................................................................................................ 6

Service Manager sizing questions .......................................................................................................................................................... 7

Service Manager sample deployment..................................................................................................................................................... 9

Prepare for sizing ................................................................................................................................................................................... 10

Hardware – size for 50 users ................................................................................................................................................................. 11

Service Manager deployment sizing ..................................................................................................................................................... 12

Deployment mode ................................................................................................................................................................................ 12

Service Manager application server and load balancer ......................................................................................................................................... 12

Service Manager web tier ............................................................................................................................................................................................. 13

Service Manager Knowledge Management .............................................................................................................................................................. 13

Minimum required reference configurations ......................................................................................................................................... 13

Service Manager application server ........................................................................................................................................................................... 13

Service Manager web tier ............................................................................................................................................................................................. 15

Service Manager load balancer server ...................................................................................................................................................................... 15

Service Manager Knowledge Management .............................................................................................................................................................. 15

Service Manager virtualization .................................................................................................................................................................................... 16

Service Manager Mobility deployment sizing ...................................................................................................................................... 16

Deployment mode ................................................................................................................................................................................ 16


Service Manager Service Request Catalog deployment sizing .......................................................................................................... 18

Deployment mode ................................................................................................................................................................................ 18


Service Manager Smart Analytics deployment sizing ......................................................................................................................... 20

Deployment mode ................................................................................................................................................................................ 20


Service Manager Collaboration deployment sizing ............................................................................................................................. 27


Deployment mode ................................................................................................................................................................................ 27


Service Manager Service Portal deployment sizing ............................................................................................................................ 28

Deployment mode ................................................................................................................................................................................ 28


Service Manager Smart Email deployment sizing ............................................................................................................................... 31

Deployment mode ................................................................................................................................................................................ 31


Service Manager IdM deployment sizing.............................................................................................................................................. 33

Deployment mode ................................................................................................................................................................................ 33


Service Manager on AWS deployment sizing ...................................................................................................................................... 34

Deployment mode ................................................................................................................................................................................ 34

Reference configuration for 1500 concurrent users .............................................................................................................................. 35

Webtier ............................................................................................................................................................................................................................. 35

Server primary host ....................................................................................................................................................................................................... 35

Server secondary hosts ................................................................................................................................................................................................ 35

RDS Database ................................................................................................................................................................................................................. 35

Service Manager on Azure deployment sizing .................................................................................................................................... 36

Deployment mode ................................................................................................................................................................................ 36

Reference configuration for 2000 concurrent users .............................................................................................................................. 37

Webtier ............................................................................................................................................................................................................................. 37

Server primary host ....................................................................................................................................................................................................... 37

Server secondary hosts ................................................................................................................................................................................................ 37

Database .......................................................................................................................................................................................................................... 37

Rules of thumb ....................................................................................................................................................................................... 38

Service Manager server (servlet container) .......................................................................................................................................... 38

Service Manager web tier and Mobility ................................................................................................................................................. 38

Service Manager software load balancer ............................................................................................................................................. 38

Service Manager RDBMS server ......................................................................................................................................................... 39

Service Manager virtualized environment (VMware) ............................................................................................................................ 39

Service Manager Service Request Catalog .......................................................................................................................................... 39

Service Manager Service Portal ........................................................................................................................................................... 40

Service Manager Collaboration ............................................................................................................................................................ 41

Service Manager Smart Email .............................................................................................................................................................. 41

Service Manager Smart Analytics ........................................................................................................................................................ 41

Service Manager Smart Analytics server .................................................................................................................................................................. 41

Service Manager Smart Analytics image server ...................................................................................................................................................... 43

Service Manager Knowledge Management search engine .................................................................................................................. 43

Service Manager - small environment deployment ............................................................................................................................... 43

Appendix A: Service Manager 9.64 CHO – Oracle 3000 user example .............................................................................................. 45

Introduction ........................................................................................................................................................................................... 45

Deployment diagram ............................................................................................................................................................................ 45

Hardware .............................................................................................................................................................................................. 45

Software ............................................................................................................................................................................................... 45


Performance success criteria ............................................................................................................................................................... 46

Average response times ....................................................................................................................................................................... 46

Appendix B: [AWS] Service Manager 9.63 CHO – PG 1500 user example ........................................................................................ 53

Introduction ........................................................................................................................................................................................... 53


Hardware .............................................................................................................................................................................................. 53

Software ............................................................................................................................................................................................... 53



Appendix C: Service Manager 9.63 CHO – Oracle 3000 user example .............................................................................................. 60

Introduction ........................................................................................................................................................................................... 60


Hardware .............................................................................................................................................................................................. 61

Software ............................................................................................................................................................................................... 61



Appendix D: Service Manager 9.62 CHO – Oracle 2500 user example .............................................................................................. 68

Introduction ........................................................................................................................................................................................... 68


Hardware .............................................................................................................................................................................................. 69

Software ............................................................................................................................................................................................... 69



Appendix E: Service Manager 9.62 CHO – PostgreSQL 1500 user example ..................................................................................... 73

Introduction ........................................................................................................................................................................................... 73


Hardware .............................................................................................................................................................................................. 73

Software ............................................................................................................................................................................................... 73



Appendix F: Service Manager 9.61 benchmark – Oracle 2500 user example ................................................................................... 77

Introduction ........................................................................................................................................................................................... 77


Hardware .............................................................................................................................................................................................. 77

Software ............................................................................................................................................................................................... 77



Appendix G: Service Manager 9.61 benchmark – PostgreSQL 1000 user example ......................................................................... 80

Introduction ........................................................................................................................................................................................... 80


Hardware .............................................................................................................................................................................................. 80

Software ............................................................................................................................................................................................... 81



Appendix H: Service Manager 9.60 benchmark – 10k user example ................................................................................................. 84

Introduction ........................................................................................................................................................................................... 84



Hardware .............................................................................................................................................................................................. 84

Software ............................................................................................................................................................................................... 85



Appendix I: Service Manager 9.60 SRC benchmark – 400 user example .......................................................................................... 94

Introduction ........................................................................................................................................................................................... 94

Deployment topology ............................................................................................................................................................................ 94

Hardware .............................................................................................................................................................................................. 94

Test Configurations .............................................................................................................................................................................. 94

JDK and Apache Tomcat specifications: .................................................................................................................................................................... 94

Dataset ............................................................................................................................................................................................................................. 95

SRC settings .................................................................................................................................................................................................................... 95


Appendix J: Service Manager 9.60 Mobility benchmark – 1,000 user example ................................................................................ 98

Introduction ........................................................................................................................................................................................... 98

Deployment topology ............................................................................................................................................................................ 98

Hardware .............................................................................................................................................................................................. 98

Software ............................................................................................................................................................................................... 98


Appendix K: Service Manager 9.60 Service Portal benchmark – 200 user example ...................................................................... 101

Introduction ......................................................................................................................................................................................... 101

Deployment topology .......................................................................................................................................................................... 101

Hardware ............................................................................................................................................................................................ 101

Average response times ..................................................................................................................................................................... 102

Appendix L: Service Manager 9.60 Smart Analytics benchmark – 1,000 user example ................................................................ 104

Introduction ......................................................................................................................................................................................... 104

Deployment topology .......................................................................................................................................................................... 104

Hardware ............................................................................................................................................................................................ 105

Software ............................................................................................................................................................................................. 106

Test configurations ............................................................................................................................................................................. 106

Average response times ..................................................................................................................................................................... 107

Appendix M: Service Manager 9.60 Collaboration benchmark – 400 user example ....................................................................... 108

Introduction ......................................................................................................................................................................................... 108

Results summary ................................................................................................................................................................................ 108

Test environment ................................................................................................................................................................................ 108

Hardware .......................................................................................................................................................................................................................108

Software .........................................................................................................................................................................................................................108

Appendix N: Service Manager 9.60 Survey benchmark – 400 user example .................................................................................. 110

Hardware ............................................................................................................................................................................................ 110

Results summary ................................................................................................................................................................................ 110

Send documentation feedback ........................................................................................................................................................... 112

Legal notices ........................................................................................................................................................................................ 112

Warranty ............................................................................................................................................................................................. 112

Restricted rights legend ...................................................................................................................................................................... 112


Copyright notice ................................................................................................................................................................................. 112

Trademark notices .............................................................................................................................................................................. 112

Disclaimer ........................................................................................................................................................................................... 112

Documentation updates...................................................................................................................................................................... 112

Support ............................................................................................................................................................................................... 112


Introduction This document provides hardware sizing practices, existing tuning information and high availability recommendations to customers who

want to implement Service Manager 9.6x. All references are based on the benchmark test results and test data in the research &

development laboratory (R&D Lab).

Guides for older versions of Service Manager as well as updated versions of this guide can be found at the following website:

https://softwaresupport.softwaregrp.com/

The reference configuration data supplied in this document is based on a Service Manager out-of-box (OOB) environment, which

includes the web tier, Service Request Catalog (SRC), Service Manager Mobility, Service Manager Service Portal and Smart Analytics

running on top of the Service Manager Runtime Environment (RTE).

Individual implementations may consume more resources or require more resources to perform in an acceptable manner. This includes

running an implementation on top of an earlier version of the Service Manager RTE.

Failure to test the application with the concurrent user load and transaction rate that is expected at the height of daily system usage and

using tailored applications in the test environment may result in an environment that is not large enough to support your requirements.

The recommendations described in this document should be considered the minimum requirements that are needed to run Service

Manager effectively.

Terminology

Term Description

SM Service Manager.

RTE Service Manager Runtime Environment.

SRC Service Request Catalog.

SMSP Service Manager Service Portal.

Concurrent users Online users who have logged on to the system to perform operations and consume system processing resources. It is different from registered users.

Workload User activities that are performed against the system.

Throughput The frequency that end users perform business transactions per hour. For example, 100 orders per hour, 100 requests per hour, and so on.

Test data Business data populated into database to simulate the customers’ data volumes.

Benchmark test A kind of performance testing method to determine a system’s performance quality. In general, it utilizes a load test tool to simulate the concurrent users performing daily operations against the underneath system.

CHO test CHO stands for Continue Hours Operation, extend the benchmark test to between 12 and 72 hours.



Service Manager sizing questions The following list of questions is designed to gather the information that is required to make recommendations about the overall system

architecture that you need for your Service Manager environment.

Note:

Although not all of the information requested here is required to size the environment, it is useful information to obtain for a thorough

architecture recommendation.

1. What kind of environment will you use?

A. An on-premise solution administered by internal IT

B. An in-house solution administered by Micro Focus

C. Software as a service

2. What is the expected hardware and software environment?

A. Do you plan to operate in separate development, test, and production environments to ensure quality?

B. Do you have any ITSCM, disaster recovery, or high availability requirements?

C. Do you plan to operate in a virtual environment or on physical machines?

3. Do you have existing hardware that you want to reuse?

A. What operating systems are you using?

B. How many CPUs are there per computer?

C. How much RAM is available per computer?

D. What is the Storage configuration?

E. Any hardware load balancer existing? Like F5.

F. What relational database management system are you using?

4. What is the average/worst network latency in your environment?

5. Can you provide a Microsoft Visio diagram of your network with minimum latency and bandwidth values (see the example

diagram)?

6. Do you plan to use any of the following integrations together with Service Manager? If so, which ones?

A. Inbound/outbound email, SMTP, or POP3

B. Active Directory (LDAP) integration or single sign-on

C. Data import of persons or organizations from an HR or other environment

D. Integration to Universal Configuration Management Database (UCMDB)/CMS

E. Integration to other Micro Focus Software solutions

F. Imported configuration items (CIs)

G. Others

7. Do you have licensing requirements for any of the following?

A. Service Catalog

B. Knowledge Management. If yes, what is the expected number of Knowledge Management users (authors, editors, and

administrators)?

C. Additional languages. If yes, which languages do you expect to operate?

D. IT specialists (Technicians, Administrators, Helpdesk). If yes, what is the overall number of IT specialists? (Technicians,

Administrators, Helpdesk)

E. Named Users. If yes, how many of them should have guaranteed access to Service Manager?


F. What are your module-level user requirements for Service Manager?

8. How many concurrent users you are expecting to support? Average and peak numbers are expected.

A. How many users for SM window client?

B. How many users for SM web tier client?

C. How many users for SM SRC client?

D. How many users for SMSP client?

E. How many users for SM mobility client?

F. How many users for SM Collaboration client?

G. How many users for Smart Analytics?

9. What is the geographical breakdown of your user base for each kind of client?

10. What is the expected business transactions throughput in production environment? Average and peak numbers are expected.

A. How many logins per hour?

B. How many interactions will be generated per hour?

C. How many incidents will be generated per hour?

D. How many requests will be generated per hour?

E. How many changes will be generated per hour?

F. How many catalog orders will be generated per hour?

G. How many smart search requests will be generated per hour?

11. What are your expected data volumes (including attachments) for the following modules?

A. Global List

B. Service Desk

C. Incident Management

D. Change Management

E. Problem Management

F. Knowledge Management

G. Request Management

H. Configuration Management

I. Service Level Management

12. What are your reporting requirements?

A. The bundled Crystal Reports solution

B. An external reporting solution

C. Data replication into a data warehouse


Service Manager sample deployment See the following diagram for Service Manager sample deployment.


Prepare for sizing Sizing is the process of determining the underneath hardware resources to support the business requirement targets in production, for

both the present and the future. No matter whether you need to build a web farm or not, create a database cluster or adopt new

hardware devices such as F5 highly depends on your actual business requirements. High availability or resiliency will produce different

hardware configurations for different scalability requirements. Customers should consider their business growth in the future 3 to 5

years, and plan enough hardware resources to accommodate these changes. In general, customers need to keep at least 30% or more

capacity for the future growth and refer to the system history to evaluate these growth.

For new customers from scratch, sizing recommendations in this guide should be treated as the minimum reference for deployment.

For existing customers who want to upgrade their SM to the latest version, we strongly suggest them to firstly learn the statistics of the

current hardware usage and bottlenecks existing in their production, carefully plan their additional hardware adoption or changes to

address existing issues, and then refer to this guide as complementary.

Before diving into the sizing part, you need to understand the key metrics utilized in this guide to provide recommendations. These

metrics include concurrent users load, business throughput and backend database data volume size. This guide will provide

corresponding values of these metrics for your comparison as well as the related references. For customers who have tremendous

different requirements on the metrics, we suggest to implement individual load and stability tests to make sure that no undersized

hardware resource are planned based on the minimum hardware reference.

See the following detail steps for each sizing decision:

1) Set expected business needs.

2) Get target deployment size level.

3) Retrieve recommended minimum hardware configuration.

4) Consider redundancy for high availability, or design disaster recovery process to prevent data lost.

5) Refer to Rules of Thumb for additional sizing information and tuning practices.

See the following table for sample target deployment size information:

Metrics Small Medium Large

Concurrent users load 200 1000 2000

Interactions per hour 5 25 50

Incidents per hour 5 25 50

Test data in R&D Lab Incidents: 100000

Interactions: 100000

Incidents: 500000


Incidents: 1000000


A similar table exists in each sizing part. You can quickly get their target deployment size level by comparing their actual business data

with the samples data, and then retrieve the detailed hardware information from the following content in that sizing part.

Here is an example for you to retrieve the recommended minimum hardware configuration.

Service Manager Web Tier

Small

Windows and Linux

HPE DL360 – 2 CPU cores, 6 GB RAM, 55 GB HD

Medium

Windows and Linux

HPE DL360 – 8 CPU cores, 16 GB RAM, 120 GB HD

Large

Windows and Linux

Web tier load balancer: HPE DL360 – 4 CPU cores, 4 GB RAM, 55 GB HD

Web tier: HPE DL360 – 12 CPU cores, 16 GB RAM, 70 GB HD


Hardware – size for 50 users All-in-one deployment is a typical requirement for customers with less than 50 concurrent users’ load. Aiming to deploy all services on

one server with less maintenance efforts, this deployment method has some limitations in high availability and scaling in the future. As a

result, we do not recommend a full all-in-one deployment for SM. For example, you can deploy the SM database and the SM Server on

the same computer for demo or testing purpose. However, we recommend to separate the SM database to another computer in actual

production. Though most of the SM related clients and services can be deployed together, SMSP has special requirement on the

underneath operating system and therefore you need to add another server to host it.

At minimum, three servers are recommended to set up all-in-one deployment in production. See the following table:

Usage CPU / RAM / Disk Deployed Services OS

SM Service Portal 4 CPU cores / 12 GB RAM / 60 GB Disk

SM Service Portal, PostgreSQL RedHat Enterprise 7.2

SM Clients and Services 12 CPU cores / 16 GB RAM / 120 GB Disk

SM RTE, SM Web Tier, Mobility, SRC, SM Collaboration, SMA or KM

Windows or Linux

(SM Collaboration only supports Windows)

SM RDBMS 8 CPU cores / 12 GB RAM / 120 GB Disk

SM database like Oracle, MS SQL Server, PostgreSQL

Windows or Linux

Additional considerations:

SM ESS, SRC and SMSP are different portals provided by Service Manager, you may choose some of them. You do not need

to prepare a separate server if you do not need SMSP.

Decrease hardware resources (CPU/RAM/Disk) accordingly if you do not need to implement all SM clients and services,

please.

All servers must be in the same subnet, and the network latency (especially between SM Clients/Services/SM RDBMS) must

be lower than 1ms.

All the servers can be deployed on either virtual machines or physical machines.

Set JVM heap size to 512 MB as the startup option for each web instance when deploying SM Webtier, Mobility, SRC, SM

Collaboration ChatUI seperately.

Set JVM heap size to 2 GB as the startup option for the web instance when deploying SM Webtier, Mobility, SRC, SM

Collaboration ChatUI together.

Add redundant servers to achieve high availability capability so as to avoid single point of failure.

If you do not have high availability enabled, we strongly recommend you to implement the disaster recovery strategy to avoid

data lost.

SM Collaboration supports Windows only, whereas SMSP supports the RedHat Enterprise platform only.


Service Manager deployment sizing

Deployment mode

Service Manager application server and load balancer

Standalone mode

The SM application standalone mode comprises only one SM servlet configured on a SM server that has no software load balancer

enabled. This is the simplest deployment mode, you may consider it the base model. SM Windows client/webtier/SRC/mobility/SMSP or

any other integration points which need to consume SM application service can be configured to connect to this servlet’s open ports

directly.

Vertical scaling mode

The SM vertical scaling mode comprises multiple SM servlet container processes running on one SM server that has a software load

balancer enabled. This implementation is typically used in an environment with 200–600 concurrent users, where hardware system

resources are limited. This implementation supports as many client connections as the Service Manager server has available system

resources.

The following diagram demonstrates how SM load balancer deployed with multiple SM servlets on a single server.

Horizontal scaling mode

The SM horizontal scaling mode comprises several SM servers managed by group parameters. Multiple vertically-scaled Service

Manager hosts can be converted to the horizontal scaling mode. Only one software load balancer port needs to be configured. The host

that obtains a license file is the primary host, and the other hosts are secondary hosts.

A horizontal scaling implementation is typically used in large environment in which system scalability and resilience is a concern. A

horizontal scaling implementation can support as many client connections as the sum of the individual Service Manager instances can

support. For example, if each instance can support 50 client connections and there are 6 instances, the system can support 300 client

connections. A horizontal scaling implementation has improved resilience features, such as the ability to stop and start the load

balancer process without causing a total system outage and the ability to add a new servlet container process to a virtual group when

the system is running.

The following diagram demonstrates how SM load balancer deployed with multiple SM servlets on several servers.


Note:

In the horizontal scaling mode, the number of supported concurrent users in Service Manager may exceed 10,000.

Service Manager web tier

Service Manager web tier is a web application packaged as either a WAR or an EAR file that needs to be deployed under web

containers such as Tomcat, WebSphere, and so on. These containers provides great capabilities on scalability and clustering support.

Similar to SM application server, web tier also supports single node deployment, vertical scaling on a big server, and horizontal scaling

on clustering of several servers. Refer to the official documents released by the container vendors for the supported load balancers.

Service Manager Knowledge Management

Service Manager Knowledge Management search engine supports single node deployment. For large deployment, we recommend to

enable load balancer on a separate small server and scale out search engine instances on different servers instead of scaling up on a

single big server.

