Docker:- Application Delivery Platform Towards Edge Computing

OPENNEBULA TECHDAY KUALA LUMPURMALAYSIA17 FEB 2016

Bukhary Ikhwan IsmailResearcher

Advanced Computing Lab

Application Delivery Platform Towards Edge Computing

Content

1. Motivation2. What is Edge Computing?3. Application Use cases4. Supporting Technology5. Demo

Motivation

• Current Trends

1. Explosive amount of data at the Edge• video, audio, smart devices, sensors or IoT

2. End users demands• better performance

• user experience

• Real time analysis

• We need a way to process data at its source to produce – fast results – real time analytics – for better decision making.

What is Edge Computing?• Pushes – application and data away from centralized nodes closer to the “things” (devices, users,

data).

• Characteristics of the Infra – Geo-distributed– Ideally – “One hop Away”– Generic platform - virtualization

• Benefits– Less data transfer - remove bottlenecks– Improves user QoS– Opportunity to improve OR create new app - Leverage resources that is closer to“things”.

Edge Computing Topology

This environment is characterized by:

Proximity low latency High bandwidth Location awareness

DCISPRANBUILDINGDEVICESThing

Own by TelcoBase station

Own by entitiesMalls, schools, clinics

Voluntary Computing Laptops, desktops, smartphones

ETSI – European Telecommunication Standards Institute

Performance : Is there a low latency requirement? E.g. gaming, safety

Data preprocessing opportunities:Does it make sense to compress or transmit selected data before transferring? e.g. Video Surveillance, traffic monitoring

Distributed application: Does processing at the edge is more attractive? E.g. smart city, monitoring, IoT?

Process locally: Is it better to process data at the edge vs. sending huge data to DC?e.g. Big Data, data cleansing

“Edge computing helps ensure that the right processing takes place at the right time and location” – CISCO

Attaining IoT Value: How To Move from Connecting Things to Capturing Insights Gain an Edge by Taking Analytics to the Edge. Andy Noronha Robert Moriarty Kathy O’Connell Nicola Villa. Cisco 2015

Application suitable at the Edge

Any suitable technology for Application Delivery?

• Light Weight Container Technology for application

• Open platform for developers and sysadmins to build, ship and run distributed app.

• Common use case

– Continuous Integration

– Continuous Delivery – build, deploy, test, release

– Infrastructure Optimization – hypervisor to container infra.

Docker

Docker as a Container System for code..

Docker Benefits• Build better software

– SoC – Developer vs. sysAdmin.

– Accelerate Development

• Eliminate env inconsistencies

• run anywhere

• Raspberry Pi supported

Why Docker for Edge Computing?• Docker Engine meets our needs for application delivery

– Application Provisioning• Simplifies distribution, installation & execution of app.

– Remote management• Easy to update • Pre-configured = easy to manage

– Can run on small devices• Lightweight & Small footprint

DEMO

12

Why Docker is suitable for Edge Computing

Demo context

13

Data Center

Site 1

Site 2 Site 3

Site 4

Video surveillance Remote app for users

Our Demo Context1. Discovery - Discover new devices and join the

platform2. Application Deployment3. Offloading example

Smart cities IoT

Demo 1: DiscoveryNew host

Form mesh network

Configure host

Join resourcePlatfor

m

DC-master

EDGE-node01 EDGE-node02

EDGE-node03

Demo 2: Deployment Simulation at School

EDGE at Remote School

Scenario 1:- Normal Setup

Scenario 2:- Scaling

EDGE-node01 EDGE-node02

LB

• Deploy Load Balancer• Deploy 2 LMS

• Reconfigure load balancer• Deploy additional LMS

DC-Mgmt

• LMS in VM requires 3GB (minimum). +/- 7 Minutes to be ready.

