Elasticity Re-Imagined: Satisfy your Dynamic JD Edwards ...

Elasticity Re-Imagined: Satisfy your Dynamic JD Edwards Infrastructure and Processing NeedsJune 8, 2020

Senior Director of Product Management

Neil Pugh

Senior Architect of Product Development

Noel D’Costa

The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, timing, and pricing of any features or functionality described for Oracle’s products may change and remains at the sole discretion of Oracle Corporation.

Statements in this presentation relating to Oracle’s future plans, expectations, beliefs, intentions and prospects are “forward-looking statements” and are subject to material risks and uncertainties. A detailed discussion of these factors and other risks that affect our business is contained in Oracle’s Securities and Exchange Commission (SEC) filings, including our most recent reports on Form 10-K and Form 10-Q under the heading “Risk Factors.” These filings are available on the SEC’s website or on Oracle’s website at http://www.oracle.com/investor. All information in this presentation is current as of September 2019 and Oracle undertakes no duty to update any statement in light of new information or future events.

Safe harbor statement

http://www.oracle.com/investor

Elasticity Overview

Program agenda

1

2

3

4

Elastic JD Edwards

Container Orchestration

Demo

5 Q&A

Elasticity Overview

Program agenda

1

2

3

4

Elastic JD Edwards


Demo

5 Q&A

Copyright © 2020 Oracle and/or its affiliates.

Elasticity is your system’s ability to balance your ever changing processing requirements against the system resources needed to manage your workloads.

JDE on OCI Elasticity• Pay for what you use!• Workload Driven

• Auto-Scale• Autonomous DB• JDE Server Elasticity

• Docker Containers for Quick Spin up/down

Elastic Infrastructure for JD Edwards Planned

Why is Elasticity Important?

Simplify Patching

Reduce Cost

Automate to Scale

• Consolidate infrastructure

• Only pay for what you use

• Resource Efficiency of Docker vs VM

• Time to Market Efficiency

• Near Zero Downtime

• Blue-Green Deployment or Rolling Updates

• Simplify Management of Large Server Pools

• Significant Automation for JDE

• Spin up JDE trial systems in minutes

• Automated Dev/Test/Prod

• OCI Auto-scale capability with JDE


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• Rapid provisioning of instances - Development and test purposes

◦ Cloud, local desktop/laptop, private data center

- Training or Sandbox environments

- General disposable environments

• Elastic scale up/down- Increase or decrease the number of servers based the rules you

configure

- Improved infrastructure utilization based on usage or seasonality

- Highly available environments

- On-demand disaster recovery

• Blue-Green Deployment- Patch or Upgrade JD Edwards instances with near zero downtime.

Use case scenarios for JD Edwards Elasticity

Copyright – © 2020, Oracle and/or its affiliates. All rights reserved.

Planned

• Containers include the application and all its dependencies.

• They share the OS kernel with other containers.

• Virtual machines include the application, the required libraries, and a full guest OS.

• Full virtualization requires more resources.

VMs vs Containers

Copyright – © 2020, Oracle and/or its affiliates. All rights reserved.8

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• Docker is an open-source project for automating the deployment of applications as portable, self-sufficient containers that can run on the cloud or on-premises.

• A Docker container image is a lightweight, standalone, executable package of software that includes everything needed to run an application: code, runtime, system tools, system libraries and settings.

• Docker containers can run natively on Linux and Windows.

What is Docker?


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• Portability – build once run anywhere.

• Speed of deployment – Fewer resources, start quickly.

• Reduction in infrastructure costs - Run more services on the same hardware.

• Efficient storage and transfer using image layering.

• High degree of automation.