Minimum required reference configurations

Service Manager application server

Metrics Small Medium Large - I Large - II Large - III Extra large

Concurrent users load 200 600 1000 2000 3000 10000

Interactions / hour 95 285 475 950 1425 4750

Incidents / hour 50 150 250 500 750 2500

Changes / hour 18 54 90 180 270 900

Problems / hour 17 51 85 170 255 850

Requests / hour 36 108 180 360 540 1800

Servlet number 6 16 26 52 78 282

SM computers 1 1 1 2 3 12

Note:

1. The values provided in above table have been verified in R&D Lab benchmark testing. If you have different metrics requirements, please adjust hardware size accordingly. See Service Manager Server (Servlet Container) for more information.


2. Test data utilized in R&D Lab is 5 million for all kinds of benchmark tests with different concurrent users loads. 3. We recommend that Service Manager 9.6x customers configure an additional computer with three CPU cores to run

background processes. 4. We recommend that customers who use Service Manager Reports heavily configure another replicated database with the

same hardware configuration so as to reduce the performance impact. 5. PostgreSQL is supported by Service Manager as of version 9.61. If you use PostgreSQL as the database, the

recommended maximum concurrent users are about 1000. 6. HugePages is configured for Oracle on Linux in R&D Lab.

Small

Windows and Linux

1 x Service Manager: HPE DL360 – 4 CPU cores, 8GB RAM, 70GB HD

1 x RDBMS (Oracle): HPE DL360 – 2 CPU cores, 8GB RAM, 4 x 146GB RAID10

1 x RDBMS (PostgreSQL): HPE DL360 – 4 CPU cores, 8GB RAM, 4 x 146GB RAID10

Medium

Windows and Linux




Large - I

Windows and Linux




Large - II

At this size, we recommend that you run Service Manager on multiple computers in horizontal scaling mode.

Windows and Linux

1 x Service Manager (Load Balancer): HPE DL360 – 2 CPU cores, 2GB RAM, 55GB HD

2 x Service Manager (Servlet): HPE DL360 – 8 CPU cores, 48GB RAM, 120GB HD


Large - III

At this size, we recommend that you run Service Manager on multiple computers in horizontal scaling mode.

Windows and Linux

1 x Service Manager (Load Balancer): HPE DL360 – 4 CPU cores, 4GB RAM, 55GB HD

3 x Service Manager (Servlet): HPE DL360 – 8 CPU cores, 48GB RAM, 120GB HD


Extra large

We recommend that you add more computers to scale up the Service Manager system depending on the actual number of

users. Additionally, we recommend that you use a hardware load balancer (such as F5) instead of a software load balancer.

For an example of how we deploy Service Manager systems in the R&D Lab to support a huge number of users, see the

appendices.


Service Manager web tier

Metrics Small Medium Large - I Large - II Large - III Extra large

Concurrent users load 200 600 1000 2000 3000 10000

Interactions / hour 95 285 475 950 1425 4750

Incidents / hour 50 150 250 500 7500 2500

Changes / hour 18 54 90 180 270 900

Problems / hour 17 51 85 170 255 850

Requests / hour 36 108 180 360 540 1800

Tomcat Instance 1 3 5 10 15 50

Note:

The values provided in above table have been verified in R&D Lab benchmark testing. If you have different metrics requirements,

please adjust hardware size accordingly.

Small

Windows and Linux

1 x HPE DL360 – 2 CPU cores, 4GB RAM, 55GB HD

Medium

Windows and Linux


Large - I

Windows and Linux


Large - II

Windows and Linux


Large - III

Windows and Linux

1 x Web tier load balancer: HPE DL360 – 4 CPU cores, 4GB RAM, 55GB HD

1 x Web tier: HPE DL360 – 12 CPU cores, 16GB RAM, 70GB HD

Extra large

We recommend that you add more computers to scale up the Service Manager system depending on the actual number of

users. Additionally, we recommend that you use a hardware load balancer (such as F5) instead of a software load balancer.

Service Manager load balancer server

For more information, see Service Manager load balancer server.

Service Manager Knowledge Management

Small (Less than 200 concurrent users)

Windows and Linux

1 x HPE DL360 – 1 CPU core, 2GB RAM, 55GB HD

Medium (200–500 concurrent users)


Windows and Linux


Large (More than 500 concurrent users)

For more information, see Service Manager Knowledge Management search engine.

Service Manager virtualization

To efficiently run all Service Manager components in a virtual environment, add at least 30% to their recommended sizing.

Service Manager Mobility deployment sizing

Deployment mode

The Mobility application deployment is based on a specific container. In this guide, we provide Tomcat as an example. Therefore, the

deployment's scalability is the same as that of Tomcat containers.

Standalone mode

In the standalone mode, only one Mobility server instance is configured. This Mobility server provides services for all incoming

requests. To achieve high availability capability, you need to add redundant Mobility servers with same configurations and

adopt load balancer between the clients and the servers.

Vertical scaling mode

To extend Mobility application capabilities, you need to add more instances on the same server and add another load balancer

between the clients and the servers. To achieve high availability, you need to add redundant Mobility servers.

Horizontal scaling mode

If you have a large number of customers, you can set up a Mobility web farm to achieve high availability capabilities in the

horizontal scaling mode.





Logins / hour 600 2000 8600

Pagination searches / hour 40000 130000 270000

Change updates / hour 2000 7000 13000

Change approves / hour 100 320 610

Change denies / hour 80 260 550

Incident updates / hour 2200 7000 13900

Interaction updates / hour 2200 6800 13200

Test data in R&D Lab 1 million 3 million 6 million

Note:



Small

Windows and Linux

1 x Mobility server: HPE DL360 – 4 CPU cores, 6GB RAM, 50GB HD

Medium

Windows and Linux


Large

Windows and Linux



For larger size deployment, scale out by adding more servers with the following configuration. Meanwhile, prepare a new small

server as the load balancer.

Windows and Linux

1 x Load balancer: HPE DL360 – 4 CPU cores, 4GB RAM, 50GB HD

Web server (for each): HPE DL360 – 8 CPU cores, 12GB RAM, 60GB HD

Service Manager Service Request Catalog deployment sizing

Deployment mode

The SRC application deployment is based on a Tomcat container, therefore the deployment's scalability is the same as that of Tomcat

containers. The deployment models may include, but are not limited to, the following:

Standalone mode, in which one Tomcat container holds one SRC application.

Vertical deployment mode, in which multiple Tomcat containers each hold one SRC application.

Horizontal mode, in which multiple Tomcat containers each hold multiple SRC servers on each server, and the implementation

of SRC applications on each server is vertical.


Example Service Request Catalog deployment diagram

In this diagram, SW Load Balancer refers to the Service Manager Software Load Balancer, and HW Load Balancer refers to the

Cisco Hardware Load Balancer and the F5 Hardware Load Balancer. As of the release of SRC 9.32, both the Cisco Hardware Load

Balancer and the F5 Hardware Load Balancer are supported. For more information, contact Micro Focus support.




Logins / hour 600 1500 3500

Submit Requests / hour 170 870 2100

Approval approves / hour 45 110 2800

Approval denies / hour 45 110 2800



Change denies / hour 50 120 3000

Submit Survey / hour 50 120 3000

Test data in R&D Lab 0.7 million 1.5 million 3.5 million

Note:



Small

Windows / Linux

1 x SRC server: HPE DL360 – 2 CPU cores, 4GB RAM, 50GB HD

Medium

Windows / Linux


Large

Windows / Linux


For configurations with more than 800 SRC concurrent users, we suggest that you scale out and use an Apache HTTP server as the

load balancer. For more information, see Service Manager Service Request Catalog.

Service Manager Smart Analytics deployment sizing

Deployment mode

Service Manager Smart Analytics consists of various components and services to provide different kinds of indexing and searching

needs. The main components are as follows:

Proxy – Includes main proxy, image proxy, and level II proxies such as Smart Search proxy, Hot Topic Analytics proxy, SMSP

proxy.

Content server – An indexed data storage in IDOL.

Image server – A special content server to provide OCR (Optical Character Recognition) capabilities.

Connectors – IDOL utilizes different kinds of connectors to index and search through external resources such as Sharepoint,

Wiki pages, files, and so on.

CFS – A special service to process attachment of document.

Depending on the data volumes size and the searching service requirements, there are several different topologies available for

customers to choose.

All-in-one

This is the minimum deployment which requires only one server to host proxy services, two Smart Search contents, one HTA

content, and an optional SMSP content, image service, connectors, and so on. You must be aware that this deployment has

limitations on the high availability support. That is, you cannot avoid single point of failure when the server is down or crashed.

Also, we do not suggest this deployment if you have heavy or unpredictable scaling requirements in the future. However, you

can still extend capabilities by adding more hardware resources like CPU/RAM/Storage to scale up on the single server.


Clustering with low scalability

This setup is an extended version based on all-in-one deployment. It is for small to medium deployment requirements with

limited scalability in the future. It is the basic deployment when you only need 1 to 2 additional content servers besides the all-

in-one deployment. Note that the first server need to be configured stronger since it has higher request processing load than

the additional content servers do. Similar to all-in-one, you can also extend capabilities by adding more hardware resources

such as CPU/RAM/storage to scale up on the single server.

At minimum, 2 servers are suggested to set up this clustering.

o 1 x server with all-in-one deployment (SMA Main server)

o 1 x content server for Smart Search

Clustering with medium scalability


This setup is recommended for customers who has much more requirements on Smart Search services and images than

others. It aims to scale out Smart Search content and image servers in the future.


o 1 x server with proxy, HTA content, SMSP content included (SMA basic server).

o 2 x content server for Smart Search.

o 1 x server for image.

o 1 x server for connectors and relating CFS service.

Note:

1. If you have high requirements on HTA and SMSP, we suggest to split these services from SMA basic server to separated servers. This is more like clustering with high scalability as described below.

2. If you do not have high requirements on image server and connectors, you can even install these services on one computer instead of different computers.

Clustering with high scalability

This deployment mode considers your large data volumes size, heavy usage on Smart Analytics, and the scaling requirements

in the future. We recommend this deployment if you have high scalability requirements on each service. The main logic is to

set up a whole clustering but split different service components to different computers.


o 1 x server to host proxy services and QMS, including main proxy, level II proxy, and so on.

o 2 x Smart Search content server.

o 1 x Hot Topic Analytics content server.

o 1 x SMSP content server.

o 1 x server to host connectors and CFS.

o 1 x server to host image proxy.

o 1 x server to host image service.


With the above configurations, you can easily extend capabilities by adding more content servers/image servers to clustering

to accommodate growing data volume size and concurrency in the future.

Clustering with high availability

If you have high availability needs, SMA provides another kind of deployment by adding redundant servers on proxy and

content server layers.

At minimum, 15 servers are suggested to setup this clustering.

o 2 x servers with the same configurations to host proxy services and QMS, including main proxy, level II proxy, and so

on.

o 8 x content servers.

4 x Smart Search content servers with fail-over enabled.

2 x Hot Topic Analytics content servers with fail-over enabled.

2 x SMSP content servers with fail-over enabled.

o 1 x server to host connectors and CFS.

o 2 x servers with the same configurations to host image proxy.

o 2 x servers to host image services.



Service Manager Smart Analytics provides plenty of features, such as Smart Search, Smart Ticket and Hot Topic Analytics. After SMSP

is introduced as of version 9.50, Smart Analytics can also work with SMSP seamlessly. The guidelines provided below suppose that

you will utilize all these features.

Firstly, you need to consider your expected business needs. There are several factors which need your attention.

Indexed data volume size in SMA IDOL

There is an upper limit on the data volume for each content server. The maximum size for each content server is 3 million. To

achieve a better performance, we still suggest 2 million for each content server especially when you have huge data volume

size requirements.

In this guide, all the recommendations are based on 2 million data size for each content server. For example, if you have 5 to 6

million indexed data requirement, we will suggest 3 content servers for setup.

From experience, the data volume size needed for Smart Search is much higher than that for Hot Topic Analytics and SMSP.

For customers from scratch, you can plan 10% to 20% data size needs of Smart Search for Hot Topic Analytics, and then plan

1% to 5% data size needs of Smart Search for SMSP.

Workload

There are different kinds of workloads which utilize SMA.

o Global search

o Context search


o Hot Topic Analytics (HTA) search

o Smart Ticket

o SMSP item and KM search

From experience, the workloads for global search and context search are much heavier than others. For customers from

scratch on Smart Search, you can plan 80% users load on global search, and then plan 20% users load on context search.

Since Smart Search consumes the most workload, the sizing is mainly related to this part. For others, the minimum required references

recommended are generally sufficient.

Metrics Small Medium Large Very Large

Concurrent users load 200 600 1000 2500

Global searches / hour 2400 7200 12000 30000

Context searches / hour 1120 3360 5600 14000

Test Data in R&D Lab 1.5 million 3.5 million 6 million 8 million

Note:

1. If you have different metrics values from the above table and cannot find recommended sizing information, see Service Manager Smart Analytics.

2. We suggest you to provide a storage instead of local disk for indexed data in IDOL to achieve best performance. Smart Analytics content servers has high requirements for the IO system.

Small

Windows and Linux

1 x Smart Analytics: HPE DL360 – 6 CPU cores, 12GB RAM, 120GB HD

Deployment: All-in-one. Refer to the all-in-one deployment mode.

Medium

Windows and Linux

1 x Smart Analytics A: HPE DL360 – 8 CPU cores, 12GB RAM, 120GB HD

1 x Smart Analytics B: HPE DL360 – 6 CPU cores, 6GB RAM, 100GB HD

Deployment: Refer to the clustering with low scalability deployment mode.

Large

Windows and Linux

1 x Smart Analytics Proxy: HPE DL360 – 4 CPU cores, 4GB RAM, 80GB HD

3 x Smart Search Content: HPE DL360 – 6 CPU cores, 8GB RAM, 100GB HD

1 x Hot Topic Analytics Content: HPE DL360 – 6 CPU cores, 8GB RAM, 100GB HD

1 x SMSP Content: HPE DL360 – 4 CPU cores, 8GB RAM, 100GB HD

1 x Smart Analytics Connectors and CFS: HPE DL360 – 6 CPU cores, 8GB RAM, 60GB HD

1 x Image Proxy: HPE DL360 – 4 CPU cores, 4GB RAM, 50GB HD

1 x Image Server: HPE DL360 – 8 CPU cores, 8GB RAM, 50GB HD

Deployment: Refer to the clustering with high scalability deployment mode. If you want to implement high availability, add

redundant servers for each content and proxy and refer to the clustering with high availability deployment mode.

Note:

1. The above configuration is based on the assumption that customers will have high business requirements on all SMA services. For customers who only have partial requirements on certain services, please adjust hardware resources accordingly.


2. For example, if you have high requirements on Smart Search only, you can refer to the clustering with medium scalability deployment mode and reduce the necessary computers. The minimum required reference configurations are as follows: 1 x Smart Analytics Proxy, HTA, SMSP: HPE DL360 – 8 CPU cores, 8GB RAM, 100GB HD




Very large

Windows and Linux




1 x Hot Topic Analytics Content: HPE DL360 – 8 CPU cores, 8GB RAM, 100GB HD

1 x SMSP Content: HPE DL360 – 6 CPU cores, 8GB RAM, 100GB HD



Deployment: Refer to the clustering with high scalability deployment mode. If you want to implement high availability, add

redundant servers for each content and proxy and then refer to the clustering with high availability deployment mode.

Note:

1. The above configuration is based on the assumption that customers will have high business requirements on all SMA services. For customers who only have partial requirements on certain services, please adjust hardware resources accordingly.

2. For example, if you have high requirements on Smart Search only, you can refer to the clustering with medium scalability deployment mode and reduce the necessary computers. The minimum required reference configurations are as follows: 1 x Smart Analytics Proxy, HTA, SMSP: HPE DL360 – 8 CPU cores, 8GB RAM, 100GB HD




For deployment requirements which exceed the above sizes, we recommend that you adopt the clustering with medium

scalability or clustering with high scalability deployment mode and scale out by adding more content servers with the following

configuration. See Service Manager Smart Analytics for more information.

Windows and Linux




Content Server (for each): HPE DL360 – 8 CPU cores, 8GB RAM, 100GB HD

Image Server (for each): HPE DL360 – 8 CPU cores, 8GB RAM, 50GB HD


Service Manager Collaboration deployment sizing

Deployment mode

The Chat Server can be configured with or without a Skype for Business integration. You can either create an integration with an

existing Skype server or use a dedicated Skype server if there are no existing Skype servers.

Example SMC deployment diagram


Chat Server and Chat Service configuration (with Skype for Business integration)

Windows

1 x HPE BL460 – 8 CPU cores, 16GB RAM, 55GB HDD

Skype for Business server configuration (available with Skype for Business integration)

Refer to the Microsoft Skype for Business Server Configuration Guide.

We recommend that you install the Chat Server and the Chat Service on a dedicated server for better performance.

JRE 1.8 (64-bit) is recommended for Chat Server and Chat Service.

The performance results for Chat Server and Chat Service with Oracle JDK and OpenJDK are same.

Windows (64-bit) is recommended for Chat Server and Chat Service.

The maximum concurrent user number is 400 and the maximum concurrent Skype user number is 30 to 40 in SM

Collaboration.

In Apache HTTP Server, update the parameters as follows:

ThreadLimit 6000

ThreadsPerChild 6000

You need to configure the Chat Server database schema together with the Service Manager Database schema. In most

cases, the Chat Server database schema requires 300MB of free disk space for every 1 million message history records.


Service Manager Service Portal deployment sizing

Deployment mode

Service Manager Service Portal (SMSP) is a new portal based on the micro-service architecture. Similar to SM ESS and SRC portals,

SMSP provides services on shopping, request support, knowledge search, ticket approval, and so on.

Being initially released in SM9.50, current SMSP supports two kinds of deployment modes:

All-in-one

All-in-one requires only one server to host all SMSP relating services, including the PostgreSQL database on which SMSP

relies.

Distributed deployment

The distributed deployment mode consists of three parts: SMSP load balancer, SMSP application nodes, and PostgreSQL

database clustering. At minimum, 5 servers are needed for this deployment mode.





Logins / hour 470 840 1500

Orders / hour 742 1360 2000

Support requests / hour 140 200 300

Approvals / hour 50 95 150

Test Data in R&D Lab 300 catalog items 1500 catalog items 5000 catalog items


Note:

If you have different metrics values and cannot find recommended sizing information, see Service Manager Service Portal (SMSP).

Small

RedHat Enterprise

SMSP Server x 1: HPE DL360 – 10 CPU cores, 16GB RAM, 80GB HD

Medium

RedHat Enterprise

1 x SMSP Load Balancer (Nginx): HPE BL460c – 2 CPU cores, 4GB RAM, 50GB HD

2 x SMSP Application Node: HPE BL460c – 6 CPU cores, 16GB RAM, 60GB HD

2 x SMSP PostgreSQL DB: HPE BL460c – 12 CPU cores, 16GB RAM, 120GB HD

Large

RedHat Enterprise

1 x SMSP Load Balancer (Nginx): HPE BL460c – 4 CPU cores, 4GB RAM, 50GB HD

3 x SMSP Application Node: HPE BL460c – 6 CPU cores, 16GB RAM, 60GB HD

2 x SMSP PostgreSQL DB: HPE BL460c – 16 CPU cores, 16GB RAM, 120GB HD


Service Manager Smart Email deployment sizing

Deployment mode

You need to configure the SM Smart Email servlets as a dedicated server and set the Smart Email servlets as debug nodes to isolate

the SM load balance nodes.

We recommend that you start Smart Email process on a dedicated SM server to avoid performance impact and use a debug node to

isolate all the SM nodes which are be used by Smart Email. A debug node can start 5 to 10 Smart Email Schedulers.

Standalone

In the standalone mode, you need to configure only one SM Smart Email debug node to process all email tasks. To achieve

high availability capability, you can add more debug nodes of the same configurations.

The email process rate is about 0.9 emails/minute in this mode. This value does not include reading emails from the network.

SM ServerEmail Server

SM -httpPort:13081 -debugnode

Vertical scaling

You can extend Smart Email capabilities by adding more SM debug nodes to the same server and start other Smart Email

Scheduler in new SM debug nodes.

In this mode, you can configure 5 debug nodes at maximum and the email process rate is about 45 emails/minute. This value

does not include reading emails from the network.

