AI can Revolutionize DevOps and Here is Why it is Important

The process of building software products is quite complex. There are many factors to consider when creating software that works and scales properly. From the ideation stage to production, deployment, and maintenance. Agile methodology has proven to make product development faster, reducing build time and getting the product to market as soon as possible. DevOps has come and made it easy to implement Agile in projects.

Artificial Intelligence is another area of technology that has been around for a long time, and it’s gradually being applied to different fields. AI makes it possible to take decisions from data, without defining rigid rules. AI can revolutionize DevOps, and in this article, you’ll see why that is the case.

What is DevOps?

DevOps is a set of practices, that involve a combination of software development and operations. These practices ensure that a project can transit smoothly and quickly from development to deployment, without compromising quality.

Continuous Integration and Continuous Deployment are critical aspects of DevOps that involves the testing of software, ensuring that it is fit for deployment. It also ensures that user feedback can be implemented on the product, and pushed to production in the shortest time possible. In short, it increases code velocity for enterprises which is the modern equivalent of saying productivity.

Automation is crucial to the success of DevOps. Hence, it is important to find ways to automate the routine tasks involved in software deployment. This way, more time can be spent on more mentally stimulating tasks and less on repeating tasks. 

At this point, the role AI can play in DevOps becomes clearer. In the next section, you’ll see why AI revolutionizing DevOps is important and can go a long way in improving productivity and efficiency.

Why is AI Important to DevOps

In DevOps, there is generation of a lot of data, especially in the logs. When something goes wrong with a deployment, or in production, the truth can be found in the logs. Artificial Intelligence thrives on data. Hence, in cases where there are too many scenarios to handle using logic, AI should be the go-to solution.

AI is important to DevOps for the following reasons:

• Prediction
• Automated Testing
• Scenario Generation

Prediction

When pushing software through the CI/CD pipeline, there are many things that can go wrong. So while the CI/CD process should be automated, a lot of time can be spent getting software to work as expected. With AI, predictions can be made on the possible problems during deployment, and those problems can be handled proactively rather than reactively. This makes the deployment process smoother, unlike the push and error-handling routine.

Automated Testing

It is important to test software appropriately before pushing to production. However, DevOps at the moment is restricted to properly-thought out tests. While this is great, it also means the tests are limited. However, with AI-powered DevOps processes, a large number of test scenarios become possible, even scenarios no one thinks about.

Scenario Generation

When software is in production, there are all kinds of scenarios that can happen. It is near impossible to handle them all. Software deployed in an environment that scales well is often considered to be free of issues. But this is often not the case in reality. Hence, the reason why there are monitoring logs. Something almost always goes wrong in production. Therefore, if these scenarios can be generated using AI even before pushing to production, it becomes easier to handle such cases. Netflix’s ChaosMonkey is an example of such an approach to software deployment.

Conclusion

DevOps practices have proven to yield good results when building products. They make it easy to quickly roll out new features to the users, and act on feedback almost immediately. However, it has its own limitations. Luckily, there’s a lot of data generated from practicing DevOps. Hence, AI can be used to open more doors and unlock potentials that make software deployment a pleasant experience.

If you are looking to improve your enterprises code velocity with state of the art AI-powered DevOps, drop us a message here