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Deploying OpenShift
On OpenStack
Diane Mueller

OpenShift Origin Community Manager
January 2014
OpenStack Meetup Seattle
@pythondj
noun ˈpī-ˌthän, -thən+ˈdē-ˌjā
Python + short for “Django”
a widely used general-purpose, a high-level Python Web
high-level programming framework that encourages rapid
............language development & clean design
Snake + Disk Jockey
a very large snake that kills the a person who plays popular
animals it eats by wrapping itself recorded music on the radio or at a
around them party or nightclub

A Snake Charmer
Red Hat's Cloud Ecosystem Evangelist
Agenda
●
●

Learn a little about PaaS & OpenShift
Learn a little about underlying PaaS
architecture

●
●

Talk about the Future of PaaS on OpenStack

●

3

Learn how to deploy OpenShift on OpenStack
Find out where to learn more
Deploying & Scaling OpenShift on OpenStack using Heat - OpenStack Seattle MeetUp 2014-01-23 by Diane Mueller @pythondj
FLAVORS OF
OPENSHIFT

Open
Source
Project

Public
Cloud
Service

5

origin

Onpremise
or Private
Cloud
Software
Deploying & Scaling OpenShift on OpenStack using Heat - OpenStack Seattle MeetUp 2014-01-23 by Diane Mueller @pythondj
Deploying & Scaling OpenShift on OpenStack using Heat - OpenStack Seattle MeetUp 2014-01-23 by Diane Mueller @pythondj
“Putting the PaaS in OpenStack”
Cross Community Collaboration

OpenStack

OpenShift
http://www.ohloh.net/
Why I love PaaS: It's Magic
SaaS/Applications Layer

Infrastructure Layer
10
IBM 1401 – the year I was born

http://www.computerhistory.org/
Deploying & Scaling OpenShift on OpenStack using Heat - OpenStack Seattle MeetUp 2014-01-23 by Diane Mueller @pythondj
First Job

http://www.computerhistory.org/
Deploying & Scaling OpenShift on OpenStack using Heat - OpenStack Seattle MeetUp 2014-01-23 by Diane Mueller @pythondj
Deploying & Scaling OpenShift on OpenStack using Heat - OpenStack Seattle MeetUp 2014-01-23 by Diane Mueller @pythondj
“SOFTWARE IS EATING
THE WORLD.”
Circa 1989 Predator vs. Prey
That's Disruptive Technology at Work
App Development Got Complicated
How to Build an App
Old School

20
Unhappy Developers
Then along came “Cloud”
Developer Expectations

●
●
●

23

Platform Flexibility
Application Portability
Increased Productivity
Infrastructure is not enough

24
Infrastructure as a Service gives you
•

Network, storage & compute as an on-demand service

•

Basically, servers in the cloud

•

You’re still on the hook to configure & manage the cloud & stack

“How do I use this?”
25
Software as a Service gives you
•

An on-demand application

•

Nothing to install or configure

“This is all my customers and users care about!”

26
Platform as a Service delivers
•

Application run-time environment in the cloud

•

Configures & manages both the cloud & stack for your
application

“The cloud is now useful!”
27
SaaS/Applications Layer

Infrastructure Layer
28
OpenShift Online (http://openshift.com)

30
OpenShift Origin on Github

http://openshift.github.io/

31
OpenShift Enterprise

ENTERPRISE IT MANAGED
●

●

32

Let developers have the benefits of self-service
PaaS while IT retains control for governance and
compliance in a Private or Hybrid Cloud
OpenShift Enterprise is designed to be deployed on
top of and run on Red Hat Enterprise Linux (RHEL).
What makes OpenShift different?
●

●

●

33

RHEL Platform
Support
SELinux-based Secure
Containers for multitenancy
Automatic Application
Scaling

●

●

●

Extensible
Architecture
System Component
Redundancy for High
Availability
Configurable
Deployment to Support
Enterprise
Requirements

●

●

●

Automatic Application
Stack Provisioning
Support for Java EE 6

Choice of Cloud
Infrastructure, Bare
Metal, or Desktop
Empowering Developers
to test, launch, fail, iterate, scale

RAPIDLY
35
https://install.openshift.com/

Deploying OpenShift
36
Origin Release 3
Fedora 19 or RHEL 6.x or CentOS 6.5
Get up and running
Vagrant
Puppet
Comprehensive guide
Ansible
Heat

http://openshift.github.io

37
OpenShift
Runs on IaaS
OpenShift PaaS

Amazon EC2

Bare Metal

OpenStack

38

Rackspace
RHEV

CloudStack
OpenShift Machines

An OpenShift Broker can manage multiple nodes

Broker
Broker
Broker

Node

Node

Nodes are where User applications live.