SM ServerEmail Server

SM -httpPort:13081 -debugnodeSM -httpPort:13083 -debugnodeSM -httpPort:13085 -debugnodeSM -httpPort:13087 -debugnodeSM -httpPort:13089 -debugnode

Horizontal scaling

This deployment mode provides high availability capabilities. For large customers (>45 emails/minute), you can choose to set

up a dedicated SM Server web farm for Smart Email.

In this mode, you can configure 5 debug nodes at maximum in each SM Server.


SM Server

Email Server


Sm Server


SM Server




Processed Emails / Hour 54 2700 > 2700

Small

Windows and Linux

1 x SM Smart Email Server: HPE BL460 – 4 Cores, 16GB RAM, 60GB HDD

Deployment: standalone mode. 1 SM debug node is configured.

Medium

Windows and Linux

1 x SM Smart Email Server: HPE BL460 – 8 Cores, 32GB RAM, 60GB HDD

Deployment: vertical scaling mode. 5 debug nodes can be configured at maximum.

Large

If you have higher requirements on Smart Email, you can extend by adding more dedicated servers based on the following

configuration. 5 debug nodes can be configured at maximum in each SM Server.

Windows and Linux

SM Smart Email Server (for each): HPE BL460 – 8 Cores, 32GB RAM, 60GB HDD

Deployment: horizontal scaling mode. 5 debug nodes can be configured at maximum.


Service Manager IdM deployment sizing

Deployment mode

Service Manager (SM) leverages Micro Focus Identity Manager (IdM) to support Single Sign-On (SSO) using SAML 2.0. IdM server

supports single node deployment.


Windows:

1 x IdM Server HPE DL360 – 4 CPU cores, 4GB RAM, 50GB HD


Service Manager on AWS deployment sizing

Deployment mode


Reference configuration for 1500 concurrent users

Webtier

EC2 instance type: t3.medium (2 vCPUs, 4 GiB RAM)

ASG desired capacity: 8

Server primary host

EC2 instance type: t3.large (2 vCPUs, 8 GiB RAM)

EC2 instance count: 1

Server secondary hosts

EC2 instance type: t3.medium (2 vCPUs, 4 GiB RAM)

ASG desired capacity: 30

RDS Database

Engine type: PostgreSQL

Version: PostgreSQL 10.7-R1

DB instance size: db.r5.2xlarge (8 vCPUs, 64 GiB RAM)


Service Manager on Azure deployment sizing

Deployment mode


Reference configuration for 2000 concurrent users

Webtier

Size:Standard B2ms (2 vcpus, 8 GiB memory)

Virtual machine scale sets scale:6

Server primary host


Virtual machine count: 1

Server secondary hosts


Virtual machine scale sets scale:27

Database

Engine type: SQL server/SQL databases

Version: Azure SQL Database V12

DB instance size: GP_Gen4_16 (16 vCPUs, 112 GiB RAM)


Rules of thumb

Service Manager server (servlet container)

A servlet container requires approximately 3GB of RAM, which is distributed in the following ways:

512 MB Java virtual machine requirement, including the 256MB default Java heap

50 MB for the process overhead

10 MB – 40 MB per user session (thread) (See the note below)

Plus shared_memory setting value equals to or greater than 256000000 in the sm.ini file. (Counted only once for all servlet

containers on a single computer)

We recommend that you start with 50 threads (users) per process (servlet container). Then, adjust the number of threads based on the

process memory usage in your environment, up to a maximum of 100 threads.

Note:

1. Increases in user session memory usage may be caused by large global lists, global variables that are not garbage collected, or multiple open application threads. These activities have a direct effect on the number of user threads that each servlet container can support.

2. Most Linux operating systems, provide ways to limit and control the usage of system resources such as threads, files, and network connections on a per-process and per-user basis. These limits prevent single users from using too many system resources. Sometimes, these limits have low default values that can cause a number of issues if there is a high number of concurrent users. We recommend that you use the ulimit –a command to check the resource limitation in the operating

system, and ensure that the resources are sufficient for Service Manager servlets. We recommend that the value set by the ulimit –d command is over 3GB or “unlimited” mode.

3. The network latency between Service Manager and the database server has a significant impact on the overall system performance. For example, every 5ms latency between the Service Manager applications server and the database server will double the login time. Therefore, we highly recommend that the network latency between the Service Manager applications server and the database server is less than 1ms.

4. If you are using horizontal scaling mode, we highly recommend that the network latency between each Service Manager application server is less than 1ms.

Service Manager web tier and Mobility

The Service Manager web tier configuration that was used to determine the sizing recommendations is based on a Tomcat web

application server with ten processes running 1 GB of heap size each, and an Apache web server to perform load balance the Java

virtual machines (by using the Apache software load balancer). For Mobility, it shares similar configurations as web tier. To support

additional users and higher loads, add computers that have additional Tomcat Java virtual machines to create a web farm as required.

Customers can also configure hardware load balancer instead of software load balancer to work with tomcat clustering. Details please

refer to Service Manager Help server documents.

Note:

In an initial setup, we recommend 150 to 200 concurrent users for each Tomcat instance.

Service Manager software load balancer

The Service Manager software load balancer should be located on a separate computer and should always be sized as a small

computer because it performs no other function than redirecting connections to an available servlet. This computer also must run the

same operating system as the Service Manager applications servers.

Because this is the one component in a configuration that is a single point of failure, it should be replicated and placed in a clustered

environment for high availability. Failure of this component will only affect users who are attempting to establish an initial connection

into the environment (additionally, the users will be affected only until the load balancer is restarted or fails over). Any currently active

users that are connected to the environment will be unaffected by the loss of the load balancer.

Load balanced computers and servlet computers should use the server sizing that is described in this document. The number of nodes

depends on the size of the computer and on the total number of concurrent production users.


Service Manager RDBMS server

The RDBMS server sizing that is specified above represents the configurations that were used during the benchmarking runs on the

OOB Service Manager system. You should plan the storage requirements of the actual servers that you will use in a production

environment based on expected data volumes, including attachments. The CPU and memory requirements for the selected database

should be based upon the recommendations of the database vendor.

Service Manager virtualized environment (VMware)

Service Manager can be deployed in both physical and virtualized environments. Provided that the sizing guidelines are followed, there

is no significant performance impact.

The Service Manager applications server, the Service Manager software load balancer, and the web tier can be deployed in a

virtualized environment if you follow the sizing that is described in Service Manager virtualization. To deploy a virtualized environment,

we recommend that you make the following configurations:

Upgrade to vSphere5/6 or a later version.

Assign dedicated resources (such as vCPU, memory, and disk I/O) to a guest operating system that acts as a Service

Manager server.

Deploy all Service Manager servers in the same virtualization resource pool.

Service Manager Service Request Catalog

For 400 to 600 concurrent users, make the following configurations:

The following Startup options below are recommended for SRC application in Java virtual machine instance:

-Xms4096m -Xmx4096m XX: MaxPermSize=128m -XX: MaxPermSize=512M

Modify the following lines of the applicationContext.properties file (SRC_HOME\src\WEB-INF\classes):

src.sm.defaultMaxConnectionsPerHost=60

src.sm.maxTotalConnections=60

For more than 800 users, we recommend the following configurations:

The size of the attachment that users upload when they submit service or support requests should not exceed 30 MB.

Otherwise, users maybe encounter long upload times and unexpected exceptions.

The hard disk on each SRC server should meet the actual requirement for storing items from users and attachments.

Therefore, we recommend a minimum of 60 GB of free space to accommodate potential increases in capacity.

The maximum number of threads in the "Connector" configuration section of the server.xml file in Apache Tomcat should be

set to the number of potential customers. Additionally, we recommend that you configure the following settings in the

server.xml file to enable compression. This will improve network transition performance.

<Connector port="8080" protocol="HTTP/1.1"

connectionTimeout="1,0000" maxThreads="1,000" minSpareThreads="100"

acceptCount="800" compression="on" compressionMinSize="1800" maxKeepAliveRequests="800"

processorCache="1,000

redirectPort="8443" />

Note:

Two user sessions are created in Service Manager for each SRC user who logs in;

Session 1 is the main session for subsequent operations after login.

Session 2 is a background session that loads categories. The session ends after the work is completed, and the duration of the session depends on the number of items and attachments. Typically, session 2 lasts for 30 seconds.


Service Manager Service Portal

Hardware size

If you cannot find recommended minimum configuration reference in the previous sections, follow the steps below to evaluate the target

SMSP hardware configurations:

1. Determine the target deployment mode

In general, the all-in-one deployment mode can achieve most requirements. For new customers from scratch, we recommend

this kind of deployment for the minimum maintenance efforts and costs.

The all-in-one deployment is also applicable for customers who have big number of concurrent users but have very low

throughput needs. For example, customer A has 600 concurrent users login SMSP, but the throughputs are 50 orders/hour, 30

requests/hour and 10 approvals/hour. In this situation, the all-in-one deployment mode is still applicable and this customer only

needs to add an additional RAM.

The basic logic is to firstly evaluate your business throughput requirements, and then determine whether you need to distribute

these load to separate computers.

If you are working with SMSP HA deployment, we suggest the typical HA setup from startup for the minimum maintenance

efforts and costs. That is, 1 SMSP load balancer (Nginx), 2 SMSP application nodes, and 2 SMSP PostgreSQL nodes.

2. Determine the number of CPU cores

If you are working with SMSP HA deployment, you need to figure out how many CPU cores should be configured. Here are

some calculations based on the following assumptions:

For each 100 users load, assume these users produce 25 logins/hour, 350 orders/hour, 48 requests/hour, and 29

approvals/hour under peak load.

Based on the above assumption, the needs for CPU cores are:

o For SMSP load balancer (Nginx), 4 CPU cores as the startup.

o For SMSP application node, configure 2 ~ 3 CPU cores for each 100 users load.

o For SMSP PostgreSQL node, configure 3 CPU cores for each 100 users load.

3. Determine the number of RAM

If you are working with SMSP HA deployment, we recommend 4GB RAM for SMSP load balancer (Nginx) as the startup, and

configure 16GB RAM for each SMSP application node. For PostgreSQL database, we suggest to configure 16 GB RAM as the

startup, and then extend the memory based on this value.

4. Determine the IO subsystem

There is no special IO requirement for SMSP. If you do not have storage supported, we suggest to configure separate disks

for PostgreSQL databases.

PostgreSQL database

For SMSP HA clustering environment, PostgreSQL only provides fail-over capabilities instead of load balancing. That is,

SMSP PostgreSQL clustering works under active-passive mode and only one PostgreSQL instance services the incoming

requests at any time.

For SMSP PostgreSQL clustering, we suggest to configure the same hardware resources for both the master and the slave

servers.

Database tuning parameters.

o shared_buffers

For small deployment, configure this parameter to 512MB as a startup option.

For large deployment, configure this parameter to 4GB as a startup option.

o effective_cache_size

For small deployment, configure this parameter to 4GB as a startup option.


For large deployment, configure this parameter to 6GB as a startup option. For a dedicated server, ~75% of the RAM

is recommended.

o maintenance_work_mem

For small deployment, keep default as startup options.

For large deployment, configure this parameter to 1GB as a startup option.

o max_connections

For small deployment, configure this parameters to 200 as a startup option.

For large deployment, configure this parameter to 1024 as a startup option. Also, make sure num_init_children *

max_pool <= max_connections (num_init_children and max_pool are pgpool connection parameters).

o work_mem

For small deployment, keep default as a startup option.

For large deployment, configure this parameter to 16MB as a startup option.

Service Manager Collaboration

The Chat Service support about 400 concurrent users.

For 400 concurrent users, the following startup option is recommended for the Chat server/service on a 32-bit Java virtual machine

instance:

-XX:ThreadStackSize=384 -Xms512m -Xmx1024m

We recommend you to run the Chat server/service on 64-bit Java. The default JVM option is as follows:

-XX:ThreadStackSize=384 -Xms512m -Xmx1536m

Service Manager Smart Email

A Smart Email servlet container requires approximately 3GB of RAM, which is distributed in the following ways:

512 MB Java virtual machine requirement, including the 256MB default Java heap

50 MB for the process overhead

10 MB to 40 MB per user session (thread)

Plus shared_memory setting value = 128000000 in the sm.ini file. (counted only once for all servlet containers on a single

computer)

We recommend that you start with 5 to 10 scheduler per process (servlet container) and 1 schedule per scheduler. The process rate is

about 1 email task/minute.

Service Manager Smart Analytics

Service Manager Smart Analytics server

Hardware size

If you cannot find recommended minimum configuration reference in the previous sizing section, follow the steps below to evaluate the

target SMA content configurations:

1. Determine the target deployment mode

Clustering with medium scalability is recommended for customers from scratch since most of them have much more

requirements on Smart Search and images OCR processing than other services. With this deployment mode, you do not have

to provide very big single server, and the load can be distributed to separate computers for better performance. Also, you can

extend capabilities in the future.


Note:

For additional content server computers, we suggest to configure one content per computer.

2. Determine the number of content servers

From the performance perspectives, the recommended volume size for each content server is 2 million for customers from

scratch. The maximum volume size for each content server is 3 million.

For example, if you plan 5 million indexed data in total for Smart Search, you need to configure 3 content servers. You can

follow the same logic for HTA content and SMSP content.

3. Determine the number of CPU cores

The number of CPU cores is highly dependent on the throughput produced to SMA IDOL services. For global search, HTA

search and SMSP search, the recommended value is 4000 searches per core per hour based on the R&D Lab benchmark.

For context search, the recommended value is 580 searches per core per hour.

For example, if you plan 15000 global searches per hour, you need to configure at least 4 CPU cores. If you plan 4000 context

searches per hour, configure at least 7 CPU cores. And the total needed CPU cores is 11 CPU cores to support both global

searches and context searches.

For proxy servers, we recommend 4 CPU cores for the clustering with high scalability deployment, and 8 CPU cores for the

clustering with medium scalability deployment.

For connectors and CFS, we recommend 6 ~ 8 CPU cores.

4. Determine the number of RAM

For each content server, we recommend 6 to 8GB RAM.

For proxy servers, we recommend 4GB RAM for the clustering with high scalability deployment, and 8GB RAM for the

clustering with medium scalability deployment.

For connectors and CFS, we recommend 6 to 8GB RAM.

5. Determine the IO subsystem.

We recommend you to configure storage instead of local disk for better performance. IDOL has provided a good utility tool

named PerfTool to evaluate your storage IO capabilities. Please consult the R&D team for more information about this tool.

The minimum IO speed is 120 MB/s, while the recommended is 280 MB/s for read/write which is verified in R&D Lab

benchmark and this value is captured from PerfTool. If you do not have supported storage, configure a separate disk for each

content server at least.

Network

We suggest that you locate the Service Manager server, IDOL server, and image server under the same switch in order to

achieve the best performance.

We suggest that you ensure a network latency that is less than 1ms between the Service Manager server and the IDOL

server, between the Service Manager server and the image server, and between the IDOL server and the image server.

On Windows-based platforms, your computer may run out of available TCP ports if your IDOL service receives a large number

of actions. If your system does not have enough ports, you can edit the following Windows registry parameters:

TCPTimedWaitDelay

MaxUserPort

These parameters are located in the HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Services\Tcpip\Parameters\

directory. For more information about these registry parameters, refer to the Windows documentation.

Operating system

We recommend that you install the IDOL server on a Linux system for better stability and maintainability.

Indexing and training

Indexing: It takes about 40 minutes to index 100,000 interaction records and 6.5 hours to index 1,000,000 interaction records.

The growth of the time according to the interaction count is linear.

Training: It takes about 16 hours to train 2,000,000 records in more than 3400 affected services.


Service Manager Smart Analytics image server

We recommend that you install the image server on a dedicated server to achieve better performance.

We recommend to use the distributed image server mode if you process more than 1.82 OCR records (with the average size

of 200 KB) per second. This mode can improve the speed in which OCR records are processed.

Distributed image servers do not support large images (over 1MB) well in environments that have a throughput greater than

3.33 OCR records per second.

Smart Analytics does not have a significant impact on the run time performance of Service Manager. But, as a result of

implementing Smart Analytics, end users and operators can submit tickets very quickly. Therefore, the following points must

be considered for optimal performance:

o The overall throughput and load on the system will increase due to rapid ticket submission. Please continue

monitoring the system resources to prevent any bottlenecks.

o The image server will save all the requested content on a local server. Disk space usage on this server may grow

quickly.

Service Manager Knowledge Management search engine

The following startup requirements are recommended for the search engine:

In a production environment, we recommend a minimum of 8GB with 4GB dedicated to the JVM that hosts the Knowledge

Management search engine. For improved performance, we recommend 16GB of RAM with 8GB dedicated to the JVM that

hosts the search engine.

In a scaling environment, we recommend that you dedicate at least 1GB to the JVM that hosts the Knowledge Management

search engine for every additional 500 users.

Note:

It is important to consider the size of the indexes when you allocate RAM. Performance is greatly improved if the operating system has

sufficient RAM to easily cache all the index files as disk seeks in order to load stored fields and other data from the Knowledge

Management index files. When 4GB of RAM is available to the operating system, an index of approximately 3GB can be cached easily.

However, if that number is doubled to 8GB of operating system RAM, a 6GB or 7GB index can be cached.

Service Manager - small environment deployment

In a small environment deployment (less than 50 users), we recommend the following best practices for the best performance:

Although the database can be deployed on the same computer as the Service Manager server, we strongly suggest that you

deploy the database on a separate computer. However, the server and database should in the same subnet and have a

latency lower than 1ms.

You can implement small environment deployments on virtual machines or on physical machines, as long as you provide

sufficient hardware resources.

We strongly suggest that you use a solid state drive (SSD) instead of a hard disk drive (HDD). An SSD significantly increases

the speed of disk I/O operations.

You can deploy all web applications, including the Service Manager web tier, Service Manager Mobility, and SRC, on the

same Tomcat node or separate Tomcat nodes. For high availability (HA), we suggest that you use a separated deployment.

If you deploy all web applications on same Tomcat node, we recommend the following startup options in the Java virtual

machine instance:

-Xms2048m –Xmx2048m

If you deploy the web applications on separate Tomcat nodes, we recommend the following startup options in the Java virtual

machine instance:

-Xms512m –Xmx1024m

For high availability (HA) and fail-over capabilities in the web applications layer, we recommend that you deploy the web

applications on two Tomcat nodes, and configure an Apache server in front of the nodes as a software load balancer to avoid

a single point of failure.


For high availability (HA) and fail-over capabilities in the Service Manager applications server, we recommend that you use a

vertical scaling model in which two servlet container processes run on one Service Manager server that has a software load

balancer enabled.


Appendix A: Service Manager 9.64 CHO – Oracle 3000 user

example

Introduction

The goal of these examples is to demonstrate the overall performance quality of different sizes of Service Manager systems under

different levels of user loads. The CHO results are based on following user workload assumptions.

Home Page Module name User load distribution Throughput (per hour)

index.do Change Management 9.09% 288 Changes

Incident Management 18.18% 864 Incidents

Problem Management 9.09% 288 Problems, 288 known errors

Request Management 18.18% 1000.8 Requests

Service Desk 27.27% 1677.6 Interactions

ess.do Order from Catalog 9.09% 1152 Tickets

Submit a request 9.09% 3477.6 Tickets

Deployment diagram

All the deployments follow the recommendations in this guide. For more information, refer to Service Manager deployment sizing.

Hardware

The servers that were used for these tests are virtual machines, except for the database computer, which is a physical machine.

The following table describes the configurations of these servers for the 3000 user CHO tests.

ID Usage Operating system CPU Memory

1 SM Server – Primary

(loadbalancer + background + servlets)

Windows 2016 8 CPU Cores

Intel(R) Xeon(R) Gold 6148 CPU @ 2.40GHz

48G

2 SM Server-Secondary

(servlets)



48G


(servlets)



48G

4 Apache Tomcat Server Windows 2008 64-bit 12 CPU Cores


16G

5 Database server Red Hat Enterprise Linux Server release 7.4 (Maipo)

24 CPU Cores

Intel(R) Xeon(R) CPU X5670 @ 2.93GHz

96G

6 Load Runner Controller Windows 2012 R2 8 CPU Cores

Intel(R) Xeon(R) CPU E7-L8867 @ 2.13GHz

16G

7 Apache HTTP Server(Load Balancer) Windows 2008 4 CPU Cores


4G

Software

All tests were run on the following software set:


Micro Focus Load Runner – 12.63.0.0

Apache Tomcat – Apache Tomcat 9.0.10

Apache – Apache 2.4

Service Manager 9.64

Oracle Database 19c Enterprise Edition Release 19.0.0.0.0 - Production

Performance success criteria

The CHO tests are considered successful when the following criteria are met:

3000 users simultaneously log in and are able to complete the recorded tests.