Benefits of containers


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What Docker Containers can do for your business


Image courtesy of docker.com

Elasticity Overview

Program agenda

1

2

3

4

Elastic JD Edwards


Demo

5 Q&A

JD Edwards Infrastructure Roadmap

20192016 2017 2018

• JDE Automation for OCI-C

• JDE Trial Edition Image for OCI-C

• JDE Payload for OCI-C

• Files to the Database

• Java Cloud Service for JDE

• SM Automation

• Simplified Upgrade to One Click Target OCI

• Improved Migration Utilities

• Automated Provisioning –Windows and iSeries

• JDE Reference Architecture Definition for OCI

• One Click Automation to Provision Reference Architecture OCI

• One Click Provisioning JDE Servers for OCI-C

• Object Tracking

• One Click Provisioning WLS and DB for JDE on OCI-C

• White Paper – HA & DR Scenarios for JDE on OCI-C

• White Paper – JDE on Baremetal Infrastructure OCI

• One Click Provisioning JDE on OCI

• One Click Support for Multiple DB Provisioning OCI

• JDE Trial Edition for OCI

• One Click Adoption of DBCS OCI

• JDE Infrastructure to Create Marketplace Images OCI

• Terraform Infrastructure Automation OCI

• Whitepaper – JDE Scalable Elastic Deployment (Autoscale)

• Server Manager Enablement for Orchestrator

2020+

• White Paper –Simplify and Automate JDE

• Server Manager Elasticity

• Certification for Manual Installation of ADB for OCI (Planned)

• Server Manager Scalability and Performance (Planned)

• Simplified Infra Patching (Planned)

• Virtual Batch Queues (Planned)


Continuous Stream of Innovation

Future

• Serialized Object Versioning (Planned)

• JDE SDK Node JS for Containers (Planned)

• ADB Feature Support (Planned)

• Grafana Web Based Monitoing of Cloud Components (Research)

Planned

14 Copyright – © 2020, Oracle and/or its affiliates. All rights reserved.

• Node.js SDK for JD Edwards REST APIs

• Automate the deployment of JD Edwards software components via Server Manager Console onto a container or VM

• Simplified management of JD Edwards via Server Manager REST APIs

• Orchestrations to automate JDE use cases such as creating users or password change.

JD Edwards SDK for Node.jsPlanned

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• Leverage One Click Utility for Base Image

• Build process is highly automated

• Scripts provided to create base container images with all pre-requisites that can be imported into the One-Click utility

• Docker build files provided for additional servers such as Orchestrator Studio, ADF, BSSV, RTE, BI

• Scripts provided to commit and push the images to a Docker

• Easily create and maintain multiple versions of container images

• Terraform and Ansible scripts to quickly replicate the containerized environments

• See whitepaper with detailed instructions.

Building JD Edwards E1 container images


White Paper

https://www.oracle.com/webfolder/technetwork/tutorials/jdedwards/White%20Papers/Deploying%20Containerized%20JD%20Edwards%20EnterpriseOne%20on%20Oracle%20Cloud%20Infrastructure.pdf


Autoscaling on OCI

The OCI autoscaling feature facilitates the replication of any of the JD Edwards EnterpriseOne container components based on the simple metrics of CPU or memory

The OCI elastic unit is a single instance that encompasses a single JD Edwards EnterpriseOne Enterprise Server and EnterpriseOne HTML or JAS Server as its container components

See whitepaper with details

White Paper

https://www.oracle.com/webfolder/technetwork/tutorials/jdedwards/White%20Papers/E1_Autoscaling_in_OCI_Cloud.pdf

Virtual Batch Queue (VBQ)Enhanced Report Management for EnterpriseOne 9.2

Key Drivers:

• Enact Single Batch Queue Properties Across Multiple Servers

• Elastic Batch Queue Server Scaling

• Supports Multiple Submission Methods

Value Solution:

• Establish “Virtual” Batch Cluster

• Utilize Batch Job Resubmission Solution – Job Detail Submitted to Database

• UBE Kernels Watch Job Table & Take Jobs as Available

• Output Centralized to Repository for Anytime/Anywhere Access


Planned

Oracle Autonomous Database for JD EdwardsLet the Database Do the Work


Data Management Challenges

• Manual provisioning and maintenance increases time to market

• Patching, scaling requires downtime impacts business momentum

• Data security, privacy and integrity affects brand reputation

• Limited data, different data sources causes lost revenue opportunities

Self-Driving

Save on Human LaborAutomates database and infrastructure management, monitoring, tuning

Self-Securing

Prevent Human ErrorProtects from both external attacks and malicious internal users

Self-Repairing

No Human InterventionProtects from all downtime including planned maintenance

Roadmap subject to change without notice. The above is intended

or information purposes and may not be incorporated into a contract.

