Will AI Replace DevOps Jobs? DevOps Engineer Demand in India

In this video, I address one of the most common questions I receive in the comments on my YouTube channel: Will AI replace DevOps engineers, and is DevOps still a safe career choice? Instead of replying repeatedly in the comments, I decided to create a detailed video to explain this topic clearly for everyone—students, fresh graduates, and working professionals.

With AI being discussed everywhere today, many people believe that AI is a robot that will completely take over jobs or that it is only about heavy coding and machine learning. Before choosing any career path, it’s natural to wonder whether AI is so powerful that certain roles may not exist in the future. Through this video, I aim to remove that fear, especially around DevOps.

I start by explaining what DevOps actually is. DevOps combines development and operations teams so they can work together using automation and shared tools to build, test, release, and deploy software faster and more reliably. DevOps is not limited to CI/CD pipelines or writing YAML files—it also includes automation, monitoring, infrastructure reliability, and taking ownership of production systems.

Next, I explain AI in simple terms. Artificial Intelligence refers to systems that analyze data, learn from past patterns, and make predictions. Most of us already use AI through tools like ChatGPT. AI is especially good at handling repetitive tasks and analyzing large amounts of data, such as logs and metrics.

A key point I make is that AI cannot replace DevOps engineers when it comes to real-world decision-making. For example, if a production system crashes at 2 a.m., AI cannot decide whether to roll back changes or move forward while considering business impact, risk tolerance, and company context. These decisions require human judgment and responsibility, which is why DevOps engineers remain essential.

At the same time, I don’t suggest ignoring AI. Just as DevOps improved earlier workflows, AI will make DevOps work more efficient. AI can help predict incidents, analyze logs, generate scripts faster, and support automation. In this setup, DevOps engineers make the decisions, and AI acts as a powerful assistant that speeds up execution.

For beginners and students, my advice is straightforward: focus on DevOps fundamentals first. Build a strong foundation, work on hands-on projects, and understand how DevOps systems operate. Once you’re comfortable, you can start integrating AI into your workflow. You don’t need to become an AI engineer—being an AI-aware DevOps engineer is enough.

I also share learning resources for AI, including beginner-friendly courses, prompt engineering, automation-focused AI learning, and professional certifications. My core message is simple: AI will not reduce DevOps jobs, but DevOps engineers who learn to work with AI will definitely grow faster.

I conclude the video by encouraging viewers not to fear AI. DevOps remains a strong and future-proof career. By strengthening DevOps fundamentals and gradually adopting AI, professionals can expand their skills, increase opportunities, and use AI as an advantage rather than a threat.