No down time and no memory leaks

Resource Utilization ≤ 80%, such as CPU, memory, etc.

Response times fall within the following parameters:

o Login – 5 seconds average

o Workflow transition actions – 3 seconds average

These actions move records to next phase

o Mass operations – 5 seconds average

“mass add,” 4 tasks on average

“mass update,” 4 tasks on average

“submit CIs to CMDB,” 5 CIs on average

o Others – 1 second

Average response times

Transaction Name SM964 3000 Oracle

Avg Std. Deviation Pass

PD_CM_SC_T01_Create_New_Change 0.175 0.074 20,588

PD_CM_SC_T02_Select_Category_Standard_Change 0.014 0.021 20,586

PD_CM_SC_T03_Select_Subcategory_Hardware 0.034 0.026 20,579

PD_CM_SC_T04_Select_Install_Memory_on_Server 0.994 0.329 20,576

PD_CM_SC_T05-1_AC_MyDevices 0.087 0.031 20,576

PD_CM_SC_T05-2_Fill_MyDevices 0.391 0.069 20,579

PD_CM_SC_T06_Click_Save_Change 1.208 0.194 20,577

PD_CM_SC_T07_Request_Plan_and_Schedule 1.347 0.237 20,576

PD_CM_SC_T09_AC_Change_Coordinator 0.224 0.042 20,579

PD_CM_SC_T10_Fill_Change_Coordinator 0.144 0.053 20,579

PD_CM_SC_T11_select_Change_Coordinator 0.566 0.072 20,586

PD_CM_SC_T12_AC_Change_Owner 0.095 0.028 20,589

PD_CM_SC_T13_Fill_Change_Owner 0.541 0.079 20,589

PD_CM_SC_T14_Request_Authorization 0.695 0.096 20,592

PD_CM_SC_T15_Request_Authorization_ok 2.077 0.258 20,588

PD_CM_SC_T16_Click_Tab_Tasks_1 0.296 0.086 20,590

PD_CM_SC_T17_Click_First_Task 0.8 0.219 20,591

PD_CM_SC_T18_Click_Close_Task_1 0.429 0.065 20,588


PD_CM_SC_T19_Click_Finish_Task_1 0.736 0.146 20,598

PD_CM_SC_T20_Cancel_Task_1 0.115 0.041 20,603

PD_CM_SC_T21_Refresh_Change_1 0.842 0.131 20,606

PD_CM_SC_T22_Request_PIR 2.097 0.253 20,606


PD_CM_SC_T24_Click_Second_Task 0.662 0.155 20,609





PD_CM_SC_T30_Link_New_Record_Related_Requests 0.346 0.065 20,621

PD_CM_SC_T31_Category_Order 0.01 0.021 20,620

PD_CM_SC_T32_Subcategory_Order 0.028 0.026 20,614

PD_CM_SC_T33_Order 0.545 0.133 20,614

PD_CM_SC_T34_Link_Request_Save 1.319 0.172 20,614

PD_CM_SC_T35_Link_Request_Cancel 0.63 0.087 20,613

PD_CM_SC_T36_Link_New_Record_Related_Changes 0.174 0.048 20,614

PD_CM_SC_T37_Category_Standard_Change 0.013 0.02 20,613

PD_CM_SC_T38_Subcategory_Software 0.034 0.026 20,612

PD_CM_SC_T39_Activate_Patch 0.597 0.111 20,611

PD_CM_SC_T40_AC_MyDevices_2 0.061 0.02 20,613

PD_CM_SC_T41_Fill_MyDevices_2 0.363 0.063 20,613

PD_CM_SC_T42_Link_Change_Save 0.976 0.127 20,605

PD_CM_SC_T43_Link_Change_Cancel 0.75 0.13 20,600

PD_CM_SC_T44_Link_Change_Unlink_Record 0.063 0.025 20,596

PD_CM_SC_T45_Link_Change_Unlink_Yes 0.627 0.095 20,596

PD_CM_SC_T46_Click_Tab_Calendar 0.595 0.112 20,592

PD_CM_SC_T47_Click_Close 0.163 0.021 20,592

PD_CM_SC_T48_Click_Close_Finish 1.22 0.171 20,591

PD_CM_SC_T49_Cancel_Change 0.082 0.033 20,583

PD_ESS_CatOrder_T02_Order_from_Catalog 0.835 0.098 83,006

PD_ESS_CatOrder_T02-1_Search_Basic_Pc_Package 1.035 0.101 58,154

PD_ESS_CatOrder_T02-2_Open_Basic_Pc_Package 0.196 0.025 58,149

PD_ESS_CatOrder_T03_Personal_Productivity_Services 0.901 0.122 24,849

PD_ESS_CatOrder_T04_Hardware_Bundles 0.724 0.095 24,843

PD_ESS_CatOrder_T05_Basic_PC_Package 0.237 0.048 24,844

PD_ESS_CatOrder_T06_Add_to_Cart 0.366 0.062 82,992

PD_ESS_CatOrder_T07_View_Cart_Checkout 0.103 0.026 82,997

PD_ESS_CatOrder_T08_Submit_Request 0.112 0.028 82,996

PD_ESS_CatOrder_T09_Submit 1.643 0.157 82,987

PD_ESS_CatOrder_T10_Continue 0.074 0.026 82,985

PD_ESS_CatOrder_T11_Logout 0.16 0.026 27,669

PD_ESS_Inc_T01_Click_SubmitRequest 0.246 0.03 250,321

PD_ESS_Inc_T04_Submit_Request 1.521 0.113 250,313

PD_ESS_Load_Login_Page 0.033 0.027 111,123


PD_ESS_Login 2.252 0.247 111,121

PD_ESS_Logout 0.194 0.022 83,440

PD_Inc_SLM_T01_Create_New_Incident 0.107 0.045 27,322

PD_Inc_SLM_T02_Select_Category_Incident 0.521 0.126 27,321

PD_Inc_SLM_T03_AC&Fill_MyDevices 0.088 0.029 27,321

PD_Inc_SLM_T05_Click_Save 0.693 0.111 27,324

PD_Inc_SLM_T06_Click_Continue 0.846 0.149 27,327

PD_Inc_SLM_T07_AC_Subcategory 0.138 0.029 27,329

PD_Inc_SLM_T08_Fill_Subcategory_hardware 0.127 0.037 27,333

PD_Inc_SLM_T09_Select_Area_hardware_Failure 0.382 0.052 27,329

PD_Inc_SLM_T10_AC&Fill_Assignment_Group 0.061 0.024 27,331

PD_Inc_SLM_T12_Incident_Assign_Phase 1.008 0.111 27,333

PD_Inc_SLM_T13_Incident_Work_In_Progress_Phase 1.237 0.173 27,329

PD_Inc_SLM_T14_Incident_Cancle_page 0.07 0.029 27,335

PD_Inc_SLM_T15_Incident_Open_Search_Page 0.298 0.087 27,336

PD_Inc_SLM_T16_Incident_Search_1 0.7 0.12 27,334

PD_Inc_SLM_T17_Incident_Update_1 0.592 0.077 27,334






PD_Inc_SLM_T23_Incident_Link_New_Task 0.134 0.036 27,348

PD_Inc_SLM_T24_Task_Select_Category_Investigation 0.345 0.086 27,347

PD_Inc_SLM_T25_Save_Investigation_Task 0.542 0.108 27,349

PD_Inc_SLM_T26_Task_Fill_Assignment_Group 0.29 0.056 27,345

PD_Inc_SLM_T27_Incident_Task_Assign_Phase 0.511 0.074 27,344

PD_Inc_SLM_T28_Incident_Task_Work_In_Progress_Phase 0.487 0.073 27,337

PD_Inc_SLM_T29_Incident_Task_Pending_Review_Phase 0.647 0.121 27,336

PD_Inc_SLM_T30_Incident_Task_Click_Close_Task 0.083 0.013 27,336

PD_Inc_SLM_T31_Incident_Task_Close_Task 0.536 0.108 27,336

PD_Inc_SLM_T32_Incident_Task_Cancel_Page 0.428 0.054 27,331

PD_Inc_SLM_T33_Incident_Resolved_Phase 1.904 0.244 27,330

PD_Inc_SLM_T34_Click_Close 0.159 0.016 27,330

PD_Inc_SLM_T35_Close_Incident 1.343 0.191 27,327

PD_Inc_SLM_T36_Cancel_Incident_Page 0.122 0.033 27,328

PD_Inc_SLM_T37_Cancel_Incident_Search_Page 0.101 0.035 27,323

PD_Inc_T01_Click_Create_New_Incident 0.122 0.044 34,968

PD_Inc_T02_Create_New_Incident 0.348 0.061 34,965

PD_Inc_T03_Click_Fill_Button 0.238 0.051 34,959

PD_Inc_T04_Back_From_Fill 0.21 0.041 34,955

PD_Inc_T05_AC_Int 0.079 0.02 34,960

PD_Inc_T06_AC_Fill_Int 0.044 0.021 34,961

PD_Inc_T07_Save_New_Incident 0.677 0.067 34,965

PD_Inc_T08_Continue_to_Save_New_Incident 0.645 0.069 34,965


PD_Inc_T09_Change_status_from_Categorize_to_Assign 1.36 0.133 34,973

PD_Inc_T10_Chaneg_phase_from_Categorization_to_Investigation 1.252 0.155 34,971

PD_Inc_T11_Load_Category_for_Incident_Task 0.147 0.041 34,975

PD_Inc_T12_Open_new_Incident_task 0.209 0.047 34,975

PD_Inc_T13_Save_Incident_Investigation_Task 0.4 0.065 34,982

PD_Inc_T14_Open_Incident_Investigation_Task_DueDate 0.412 0.06 34,981

PD_Inc_T15_Open_Incident_Investigation_Task_from_Ready_to_Assigned 1.371 0.158 34,992

PD_Inc_T16_Open_Incident_Investigation_Task_from_Assigned_to_WIP 0.875 0.105 34,985

PD_Inc_T17_Open_Incident_Investigation_Task_from_WIP_to_PendingReview 0.681 0.115 34,992

PD_Inc_T18_Open_Incident_Investigation_Task_Prepare_Close 0.087 0.01 34,992

PD_Inc_T19_Close_Incident_Investigation_Task_Close 0.729 0.12 34,992

PD_Inc_T20_Go_back_to_Incident_page 0.374 0.041 34,985

PD_Inc_T21_Change_phase_from_Investigation_to_Resolved 1.481 0.186 34,985

PD_Inc_T22_Open_Incident_Close_page 0.189 0.019 34,985

PD_Inc_T23_Close_Incident 1.485 0.16 34,990

PD_Inc_T24_Cancel_Incident 0.119 0.039 34,984

PD_Load_Login_Page 0.092 0.09 98,383

PD_Operator_Login 3.443 0.475 98,365

PD_Operator_Logout 0.211 0.058 98,415

PD_PM_KE_T01_Create_New_Problem 0.639 0.207 20,666

PD_PM_KE_T02_AC_MyDevices 0.057 0.024 20,657

PD_PM_KE_T03_Fill_MyDevices 0.031 0.026 20,655

PD_PM_KE_T04_Save_Problem 0.786 0.115 20,652

PD_PM_KE_T05_Continue 0.694 0.137 20,657

PD_PM_KE_T06_Link_New_Task_1 0.138 0.047 20,660

PD_PM_KE_T07_New_Task_1 0.375 0.1 20,657

PD_PM_KE_T08_Save_Task_1 0.573 0.119 20,662

PD_PM_KE_T09_Cancel_Task_Page_1 0.518 0.1 20,659


PD_PM_KE_T11_New_Task_2 0.347 0.101 20,662



PD_PM_KE_T14-1_Refresh 0.335 0.046 20,660

PD_PM_KE_T14-2_Fill_Subcategory 0.143 0.06 20,671

PD_PM_KE_T15_Select_Subcategory 0.101 0.042 20,674

PD_PM_KE_T16_Select_Area 0.509 0.104 20,675

PD_PM_KE_T17_AC_AssignmentGroup 0.044 0.022 20,675

PD_PM_KE_T18_Fill_AssignmentGroup 0.029 0.024 20,681

PD_PM_KE_T19_Move_To_Investigation 0.897 0.139 20,681

PD_PM_KE_T20_Move_To_Resolution 1.175 0.19 20,688

PD_PM_KE_T21_Move_To_Review 0.778 0.101 20,688

PD_PM_KE_T22_Link_New_KnownError 0.927 0.167 20,694

PD_PM_KE_T23_Save_New_KnownError 0.541 0.128 20,695

PD_PM_KE_T24_KnownError_Click_Close 0.114 0.042 20,701

PD_PM_KE_T25_KnownError_Click_Finish 0.61 0.122 20,700


PD_PM_KE_T26_Cancel_KnownError_Page 0.532 0.119 20,697

PD_PM_KE_T27_Cancel_Problem_Page 0.076 0.036 20,695

PD_PM_KE_T28_Click_Search_Problems 0.264 0.105 20,692

PD_PM_KE_T29_Click_Search 0.595 0.108 20,694

PD_PM_KE_T30_Visit_Task1 0.448 0.107 20,689

PD_PM_KE_T31_Cancel_Task1 0.118 0.039 20,683

PD_PM_KE_T32_Finish_Cancel_Task1 0.493 0.11 20,681

PD_PM_KE_T33_Cancel_Task1_Page 0.522 0.104 20,678





PD_PM_KE_T38_Click_Close_Problem 0.112 0.014 20,666

PD_PM_KE_T39_Finish_Close_Problem 0.786 0.109 20,666


PD_PM_KE_T41_Cancel_Problem_Search_Page 0.088 0.037 20,663

PD_RMWF1_Mass_T01_Click_Search_Request_Tasks 0.29 0.085 26,744

PD_RMWF1_Mass_T02_Search_Request_Tasks 0.843 0.157 26,741

PD_RMWF1_Mass_T03_Click_Mass_Update 0.158 0.035 26,737

PD_RMWF1_Mass_T04_Click_Activity 0.079 0.026 26,744

PD_RMWF1_Mass_T05_Activity_Next 0.081 0.022 26,745

PD_RMWF1_Mass_T06_Click_Description 0.057 0.021 26,749

PD_RMWF1_Mass_T07_Description_Next 0.078 0.022 26,750

PD_RMWF1_Mass_T08_Click_Impact 0.056 0.022 26,747

PD_RMWF1_Mass_T09_Impact_Next 0.071 0.011 26,752

PD_RMWF1_Mass_T10_Mass_Update 1.85 0.259 26,749

PD_RMWF1_Mass_T11_Click_Mass_Cancel 0.055 0.035 26,749

PD_RMWF1_Mass_T12_Mass_Cancel_1 0.085 0.027 26,749


PD_RMWF1_Mass_T14_Cancel_Task_Detail_Page 0.207 0.053 26,757

PD_RMWF1_Mass_T15_Cancel_Task_Search_Page 0.088 0.037 26,746

PD_RMWF1_T03_Click_Open_New_Request 0.16 0.047 26,730

PD_RMWF1_T04_Click_New_Employee_Onboarding 0.748 0.178 26,738

PD_RMWF1_T05_Click_Save_Request 1.041 0.168 26,738

PD_RMWF1_T06_Submit_for_Approval 3.019 0.345 26,736

PD_RMWF1_T07_Cancel_Request_Detail_Page 0.064 0.031 26,739

PD_RMWF1_T08_Click_Search_Requests 0.202 0.046 26,749

PD_RMWF1_T09_Search_Requests 0.619 0.12 26,751

PD_RMWF1_T10_Review 0.943 0.121 26,751

PD_RMWF1_T11_Click_Close 0.281 0.039 26,751

PD_RMWF1_T12_Close_Finish 0.918 0.111 26,751


PD_RMWF1_T14_Cancel_Request_Search_Page 0.062 0.029 26,754


PD_RMWF2_T04_Click_Order 0.697 0.11 45,291



PD_RMWF2_T05_Click_Tab_Tasks 0.235 0.062 45,273

PD_RMWF2_T06_Click_Task_ID 0.697 0.116 45,284

PD_RMWF2_T07_Update_Task_1 0.649 0.091 45,284

PD_RMWF2_T08_Click_Receive 0.104 0.029 45,286

PD_RMWF2_T09_Receive_OK 0.133 0.026 45,291

PD_RMWF2_T09_Receive_OK_2 0.488 0.111 45,286

PD_RMWF2_T10_Update_CMDB 0.82 0.123 45,286

PD_RMWF2_T11_Submit_to_CMDB 0.928 0.116 45,287

PD_RMWF2_T12_Review 0.816 0.127 45,288

PD_RMWF2_T13_Close_Task 0.205 0.023 45,288

PD_RMWF2_T14_Close_Task_Finish 0.735 0.108 45,292

PD_RMWF2_T15_Cancel_Task_Detail_Page 0.062 0.026 45,301

PD_RMWF2_T16_Close_Request 0.451 0.055 45,306

PD_RMWF2_T16_Close_Request_1 0.745 0.149 45,307

PD_RMWF2_T17_Close_Request_Finish 0.833 0.125 45,307


PD_SD_Inc_T01_Open_Streamlined_Interaction 0.184 0.04 42,860

PD_SD_Inc_T02_AC_Contact 0.056 0.019 42,858

PD_SD_Inc_T03_Fill_Contact 0.089 0.021 42,857

PD_SD_Inc_T04_Fill_Category_Incident 0.142 0.039 42,857

PD_SD_Inc_T05_Select_Subcategory_hardware 0.112 0.028 42,866

PD_SD_Inc_T06_Select_Area_hardware_failure 0.078 0.022 42,873

PD_SD_Inc_T07_AC_MyDevices 0.076 0.019 42,873

PD_SD_Inc_T08_Fill_MyDevices 0.027 0.02 42,867

PD_SD_Inc_T09_Continue_Escalate_Interaction 1.533 0.179 42,866

PD_SD_Inc_T10_Save_Incident 0.592 0.071 42,862

PD_SD_Inc_T11_Continue_New_Incident 0.866 0.107 42,869

PD_SD_Inc_T12_AC_Assignee_Incident_Coordinator 0.406 0.041 42,873

PD_SD_Inc_T13_Incident_Resolved 2.782 0.278 42,864

PD_SD_Inc_T14_Click_Close 0.222 0.019 42,864

PD_SD_Inc_T15_Close_Incident 1.478 0.169 42,866

PD_SD_Inc_T16_Cancel_Incident_Page 0.175 0.038 42,871

PD_SD_Inc_T17_Cancel_Interaction_Page 0.194 0.04 42,863

PD_SD_Inc_T18_Cancel_Interaction_Page_Yes 0.045 0.024 42,862

PD_SD_SD_T01_Create_Streamlined_Interaction 0.188 0.039 45,359

PD_SD_SD_T02_AC_Contact 0.059 0.017 45,360

PD_SD_SD_T03_Fill_Contact 0.089 0.02 45,359

PD_SD_SD_T04_AC_MyDevices 0.091 0.021 45,361

PD_SD_SD_T05_Fill_MyDevices 0.103 0.02 45,353

PD_SD_SD_T06_Fill_Category_Incident 0.206 0.048 45,354

PD_SD_SD_T07_Select_Subcategory_hardware 0.115 0.029 45,360

PD_SD_SD_T08_Select_Area_hardware_failure 0.078 0.019 45,364

PD_SD_SD_T09_Continue 1.551 0.181 45,364

PD_SD_SD_T10_Save 0.638 0.075 45,371



PD_SD_SD_T12_change_status_resolve 0.147 0.022 45,367

PD_SD_SD_T13_AC_and_Fill_Assignee 0.157 0.031 45,368

PD_SD_SD_T14_Save 1.904 0.216 45,364

PD_SD_SD_T15_Close 0.16 0.013 45,364

PD_SD_SD_T16_Finish 1.31 0.17 45,358

PD_SD_SD_T17_Cancel_Incident_Page 0.094 0.021 45,354

PD_SD_SD_T18_Cancel_Interaction_Page 0.073 0.028 45,354

PD_SD_SR_T01_Open_Streamline_Interaction 0.19 0.048 32,155

PD_SD_SR_T02_AC_Contact 0.1 0.024 32,162

PD_SD_SR_T03_Fill_Contact 0.098 0.027 32,154

PD_SD_SR_T04_AC_MyDevices 0.08 0.021 32,155

PD_SD_SR_T05_Fill_MyDevices 0.03 0.02 32,161

PD_SD_SR_T06_Fill_service_request 0.129 0.034 32,161

PD_SD_SR_T07_Select_Subcategory_Hardware 0.091 0.023 32,166

PD_SD_SR_T08_Continue 1.132 0.151 32,172

PD_SD_SR_T09_Request_Click_Order 0.69 0.123 32,171

PD_SD_SR_T10_Request_Save_New_Request 1.578 0.184 32,173

PD_SD_SR_T11_Request_Tab_Tasks 0.263 0.063 32,178

PD_SD_SR_T12_Request_View_Task 0.723 0.122 32,171

PD_SD_SR_T14_Request_Task_AC_Part_No 0.177 0.038 32,181

PD_SD_SR_T15_Request_Task_Fill_Part_No 0.392 0.097 32,182

PD_SD_SR_T16_Request_Task_AC_Ship_Location 0.058 0.019 32,185

PD_SD_SR_T17_Request_Task_Fill_Ship_Location 0.027 0.019 32,181

PD_SD_SR_T18_Request_Click_Cancel_Task 0.264 0.043 32,181

PD_SD_SR_T19_Request_Finish_Cancel_Task 0.791 0.14 32,177

PD_SD_SR_T20_Request_Cancel_Task_Page 0.075 0.036 32,183

PD_SD_SR_T21_Request_Click_Close 0.29 0.033 32,186

PD_SD_SR_T22-1_Request_Finish_Close 0.206 0.069 32,179

PD_SD_SR_T22-2_Request_Finish_Close_yes 0.909 0.142 32,170

PD_SD_SR_T23_Request_Cancel_Request_Page 0.09 0.022 32,170

PD_SD_SR_T24_Cancel_Interaction_Page 0.068 0.031 32,165


Appendix B: [AWS] Service Manager 9.63 CHO – PG 1500 user

example

Introduction




index.do Change Management 9.09% 146 Changes


Problem Management 9.09% 154 Problems, 154 known errors

Request Management 18.18% 523 Requests

Service Desk 27.27% 882 Interactions

ess.do Order from Catalog 9.09% 590 Tickets

Submit a request 9.09% 1795 Tickets

Deployment diagram

All the deployments follow the recommendations in this guide. For more information, refer to Service Manager deployment sizing and

Service Manager on AWS deployment sizing.

