Strategies for Cloud Computing Application Deployment

As already mentioned in the last post, Application deployment in the Cloud is not an easy task. It requires a lot of work and knowledge, unless you use Platform as a Service. The later one might reduce this complexity significantly. In order to deploy your Applications to an Infrastructure as a Service Layer, you might need additional knowledge. Let us now built upon what we have heard from the last post by looking at several strategies and how they are implemented by different enterprises.

Some years ago before joining IDC, I worked for a local Software Company. We had some large-scale deployments in place and we used Cloud Services to run our Systems. In this company, my task was to work on the deployment and iteration strategy (but not only on that ;)). We developed in an agile iteration model (basically it was Scrum). This means that our Team had a new “Release” every 2 weeks. During these two weeks, new Features were developed and bugs fixed. The Testing department checked for Bugs and the development Team had to fix them. We enforced daily check-ins and gated them. A gated check-in means that the check-in is only accepted if the Source Code can be compiled on the Build Server(s). The benefit of this was to have a working Version every morning as some started early (e.g. 6am) and others rather late (e.g. at 10am). Before starting with that, our Teams often ran into the error of having to debug bad code that was checked in by someone the day before. Different teams worked on different Features and if the team decided a feature to be final, it was merged to the “stable” branch. Usually on Thursdays (we figured out that Fridays are not good for deployment for various reasons) we deployed the stable branch. The features initially get deployed to a staging system. The Operations Team tests the features. If a feature isn’t working, it has to be disabled and removed from the stable release. Once there was a final version with working features, we deployed them to the live system. This usually happened on Friday evening or Saturdays. Over the years, the Development and Operations Team got a real “Team” and less features had to be removed from the staging system due to errors/bugs. My task was to keep the process running since it was now “easy” to forget about the rules once everything seems to run good.

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A very advanced environment is Windows Azure. Windows Azure is Microsoft’s Cloud Platform and was usually designed as a PaaS-Platform. However, they added several IaaS-Features so far. In this post, I will only focus on the PaaS-Capapilities of Windows Azure. There are several steps involved:

  1. Full Package with Assemblies gets uploaded
  2. If a new Package is added, a Staging Environment is started. There is now the possibility to Test on that Staging Environment
  3. Once the Administrator decides the Package to be „safe“, Staging is switched to Production
  4. New Roles with the new Binaries are started
  5. Old Roles that still have Sessions are up and running until all Sessions are closed
Deployment for Windows Azure PaaS
Deployment for Windows Azure PaaS
This is a very mature deployment process and solves a lot of problems that are normally associated with deployment for large-scale Cloud Systems.
Facebook described their process for deployment very clear:
  1. Facebook takes advantage of BitTorrent
  2. New Versions of the Software gets added to a Tracker
  3. Each Server listens to the Trackers
  4. Once a new Version is available, it is downloaded to the Server
  5. The Server then unloads the current Version and Loads the new one
  6. Old Versions always stay on the Server
  7. Easy Rollback
Any Questions/Issues on deployment? Post your comments below.

Published by

Mario Meir-Huber

I work as Big Data Architect for Microsoft. With this role, I support my customers in applying Big Data technologies - mainly Hadoop/Spark - for their use-cases. I also teach this topic at various universities and frequently speak at various Conferences. In 2010 I wrote a book about Cloud Computing, which is often used at German & Austrian Universities. In my home country (Austria) I am part of several organisations on Big Data.

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