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Noel King – 10 July 2013

CloudStack enabled

Continuous Delivery

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Me

• Software engineer at Paddy Power

• Develop a PAAS solution for development teams

• Primarily Java developer• Mentor at CoderDojo

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Agile

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Lets review Dev process

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Dev now focused on single user story

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User story demo

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2 … n weeks later regression testing .. and

then …

Think we have a major performance issue

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Developer reaction!

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Yes fixed it quickly!

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Great its go live day

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Or its …

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Observations

• Business & Developers > Product to market quicker

• Go Lives still to big and risky• Production application

monitoring inadequate

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Could we do better – Behavioral change

• Automated testing• Automate environment provisioning• Smaller incremental releasing• Implement proper application

monitoring• Blue / Green releasing

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Use Case

haproxy > tomcat > mysql > app dynamics

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Continuous DeliveryPart 1:

Automate environment provisioning

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Automation with Cloudstack

• Create new VM’s as required• Bootstrap VM’s with the necessary

role• Update firewall rules as necessary• Scale based on demand• Automatically rebuild failed instances

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Continuous DeliveryPart 2:

Orchestrate release management

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Let’s automate from Check-in to Production

• Jenkins Build Pipeline plugin manages from check-in through to production– Unit tests– Integration test– Sonar– Artifactory– Acceptance– Performance– Live

• Every check-in is release candidate

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The must haves

• Set version number and create new git branch• Compile and run unit tests with Maven• Clone workspace for other jobs• Run integration tests with Maven• Run sonar analysis• Publish binary to artifactory• Failed tests / Inadequate test coverage / Sonar

alerts break build

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Acceptance + Performance

• Python Script– Create a new server with Cloudstack API– Retrieve IP address from Cloudstack API

• Chef – bootstrap server with role• Binaries from artifactory• Run acceptance tests using maven• Performance tests ran using JMeter• Teardown server with Cloudstack API

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Sample CloudStack API Call in Jenkins

import urllibobj = eval(urllib.urlopen("http://192.168.1.110:8096/client/api?command=deployVirtualMachine&zoneid=98c822f1-ef7a-4f57-8bce-bf955779e5f7&templateId=92c2d4ae-f2b9-4028-a331-d1b77cba6f74&hypervisor=KVM&serviceOfferingId=15ed9345-9e6d-43ec-8508-186a261b30f7&displayname=acceptance-test&name=acceptanc-test&response=json").read());

deployVirtualMachine

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Live

• Authorised promotion only• Can only be promoted if all

previous steps in the pipeline pass

• SSH onto production server and run a chef-client

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Kick ass App monitoring

App Dynamics

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Chef

"run_list": [ "recipe[mysql::server]", "recipe[mysql::runInitSql]", "recipe[java]", "recipe[appdynamicslite]", "recipe[tomcat]", "recipe[tomcat::jndi]", "recipe[tomcat::deployWar]", "recipe[haproxy]" ]

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Why stop here, what’s next?

• Logstash• Auto scheduled scaling• Knife cloudstack• Jenkins jclouds pluginMaybe cache service

–Memcached

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Questions

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NEED YOUR VOTE

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www.azuredevs.com