Hardware

The servers that were used for these tests are EC2, except for the database computer, which is a RDS.


ID Usage Type Instances Number CPU / MEM (Per Instances)

1 Load Balancers - Frontend application

2 Webtier - EC2 - Auto Scaling Groups t3.medium 5 2 CPU Cores / 4 GB

3 Load Balancers - Backend application

4 Server primary host - Auto Scaling Groups t3.medium 1 2 CPU Cores / 4 GB

5 Server secondary hosts - Auto Scaling Groups t3.medium 25 2 CPU Cores / 4 GB

6 PostgreSQL 10.7-R1 - RDS Database db.m5.4xlarge 1 16 CPU Cores / 64 GB

7 LoadRunner - EC2 c5.2xlarge 1 8 CPU Cores / 16 GB

Software




JDK – OpenJDK 1.8.0_181


RDS Database - PostgreSQL 10.7-R1

















Transaction Name SM963 1500 PG


PD_CM_SC_T01_Create_New_Change 0.203 0.171 10,374
































PD_CM_SC_T33_Order 0.448 0.061 10,393















PD_CM_SC_T47_Click_Close_again 0.153 0.027 22


















PD_ESS_Login 1.594 0.056 55,699

PD_ESS_Logout 0.178 0.013 41,903









































PD_Inc_T05_AC_Int 0.07 0.014 17,492













PD_Inc_T17_Open_Incident_Investigation_Task_from_WIP_to_PendingReview

0.572 0.033 17,512








PD_Inc_T25_Operator_Logout 0.192 0.029 5,826










PD_PM_KE_T07_New_Task_1 0.285 0.039 10,379




PD_PM_KE_T11_New_Task_2 0.269 0.028 10,385



PD_PM_KE_T14-1_Refresh 0.267 0.029 10,378




















PD_PM_KE_T31_Cancel_Task1_again 0.08 0.028 19


PD_PM_KE_T32_Finish_Cancel_Task1_again 0.361 0.017 19




PD_PM_KE_T35_Cancel_Task2_again 0.071 0.004 18





























PD_RMWF1_T10_Review 0.847 0.061 13,335

PD_RMWF1_T10_Review_again 0.811 0 1





PD_RMWF1_T15_Logout 0.189 0.025 4,384













PD_RMWF2_T12_Review 0.698 0.045 22,562








PD_RMWF2_T19_Logout 0.166 0.024 7,501




























PD_SD_SD_T10_Save 0.528 0.032 22,777





PD_SD_SD_T14_Save 1.59 0.084 22,780

PD_SD_SD_T15_Close 0.127 0.013 22,780

PD_SD_SD_T16_Finish 1.2 0.122 22,779



























Appendix C: Service Manager 9.63 CHO – Oracle 3000 user

example

Introduction





index.do Change Management 9.09% 287.7 Changes


Problem Management 9.09% 287.7 Problems, 287.7 known errors

Request Management 18.18% 997.9 Requests

Service Desk 27.27% 1670.5 Interactions

ess.do Order from Catalog 9.09% 1041.7 Tickets

Submit a request 9.09% 2634.3 Tickets

Deployment diagram


Hardware




1 SM Server – Primary

(loadbalancer + background + servlets)



48G


(servlets)



48G


(servlets)



48G



16G


24 CPU Cores


96G



16G



4G

Software







Oracle Database - Oracle Database 12c Enterprise Edition Release 12.2.0.1.0 - 64bit Production

















Transaction Name SM963 3000 Oracle

Avg Std. Deviation Pass PD_CM_SC_T01_Create_New_Change 0.187 0.073 20,714
































PD_CM_SC_T33_Order 0.594 0.114 20,751
































PD_ESS_Login 2.365 0.232 88,216

PD_ESS_Logout 0.253 0.03 63,234









































PD_Inc_T05_AC_Int 0.085 0.025 34,938













PD_Inc_T17_Open_Incident_Investigation_Task_from_WIP_to_PendingReview 0.714 0.124 34,968








PD_Inc_T25_Operator_Logout 0.298 0.057 11,661










PD_PM_KE_T07_New_Task_1 0.39 0.098 20,707




PD_PM_KE_T11_New_Task_2 0.364 0.09 20,723



PD_PM_KE_T14-1_Refresh 0.331 0.049 20,727




















































PD_RMWF1_T10_Review 0.967 0.138 26,624





PD_RMWF1_T15_Logout 0.247 0.039 8,842













PD_RMWF2_T12_Review 0.816 0.103 45,243








PD_RMWF2_T19_Logout 0.236 0.042 15,083




























PD_SD_SD_T10_Save 0.694 0.079 45,345




PD_SD_SD_T14_Save 1.974 0.21 45,333


PD_SD_SD_T15_Close 0.181 0.015 45,333

PD_SD_SD_T16_Finish 1.369 0.143 45,328



























Appendix D: Service Manager 9.62 CHO – Oracle 2500 user

example

Introduction



ID Module name User load distribution Throughput (per user per hour)

1 Change Management 16.68% 3.54 changes

2 Service Desk 16.64% 1.37 interaction

3 Incident Management 16.68% 1.65 incidents


4 Problem Management 16.64% 3.25 problems, 3.25 known errors

5 Request Management 16.68% 3.54 request

6 Service Catalog 16.68% 3.54 tickets

Deployment diagram


Hardware




1 SM Server – Primary Windows 2016 8 CPU Cores


32G

2 SM Server-Secondary Windows 2016 8 CPU Cores


32G



32G



32G


24 CPU Cores


96G



16G



16G

Software







Oracle Database - Oracle Database 12c Enterprise Edition Release 12.2.0.1.0 - 64bit Production















Transaction Name

SM962 2500 Oracle


Init_load_login_page 0.083 0.049 171,872

Init_login 3.294 0.186 171,784

CM_T001_click_new_change 0.154 0.028 107,844

CM_T002_select_emergency_RFC 0.827 0.075 107,825

CM_T003_change_click_save 1.29 0.076 107,801

CM_T004_change_cancel 0.07 0.022 107,777

CM_T005_click_search_changes 0.289 0.038 107,740

CM_T006_search_by_id 0.848 0.054 107,720

CM_T007_update_change_owner 1.022 0.062 107,696

CM_T008_update_risk&financial 0.973 0.06 107,669


CM_T010_change_cancel_search_page 0.608 0.045 107,610

IM_T002_click_new_incident 0.088 0.03 50,123

IM_T003_select_category_complaint 0.421 0.076 50,119

IM_T004_subcategory_click_fill 0.108 0.038 50,117

IM_T005_subcategory_select_service_delivery 0.087 0.028 50,103

IM_T006_area_select_availability 0.176 0.035 50,101

IM_T007_incident_click_save 0.94 0.095 50,088

IM_T008_incident_save_continue 0.722 0.079 50,082

IM_T009_incident_cancel 0.053 0.027 50,074

IM_T010_click_search_incidents 0.247 0.06 50,062

IM_T011_search_by_id 0.531 0.049 50,038

IM_T012_update_impact_urgency 0.73 0.053 50,035


IM_T014_search_by_impact_urgency 2.123 0.146 50,006


IM_T016_search_by_id 0.492 0.043 49,979

IM_T017_update_activities 0.644 0.055 49,968

IM_T018_update_expected_resolution_time 0.615 0.045 49,944

IM_T019_update_escalated 0.826 0.064 49,943


IM_T021_click_text_search 0.015 0.021 49,928

IM_T022_IR_search_by_text_all_words 1.097 0.062 49,909


IM_T023_IR_search_cancel 0.163 0.028 49,905

IM_T024_incident_cancel_search_page 0.614 0.049 49,895

PM_T002_click_new_problem 0.52 0.057 98,889

PM_T003_problem_click_save 2.254 0.133 98,871

PM_T004_problem_save_continue 0.655 0.052 98,848

PM_T005_problem_click_back 0.062 0.022 98,833

PM_T006_click_new_known_error 0.327 0.039 98,818

PM_T007_known_error_save 0.375 0.036 98,794

PM_T008_known_error_click_back 0.59 0.046 98,769

PM_T009_click_search_problems 0.214 0.036 98,742

PM_T010_search_by_id 0.482 0.04 98,708


PM_T012_problem_cancel_search_page 0.05 0.022 98,645

RF_T002_click_new_request 0.141 0.028 107,896

RF_T003_model_select_order_hardware 0.857 0.071 107,879

RF_T004_request_click_save 0.842 0.055 107,863

RF_T005_request_cancel 0.052 0.021 107,837

RF_T006_click_search_request 0.264 0.039 107,790

RF_T007_search_by_id 0.542 0.046 107,768

RF_T008_update_expected_finish_data 0.572 0.038 107,741

RF_T009_update_submit_for_approval 1.576 0.08 107,707


RF_T011_request_cancel_search_page 0.597 0.044 107,662

SC_T002_click_order_from_catalog 0.829 0.061 107,907

SC_T003_click_personal_productivity_services 0.908 0.06 107,875

SC_T004_click_hardware_bundles 0.687 0.048 107,858

SC_T005_click_basic_pc_package 0.205 0.025 107,837

SC_T006_click_add_to_cart 0.281 0.033 107,822

SC_T007_click_view_cart_checkout 0.083 0.017 107,807

SC_T008_click_submit_request 0.101 0.02 107,786

SC_T009_click_submit 1.454 0.08 107,769

SC_T010_click_submit_continue 0.053 0.021 107,764

SC_T011_refresh_toDO_queue 0.865 0.07 107,731

SD_T002_click_new_interaction 0.087 0.033 41,448

SD_T003_select_category_incident 0.481 0.106 41,447

SD_T004_contact_click_fill 0.088 0.04 41,450

SD_T005_contact_search_operators 0.213 0.032 41,446

SD_T006_subcategory_click_fill 0.093 0.035 41,444

SD_T007_subcategory_hardware 0.095 0.03 41,439

SD_T008_area_hardware_failure 0.2 0.029 41,428

SD_T009_service_click_fill 0.153 0.037 41,427

SD_T010_service_displayname_MyDevices 0.219 0.036 41,434

SD_T011_save_interaction 1.641 0.157 41,434

SD_T012_escalate_incident 0.475 0.057 41,434

SD_T013_click_create_new_incident 0.344 0.043 41,428

SD_T014_save_new_incident 0.871 0.089 41,429

SD_T015_cancel_incident_page 0.416 0.038 41,414


SD_T016_cancel_interaction_back 0.062 0.029 41,403

SD_T017_click_search_interactions 0.239 0.071 41,391

SD_T018_search_by_contact 0.875 0.073 41,380

SD_T019_search_by_contact_back 0.18 0.031 41,365

SD_T020_click_text_search 0.014 0.021 41,361

SD_T021_IR_search_by_text_all_words 1.104 0.067 41,339

SD_T022_IR_search_back 0.193 0.03 41,324

SD_T023_search_by_id 0.549 0.049 41,308

SD_T024_update_activities 0.741 0.056 41,293

SD_T025_update_to_resolved 1.325 0.093 41,277

SD_T026_click_close_interaction 0.094 0.027 41,255

SD_T027_close_interaction_finish 0.97 0.064 41,253

SD_T028_cancel_interaction_page_after_close 0.111 0.025 41,244

SD_T029_cancel_interaction_search_page 0.629 0.05 41,238

SD_T030_refresh_toDO_queue_page 0.235 0.154 41,224

End_logout 0.177 0.047 171,461


Appendix E: Service Manager 9.62 CHO – PostgreSQL 1500

user example

Introduction




1 Change Management 16.67% 2 changes

2 Service Desk 16.67% 1 interaction

3 Incident Management 16.67% 2 incidents

4 Problem Management 16.67% 1.9 problems, 1.9 known errors

5 Request Management 16.67% 1.9 request

6 Service Catalog 16.67% 1.9 tickets

Deployment diagram


Hardware





Intel(R) Xeon(R) CPU E5-2680v3 @ 2.50GHz

32G



32G



32G



32G

15 Database server CentOS Linux release 7.4.1708 (Core)

24 CPU Cores


96G



12G



16G

Software








PostgreSQL Database - PostgreSQL 10.5














Transaction Name

SM962 1500 PostgreSQL


Init_load_login_page 0.173 0.487 21,072

Init_login 3.641 0.989 21,045

CM_T001_click_new_change 0.249 0.215 13,229

CM_T002_select_emergency_RFC 1.175 0.563 13,231

CM_T003_change_click_save 1.912 0.52 13,228


CM_T005_click_search_changes 0.395 0.293 13,234

CM_T006_search_by_id 1.278 0.421 13,238

CM_T007_update_change_owner 1.566 0.438 13,234

CM_T008_update_risk&financial 1.497 0.491 13,239


CM_T010_change_cancel_search_page 0.202 0.183 13,242

IM_T002_click_new_incident 0.15 0.162 6,163

IM_T003_select_category_complaint 0.697 0.485 6,166

IM_T004_subcategory_click_fill 0.179 0.252 6,168

IM_T005_subcategory_select_service_delivery 0.143 0.169 6,169

IM_T006_area_select_availability 0.281 0.163 6,163

IM_T007_incident_click_save 1.015 0.409 6,167

IM_T008_incident_save_continue 1.136 0.397 6,171


IM_T010_click_search_incidents 0.336 0.208 6,179


IM_T011_search_by_id 0.991 0.316 6,173

IM_T012_update_impact_urgency 1.114 0.311 6,172


IM_T014_search_by_impact_urgency 1.787 0.624 6,157


IM_T016_search_by_id 0.931 0.293 6,158

IM_T017_update_activities 1.009 0.346 6,149

IM_T018_update_expected_resolution_time 0.987 0.397 6,142

IM_T019_update_escalated 1.331 0.49 6,134


IM_T021_click_text_search 0.035 0.123 6,126

IM_T022_IR_search_by_text_all_words 1.238 0.375 6,122

IM_T023_IR_search_cancel 0.215 0.188 6,117

IM_T024_incident_cancel_search_page 0.208 0.179 6,122

PM_T002_click_new_problem 0.767 0.343 12,211

PM_T003_problem_click_save 1.402 0.365 12,221

PM_T004_problem_save_continue 0.944 0.381 12,226


PM_T006_click_new_known_error 0.483 0.211 12,223

PM_T007_known_error_save 0.612 0.239 12,216

PM_T008_known_error_click_back 0.177 0.14 12,202

PM_T009_click_search_problems 0.305 0.251 12,204

PM_T010_search_by_id 0.741 0.302 12,199


PM_T012_problem_cancel_search_page 0.085 0.158 12,197

RF_T002_click_new_request 0.236 0.256 13,267

RF_T003_model_select_order_hardware 0.975 0.348 13,257

RF_T004_request_click_save 1.333 0.371 13,250


RF_T006_click_search_request 0.365 0.264 13,240

RF_T007_search_by_id 0.817 0.331 13,244

RF_T008_update_expected_finish_data 0.861 0.274 13,240

RF_T009_update_submit_for_approval 2.327 0.658 13,250


RF_T011_request_cancel_search_page 0.196 0.195 13,272

SC_T002_click_order_from_catalog 1.336 0.503 13,260

SC_T003_click_personal_productivity_services 1.354 0.577 13,252

SC_T004_click_hardware_bundles 1.079 0.49 13,249

SC_T005_click_basic_pc_package 0.3 0.171 13,241

SC_T006_click_add_to_cart 0.437 0.242 13,245

SC_T007_click_view_cart_checkout 0.112 0.106 13,250

SC_T008_click_submit_request 0.16 0.148 13,245

SC_T009_click_submit 2.324 0.698 13,247

SC_T010_click_submit_continue 0.084 0.139 13,253

SC_T011_refresh_toDO_queue 0.23 0.216 13,264

SD_T002_click_new_interaction 0.155 0.236 5,178

SD_T003_select_category_incident 0.716 0.389 5,175


SD_T004_contact_click_fill 0.134 0.249 5,178

SD_T005_contact_search_operators 0.339 0.218 5,183

SD_T006_subcategory_click_fill 0.155 0.238 5,177

SD_T007_subcategory_hardware 0.164 0.23 5,179

SD_T008_area_hardware_failure 0.313 0.179 5,177

SD_T009_service_click_fill 0.287 0.191 5,175

SD_T010_service_displayname_MyDevices 0.325 0.146 5,164

SD_T011_save_interaction 2.411 0.881 5,165

SD_T012_escalate_incident 0.676 0.201 5,117

SD_T013_click_create_new_incident 0.535 0.244 5,111

SD_T014_save_new_incident 1.437 0.508 5,106

SD_T015_cancel_incident_page 0.698 0.32 5,099

SD_T016_cancel_interaction_back 0.104 0.207 5,057

SD_T017_click_search_interactions 0.334 0.29 5,049

SD_T018_search_by_contact 2.568 0.477 5,043

SD_T019_search_by_contact_back 0.225 0.254 5,038

SD_T020_click_text_search 0.035 0.119 5,045

SD_T021_IR_search_by_text_all_words 1.229 0.399 5,050

SD_T022_IR_search_back 0.253 0.2 5,044

SD_T023_search_by_id 1.114 0.576 5,043

SD_T024_update_activities 1.245 0.543 5,048

SD_T025_update_to_resolved 2.146 0.765 5,052

SD_T026_click_close_interaction 0.145 0.155 5,058

SD_T027_close_interaction_finish 1.575 0.614 5,062

SD_T028_cancel_interaction_page_after_close 0.155 0.225 5,063

SD_T029_cancel_interaction_search_page 0.188 0.177 5,061

SD_T030_refresh_toDO_queue_page 0.113 0.194 5,059

End_logout 0.199 0.135 21,051


Appendix F: Service Manager 9.61 benchmark – Oracle 2500

user example

Introduction


different levels of user loads. The benchmark results are based on following user workload assumptions.


