![]() 1 cloud priority for enterprises today is optimizing costs. Over the next 18 to 24 months, AI Ops will make the practice of waking up engineers in the middle of the night for downtime and other issues part of a bygone era.īelow are the top four areas of cloud IT operations where AIOps promises to deliver the biggest improvements. The increasing adoption of cloud (soon, 80% of all IT budgets will be committed to cloud solutions) and the emergence of artificial intelligence (AI) and machine-learning (ML) technologies are allowing companies to use intelligent software automation to make decisions on known problems, predict issues, and provide diagnostic information to reduce the operational overhead for engineers. However, DevOps hasn’t truly delivered what was expected from it, since engineers still have to respond to many of the alerts about issues and events in their infrastructure.īut what if we could let humans solve the newer, complex problems while we let machines resolve known, repetitive, and identifiable problems? Enter a new philosophy: AI Ops. ![]() ![]() This has led to a more widespread embrace of the DevOps philosophy-saving time and improving performance, bridging the gap between engineers and IT operations. From on-premises data centers to cloud and converged architecture, IT operations has evolved exponentially over the last decade with the help of companies such as Amazon, Microsoft, and Google that have removed much of the heavy lifting related to installing data centers, servers, managing networks, storage, and more.
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