Planned

Elasticity Overview

Program agenda

1

2

3

4

Elastic JD Edwards


Demo

5 Q&A

20

• Docker can build images automatically by reading the instructions from a Dockerfile

• A Dockerfile is a text document that contains all the commands a user could call on the command line to assemble an image

• Using docker build allows users to create an automated build that executes several command-line instructions in succession

- docker build -t $IMAGE_NAME $PATH

- docker build -t oracle/jde/ent:9.2.4.3-base .

• The docker commit command may also be used to commit the state of a running container to a new image

- docker commit “$CONTAINER_NAME” “$IMAGE_NAME”

- docker commit “jdeent” “iad.ocir.io/tenancy-name/jde/ent:9.2.4.3”

• Image can then be pushed to a Docker Registry (storage and distribution system for named Docker images)

- docker push “iad.ocir.io/tenancy-name/jde/ent:9.2.4.3”

Building a Docker container image


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• Leverage One Click Utility for Base Image

• Build process is highly automated

• Scripts provided to create base container images with all pre-requisites that can be imported into the One-Click utility

• Docker build files provided for additional servers such as Orchestrator Studio, ADF, BSSV, RTE, BI

• Scripts provided to commit and push the images to a Docker

• Easily create and maintain multiple versions of container images

• Terraform and Ansible scripts to quickly replicate the containerized environments

• See whitepaper with detailed instructions.

Building JD Edwards E1 container images


White Paper

https://www.oracle.com/webfolder/technetwork/tutorials/jdedwards/White%20Papers/Deploying%20Containerized%20JD%20Edwards%20EnterpriseOne%20on%20Oracle%20Cloud%20Infrastructure.pdf

22

• Container orchestration is all about managing the lifecycles of containers, especially in large, dynamic environments

• When you’re operating at scale, container orchestration—automating the deployment, management, scaling, networking, and availability of your containers—becomes essential.

• Software teams use container orchestration to control and automate many tasks:

• Provisioning and deployment of containers

• Scaling up or removing containers to spread application load evenly across host infrastructure

• Movement of containers from one host to another if there is a shortage of resources in a host, or if a host dies

• Allocation of resources between containers

• External exposure of services running in a container with the outside world

• Load balancing and routing

• Monitoring and health checking

• Rolling updates

Container orchestration


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• Compose is a tool for defining and running multi-container Docker applications

• Application’s services are defined in a Compose file (docker-compose.yml)

• Get an app running in one command- $ docker-compose up

• Convenient to orchestrate JD Edwards containers on a single Linux VM

Docker Compose


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• Pod – smallest unit that can be scheduled to be deployed through K8s

• Service – grouping of pods that are running on the cluster

• API server is the entry point for all the REST commands used to control the cluster

• kubectl is a command line interface for running commands against Kubernetes clusters

• etcd is a simple, distributed, consistent key-value store. It’s mainly used for shared configuration and service discovery.

• Scheduler - deployment of configured pods and services onto the nodes

• Controller-manager runs different kinds of controllers like Replication controller. A controller uses apiserver to watch the shared state of the cluster and makes corrective changes to the current state to change it to the desired one

• kubelet gets the configuration of a pod from the apiserver and ensures that the described containers are up and running

• kube-proxy acts as a network proxy and a load balancer for a service on a single worker node. It takes care of the network routing for TCP and UDP packets.

Kubernetes (k8s) high level architecture


Elasticity Overview

Program agenda

1

2

3

4

Elastic JD Edwards


Demo

5 Q&A

26

Demo: JDE running in a Kubernetes cluster on OCI


Link to Whitepaperwww.learnjde.com


https://apexapps.oracle.com/pls/apex/f?p=44785:24:0::::P24_CONTENT_ID,P24_PREV_PAGE:28080,1

Elasticity Overview

Program agenda

1

2

3

4

Elastic JD Edwards


Demo

5 Q&A

Q&A

Thank you!

Elasticity Re-Imagined: Satisfy your Dynamic JD Edwards ...

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