1 Change Management 16% 2 changes

2 Service Desk 17% 1 interaction

3 Incident Management 17% 2 incidents

4 Problem Management 16% 1.6 problems, 1.6 known errors

5 Request Management 16% 1.8 request

6 Service Catalog 16% 1.8 tickets

Deployment diagram


Hardware


The following table describes the configurations of these servers for the 2500 user benchmark tests.



Inter Xeon X5650 2.67GHZ

32G



32G



32G



32G

15 Database server Windows 2008 64-bit 24 CPU Cores


128G

16 Load Runner Controller Windows 2012 R2 Inter Xeon X5650 2.67GHZ 16G



16G

Software





JRE – JRE 1.8.



Oracle Database - Oracle Database 12c Enterprise Edition – 64-bit Production


The benchmark tests are considered successful when the following criteria are met:












Transaction Name

SM961 2500 Oracle


logout 0.306 0.142 6,081

SM961_CM_T001_click_new_change 0.274 0.189 3,753

SM961_CM_T002_select_emergency_RFC 1.536 0.826 3,753

SM961_CM_T003_change_click_save 2.171 0.824 3,753

SM961_CM_T004_change_cancel 0.11 0.09 3,753

SM961_CM_T005_click_search_changes 0.499 0.306 3,753

SM961_CM_T006_search_by_id 1.477 0.482 3,753

SM961_CM_T007_update_change_owner 1.654 0.611 3,753

SM961_CM_T008_update_risk_financial 1.538 0.524 3,753


SM961_CM_T010_change_cancel_search_page 0.138 0.123 3,753

SM961_IM_T002_click_new_incident 0.158 0.138 2,480

SM961_IM_T003_select_category_complaint 0.865 0.518 2,480

SM961_IM_T004_subcategory_click_fill 0.18 0.128 2,480

SM961_IM_T005_subcategory_select_service_delivery 0.16 0.102 2,480

SM961_IM_T006_area_select_availability 0.334 0.144 2,480

SM961_IM_T007_incident_click_save 1.088 0.503 2,480

SM961_IM_T008_incident_save_continue 1.337 0.544 2,480

SM961_IM_T009_incident_cancel 0.083 0.083 2,480

SM961_IM_T010_click_search_incidents 0.445 0.272 2,480

SM961_IM_T011_search_by_id 1.128 0.372 2,480

SM961_IM_T012_update_impact_urgency 1.181 0.428 2,480


SM961_IM_T014_search_by_impact_urgency 1.786 0.481 2,480


SM961_IM_T016_search_by_id 0.789 0.252 2,480


SM961_IM_T017_update_activities 1.229 0.481 2,480

SM961_IM_T018_update_expected_resolution_time 1.058 0.364 2,480

SM961_IM_T019_update_escalated 1.583 0.547 2,480


SM961_IM_T021_incident_cancel_search_page 0.122 0.097 2,480

SM961_Op_load_login_page 1.062 0.07 6,116

SM961_Op_login 4.569 1.387 6,115

SM961_PM_T002_click_new_problem 1.022 0.601 2,750

SM961_PM_T003_problem_click_save 1.064 0.553 2,735

SM961_PM_T004_problem_save_continue 1.16 0.504 2,735

SM961_PM_T005_problem_cancel 0.083 0.079 2,735

SM961_PM_T006_click_new_known_error 0.693 0.41 2,735

SM961_PM_T007_known_error_save 0.623 0.335 2,735

SM961_PM_T008_known_error_cancel 0.113 0.141 2,735

SM961_PM_T009_click_search_problems 0.387 0.235 2,735

SM961_PM_T010_search_by_id 1.014 0.365 2,735

SM961_PM_T011_problem_cancel 0.187 0.116 2,735

SM961_PM_T012_problem_cancel_search_page 0.081 0.09 2,735

SM961_RF_T002_click_new_request 0.25 0.16 3,784

SM961_RF_T003_model_select_order_hardware 1.191 0.637 3,784

SM961_RF_T004_request_click_save 1.552 0.636 3,784

SM961_RF_T005_request_cancel 0.072 0.074 3,765

SM961_RF_T006_click_search_request 0.509 0.342 3,708

SM961_RF_T007_search_by_id 1.066 0.367 3,708

SM961_RF_T008_update_expected_finish_data 1.069 0.42 3,708

SM961_RF_T009_update_submit_for_approval 2.625 0.861 3,708


SM961_RF_T011_request_cancel_search_page 0.119 0.128 3,708

SM961_SC_T002_click_order_from_catalog 1.442 0.629 3,730

SM961_SC_T003_click_personal_productivity_services 1.538 0.507 3,730

SM961_SC_T004_click_hardware_bundles 1.105 0.369 3,730

SM961_SC_T005_click_basic_pc_package 0.354 0.147 3,730

SM961_SC_T006_click_add_to_cart 0.538 0.364 3,730

SM961_SC_T007_click_view_cart_checkout 0.136 0.114 3,730

SM961_SC_T008_click_submit_request 0.186 0.128 3,730

SM961_SC_T009_click_submit 2.547 0.933 3,730

SM961_SC_T010_click_submit_continue 0.073 0.076 3,730

SM961_SC_T011_refresh_toDO_queue 0.114 0.099 3,730

SM961_SD_T002_click_new_interaction 0.155 0.131 1,768

SM961_SD_T003_select_category_incident 1.125 0.525 1,768

SM961_SD_T004_contact_ac_first 0.242 0.112 1,768

SM961_SD_T005_contact_ac_next 0.238 0.113 9,620

SM961_SD_T006_contact_ac_select_contact 0.381 0.164 1,768

SM961_SD_T007_subcategory_click_fill 0.183 0.11 1,768

SM961_SD_T008_subcategory_hardware 0.168 0.104 1,768

SM961_SD_T009_area_hardware_failure 0.367 0.177 1,768

SM961_SD_T010_service_ac_first 0.163 0.098 1,768


SM961_SD_T012_save_interaction 2.802 0.978 1,768

SM961_SD_T013_escalate_incident 0.991 0.45 1,768

SM961_SD_T014_click_create_new_incident 0.756 0.374 1,729

SM961_SD_T015_save_new_incident 1.936 0.737 1,729

SM961_SD_T016_cancel_incident_page 0.834 0.268 1,729

SM961_SD_T017_cancel_interaction_page 0.091 0.088 1,729

SM961_SD_T018_click_search_interactions 0.411 0.28 1,729

SM961_SD_T019_search_by_contact 1.781 0.504 1,729

SM961_SD_T020_search_by_contact_back 0.3 0.137 1,729

SM961_SD_T021_search_by_id 1.111 0.354 1,704

SM961_SD_T022_update_activities 1.048 0.354 1,704

SM961_SD_T023_update_to_resolved 2.383 0.72 1,704

SM961_SD_T024_click_close_interaction 0.217 0.232 1,704

SM961_SD_T025_close_interaction_finish 1.958 0.644 1,704

SM961_SD_T026_cancel_interaction_page_after_close 0.182 0.105 1,704

SM961_SD_T027_cancel_interaction_search_page 0.115 0.08 1,704

SM961_SD_T028_refresh_toDO_queue_page 0.087 0.142 1,704

SM961_workFlow_request 0.127 0.139 160,988

Appendix G: Service Manager 9.61 benchmark – PostgreSQL

1000 user example

Introduction


different levels of user loads. The benchmark results are based on following user workload assumptions.


1 Change Management 16% 2 changes

2 Service Desk 17% 1 interaction

3 Incident Management 17% 2 incidents

4 Problem Management 16% 1.9 problems, 1.9 known errors

5 Request Management 16% 1.9 request

6 Service Catalog 16% 1.9 tickets

Deployment diagram


Hardware


The following table describes the configurations of these servers for the 1000 user benchmark tests.





48G



24G



96G




16G

Software





JRE – JRE 1.8.


PostgreSQL Database - PostgreSQL 9.6.8


The benchmark tests are considered successful when the following criteria are met:












Transaction Name SM961 1000 PostgreSQL


logout 0.324 0.108 1,665

SM961_CM_T001_click_new_change 0.241 0.139 1,002

SM961_CM_T002_select_emergency_RFC 1.312 0.562 1,002

SM961_CM_T003_change_click_save 1.985 0.725 1,002


SM961_CM_T005_click_search_changes 0.417 0.204 1,002

SM961_CM_T006_search_by_id 1.39 0.363 1,002


SM961_CM_T007_update_change_owner 1.623 0.492 1,002

SM961_CM_T008_update_risk_financial 1.545 0.523 1,002


SM961_CM_T010_change_cancel_search_page 0.134 0.03 1,002

SM961_IM_T002_click_new_incident 0.131 0.085 500

SM961_IM_T003_select_category_complaint 0.701 0.25 500

SM961_IM_T004_subcategory_click_fill 0.155 0.086 500

SM961_IM_T005_subcategory_select_service_delivery 0.144 0.068 500

SM961_IM_T006_area_select_availability 0.301 0.063 500

SM961_IM_T007_incident_click_save 0.995 0.349 500

SM961_IM_T008_incident_save_continue 1.285 0.377 500

SM961_IM_T009_incident_cancel 0.071 0.021 500

SM961_IM_T010_click_search_incidents 0.402 0.191 500

SM961_IM_T011_search_by_id 1.548 0.328 500

SM961_IM_T012_update_impact_urgency 1.291 0.352 500


SM961_IM_T014_search_by_impact_urgency 1.656 0.321 500


SM961_IM_T016_search_by_id 1.13 0.181 500

SM961_IM_T017_update_activities 1.237 0.354 500

SM961_IM_T018_update_expected_resolution_time 1.049 0.264 500

SM961_IM_T019_update_escalated 1.552 0.379 500


SM961_IM_T021_incident_cancel_search_page 0.129 0.034 500

SM961_Op_load_login_page 1.048 0.014 1,676

SM961_Op_login 3.691 1.123 1,676

SM961_PM_T002_click_new_problem 0.923 0.418 1,002

SM961_PM_T003_problem_click_save 0.927 0.358 998

SM961_PM_T004_problem_save_continue 1.12 0.244 998

SM961_PM_T005_problem_cancel 0.073 0.023 998

SM961_PM_T006_click_new_known_error 0.616 0.095 998

SM961_PM_T007_known_error_save 0.597 0.117 998

SM961_PM_T008_known_error_cancel 0.105 0.017 998

SM961_PM_T009_click_search_problems 0.33 0.145 998

SM961_PM_T010_search_by_id 0.99 0.216 998

SM961_PM_T011_problem_cancel 0.165 0.037 998

SM961_PM_T012_problem_cancel_search_page 0.059 0.015 998

SM961_RF_T002_click_new_request 0.216 0.119 1,013

SM961_RF_T003_model_select_order_hardware 1.054 0.431 1,013

SM961_RF_T004_request_click_save 1.428 0.402 1,013


SM961_RF_T006_click_search_request 0.384 0.141 990

SM961_RF_T007_search_by_id 1.069 0.229 990

SM961_RF_T008_update_expected_finish_data 0.996 0.22 990


SM961_RF_T009_update_submit_for_approval 2.446 0.567 990

SM961_RF_T010_request_cancel 0.237 0.034 990

SM961_RF_T011_request_cancel_search_page 0.114 0.027 990

SM961_SC_T002_click_order_from_catalog 1.145 0.374 996

SM961_SC_T003_click_personal_productivity_services 1.158 0.338 996

SM961_SC_T004_click_hardware_bundles 0.944 0.315 996

SM961_SC_T005_click_basic_pc_package 0.306 0.086 996

SM961_SC_T006_click_add_to_cart 0.443 0.119 996

SM961_SC_T007_click_view_cart_checkout 0.113 0.033 996

SM961_SC_T008_click_submit_request 0.127 0.031 996

SM961_SC_T009_click_submit 2.454 0.698 996

SM961_SC_T010_click_submit_continue 0.057 0.012 996

SM961_SC_T011_refresh_toDO_queue 0.114 0.043 996

SM961_SD_T002_click_new_interaction 0.129 0.076 501

SM961_SD_T003_select_category_incident 1.033 0.337 501

SM961_SD_T004_contact_ac_first 0.129 0.053 501

SM961_SD_T005_contact_ac_next 0.125 0.057 2,802

SM961_SD_T006_contact_ac_select_contact 0.348 0.08 501

SM961_SD_T007_subcategory_click_fill 0.159 0.072 501

SM961_SD_T008_subcategory_hardware 0.153 0.08 501

SM961_SD_T009_area_hardware_failure 0.353 0.09 501

SM961_SD_T010_service_ac_first 0.143 0.071 501

SM961_SD_T012_save_interaction 2.678 0.804 501

SM961_SD_T013_escalate_incident 0.911 0.304 501

SM961_SD_T014_click_create_new_incident 0.727 0.138 494

SM961_SD_T015_save_new_incident 1.892 0.603 494

SM961_SD_T016_cancel_incident_page 0.807 0.163 494

SM961_SD_T017_cancel_interaction_page 0.078 0.023 494

SM961_SD_T018_click_search_interactions 0.359 0.178 494

SM961_SD_T019_search_by_contact 2.655 0.341 494

SM961_SD_T020_search_by_contact_back 0.268 0.041 494

SM961_SD_T021_search_by_id 1.346 0.226 494

SM961_SD_T022_update_activities 1.012 0.259 494

SM961_SD_T023_update_to_resolved 2.187 0.532 493

SM961_SD_T024_click_close_interaction 0.159 0.047 493

SM961_SD_T025_close_interaction_finish 1.755 0.434 493

SM961_SD_T026_cancel_interaction_page_after_close 0.164 0.031 493

SM961_SD_T027_cancel_interaction_search_page 0.123 0.021 493

SM961_SD_T028_refresh_toDO_queue_page 0.062 0.054 493

SM961_workFlow_request 0.113 0.097 43,870


Appendix H: Service Manager 9.60 benchmark – 10k user

example

Introduction

The goal of the benchmark test is to determine the system performance with 10,000 concurrent users. The user workload assumptions

are same as benchmark test for 2500 users.

Note:

The benchmark test is only performed on a Server Manager 9.60 environment. The test results are for your reference only, especially if

you use a different version of Service Manager 9.6x.

Deployment diagram

Our test environment for 10,000 concurrent users consists 12 Service Manager servers, 40 Tomcat instances (on two computers), 3

Apache instances (on one computer), and 1 database computer.

Hardware


The following table describes the configurations of these servers for the 10,000 user benchmark tests.



1 SM Server – Primary Windows 2012 R2 8 CPU Cores


32G

2 SM Server-Secondary Windows 2012 R2 8 CPU Cores


32G



32G



32G



32G



32G



32G



32G



32G



32G



32G



32G



32G



32G



128G


17 Apache HTTP Server(Load Balancer)



16G

Software


Micro Focus Load Runner 12.00

Apache Tomcat 7.0.57

Apache 2.2.29

JRE 1.8

Service Manager 9.60 GA Build

Oracle Database 12c Enterprise Edition (64-bit Production)


The 10,000 user benchmark tests are considered successful when the following criteria are met:


10,000 users simultaneously log in and are able to complete the recorded tests.



Compared with 2500 users response time the downgrade should less than 10%.


These actions will trigger ticket move to next phase.

Compared with 2500 users response time the downgrade should less than 15%.



