DevOps +AI can be a winning combination. Implementing the DevOps model, using AI for testing, and utilizing observability projects can help companies release software without bottlenecks, improve performance, and handle high demand effectively.
Video Insights on DevOps + AI
🎥 Asaf Kivity, general manager at Matrix DevOps, discusses successfully implementing the DevOps model to release software without bottlenecks.
🤖 Companies are using AI to automatically convert user stories into test cases and this is revolutionizing the QA industry. It is making the tester’s work much easier and speeding things up.
🤖 Trusting AI and co-pilot in DevOps requires human oversight for steering in the right direction.
🛠️ Various tools, including some from other vendors, may claim to have tested everything and have no licensing issues, but it’s important to verify that the tool’s actions align with your intentions.
🚀 One of the biggest success stories in recent time was an observability project for an Israeli airline, observing all of their applications including the mobile app.
🚀 The observability project helped identify and fix performance issues, saving money and ensuring the platform could handle high demand for tickets.
Summary on DevOps + AI
Faster software deployments in today’s IT environment requires a lot of automation. DevOps + AI can increase the productivity and deliver more releases while keeping quality high – if it’s done correctly.
Check out this other episode on DevOps + AI.
Notes
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