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From Vidya Sagar Kalvakunta <>
Subject Continuous Integration/ Continuous Deployment
Date Sat, 06 May 2017 19:14:54 GMT
Hello Dev,

I have worked on finding solutions to implement a cloud agnostic Continuous
Integration/Continuous Deployment Pipeline for Airavata.

For the Continuous Integration part, we have considered Travis CI and
Jenkins. They both come with their own pros and cons. But we found that the
fine-grained control that can be achieved using plugins to create complex
pipelines makes Jenkins better suited for Airavata's use case.

For continuous delivery, we have considered Spinnaker and Jenkins in
Master/Slave configuration.

Spinnaker operates on the principle of immutable infrastructure i.e, every
instance in the cluster is pre-baked with the applications that it is
supposed to run and is not modified in any way after it is deployed.
Whenever a new change is committed, a new immutable cluster is created and
replaces the existing cluster.

Though Spinnaker seems to be a full-fledged solution, it lacks proper
support and its installation process is difficult. Its concept of
constantly creating new instances and destroying old instances may not be
suitable for Airavata as we may need to reuse existing reserved
instances.Using Jenkins for Continuous Delivery using a master/slave
configuration seems to be the better option.

We have considered three deployment strategies for rolling updates.

   - In-place deployment
   - Red/Black or Blue/Green deployment
   - Canary Deployment

In-place deployment is the basic approach where we update each instance
sequentially. The potential drawbacks are the loss of availability of the
service during the upgrade cycle.

In Red/Black strategy, red is the color denoting the current production
cluster. Whenever a new update is committed, a new cluster which is denoted
by the black color is created. The black cluster will be running the
updated version of the application. The red cluster is slowly scaled down
to about 50% of its capacity while the black is scaled up to 50% of the
total capacity. Then the router switches all requests to the black cluster.
The red cluster is then kept alive for about 2 hours to make a switch back
in case of failures or bugs.

In Canary deployments, a very small cluster with the updated application is
created and 2% or so of the requests are routed to this cluster. All the
requests sent to the canary cluster are monitored to check if there are any
failures. If successful, the update is deployed using Red/Black Strategy.

Vidya Sagar

Vidya Sagar Kalvakunta | Graduate MS CS Student | IU School of Informatics
and Computing | Indiana University Bloomington | (812) 691-5002 |

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