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Continuous deployment can be thought of as an extension of continuous integration and Continuous Delivery aiming at minimizing lead time, the time elapsed between development writing one new line of code and this new code being used by live users, in production.

To achieve continuous deployment, the team relies on infrastructure that automates and instruments the various steps leading up to deployment, so that after each integration successfully meeting these release criteria, the live application is updated with new code.

Instrumentation is needed to ensure that any suggestion of lowered quality results in aborting the deployment process, or rolling back the new features, and triggers human intervention.

Continuous Deployment Following the motto of Extreme Programming—if it hurts, do it more often—the logical extreme is to deploy every change that passes your automated tests to production. Of course it’s not just continuous deployment (I can continuously deploy to UAT all I like: no big deal). The crucial point is that it is continuous deployment to production. The idea is simply this: I take my pipeline and make the final step—deployment to production—automatic. That way, if a check-in passes all the automated tests, it gets deployed directly to production.

Change in Iteration and Release Plans for Continuous Deployments

  • Preventive Measures for Breakages in Production : In order for Continuous Deployments not to cause breakages, your automated tests have to be fantastic—there should be automated unit tests, component tests, and acceptance tests (functional and nonfunctional) covering your entire application. You have to write all your tests—including acceptance tests—first, so that only when a story is complete will check-ins pass the acceptance tests.
  • Release Plan changing to Canary Release Strategy : Continuous deployment can be combined with canary releasing by using an automated process that rolls out a new version to a small group of users first, rolling it out to all users once it has been determined (probably as a manual step) that there are no problems with the new version. The added safeguards provided by a good canary releasing system make continuous deployment an even less risky proposition.
  • Catering to Constraints and Compliances : Continuous deployment isn’t for everyone. Sometimes, you don’t want to release new features into production immediately. In companies with constraints on compliance, approvals are required for deployments to production. Product companies usually have to support every release they put out. However, it certainly has the potential to work in a great many places.
  • Managing Risk in the Release/Sprint Plan : The intuitive objection to continuous deployment is that it is too risky. But, as we have said before, more frequent releases lead to lower risk in putting out any particular release. This is true because the amount of change between releases goes down. So, if you release every change, the amount of risk is limited just to the risk inherent in that one change.
  • Release and Iteration Plan adding stories for Automations : Continuous deployment is a great way to reduce the risk of any particular release. Perhaps most importantly, continuous deployment forces you to do the right thing. You can’t do it without automating your entire build, deploy, test, and release process. You can’t do it without a comprehensive, reliable set of automated tests. You can’t do it without writing system tests that run against a production-like environment. That’s why, even if you can’t actually release every set of changes that passes all your tests, you should aim to create a process that would let you do so.

Release Plan catering to a Paradigm shift : Deployment pipelines are all about creating a repeatable, reliable, automated system for getting changes into production as fast as possible. It is about creating the highest quality software using the highest quality process, massively reducing the risks of the release process along the way. Continuous deployment takes this approach to its logical conclusion. It should be taken seriously, because it represents a paradigm shift in the way software is delivered. Even if you have good reasons for not releasing every change you make—and there are less such reasons than you might think—you should behave as if you were going to do so.