39
OpenShift Architecture
Broker

40
OpenShift Machines

An OpenShift Broker can manage multiple nodes

Broker
Broker
Broker

Node

Node

Nodes are where User applications live.

41
Applications and Gears
Node
Gear

Node
Gear

Gear

Jboss

MariaDB

User application

42

Jboss

Gear
Key OpenShift Terms
Broker – Management host, orchestration of Nodes
Node – Compute host containing Gears
Gear – Allocation of fixed memory, compute, and
storage resources for running applications
Cartridge – A technology/framework (PHP, Perl,
Java/JEE, Ruby, Python, MySQL, etc.) to build
applications

43
Architecture

44

44
https://install.openshift.com/

Deploying on OpenStack with Heat
45
Heat Overview
●

Entering OpenStack Integrated status in November 2013
–

Active code base
3048 commits as of September 2013
● 56 contributors
Cross Project functionality with OpenStack projects Keystone, Nova,
Neutron, Cinder, Ceilometer, Swift, Glance, Horizon, TripleO and Tempest
●

–

●

●

OpenStack Heat provides application autoscaling today with a stable workflow
model
OpenShift on OpenStack
–
–

46

OpenShift Enterprise Templates for RHEL ready
OpenShift Origin Templates for CentOS & Fedora in progress
Heat's Mission: Orchestration
To explicitly model the relationships between
OpenStack resources of all kinds; and to
harness those models, expressed in forms
accessible to both humans and machines, to
manage infrastructure resources throughout
the life-cycle of applications.

47
Heat Overview
Horizon
Dashboard
Heat
Orchestration
Keystone
Nova

Glance

Swift

Quantum

Cinder

Compute
Node

Image
Service

Object
Store

Networking

Volume
Service

●

Provides AWS Cloudformation and native ReST API

●

Abstract configuration of services to single-template

●

HA/Autoscaling/Monitoring features

●

Openstack integrated project

48

Identity
Service
OpenStack Heat Architecture

49
Heat API

50
OpenStack Heat Engine Architecture

51
Autoscaling
●

●

●

●

52

Metrics or user events drive scaling
Metrics can include CPU utilization, memory
utilization, many more as well as custom
dimensions
Dynamically add and reduce OS::Nova::Server
resources to meet demand
Front end Neutron LBAAS or Heat provided HAProxy Load Balancer distributes load to server
resources
Autoscaling Workflow – Internal View
●
●

●

●

53

User instantiates template with Heat's CLI
Heat registers with Ceilometer for callbacks on
Alarm events
Ceilometer tells Heat about Alarm events and
Heat scales a Group based upon a Policy
decision to scale up or down
OS::Nova::Server instances can also call
Alarms internally
OpenShift on OpenStack Autoscaling Workflow

http://github.com/openstack/heat-templates
54
Demo
Deploying OpenShift Enterprise
With Heat Templates
On
OpenStack

55
Learn more about Heat & OpenShift:
●

Users, testers and developers wanted!
–

Connect via IRC on #openshift-dev@freenode

–

Check out the repositories:

–

https://github.com/openstack/heat
https://github.com/openstack/heat-templates
https://github.com/openshift
Read the Heat Documentation:

–

http://docs.openstack.org/developer/heat
Read the OpenShift Documentation:
http://openshift.github.io

56
Future of PaaS

https://github.com/openshift/openshift-pep/blob/master/openshift-pep-010-docker-cartridges.md
http://docs.docker.io/en/latest/installation/kernel/
57
Future of PaaS on OpenStack
●

Solum initiative
–

●

also http://solum.io

Current efforts
–

Connecting Git to Solum
●

–

Building Images that can be run
●
●
●

58

Via project zuul (current OS tool for testing infrastructure)
Docker (normal image w/ docker pre-installed)
Normal Nova Images
Deploying & Scaling OpenShift on OpenStack using Heat - OpenStack Seattle MeetUp 2014-01-23 by Diane Mueller @pythondj
OpenShift Autoscaling Workflow
Step 1: Create DIB Elements
Building the broker image

Part 1: Parse Dependencies
[sdake@freedom openshift­origin­broker]$ more element­deps
openshift­origin­repos

Part 2: Load Dependencies
[sdake@freedom openshift­origin­repos]$ ls ­l pre­install.d
­rwxrwxr­x. 1 sdake sdake 286 Jun  2 12:14 29­puppetlabs­release
­rwxrwxr­x. 1 sdake sdake 648 Jun  2 12:14 30­openshift­origin­repos

