CSC/ECE 517 Spring 2015/ch1a 4 RW: Difference between revisions

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<font size="5"><b>Blue-Green Deployment</b></font>
<font size="5"><b>Blue-Green Deployment</b></font>
='''Blue-Green Deployment'''=


Blue-Green deployment is a technique used to reduce risk and delay in continuous integration. It uses an exact copy of production environment, where new changes can be deployed and production testing can be done. After running successful tests, we can just point router to this copy and make it production. In case of any error in system after this step, we can roll back by re-pointing router to old application instance. This process reduces the production downtime during migration and expedite any rollback operation in case of error in production to last successful build.
Blue-Green deployment is a technique used to reduce risk and delay in continuous integration. It uses an exact copy of production environment, where new changes can be deployed and production testing can be done. After running successful tests, we can just point router to this copy and make it production. In case of any error in system after this step, we can roll back by re-pointing router to old application instance. This process reduces the production downtime during migration and expedite any rollback operation in case of error in production to last successful build.

Revision as of 19:51, 8 February 2015

Blue-Green Deployment

Blue-Green Deployment

Blue-Green deployment is a technique used to reduce risk and delay in continuous integration. It uses an exact copy of production environment, where new changes can be deployed and production testing can be done. After running successful tests, we can just point router to this copy and make it production. In case of any error in system after this step, we can roll back by re-pointing router to old application instance. This process reduces the production downtime during migration and expedite any rollback operation in case of error in production to last successful build.

Background

Software applications are becoming more and more complex nowadays. Software development life cycle is trying to adapt to this new paradigm by implementing ways to release new features/updates as frequently as they can be conceptualized. Agile methodology has reduced time for release of new piece of code. With application changes going into production at such a remarkable frequency, a need was felt to automate production deployment. More and more software development houses are using Continuous Integration (CI) nowadays. In continuous integration, a new piece of software is easily integrated into existing application code, and tested to make it ready for release. With continuous integration becoming a norm, continuous delivery is becoming a necessity. As per Martin Fowler, "Continuous Delivery is a software development discipline where you build software in such a way that the software can be released to production at any time". On an average, Amazon is pushing changes to production every 11.6 seconds. Google and Facebook are releasing frequent changes to production. Continuous delivery demands ability to automate deployment on production and create environment that can support frequent deployments. One of the challenges of automated deployment is to take software from test environment to live production. The new update may include a change in database schema as well. Updating existing production database server without bringing application down, is an arduous and risky task. Many business domains expect a minimum downtime for such updates, while maintaining a need for continuous delivery.
Blue-Green deployment provides a solution for continuous delivery by using two nearly identical production environments. One environment, which is in production at the moment is called Blue and other environment is called Green.

Green environment is used to deploy all the new updates and tested. After successful testing, router can be configured to route all the new requests to Green system. In case of any error in Green system, instead of using usual roll back mechanism, we can just point router to Blue system. There are few database consistency issues involved in such methods. There is a time delay between the moment, Green copy was generated from Blue system and the moment when Green was made live. Any change that took place on Blue system during this interval must be replicated on Green system. For database applications, this can achieved using modification scripts. Similarly, in case of error in Green system after making it live, we have to use modification scripts to bring consistency between Blue database an Green database. This process can not be completed without loosing information, if new features include database schema changes. Since database schema of Blue system and Green system differs, transferring new database changes may take a lot of time and it requires use of a complex and rigorous design.
Both these issues can be handled to a greater extent by making each system read-only during transition phase. Just before Blue environment is copied to Green, Blue can be made read only. Application can be up and running while certain/all write features can be blocked. After Green environment is tested for production and made live, we can keep it read only for a fixed amount of time. If any error occurs during this phase, then for roll back, all we have to do is point router to Blue environment and debug Green environment for error.

Advantages

Two basic necessities of a smooth production deployment is:

  • Nearly zero downtime
  • In case of error, immediate roll back from new version to older version


By using read only constraint on database during transition, Blue-Green deployment can be used to achieve almost zero down time. In case of error, roll back from new version to older version is almost immediate.

Disadvantage

Though Blue-Green deployment offers a nearly zero downtime solution for many applications which require continuous delivery and no downtime. In domains such as Banking, Retail and Social Networking, application downtime is unacceptable. Blue-Green deployment offers an acceptable solution but with a Read-Only constraint on database.
Space and computing requirements associated with Blue-Green deployment is a big discouraging factor. Maintaining two identical production environment requires a lot of resource. This requirement can put a considerable amount of financial burden on companies. In some cases, same machine can be used to host both the environment. Virtual machines can be used to maintain two separate identical environments. Lot of applications have huge databases and keeping two copies of databases during application deployment is a big financial commitment.

Conclusion

In the agile software development world, where continuous delivery is increasing becoming a necessity, Blue-Green deployment provides a solution with almost zero downtime. The performance provided by this methodology requires a huge financial commitment. Maintaining two separate production environment is a big investment. But in application domains, where continuous delivery and zero downtime is a necessity, this methodology should be used to achieve better results.