Transaction name

SM9.60 10K

Avg Nb txn

PD_CM_SC_T01_Open_New_Change 0.368 1792

PD_CM_SC_T02_Select_Category_Standard 1.574 1792

PD_CM_SC_T03_AC_MyDevices 0.214 1792

PD_CM_SC_T04_Fill_MyDevices 0.092 1792

PD_CM_SC_T05_Click_Save_Change 2.416 1792

PD_CM_SC_T06_Request_Plan_and_Schedule 2.423 1792

PD_CM_SC_T07_AC_Change_Coordinator 0.277 1792

PD_CM_SC_T08_Fill_Change_Coordinator 0 1792

PD_CM_SC_T09_AC_Change_Owner 0.157 1792

PD_CM_SC_T10_Fill_Change_Owner 0 1792

PD_CM_SC_T11_Request_Authorization 5.405 1792

PD_CM_SC_T11_Request_Authorization_again 3.771 1792

PD_CM_SC_T12_Click_Tab_Tasks_1 0.607 1792

PD_CM_SC_T13_Click_First_Task 1.474 1792

PD_CM_SC_T14_Click_Close_Task_1 0.628 1792

PD_CM_SC_T15_Click_Finish_Task_1 1.372 1792

PD_CM_SC_T16_Cancel_Task_1 0.157 1792

PD_CM_SC_T17_Refresh_Change_1 1.585 1792

PD_CM_SC_T18_Request_PIR 4.206 1792

PD_CM_SC_T19_Click_Tab_Tasks_2 0.551 1792

PD_CM_SC_T20_Click_Second_Task 1.365 1792

PD_CM_SC_T21_Click_Close_Task_2 0.652 1792

PD_CM_SC_T22_Click_Finish_Task_2 1.386 1792

PD_CM_SC_T23_Cancel_Task_2 0.17 1792

PD_CM_SC_T24_Refresh_Change_2 2.172 1792

PD_CM_SC_T26_Link_Request 0.443 1792

PD_CM_SC_T27_Link_Request_Cancel 0.575 1792

PD_CM_SC_T27_Link_Request_Order 1.066 1792


Transaction name

SM9.60 10K

Avg Nb txn

PD_CM_SC_T28_Link_Change 1.228 1792

PD_CM_SC_T28_Link_Request_Save 0.772 1792

PD_CM_SC_T29_Link_Change_Software 2.028 1792

PD_CM_SC_T30_AC_MyDevices_2 0.154 1792

PD_CM_SC_T31_Fill_MyDevices_2 0.059 1792

PD_CM_SC_T32_Link_Change_Save 0.655 1792

PD_CM_SC_T33_Link_Change_Cancel 1.532 1792

PD_CM_SC_T34_Link_Change_Unlink 1.263 1792

PD_CM_SC_T35_Link_Change_Unlink_Yes 1.016 1792

PD_CM_SC_T36_Click_Tab_Calendar 0.53 1792

PD_CM_SC_T37_Click_Close 0.489 1792

PD_CM_SC_T38_Click_Close_Finish 2.398 1792

PD_CM_SC_T39_Cancel_Change 0.159 1792

PD_ESS_CatOrder_T02_Order_from_Catalog 1.752 5376

PD_ESS_CatOrder_T03_Personal_Productivity_Services 1.942 5376

PD_ESS_CatOrder_T04_Hardware_Bundles 1.49 5376

PD_ESS_CatOrder_T05_Basic_PC_Package 0.474 5376

PD_ESS_CatOrder_T06_Add_to_Cart 0.679 5376

PD_ESS_CatOrder_T07_View_Cart_Checkout 0.186 5376

PD_ESS_CatOrder_T08_Submit_Request 0.202 5376

PD_ESS_CatOrder_T09_Submit 3.429 5376

PD_ESS_CatOrder_T10_Continue 0.103 5376

PD_ESS_CatOrder_T11_Logout 0.391 1792

PD_ESS_Inc_T01_Click_SubmitRequest 0.503 10752

PD_ESS_Inc_T04_Submit_Request 2.785 10752

PD_ESS_Load_Login_Page 0.111 5376

PD_ESS_Login 2.761 5376

PD_ESS_Logout 0.324 3584

PD_Inc_T01_Click_Create_New_Incident 0.314 1792

PD_Inc_T01_Create_New_Incident 0.26 1792

PD_Inc_T02_Create_New_Incident 0.672 1792

PD_Inc_T02_Select_Category_Incident 0.992 1792

PD_Inc_T03_AC_MyDevices 0.181 1792

PD_Inc_T03_Click_Fill_Button 0.555 1792

PD_Inc_T04_Back_From_Fill 0.293 1792

PD_Inc_T04_Fill_MyDevices 0 1792

PD_Inc_T05_AC_Int 0.167 1792

PD_Inc_T05_Click_Save 1.358 1792

PD_Inc_T06_AC_Fill_Int 0.031 1792


Transaction name

SM9.60 10K

Avg Nb txn

PD_Inc_T06_Click_Continue 1.189 1792

PD_Inc_T07_AC_Subcategory 0.36 1792

PD_Inc_T07_Save_New_Incident 1.414 1792

PD_Inc_T08_Continue_to_Save_New_Incident 1.162 1792

PD_Inc_T08_Fill_Subcategory_hardware 0.281 1792

PD_Inc_T09_Change_status_from_Categorize_to_Assign 2.587 1792

PD_Inc_T09_Select_Area_hardware_Failure 0.793 1792

PD_Inc_T10_AC_Assignment_Group 0.121 1792

PD_Inc_T10_Chaneg_phase_from_Categorization_to_Investigation 1.979 1792

PD_Inc_T11_Fill_Assignment_Group 0 1792

PD_Inc_T11_Load_Category_for_Incident_Task 0.277 1792

PD_Inc_T12_Incident_Assign_Phase 2.101 1792

PD_Inc_T12_Open_new_Incident_task 0.461 1792

PD_Inc_T13_Incident_Work_In_Progress_Phase 2.529 1792

PD_Inc_T13_Save_Incident_Investigation_Task 0.807 1792

PD_Inc_T14_Incident_Cancle_page 0.119 1792

PD_Inc_T14_Open_Incident_Investigation_Task_DueDate 0.254 1792

PD_Inc_T15_Incident_Open_Search_Page 0.572 1792

PD_Inc_T15_Open_Incident_Investigation_Task_from_Ready_to_Assigned 2.5 1792

PD_Inc_T16_Incident_Search_1 1.307 1792

PD_Inc_T16_Open_Incident_Investigation_Task_from_Assigned_to_WIP 2.063 1792

PD_Inc_T17_Incident_Update_1 1.294 1792

PD_Inc_T17_Open_Incident_Investigation_Task_from_WIP_to_PendingReview 1.243 1792


PD_Inc_T18_Open_Incident_Investigation_Task_Prepare_Close 0.251 1792

PD_Inc_T19_Close_Incident_Investigation_Task_Close 1.186 1792


PD_Inc_T20_Go_back_to_Incident_page 0.782 1792


PD_Inc_T21_Change_phase_from_Investigation_to_Resolved 3.819 1792



PD_Inc_T22_Open_Incident_Close_page 0.427 1792

PD_Inc_T23_Close_Incident 2.801 1792

PD_Inc_T23_Incident_Link_New_Task 0.26 1792

PD_Inc_T24_Cancel_Incident 0.279 1792

PD_Inc_T24_Task_Select_Category_Investigation 0.385 1792

PD_Inc_T25_Operator_Logout 0.691 896

PD_Inc_T25_Save_Investigation_Task 1.269 1792


Transaction name

SM9.60 10K

Avg Nb txn

PD_Inc_T26_Task_Fill_Assignment_Group 0.575 1792

PD_Inc_T27_Incident_Task_Assign_Phase 1.122 1792

PD_Inc_T28_Incident_Task_Work_In_Progress_Phase 1.249 1792

PD_Inc_T29_Incident_Task_Pending_Review_Phase 1.402 1792

PD_Inc_T30_Incident_Task_Click_Close_Task 0.207 1792

PD_Inc_T31_Incident_Task_Close_Task 1.153 1792

PD_Inc_T32_Incident_Task_Cancel_Page 0.802 1792

PD_Inc_T33_Incident_Resolved_Phase 4.627 1792

PD_Inc_T34_Click_Close 0.311 1792

PD_Inc_T35_Close_Incident 2.658 1792

PD_Inc_T36_Cancel_Incident_Page 0.223 1792

PD_Inc_T37_Cancel_Incident_Search_Page 0.217 1792

PD_Load_Login_Page 0.202 8064

PD_Operator_Login 4.523 8064

PD_Operator_Logout 0.509 5376

PD_PM_KE_T01_Open_New_Interaction 1.267 1789

PD_PM_KE_T02_AC_MyDevices 0.14 1789

PD_PM_KE_T03_Fill_MyDevices 0.028 1789

PD_PM_KE_T04_Save_Problem 1.559 1789

PD_PM_KE_T05_Continue 1.087 1789

PD_PM_KE_T06_Link_New_Task_1 0.278 1789

PD_PM_KE_T07_New_Task_1 0.701 1789

PD_PM_KE_T08_Save_Task_1 0.95 1789

PD_PM_KE_T09_Cancel_Task_Page_1 0.925 1789

PD_PM_KE_T10_Link_New_Task_2 0.195 1789

PD_PM_KE_T11_New_Task_2 0.597 1789

PD_PM_KE_T12_Save_Task_2 0.927 1789

PD_PM_KE_T13_Cancel_Task_Page_2 0.951 1789

PD_PM_KE_T14_Fill_Subcategory 0.366 1789

PD_PM_KE_T15_Select_Subcategory 0.243 1789

PD_PM_KE_T16_Select_Area 0.815 1789

PD_PM_KE_T17_AC_AssignmentGroup 0.101 1789

PD_PM_KE_T18_Fill_AssignmentGroup 0.054 1789

PD_PM_KE_T19_Move_To_Investigation 2.046 1789

PD_PM_KE_T20_Move_To_Resolution 2.623 1789

PD_PM_KE_T21_Move_To_Review 2.472 1789

PD_PM_KE_T22_Link_New_KnownError 1.86 1789

PD_PM_KE_T23_Save_New_KnownError 1.215 1789

PD_PM_KE_T24_KnownError_Click_Close 0.367 1789


Transaction name

SM9.60 10K

Avg Nb txn

PD_PM_KE_T25_KnownError_Click_Finish 1.28 1789

PD_PM_KE_T26_Cancel_KnownError_Page 1.214 1789

PD_PM_KE_T27_Cancel_Problem_Page 0.156 1789

PD_PM_KE_T28_Click_Search_Problems 0.658 1789

PD_PM_KE_T29_Click_Search 1.279 1789

PD_PM_KE_T30_Visit_Task1 0.912 1789

PD_PM_KE_T31_Cancel_Task1 0.245 1789

PD_PM_KE_T32_Finish_Cancel_Task1 0.948 1789

PD_PM_KE_T33_Cancel_Task1_Page 1.246 1789

PD_PM_KE_T34_Visit_Task2 0.878 1789

PD_PM_KE_T35_Cancel_Task2 0.241 1789

PD_PM_KE_T36_Finish_Cancel_Task2 0.959 1789

PD_PM_KE_T37_Cancel_Task2_Page 1.227 1789

PD_PM_KE_T38_Click_Close_Problem 0.319 1789

PD_PM_KE_T39_Finish_Close_Problem 2.173 1789

PD_PM_KE_T40_Cancel_Problem_Page 0.288 1789

PD_PM_KE_T41_Cancel_Problem_Search_Page 0.197 1789

PD_RMWF1_Mass_T01_Click_Search_Request_Tasks 0.924 1006

PD_RMWF1_Mass_T02_Search_Request_Tasks 1.917 1006

PD_RMWF1_Mass_T03_Click_Mass_Update 0.367 1006

PD_RMWF1_Mass_T04_Click_Activity 0.21 1006

PD_RMWF1_Mass_T05_Activity_Next 0.151 1006

PD_RMWF1_Mass_T06_Click_Description 0.091 1006

PD_RMWF1_Mass_T07_Description_Next 0.132 1006

PD_RMWF1_Mass_T08_Click_Impact 0.089 1006

PD_RMWF1_Mass_T09_Impact_Next 0.132 1006

PD_RMWF1_Mass_T10_Mass_Update 3.72 1006

PD_RMWF1_Mass_T11_Click_Mass_Cancel 0.084 1006

PD_RMWF1_Mass_T12_Mass_Cancel_1 0.16 1006

PD_RMWF1_Mass_T13_Mass_Cancel_2 2.676 1006

PD_RMWF1_Mass_T14_Cancel_Task_Detail_Page 0.376 1006

PD_RMWF1_Mass_T15_Cancel_Task_Search_Page 0.182 1006

PD_RMWF1_T03_Click_Open_New_Request 0.45 1006

PD_RMWF1_T04_Click_New_Employee_Onboarding 1.8 1006

PD_RMWF1_T05_Click_Save_Request 2.71 1006

PD_RMWF1_T06_Submit_for_Approval 7.236 1006

PD_RMWF1_T07_Cancel_Request_Detail_Page 0.109 1006

PD_RMWF1_T08_Click_Search_Requests 0.389 1006

PD_RMWF1_T09_Search_Requests 1.512 1006


Transaction name

SM9.60 10K

Avg Nb txn

PD_RMWF1_T10_Review 3.039 1006

PD_RMWF1_T11_Click_Close 0.838 1006

PD_RMWF1_T12_Close_Finish 2.261 1006


PD_RMWF1_T14_Cancel_Request_Search_Page 0.109 1006

PD_RMWF1_T15_Logout 0.563 896

PD_RMWF2_T03_Click_Open_New_Request 0.335 1708

PD_RMWF2_T04_Click_Order 1.211 1708

PD_RMWF2_T05_Click_Save_Request 3.025 1708

PD_RMWF2_T05_Click_Tab_Tasks 0.537 1708

PD_RMWF2_T06_Click_Task_ID 1.521 1708

PD_RMWF2_T07_Update_Task_1 1.576 1708

PD_RMWF2_T08_Click_Receive 0.242 1708

PD_RMWF2_T09_Receive_OK 0.397 1708

PD_RMWF2_T09_Receive_OK_2 1.004 1708

PD_RMWF2_T10_Update_CMDB 1.63 1708

PD_RMWF2_T11_Submit_to_CMDB 2.127 1708

PD_RMWF2_T12_Review 1.638 1708

PD_RMWF2_T13_Close_Task 0.491 1708

PD_RMWF2_T13_Close_Task_again 0.438 1

PD_RMWF2_T14_Close_Task_Finish 1.373 1708

PD_RMWF2_T15_Cancel_Task_Detail_Page 0.143 1708

PD_RMWF2_T16_Close_Request 1.174 1708

PD_RMWF2_T16_Close_Request_1 1.62 1708

PD_RMWF2_T17_Close_Request_Finish 1.883 1708


PD_RMWF2_T19_Logout 0.486 896

PD_SD_Inc_T01_Open_Streamlined_Interaction 0.344 2688

PD_SD_Inc_T02_AC_Contact 0.109 2688

PD_SD_Inc_T03_Fill_Contact 0.124 2688

PD_SD_Inc_T04_Fill_Category_Incident 0.341 2688

PD_SD_Inc_T05_Select_Subcategory_hardware 0.248 2688

PD_SD_Inc_T06_Select_Area_hardware_failure 0.109 2688

PD_SD_Inc_T07_AC_MyDevices 0.182 2688

PD_SD_Inc_T08_Fill_MyDevices 0.035 2688

PD_SD_Inc_T09_Continue_Escalate_Interaction 3.476 2688

PD_SD_Inc_T10_Save_Incident 1.328 2688

PD_SD_Inc_T11_Continue_New_Incident 2.106 2688

PD_SD_Inc_T12_AC_Assignee_Incident_Coordinator 0.483 2688


Transaction name

SM9.60 10K

Avg Nb txn

PD_SD_Inc_T13_Incident_Resolved 5.734 2688

PD_SD_Inc_T14_Click_Close 0.453 2688

PD_SD_Inc_T15_Close_Incident 2.761 2688

PD_SD_Inc_T16_Cancel_Incident_Page 0.303 2688

PD_SD_Inc_T17_Cancel_Interaction_Page 0.254 2688

PD_SD_Inc_T18_Cancel_Interaction_Page_Yes 0.094 2688

PD_SD_SD_T01_Open_Streamlined_Interaction 0.323 2286

PD_SD_SD_T02_AC_Contact 0.112 2286

PD_SD_SD_T03_Fill_Contact 0.119 2286

PD_SD_SD_T04_AC_MyDevices 0.189 2286

PD_SD_SD_T05_Fill_MyDevices 0.032 2286

PD_SD_SD_T06_Fill_Category_Incident 0.326 2286

PD_SD_SD_T07_Select_Subcategory_hardware 0.246 2286

PD_SD_SD_T08_Select_Area_hardware_failure 0.106 2286

PD_SD_SD_T09_Continue 3.377 2286

PD_SD_SD_T10_Click_CloseDirectly 0.32 2286

PD_SD_SD_T11_Finish_Close_Incident 3.288 2286

PD_SD_SD_T12_Cancel_Incident_Detail_Page 0.135 2286

PD_SD_SD_T13_Cancel_Interaction_Detail_Page 0.071 2286

PD_SD_SR_T01_Open_Streamline_Interaction 0.412 1445

PD_SD_SR_T02_AC_Contact 0.439 1445

PD_SD_SR_T03_Fill_Contact 0.14 1445

PD_SD_SR_T04_AC_MyDevices 0.212 1445

PD_SD_SR_T05_Fill_MyDevices 0.035 1445

PD_SD_SR_T06_Fill_service_request 0.323 1445

PD_SD_SR_T07_Select_Subcategory_Hardware 0.146 1445

PD_SD_SR_T08_Continue 3.133 1445

PD_SD_SR_T09_Request_Click_Order 1.411 1445

PD_SD_SR_T10_Request_Save_New_Request 4.251 1445

PD_SD_SR_T11_Request_Tab_Tasks 0.621 1445

PD_SD_SR_T12_Request_View_Task 1.696 1445

PD_SD_SR_T14_Cancel_Interaction_Page_Yes 0.118 2286

PD_SD_SR_T14_Request_Task_AC_Part_No 0.37 1445

PD_SD_SR_T15_Request_Task_Fill_Part_No 0.648 1445

PD_SD_SR_T16_Request_Task_AC_Ship_Location 0.139 1445

PD_SD_SR_T17_Request_Task_Fill_Ship_Location 0.055 1445

PD_SD_SR_T18_Request_Click_Cancel_Task 0.698 1445

PD_SD_SR_T19_Request_Finish_Cancel_Task 1.839 1445

PD_SD_SR_T20_Request_Cancel_Task_Page 0.172 1445


Transaction name

SM9.60 10K

Avg Nb txn

PD_SD_SR_T21_Request_Click_Close 0.652 1445

PD_SD_SR_T22_Request_Finish_Close 2.111 1445

PD_SD_SR_T23_Request_Cancel_Request_Page 0.166 1445

PD_SD_SR_T24_Cancel_Interaction_Page 0.139 1445

PD_SD_SR_T25_Cancel_Interaction_Page_Yes 0.114 1445

rest_incident_create 1.117 0.934

soap_incident_create 1.017 0.519


Appendix I: Service Manager 9.60 SRC benchmark – 400 user

example

Introduction

This section provides customers with an SRC deployment sizing guide that is based on performance testing with 400 concurrent users.

The principles in this guide are based on critical data that has a real impact on SRC performance and on tests that were conducted by

the SRC Performance team. Recommendations in the Service Manager Service Request Catalog deployment sizing section are based

on results from Benchmark Performance testing. The volume of data in the Service Manager database is 1 million interactions.

Note:



Deployment topology

Please refer to the deployment diagram in the Deployment mode section.

Hardware

ID Usage Operating System CPU Memory

2 SM Server (Servlet) Windows 2012 R2 12 CPU Cores

Inter Xeon X5670 @ 2.93GHz

96G

5 Apache HTTP Server (Load Balancer)

Windows 2008 R2 SP1 4 CPU Cores

Inter Xeon E7-4890 V2 @ 2.80GHz

8G

2 Apache Tomcat Server Windows 2008 R2 SP1 8 CPU Cores


16G

3 Database server Windows 2012 R2 Standard

20 CPU Cores

Inter Xeon E7-4820 v3 @ 1.90GHz

128G

4 Load Runner Controller Windows 2008 R2 SP1 16 CPU Cores


16G

Test Configurations

JDK and Apache Tomcat specifications:

JDK 1.8.0_45 (64-bit)

Apache Tomcat 8.0.21 (64-bit)

Java virtual machine settings

Xms4096M -Xmx4096M

XX:PermSize=128M

XX:MaxPermSize=512M

Thread settings in server.xml:

maxThreads="600"

minSpareThreads="100"

acceptCount="575"

connectionTimeout="180000"


maxKeepAliveRequests="1000"

Dataset

Testing is based on 1,000,000 interactions, 6,000 Service Categories, over 20,000 catalog items, 10,000 subscriptions, 300,000 users

with Operator, SDA, and ESS roles in an Oracle 12c database. The data types that are critical to SRC performance are the service

category, Catalog Items, Interactions, and users.

Data type Volume Criteria

Change 100,000 • Login transaction server response time is not more than 10s.

• Typical transaction server response time is not more than 5s.

Company 3,000

Device 150,000

ESS 30,000

Interaction 1,000,000

Operator 6000

Request 100,000

SDA 6000

Service catalog 6,000

Service catalog item 27,000

Subscription 10,000

Survey 300,000

SRC settings

Configure the applicationContext.properties file as follow:

src.sm.defaultMaxConnectionsPerHost=60

src.sm.maxTotalConnections=60

src.refreshCatalogAfterEvery=36000

src.km.enabled=true

km.defaultMaxConnectionsPerHost=60

km.maxTotalConnections=60

sm.km.doctype.expireDuration=3600

src.requestedFor.editable=true

src.security.mode=default

src.security.secureLogin=false


Transaction Name Average 90 Percent

src_getAllCatalogCategories 9.447 12.597

src_login 1.833 2.153

src_logout 0.152 0.187

src_welcome 0.331 0.448



src02_01_autoComplete 0.013 0.015

src02_02_search 0.342 0.468

src02_03_pagination50 0.011 0.008

src02_04_item_details 1.016 1.233

src02_07_field1_1_initClick 0.335 0.427

src02_07_field1_2_nextPage 0.258 0.295


src02_08_field2_2_targetSearch 0.207 0.234


src02_09_field3_2_targetSearch 0.669 0.743


src02_10_field8_2_nextPage 0.293 0.334

src02_11_requestNow 0.007 0.006

src02_12_contactName_1_initClick 0.173 0.191

src02_12_contactName_1_Search 0.51 0.564

src02_13_uploadAttachment 0.016 0.016

src02_14_submit 2.075 2.348

src02_15_status 0.549 0.672

src02_17_postComments 0.537 0.653

src02_18_back2dashboard 0.202 0.235

src03_01_services 0.172 0.219

src03_02_yourApprovals 0.229 0.262

src03_03_sid_approval 0.761 0.914

src03_04_approval 0.809 0.952

src03_05_back_approval 0.219 0.25

src03_06_sid_deny 0.653 0.809

src03_07_deny 0.62 0.75

src03_08_back_deny 0.211 0.247

src03_09_pagnination50 0.582 0.717


src04_01_autoComplete 0.015 0.016

src04_02_search 0.302 0.38

src04_03_bundleDetails 0.939 1.149

src04_07_requestNow 0.01 0.009

src04_09_contact_initSearch 0.23 0.318

src04_10_contact_targetSearch 0.572 0.641

src04_11_submit 2.778 3.299

src04_12_status 0.58 0.717





src05_04_requestFor_1_initClick 0.235 0.287

src05_04_requestFor_2_targetSearch 0.556 0.611

src05_05_contactFor_1_initClick 0.177 0.197

src05_05_contactFor_2_targetSearch 0.512 0.563

src05_09_submit 1.193 1.453

src05_10_status 0.23 0.262


src05_12_updateButton 0.148 0.157

src05_13_update 0.689 0.815

src05_14_close 0.705 0.866

src05_15_close_back 0.235 0.298


src06_01_Services 0.173 0.206

src06_02_yourApprovals 0.221 0.251

src06_03_Change 0.145 0.166

src06_05_approve 0.563 0.702

src06_06_back_approval 0.192 0.211

src06_07_cid_deny 0.126 0.136

src06_08_deny 0.431 0.496

src06_09_back_deny 0.187 0.212

src06_10_pagination50 0.546 0.654


src07a_01_YourApprovals 0.239 0.28

src07a_02_rid_approval 0.252 0.294

src07a_03_approve 1.021 1.158

src07a_04_back_approve 0.214 0.244

src07a_05_rid_deny 0.212 0.228

src07a_06_deny 0.772 0.882

src07a_07_back_deny 0.206 0.233

src07a_08_pagination50 0.599 0.727

src07a_09_back2dashboard 0.211 0.241

src08_01_subscriptions 0.099 0.104

src08_02_active 0.099 0.11

src08_04_denied 0.052 0.055


src10_01_YourSurveys 0.125 0.139

src10_02_OpenSurveyId 0.078 0.094

src10_03_SubmitSurvey_NoInteraction 0.179 0.198

src10_04_SubmitSurvey_Complaint 0.183 0.2

src10_05_SendSurvey_Compliment 0.175 0.192



src10_06_Pagination50 0.206 0.247

src10_07_Pagination50_NextPage 0.174 0.22


Appendix J: Service Manager 9.60 Mobility benchmark – 1,000

user example

Introduction

Service Manager Mobility performed acceptably during testing and demonstrated good scalability. All of the response time goals, up to

the maximum tested concurrent user level of 1,000 users, were met. Additionally, there was a significant margin for increased workload.