• App in a container would be up in seconds

2 containers 4 containers 8 containers 16 containers

0.29 0.510.97

2.60

Scaling CONTAINERSSE

CON

DS

Deployment Discussion – Fast Start Time

• Two contributing factors that makes it fast

VM

LMS 84 MBAPACHE/PHP 211 MB

Centos VM Image

2355 MB

LMS 84 MB

211MBAPACHE/PHP

181MBContainer

Centos minimal library

1st Factor: Image size

13X smaller

Deployment Discussion – Why is it fast?

Image

App 1

Ver. 1 (1MB)

Ver. 2 (3.4MB)

Ver. 3 (1.4MB)

App 2 (24MB)

App 3 (20MB)

Tomcat (50MB)

JDK (240MB)

APACHE/PHP

Centos

Benefits- Small changes to image.- Transfer only deltas (making transferring app faster)- lower storage usage.

Deployment Discussion – Why it is fast?• Two contributing factors that makes it fast

1st Factor: Image size: Layering

Image Transfer (3GB) VM Boot LMS

4 ~ 6 min 70 sec 2 sec

7 MinutesVM

Image Transfer LMS

20 sec 0.294 sec

Container 20.294 sec

0.294 sec

Cached Container 0.294 secLMS

2nd Factor: start sequence

Benefits1. EC – Generic platform - change app fast.

1. H. M. Patel, Y. Hu, P. Hédé, I. B. M. J. Joubert, C. Thornton, B. Naughton, I. Julian, R. Ramos, C. Chan, V. Young, S. J. Tan, and D. Lynch, “Mobile-Edge Computing-– Introductory Technical White Paper,” Sophia Antipolis, 2014.

Deployment Discussion – Why it is fast?• Two contributing factors makes it fast

Memory Storage0

10002000300040005000

4750

2650

113 475

VM Container

MB

Benefits1. Low footprint & lower resource consumption - edge consists of low end devices [2] .

1. European Telecommunications Standards Institute (ETSI), “Executive Briefing – Mobile Edge Computing ( MEC ) Initiative,” Sophia Antipolis, 2014

Reduce up to 97.62% in memory

Reduce up to 82.08% in storage

Deployment Discussion – Resource Foot Print

Sample Usecase: Mi-Morphe• Mi-Morphe - data cleansing application

– ETL (Extract Transform & Load)– Removes missing/undefined data– Remove duplicate data

Process locally: Is it better to run app OR process data at the edge instead of sending huge data to DC?

Method 1:- User upload data to Cloud

WAN

Cloud Datacenter

User Data

VMMi-morphe

Boot VM

Upload 5GB Data

Process Data

Download 5GB Data

Clone image

WAN

Cloud Datacenter

Mi-MorpheVM image

HypervisorDownload VM

image

VMMi-Morphe

Process Data

User Data

Method 2:- Download VM to user site

Solution – Offload Mi-Morphe to Data Source

WAN

Container Image

Mi-Morphe

edge03Offload container Image to the edge

resource ContainerMi-Morphe

Start Database, Apache Tomcat,

Carte Server

Process Data

Hostcloud01

Hostcloud-registry

User Data

Customer end-pointe.g..

Laptop/Desktop/Server

• Method 1: User Upload data to cloud

• Method 2: Download VM to user site

• Solution: Offload Mi-Morphe engine to data source.

Clone 10GB Image

5 minBoot

5 minUpload 5G of Data

73 minMi-Morphe Process

50 minDownload 5GB of Data

73 min 3H 26 min

Boot

5 minMi-Morphe Process

3000 secsDownload 10GB of VM

140 min 3H 15 min

Download 1.3 GB image

19 min:Launch Container Mi-Morphe Process

50 min 1H 9 min

• Reduce bandwidth usage on WAN. • Offload the applications to the edge. 1 hop away from compute resources.

Benefits:

Sample Usecase: Mi-Morphe

*19 min - but if the layers are cached, the time to download is much more smaller.

Some of Docker Ecosystem

We may use some of it

Conclusion• Docker is suitable for Edge Computing Application Delivery

– Docker as in Docker Engine

• Some of tools in Docker ecosystem – might help

• The orchestration platform is unique toward Edge. – Need to address those requirements.