Part 3: Configure Broker
[sdake@freedom openshift­origin­broker]$ ls ­l install.d
­rwxrwxr­x. 1 sdake sdake 1598 Jun  2 12:14 30­openshift­origin­broker

61
[sdake@freedom install.d]$ more 30­openshift­origin­broker
#!/bin/bash
set ­uex
install­packages 
    openshift­origin­broker 
    rubygem­openshift­origin­msg­broker­mcollective 
    rubygem­openshift­origin­dns­nsupdate 
    rubygem­openshift­origin­dns­bind 
    rubygem­openshift­origin­controller 
    openshift­origin­broker­util 
    rubygem­passenger 
    mod_passenger 
    openssh 
    rubygem­openshift­origin­auth­mongo 
    rubygem­openshift­origin­remote­user 
    rubygem­openshift­origin­console 
    openshift­origin­console 
    mongodb 
    mongodb­server 
    bind 
    bind­utils 
    ntpdate 
    policycoreutils 
    mcollective 
    httpd 
    openssh­server 
    rhc 
    activemq 
    activemq­client 
    git 
    puppet 
    ruby 
    ruby­devel 
    ruby­irb 
    

OpenShift Autoscaling Workflow
Step 1: Create DIB elements
Contents of 30-openshift-origin30-openshift-origin
    ruby­libs 
    tar 
    yum­plugin­priorities 
    mysql­devel 
    mongodb­devel 
    system­config­firewall­base 
    rubygem­execjs 
    rubygem­uglifier 
    rubygem­listen 
    rubygem­sass 
    rubygem­sass­rails 
    autogen­libopts 
    ntp 
    rubygem­coffee­script­source 
    rubygem­coffee­script 
    rubygem­coffee­rails 
    rubygem­idn 
    rubygem­addressable 
    rubygem­crack 
    rubygem­webmock 
    rubygem­fakefs 
    rubygem­chunky_png 
    rubygem­hpricot 
    rubygem­haml 
    rubygem­fssm 
    rubygem­compass 
    rubygem­compass­rails 
    rubygem­mongo 
    rubygem­jquery­rails 
    rubygem­openshift­origin­dns­avahi 
    rubygem­ref 
    rubygem­therubyracer
sed ­­in­place ­e 
   s/Type=oneshot/"Type=oneshotnTimeoutSec=0"/
  /lib/systemd/system/cloud­final.service

62
resources:
  OpenshiftUser:
    Type: AWS::IAM::User
  OpenshiftOriginKeys:
    Type: AWS::IAM::AccessKey
    Properties:
      UserName:
        Ref: OpenshiftUser
  OpenshiftOriginNodeGroup:
    Type: AWS::AutoScaling::AutoScalingGroup
    DependsOn: BrokerWaitCondition
    Properties:
      AvailabilityZones: []
      LaunchConfigurationName:
        Ref: NodeLaunchConfig
      MinSize:
        Ref: NodeCountMinimum
      MaxSize:
        Ref: NodeCountMaximum
      LoadBalancerNames: []
  OpenshiftOriginScaleUpPolicy:
    Type: AWS::AutoScaling::ScalingPolicy

OpenshiftOriginScaleDownPolicy:
    Type: AWS::AutoScaling::ScalingPolicy
    Properties:
      AdjustmentType: ChangeInCapacity
      AutoScalingGroupName:
        Ref: OpenshiftOriginNodeGroup
      Cooldown: '60'
      ScalingAdjustment: '­1'
  

OpenShift Autoscaling Workflow
Step 2: Create Heat Template - Policy

    Properties:
      AdjustmentType: ChangeInCapacity
      AutoScalingGroupName:
        Ref: OpenshiftOriginNodeGroup
      Cooldown: '120'
      ScalingAdjustment: '1'
  

Alarm
Policy
Group
63
OpenShift Autoscaling Workflow
Step 2: Create Heat Template - Alarms

  
  NodeScaleDown:
  NodeScaleUp:
    Type: AWS::CloudWatch::Alarm
    Type: AWS::CloudWatch::Alarm
    Properties:
    Properties:
      AlarmDescription: Scale­down if event received fr
      AlarmDescription: Scale­up if event received from broker
      MetricName: Heartbeat
      MetricName: Heartbeat
      Namespace: system/linux
      Namespace: system/linux
      Statistic: SampleCount
      Statistic: SampleCount
      Period: '60'
      Period: '60'
      EvaluationPeriods: '1'
      EvaluationPeriods: '1'
      Threshold: '0'
      Threshold: '0'
      AlarmActions: [{Ref: OpenshiftOriginScaleDownPoli
     AlarmActions: [{Ref: OpenshiftOriginScaleUpPolicy}]
      Dimensions:
      Dimensions:
      ­ Name: AutoScalingGroupName
      ­ Name: AutoScalingGroupName
        Value:
        Value:
          Ref: OpenshiftOriginNodeGroup
          Ref: OpenshiftOriginNodeGroup
      ComparisonOperator: GreaterThanThreshold
      ComparisonOperator: GreaterThanThreshold
  

