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DevOps and Artificial Intelligence (AI) by Alec M
"DevOps is a cultural and operational movement that fosters collaboration to enable high-performance IT to achieve business goals," a definition from the DevOps and Agile Skills Association (DASA) that has always resonated with me. As AI took centre stage this year, and unleashed a proliferation of AI tools, I am also reminded of one of the core principles of DevOps: "Experimentation". Embracing and adopting new technologies like AI embodies this principle and I feel certain is a necessary stride towards ensuring that the software we design, fully supports our business ambitions while at the same time ensuring that we – both at an individual level and organisation level - constantly evolve and don’t get left behind.
Having highlighted the benefits of experimenting with AI in DevOps, here are some of the AI tools I found that help enhance the speed and efficiency of DevOps:
1. Automated Testing
Software testing is a crucial part of the software development lifecycle and can require extensive resources depending on the size of project. Therefore, it is only natural to want to streamline the process and take some weight off your trusty tester’s shoulders. AI tools such as Applitools and Testim can generate test scripts tailored to your project type. One cool feature I found is that Applitools can test for visual inconsistencies and bugs across different devices and browsers, so whether your user is using a desktop or tablet, you know your application will run smoothly on both.
2. Code Review
Most developers would much rather be writing their own code instead of reviewing someone else’s, however this is a crucial task to complete. Without a second pair of eyes on the code, potential bugs and security vulnerabilities can easily slip through, especially after those late-night coding sessions. I have found a lot of success with tools like SonarQube and DeepCode that use machine learning to analyse code repositories. As well as integrating with popular version control systems, these technologies cover a wide range of languages and usually provide suggestions for improving code quality. For example, code smells are often the result of poor or ill-judged programming and these tools will pick up on them, and offer advice on how to resolve them.
3. Continuous Deployment
Traditionally, the last step in most DevOps pipelines is to deploy your application. Whether you are deploying to a test, staging or production environment, the correct deployment strategy can save both time and money. Automating the compilation, packaging and deployment are the bare minimum you would expect from any deployment tool. Tools such as CircleCI and Harness include extra features that make them really stand out. For example, rolling back failed deployments and scaling environment resources based on your applications new demand. Either way you will be reducing any manual tasks while ensuring a smooth deployment and minimizing downtime.
4. Monitoring
To maintain a DevOps mindset, you should aim to automate as many end-to-end processes as possible. The scope of monitoring is huge, you can monitor infrastructure, platforms, applications, business', you can even monitor the monitoring applications. One of the simpler tasks to automate is application monitoring. This style of monitoring is primarily used to analyse your applications data, detect anomalies, and provide insights into the applications health and usage. Tools such as Dynatrace and AppDynamics leverage artificial intelligence to help monitor environments and applications. They primarily deliver comprehensive analytics and easy to read data, as well as providing the user with insights to optimise application performance.
While it’s evident that there is a seemingly endless supply of new AI tools, it is important to note that it’s not just about finding the right tool, it’s also about understanding how they can be effectively integrated into your DevOps cycle. To make the most of them, it's essential to tailor their application based on individual project requirements. Some may align perfectly with your project, while others might not. It's vital to assess them based on both your specific DevOps and business needs. These tools, when used in tandem with experienced consultancy, can bring out the best in your operations and that’s where CTG can help. Remember, CTG offers a portfolio of both DevOps services and Testing Solutions which can be tailored to compliment and support your existing in-house capabilities.
At times, the rapid emergence of new practices and technologies can feel daunting. However, with the right mindset and thorough research, navigating the ever-changing technological landscape becomes more manageable. With expert guidance to help identify and implement the best solutions, you can not only stay ahead but also help ensure your business thrives.
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