Note:



Deployment topology

Please refer to the vertical scaling mode in the Deployment Mode section. In the R&D Lab, the Apache HTTP server and Tomcat

compose the clustering environment.

Hardware

No. Usage Configuration Operating system

1 Apache Server Virtual Machine, Xeon E7-4890 2.79GHz 4 cores / 4GB RAM Windows Server 2003, 64-bit

2 Tomcat Server Virtual Machine, Xeon E7-4890 2.79GHz 8 cores / 16GB RAM Win 2008, 64-bit

3 Primary SM Virtual Machine, Xeon E7-4890 2.79GHz 8 cores / 32GB RAM Windows 2012 R2

4 Secondary SM Server Virtual Machine, Xeon E7-4890 2.79GHz 8 cores / 32GB RAM Windows 2012 R2

5 LoadRunner computer Virtual Machine, Xeon E7-4890 2.79GHz 4 cores / 8GB RAM Win 2008, 64-bit

6 LoadRunner Generator Virtual Machine, Xeon E7-4890 2.79GHz 2 cores / 16GB RAM Win 2008, 64-bit

7 Oracle Database Physical machine, Xeon X5670 @2.93GHz 24 cores / 96GB RAM Linux, 64-bit

Software

All tests were conducted with the following software set:

Oracle 12c

Windows Server 2008 Enterprise (64-bit)

Windows Server 2003 Enterprise (64-bit) and Standard (32-bit) Editions

Micro Focus LoadRunner 11.50

Apache HTTP Server 2.2.22

Apache Tomcat Server 8.0.35 64-bit

Java 1.8 (64-bit)

Service Manager 9.60 GA Build



Transaction Name Transaction Response Time (in seconds)

Average 90 Percent

SM960_mobility_CM_T01_load_login_page 0.058 0.072

SM960_mobility_CM_T02_login 1.828 2.2

SM960_mobility_CM_T03_navigate_to_change 0.112 0.173

SM960_mobility_CM_T04_switch_to_awaiting_my_approval 0.217 0.257

SM960_mobility_CM_T05_load_next 0.06 0.091

SM960_mobility_CM_T06_activities 0.148 0.172

SM960_mobility_CM_T06_select_change 0.42 0.604

SM960_mobility_CM_T07_update_change 0.784 1.072

SM960_mobility_CM_T08_back 0.123 0.162

SM960_mobility_CM_T09_switch_to_assigned_my_groups 0.087 0.103

SM960_mobility_CM_T10_logout 0.214 0.301

SM960_mobility_CMA_T01_load_login_page 0.057 0.067

SM960_mobility_CMA_T02_login 1.824 2.217

SM960_mobility_CMA_T03_navigate_to_change 0.186 0.226

SM960_mobility_CMA_T04_switch_to_awaiting_my_approval 0.231 0.272

SM960_mobility_CMA_T05_select_first_change 0.604 0.789

SM960_mobility_CMA_T06_approve 2.253 3.006

SM960_mobility_CMA_T07_back 0.114 0.138

SM960_mobility_CMA_T07_logout 0.175 0.249

SM960_mobility_CMD_T01_load_login_page 0.065 0.072

SM960_mobility_CMD_T02_login 1.858 2.216

SM960_mobility_CMD_T03_navigate_to_change 0.185 0.232

SM960_mobility_CMD_T04_switch_to_awaiting_my_approval 0.229 0.27

SM960_mobility_CMD_T05_select_first_change 0.612 0.781

SM960_mobility_CMD_T06_deny 0.11 0.134

SM960_mobility_CMD_T07_deny_ok 1.541 2.126

SM960_mobility_CMD_T08_back 0.119 0.149

SM960_mobility_CMD_T09_logout 0.227 0.354

SM960_mobility_IM_T03_click_assigned_to_me_1 0.207 0.24

SM960_mobility_IM_T04_click_first_incident 0.318 0.417

SM960_mobility_IM_T05_work_in_progress 0.138 0.157

SM960_mobility_IM_T06_update_incident_1 0.649 0.858

SM960_mobility_IM_T07_click_back_1 0.082 0.098


SM960_mobility_IM_T09_search_incident_1 0.393 0.544

SM960_mobility_IM_T10_resolved 0.251 0.344

SM960_mobility_IM_T11_go_to_proposed_solution 0 0


Transaction Name Transaction Response Time (in seconds)

Average 90 Percent

SM960_mobility_IM_T12_update_incident_2 0.909 1.128

SM960_mobility_IM_T12_update_incident_2_reload 0.521 0.783



SM960_mobility_IM_T16_search_incident_2 0.31 0.416

SM960_mobility_IM_T17_click_close 0.186 0.316

SM960_mobility_IM_T17_click_close_reload 0.146 0.21

SM960_mobility_IM_T18_click_finish 0.901 1.54



SM960_mobility_SD_T01_load_login_page 0.057 0.069

SM960_mobility_SD_T02_login 1.797 2.174

SM960_mobility_SD_T03_navigate_to_interaction 0.223 0.266

SM960_mobility_SD_T04_sort_status 0.13 0.151

SM960_mobility_SD_T05_select_first_interaction 0.482 0.667

SM960_mobility_SD_T06_dispatched 0.129 0.153

SM960_mobility_SD_T07_update_interaction_1 0.934 1.165

SM960_mobility_SD_T08_back_1 0.129 0.15

SM960_mobility_SD_T08_search_interaction_1 0.472 0.66

SM960_mobility_SD_T08_search_interaction_selectFirst 0.294 0.412

SM960_mobility_SD_T09_resolved 0.135 0.159

SM960_mobility_SD_T10_update_interaction_2 0.846 1.085


SM960_mobility_SD_T11_back_2_again 0.095 0.109

SM960_mobility_SD_T12_search_interaction_2 0.283 0.396

SM960_mobility_SD_T12_search_interaction_2_selectFirst 0.286 0.365

SM960_mobility_SD_T13_close 0.115 0.156

SM960_mobility_SD_T14_finish_close 1.265 1.485


SM960_mobility_SD_T15_back_3_again 0.095 0.107

SM960_mobility_SD_T16_click_all_my_interactions 0.149 0.169

SM960_mobility_SD_T17_logout 0.183 0.252

SM960_mobility_T01_load_login_page 0.066 0.077

SM960_mobility_T02_login 1.591 1.988

SM960_mobility_T19_logout 0.145 0.202


Appendix K: Service Manager 9.60 Service Portal benchmark –

200 user example

Introduction

This section provides customers with benchmark results on SMSP portal. The environment is deployment under all-in-one mode, that

is, all SMSP services are deployed in a single server (virtual machine in the example). The results show good performance quality and

no obvious performance issues were found.

Note:



Deployment topology

Hardware


1 SMSP Server Virtual Machine, Xeon E7-L8867 2.79GHz 4 cores / 4GB RAM Windows Server 2003, 64-bit

2 LDAP Server Virtual Machine, Xeon E7-L8867 2.13GHz 8 cores / 16GB RAM Windows 2012 R2

3 SM Server Virtual Machine, Xeon E7-L8867 2.13GHz 8 cores / 32GB RAM Windows 2012 R2

4 Load Balancer F5 F5

5 LoadRunner Computer Virtual Machine, Xeon E7-L8867 2.79GHz 4 cores / 8GB RAM Win 2008, 64-bit

6 LoadRunner Generator Virtual Machine, Xeon E7-L8867 2.79GHz 2 cores / 16GB RAM Win 2008, 64-bit

7 Oracle Database Physical machine, Xeon X5670 @2.93GHz 24 cores / 96GB RAM Linux, 64-bit



Transaction name Transaction response time (in seconds)

Average 90 Percent

SMSP960_OrderMultiCatalog_T01_load_login_page 5.242 5.679

SMSP960_OrderMultiCatalog_T02_load_token 0.355 0.399

SMSP960_OrderMultiCatalog_T03_login_propel 3.247 3.487

SMSP960_OrderMultiCatalog_T04_enter_shop 2.622 4.102

SMSP960_OrderMultiCatalog_T05_popularService_see_all 0.958 1.128

SMSP960_OrderMultiCatalog_T06_popularService_select_random_item 1.131 1.265

SMSP960_OrderMultiCatalog_T07_configure_item 0.323 0.351

SMSP960_OrderMultiCatalog_T08_add_to_cart 0.866 1.19

SMSP960_OrderMultiCatalog_T09_continue_shopping 0.56 0.569

SMSP960_OrderMultiCatalog_T10_next_page_final 0.446 0.471

SMSP960_OrderMultiCatalog_T10_next_page_repeat 0.458 0.488

SMSP960_OrderMultiCatalog_T11_next_page_select_random_item 1.291 1.393

SMSP960_OrderMultiCatalog_T12_configure_item 0.667 0.737

SMSP960_OrderMultiCatalog_T13_add_to_cart 0.907 1.193

SMSP960_OrderMultiCatalog_T14_checkout 0.735 0.774

SMSP960_OrderMultiCatalog_T15_submit_all 0.343 0.559

SMSP960_OrderMultiCatalog_T16_return_my_application 1.575 1.808

SMSP960_OrderMultiCatalog_T17_logout_propel 0.898 1.039

SMSP960_OrderSingleCatalog_T01_load_login_page 5.355 5.694

SMSP960_OrderSingleCatalog_T02_load_token 0.359 0.413

SMSP960_OrderSingleCatalog_T03_login_propel 3 3.399

SMSP960_OrderSingleCatalog_T04_enter_shop 3.464 4.956

SMSP960_OrderSingleCatalog_T05_search_catalog_item 1.132 1.264

SMSP960_OrderSingleCatalog_T06_choose_first_item 1.12 1.275

SMSP960_OrderSingleCatalog_T07_configure_item 0.361 0.375

SMSP960_OrderSingleCatalog_T08_order_now 1.048 1.076

SMSP960_OrderSingleCatalog_T09_click_submit 0.404 0.636

SMSP960_OrderSingleCatalog_T10_click_order_num 0.43 0.562

SMSP960_OrderSingleCatalog_T11_check_order_until_pending_approval 14.006 19.674

SMSP960_OrderSingleCatalog_T12_return_my_application 1.759 1.994

SMSP960_OrderSingleCatalog_T13_logout_propel 0.805 0.912

SMSP960_RequestSupport_T01_load_login_page 5.35 5.647

SMSP960_RequestSupport_T02_load_token 0.364 0.427

SMSP960_RequestSupport_T03_login_propel 3.036 3.345

SMSP960_RequestSupport_T04_enter_support 3.559 4.868

SMSP960_RequestSupport_T05_select_random_item 1.675 1.923

SMSP960_RequestSupport_T06_submit_support_request 0.46 0.606


Transaction name Transaction response time (in seconds)

Average 90 Percent

SMSP960_RequestSupport_T07_check_ticket_created_in_sm 0.616 0.81

SMSP960_RequestSupport_T08_add_comment 0.33 0.373

SMSP960_RequestSupport_T09_return_my_application 1.568 1.987

SMSP960_RequestSupport_T10_logout_propel 0.832 1.059


Appendix L: Service Manager 9.60 Smart Analytics benchmark

– 1,000 user example

Introduction

This section provides the performance benchmark test results of Service Manager Smart Analytics 9.60 on Windows Server 2012 and

Oracle 12c.

Note:



Deployment topology

The Service Manager Smart Analytics 9.60 benchmark tests were conducted on a horizontally load-balanced configuration that was

running Oracle on Windows. All testing was conducted using the Service Management web client interface supported by the Apache

HTTP and Tomcat servers.

In our test environment for 1,000 concurrent users, there are three Service Manager server computers, ten Tomcat instances (on one

computer), one Apache instance (on one computer), one Load Runner computer, and Smart Analytics clustering with high scalability

deployment on virtual machines.


Hardware


The following table describes the configurations of these servers for the Service Manager Smart Analytics benchmark tests.

No. Usage Configuration Operating System

1 Apache Server VM, Xeon E7-L8867 2.13GHz 4 Cores / 4GB RAM Windows Server 2003, 64-bit

2 Tomcat Server x 10 node VM, Xeon E7-L8867 2.13GHz 8 Cores / 16GB RAM Windows Server 2008 R2

3 SM Server x 9 servlet VM, Xeon E7-4890 2.79GHz 8 cores / 32GB RAM Windows Server 2012



6 LR Computer VM, Xeon E7-L8867 2.13GHz 16 Cores / 16GB RAM Windows Server 2003, 64-bit

7 Oracle Database Physical machine, Xeon X5670 @2.93GHz 24 Cores / 96GB RAM

Windows Server 2008 R2

8 SMA Proxy Server VM, 4 cores / 4 GB RAM SUSE Linux Enterprise 11


No. Usage Configuration Operating System

9 SMA Smart Search Content Server x 2

VM, 8 cores / 8 GB RAM SUSE Linux Enterprise 11

10 SMA HTA Content Server x 2


11 SMA SMSP Content Server x 2


12 SMA Image Server VM, 8 cores / 8 GB RAM SUSE Linux Enterprise 11

13 SMAP Connectors & CFS VM, 8 cores / 8 GB RAM SUSE Linux Enterprise 11

Software

The Service Manager Smart Analytics 9.60 benchmark tests were run on the following software set:

Service Manager 9.60 GA


Windows Server 2003 Enterprise (32-bit) – for Apache



Apache Tomcat Server 7.0.54 64-bit

IDOL Daily build

Java 1.8 (64-bit)


Test configurations

The following scripts are covered in this test.

Smart Search scenario:

No. Step description Mapped LoadRunner transaction name

1 Log in SM as operators. @SM_GlobalSearch_T01_login

2 Click smart search to open global search widget. @SM_GlobalSearch_T02_open_global_search

3 Type in "*", and click search. @SM_GlobalSearch_T03_search_all

4 Repeat clicking next page for 3 times. @SM_GlobalSearch_T04_next_page

5 Search with one random key word. @SM_GlobalSearch_T05_search_one_key_word

6 Search with two random key words. @SM_GlobalSearch_T06_search_two_key_words

7 Search with three random key words. @SM_GlobalSearch_T07_search_three_key_words

8 Close global search widget. @SM_GlobalSearch_T08_close_global_search

9 Log out SM. @SM_GlobalSearch_T09_logout

Context search scenario:


1 Login SM as operators. @SM_ContextSearch_SD_T01_login

2 Expand Service Desk in left panel.

3 Click Create New Interaction. @SM_ContextSearch_SD_T02_click_create_new_interaction



4 Select category - incident. @SM_ContextSearch_SD_T03_select_category_incident

5 Click Suggested Solution to open context search. @SM_ContextSearch_SD_T04_open_context_search

6 Type in description and search (repeat for 10 times) @SM_ContextSearch_SD_T05_context_search

7 Click back to un-save interaction. @SM_ContextSearch_SD_T06_cancel_interaction_without_saving

8 Logout SM. @SM_ContextSearch_SD_T07_logout

Test data

5 million records from Micro Focus IT.


Transaction Name Transaction response time (in seconds)

Average 90 Percent

SM_ContextSearch_SD_T01_login 1.256 1.354

SM_ContextSearch_SD_T02_click_create_new_interaction 0.056 0.072

SM_ContextSearch_SD_T03_select_category_incident 0.159 0.217

SM_ContextSearch_SD_T04_open_context_search 0.115 0.15

SM_ContextSearch_SD_T05_context_search 2.951 3.843

SM_ContextSearch_SD_T06_cancel_interaction_without_saving 0.069 0.091

SM_ContextSearch_SD_T07_logout 0.097 0.117

SM_GlobalSearch_T01_login 1.574 1.498

SM_GlobalSearch_T02_open_global_search 0.125 0.161

SM_GlobalSearch_T03_search_all 3.019 4.358

SM_GlobalSearch_T04_next_page 3.025 4.414

SM_GlobalSearch_T05_search_one_key_word 0.914 2.058

SM_GlobalSearch_T06_search_two_key_words 1.202 2.502

SM_GlobalSearch_T07_search_three_key_words 1.479 2.779

SM_GlobalSearch_T08_close_global_search 0 0

SM_GlobalSearch_T09_logout 0.1 0.127


Appendix M: Service Manager 9.60 Collaboration benchmark –

400 user example

Introduction

This section provides the performance benchmark test results of Service Manager Collaboration on Windows Server 2008 and Oracle

12c. All response time are accepted in 400 concurrent users.

Note:



Results summary

Transaction Name SM 960 Chat

90 Percent Pass

ESS_Login_Page_Load 0.621 4,017

ESS_Logout 0.067 3,889

T01_ESS_Login 2.579 4,017

T02_Click_Chat_Diaglog_Icon 0 4,017

T03_Click_Start_Chat_Button 2.619 3,994

T04_Send_Yes_Message 0.024 3,989

T05_Send_Yes_Message 0.018 3,987

T06_Close_Chat_Dialog_Box 0 3,987

T07_Select_Reason 0 3,987

T08_Click_End_Chat_Button 1.366 3,889

Test environment

Hardware


1 Apache Server VM, Xeon E7-L8867 2.13GHz 4 Cores / 4GB RAM Windows Server 2003, 64-bit

2 Tomcat Server x 2 node VM, Xeon E7-L8867 2.13GHz 8 Cores / 16GB RAM Windows Server 2008 R2

3 SM Server x 9 servlet VM, Xeon E7-L8867 2.13GHz 8 Cores / 32GB RAM Windows Server 2008 R2

4 SM Server x 12 servlet VM, Xeon E7-L8867 2.13GHz 8 Cores / 32GB RAM Windows Server 2008 R2

6 LR Computer VM, Xeon E7-L8867 2.13GHz 4 Cores / 4GB RAM Windows Server 2003, 64-bit

10 Oracle Database Physical machine, Xeon X5670 @2.93GHz 24 Cores / 96GB RAM


11 IDOL Server VM, Xeon E7-L8867 2.13GHz 8 Cores / 32GB RAM Windows Server 2008 R2

Software

All tests were conducted with the following software set:




Windows Server 2003 Enterprise (32-bit) - for Apache



Apache Tomcat Server 7.0.54 (64-bit)

Java 1.8 (64-bit)



Appendix N: Service Manager 9.60 Survey benchmark – 400

user example Service Manager Survey end user module and Survey background scheduler are performed acceptably. All of the response time are

accepted.

Note:



Hardware

The servers that were used for these tests are virtual machines except that the Service Manager database is a physical machine.


2 SM Server(Servlet) Windows 2008 R2 8 CPU Cores

Inter Xeon E7-4890 V2 @80GHZ

32G

5 Apache HTTP Server(Load Balancer) Windows 2003 EE SP2 4 CPU Cores

Inter Xeon E7-4890 V2 @ 2. 80GHz

4G

2 Apache Tomcat Server Windows 2008 64-bit R2

8 CPU Cores

Inter Xeon E7-4890 V2 @ 2. 80GHz

16G

3 Database server Windows 2008 64-bit R2

24 CPU Cores


128G

4 Load Runner Controller Windows 2008 R2 SP1 16 CPU Cores


16G

Results summary

1. Service Manager Background Survey Scheduler performance testing results.

There are 10144 survey records to be sent to end user without any filter condition:

a. All these survey records to be sent will cost about 36 minutes. Therefore, the survey processing rate is about 281

records/minute in this data volume.

b. If the survey data volume is increased, the processing rate will be impacted. For example, send 400K survey records

will take about 71 hours.

2. Service Manager Survey end user performance testing results.

Transaction name Average Nb txn

ESS_Logout 0.14 400

T01_ESS_Login 2.677 400

T02_Open_Survey_Navigator 0 12025

T03_Click_View_Open_Survey 0.965 12025

T04_Click_First_Survey_Record 0.299 12025

T05_Choice_Survey_Answer 0.902 12025

T06_Submit_Survey 0.227 12025

T07_Click_Cancel 0.325 12025


T08_Click_Back 0.078 12025


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Service Manager 9.6x Deployment Sizing Guide Service Manager 9.6x Deployment Sizing Guide Page 7 Service Manager sizing questions The following list of questions is designed to gather

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