Alarm
Policy
Group
64
OpenShift Autoscaling Workflow
Step 3: Register images with glance
[sdake@freedom heat­templates] glance image­create 
–name=openshift­origin­broker ­­disk­format=qcow2 
­­container­format=bare < openshift­origin­broker.qcow2

[sdake@freedom heat­templates] glance image­create 
–name=openshift­origin­node ­­disk­format=qcow2 
­­container­format=bare < openshift­origin­node.qcow2

66

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Notas do Editor

  1. What if you could use existing infractructure (bare metal or virtualized), private cloud, and public cloud in one, unified environment? Open hybrid cloud lets you take advantage of your existing resources, and be open to new advances. Build a cloud infrastructure that’s easy to integrate, agile, and future-proof. UNIVERSAL (UNIFIED?) ENVIRONMENT: An environment that is ready any time, all the time. Because it’s built with technology that is standardized, interoperable, and modular. This allows you to reuse the infrastructure you have to build more agile enterprise I.T.
  2. A bit about Heat: The Heat API implements the AWS Cloud Formations API. This API provides a rest interface for creating composite VMs called Stacks from template files. The goal of the software is to be able to accurately launch AWS CloudFormation Stacks on OpenStack. We will also enable good quality high availability based upon the technologies we created in Pacemaker Cloud including escalation.
  3. 1989 Prey: Meg Ryan – boutique book store Predator: Tom Hanks - “Fox” as a Stand in for Barnes &amp; Noble
  4. http://www.theguardian.com/media-network/media-network-blog/2013/nov/18/werner-vogels-cloud-trends-amazon 4 trends according to Werner Cloud will enable your content to follow you wherever you go Cloud has changed how we interact with mobile devices. In the past content would be moved to the device, now devices are just a window to content and services that live in the cloud. This started with our smartphones and tablets, where regardless of which device we use, or the location, we have access to our content and subscriptions. Now this approach is migrating to non-mobile devices such as Samsung smart TV&apos;s. The devices are beautifully designed and beautifully built, but the core functionally of these television sets is software connected to services running in the cloud. This is also moving beyond traditional devices, for example my car is already connected to my Amazon Cloudplayer giving me music everywhere I go. I have seen the first treadmills where the moment I step on them they reconfigure to give access to my music and videos, my newspaper subscriptions and books, but also my documents in services like Dropbox. I no longer need to bring my content; cloud enables my content to follow me wherever I go. Cloud based analytics enhances the offline world The cloud is already the place where researchers collaborate on data that flows in real-time from devices such as the Mars rover or the Ilumina DNA sequencer into cloud storage. In 2014 expect an explosion in data generation by real-world devices and where that data is stored, analysed and shared in the cloud. For example we will see a rise in the industrial cloud where industrial environments are equipped with sensors producing data to improve efficiency and reliability. An example is the project we run with GE on instrumenting their gas turbines or with Shell where they are going to drop sensors in their oil wells that generate petabytes of data. Also in our daily lives we will see the rise of cloud connected sensors and devices such as the Nest Thermostat or the home control applications built by energy companies like Essent. Around the world public transport companies are instrumenting their busses and trams with sensors that feed into platforms like OneBusAway that can give real-time updates to travellers. Passengers themselves can also become sensors: services like Mooveit use the information from an application on passengers&apos; phones to give real time transport information in the same way that Waze does for cars. The cloud allows everyone to become a media company In 2014 expect a great rise in organisations that are adding media capabilities to their offerings. A good example is sports clubs; all are looking for ways to establish an engagement with their fan base beyond the two hours on a weekend. A successful way to achieve a weeklong engagement is by daily distribution or fresh, exclusive media content. The subscription revenues for clubs that often have millions of fans around the world are substantial. Cloud based services for pre and post production, as well as distribution, are readily available such that anyone can become an internet broadcaster operating worldwide without any capital investment. A well-known case is that of the Amazon Web Services (AWS) powered LiverpoolTV, but every football club worldwide is following their example. Another very popular case is that of performing arts organisations, from orchestras to theatre companies, which give exclusive access to their performances through cloud-based media production. This way they are able to reach a much larger audience, which would often not be able to attend their performances in person. It extends their revenue potential, which is needed in times where arts subsidies are disappearing. A good example is Berliner Philharmoniker, the world famous orchestra that gives access to their live performances through the digitalconcerthall.com that makes use of all AWS