A software development life cycle is divided into several stages, out of which deployment is considered the last and most crucial phase. When the entire software is developed and tested with positive results, the codes need to be pushed into the production environment from the development or offshore environment. The process of transferring code from one environment to the other is known as deployment. DevOps considers deployment to be one of the major phases of the entire SDLC, which is why many new innovative methods have been introduced.
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Why are Traditional Deployment Procedures Ineffective?
Until the introduction of the DevOps process, deployment was done traditionally. Here, professionals gathered all codes, libraries, configurations, and other documents and uploaded them to the repository. Once all codes are committed, class files are given. These files are uploaded into the deployment software, which pushes the code further into the production environment.
If there is any issue in the class files or the deployment commands have glitches, issues will arise, and the server won’t be up till they are resolved. This was one of the main reasons professionals needed to integrate new deployment processes. Apart from this, DevOps professionals encountered a couple of more problems:
- If the code needs to be released into multiple environments simultaneously, it increases the load and introduces discrepancies.
- Often deployment processes get stuck with system exceptions or null pointer errors due to sudden changes in codes that are yet to be locked.
- While giving incremental class files for immediate code deployment, servers need to be shut down till the process is completed.
Top Innovative Deployment Practices for DevOps
With so many issues in the traditional deployment processes, it has become imperative for DevOps professionals to adopt innovative approaches. These can resolve the pain points of deployment processes and reduce server downtime. Over the years, several such approaches have been adopted, out of which the top ones are:
- Canary Deployment
- Recreate Deployment
- Blue-green Deployment
- A/B Testing Deployment
- Shadow Deployment
- Rolling Update Deployment
Brief Introduction of Deployment Strategies
Canary Deployment
Canary deployment is considered a staged release of codes into the target environment. For example, first, 25% of the developed software is made available to 10 users out of 100. The other 90 users will use the old, stable version of the software. Once the deployed codes are tested, and positive feedback, another 25% of codes are released into the same target environment. The process continues in the staged process, where a particular section of codes is rolled into production.
Pros:
- Reduces risks and failures
- Helps in receiving feedback on time.
- Reduces server downtime.
- Easy code rollback.
Cons:
- Time-consuming process.
- Increases deployment costs.
- Is more complex.
Recreate Deployment
In this deployment technology, two application versions are maintained. When version A is deployed, its corresponding server is bounced, but the server on which version B operates is up. A toggle is done between two servers until both versions of the entire software are deployed ultimately. In this methodology, server downtime is significant, and thus, one must consider it when uptime isn’t a performance metric.
Pros:
- Easier to process.
- Software updates are deployed simultaneously.
Cons:
- Increases server downtime.
Blue-Green Deployment
In this deployment strategy, two environments with identical features are used. One environment is used for staging or testing purposes and is marked as blue. Another environment is the production or live one and is marked as green. Codes are deployed in both environments. However, testing and QA are done in the blue environment mainly. Once the changes and updates are adopted and all bugs are fixed, traffic from the green environment is shifted to the blue one, and it is then considered the live version.
Pros:
- Easier to implement and operates faster.
- Rollback time is less.
- Harbors lesser risks of failures.
Cons:
- Costly process to setup
- Errors may appear during traffic shift.
A/B Testing Deployment
A/B testing deployment is done by routing codes to a specific group of users under specific conditions. Each user has to perform on different versions of the modified codes. Once the results are gathered, statistical analysis is performed to check which version is closer to the expected results. Only that particular software version will be rolled out into the deployment server.
Pros:
- Multiple software versions are tested parallelly.
- Distributes traffic evenly.
- Relies on statistics and hence, introduces more accuracy.
Cons:
- Needs a high-level load balancer for traffic routing
Shadow Deployment
In this technique, service requests are processed from the live environment and routed to the environment where new features have been deployed. This way, one can test the changes and their impacts in real-life scenarios without causing any impact on live customers.
Pros:
- Enables performance testing.
- No need to rollout codes multiple times.
- Doesn’t impact the live user.
Cons:
- Extremely complicated process.
- Needs duplicated environments
Rolling Update Deployment
In this deployment strategy, the codes and other snippets are added to a pool of software version A in the form of multiple instances. Now when the version B instance is deployed, it is added to the pool, and accordingly, one version A instance is removed. This continues till the pool is filled with new and updated version B instances. Once done, the instances are merged and deployed in a production environment.
Pros:
- Helps in testing and debugging due to instance deployment.
- Easier setup process.
Cons:
- Time-consuming process.
Summing up
The choice of deployment strategies depends on the software requirements, user profile, testing results, server downtime and uptime, and the overall project budget. For instance, most large projects implement the blue/green or recreate deployment strategies where two environment or server versions must be maintained respectively. Similarly, the canary deployment strategy seems more feasible for a smaller project.
Similarly, when the testing results are unstable, A/B testing deployment is a better option as it compiles all the testing reports and ensures only the most stable software version is rolled out into the production environment. Shadow deployment is also a growing model where testing and changes can be directly done in the production environment without affecting the live customers.
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