Does DevOps need coding?

DevOps requires some coding mainly for automation, scripting, and CI/CD pipelines, but it focuses more on tools, processes, and collaboration than full-scale software development.

What are the latest trends in DevOps?

Latest DevOps trends include AI-driven automation, GitOps, infrastructure as code, DevSecOps integration, and cloud-native CI/CD pipelines.

Which tool is most used in DevOps?

Git is foundational for version control in DevOps, while Jenkins remains one of the most widely adopted tools for CI/CD automation.

How is AI and ML used in DevOps?

AI and ML are used in DevOps to automate monitoring, predict failures, optimize pipelines, improve incident response, and enhance capacity planning using historical system data.

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Browse through frequently asked questions

DevOps does require some coding, mainly for automation, scripting, and CI/CD pipelines. However, it focuses more on tools, processes, and collaboration than full-scale software development.

The 5 W’s of DevOps are Who collaborates, What is automated, When changes are released, Where systems are deployed, and Why processes are optimized. Together, they align development and operations to deliver faster, reliable, and scalable software.

Latest DevOps trends include increased adoption of AI/ML for automation and predictive operations, and expanded use of GitOps and infrastructure as code for scalable, reliable deployments. Other key trends are security integrated into DevOps (DevSecOps) and enhanced cloud-native toolchains for continuous delivery.

There is no single most-used DevOps tool, but Git is universally foundational for version control and collaboration. For CI/CD, Jenkins remains one of the most widely adopted tools across DevOps pipelines.

AI/ML is used in DevOps to automate monitoring, predict failures, and optimize CI/CD pipelines through anomaly detection and intelligent insights. It also improves incident response, testing, and capacity planning by learning from historical system data.

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