regions around the world to provide a high quality media experience. Faster and faster, cloud moves data processing to real-time Up until this point big data has very much focused on looking historically - people who brought product X also brought product Y, the market moved in this direction last week so is likely to move in that direction now. There has always been a close relationship between big data and cloud computing as it requires no limits in terms of compute and storage but by adding real-time processing capabilities, we will see a rise in data analytics that are able to produce results for in real-time, radically changing the products companies can build. For example we see companies with real time recommendations, in the form of &apos;other people in your network are reading X&apos;. Some of the frontrunners here are the companies working on second-screen technologies, such as Channel 4, that make use of real-time data to power the information they present to augment TV watching. A company like Netflix that processes over 40bn events a day uses real-time analytics to power their operations, their customer engagement and their business metrics. We see almost every industry taking advantage of the cloud to radically improve the speed at which they can process their data. Werner Vogels is vice president and CTO at Amazon.com
  5. For either the Entrepreneurial or the Enterprise Developer, PaaS is the way of the future. Let&apos;s take a quick look at the before-and-after of the application development process. In the old days, when you wanted to build a new app (or were assigned a project to build a new app), you had to jump through a million hoops to get it up and running. Everything from ordering hardware, to installing middleware, to tuning and testing every facet of the development environment. With PaaS, life is much easier. You have an idea for an application? You just start writing the code and let OpenShift PaaS handle the rest. Write your code, Push to OpenShift, Test with Jenkins, and Deploy when ready! Even Gartner knows that PaaS will be the way of the future for application development.
  6. 61 So, what you need is the ease of use and access of a SaaS application, but you need it with your purpose-built, mission-critical, applications. PaaS gives you just that. It allows you to quickly and easily build the application that YOU need. Whether this is for your group, your enterprise, or your next BIG IDEA, you can build it and launch your specific code on a PaaS and not have to deal with the underlying infrastructure, middleware, and management headaches. Because of the built-in auto-scaling and elasticity provided by the PaaS infrastructure, PaaS&apos;s are ideal for modern data-hungry Big Data, Mobile, and Social applications. With a PaaS, you can focus on what you should be focused on... your application code. And let the Cloud provide what it is suppose to: Ease, Scale and Power
  7. 61 So, what you need is the ease of use and access of a SaaS application, but you need it with your purpose-built, mission-critical, applications. PaaS gives you just that. It allows you to quickly and easily build the application that YOU need. Whether this is for your group, your enterprise, or your next BIG IDEA, you can build it and launch your specific code on a PaaS and not have to deal with the underlying infrastructure, middleware, and management headaches. Because of the built-in auto-scaling and elasticity provided by the PaaS infrastructure, PaaS&apos;s are ideal for modern data-hungry Big Data, Mobile, and Social applications. With a PaaS, you can focus on what you should be focused on... your application code. And let the Cloud provide what it is suppose to: Ease, Scale and Power
  8. 61 So, what you need is the ease of use and access of a SaaS application, but you need it with your purpose-built, mission-critical, applications. PaaS gives you just that. It allows you to quickly and easily build the application that YOU need. Whether this is for your group, your enterprise, or your next BIG IDEA, you can build it and launch your specific code on a PaaS and not have to deal with the underlying infrastructure, middleware, and management headaches. Because of the built-in auto-scaling and elasticity provided by the PaaS infrastructure, PaaS&apos;s are ideal for modern data-hungry Big Data, Mobile, and Social applications. With a PaaS, you can focus on what you should be focused on... your application code. And let the Cloud provide what it is suppose to: Ease, Scale and Power
  9. Platform agnostic SELinux
  10. HIgh level - 2 types of machines
  11. KEY POINTS Heat provides a way of defining all your openstack resources / services from a single template Ties together the underlying IAAS services, so you can provide a consolidated infrastructure service, single integration point Compatible with AWS Cloudformation (templates and API) Has Autoscaling and HA features Recently became an incubated project
  12. KEY POINTS Lifecycle operations Create creates a stack from a template Delete deletes an existing instantiated stack Update updates an existing instantiated stack Introspection operations List obtains a list of existing stacks Describe obtains details of existing stacks Events List obtains events that have occurred for a stack List resources lists resources associated with a stack Template describes a stack
  13. Reasons to precreate images: Performance of scaling availability Reliability of not loading at runtime image contents