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AIOPS

“Where rubber hit the road in Agentic-AI era”

AIOPS is a definition that has been around for 6-7 years. For a couple of years the solutions were still embedded in establishing an AI-Assistent promt and through chatgpt type of dialog extract valuable insight from observability data lake with logs, metrics and traces.

Now when we enter the Agentic AI era, with AI-agent taking actions in collecting, correlating and analysing data, making suggestions and taking mitigation actions. AI agents are now part of Command Center team. The release of DevOps agent in AWS Cloud is just the beginning.

This profound change is leading to a major transformation of how we operate within IT today. This transformation is no longer about some new technologies for monitoring or some new standard of operational process, rather a shift toward new way of human-machine collaborated operation where machine doing equivelent or more than IT technicians do.

McKinsey call this the "Agentic Organization". The impact on people, organization, workflow with roles and responsibilities are not to be underestimated. The change journey will as well be challenging as it is not only about technology, but main focus will be on people.

The same MaKinsey paper named "AI-First" 11 times. And we shake our heads as we recognize the journey with "Cloud-First" that may backfire. However this AI-agent journey could be different, as it no longer needs as much "heavy-lifting" as cloud transformation, and the nature of iterative automation process makes it easy to roll-up snowball effect.

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Case: AIOPS Driven Observability

So what's the strategy here:

  • We need to understand the technology and follow development continuous as agent AI evolves week by week

  • We need to have a strategy with plan and roadmap

  • All change journey starts with pilot and sandbox test to grep the scope, effort and value, with other words learning by doing:

    • Identify use cases in close collaboration with main stakeholders

    • Showcase the value and productivity gains

    • Establish a reference architecture with integration model toward current infrastructure

    • Expand and rolling out through automation pipeline

CMI helped a large goverment agency in establishing an observability roadmap, driving the implementation journey through pilot to expansion and taking on the change journey toward AIOPS.

We would be thrilled to tell you more about what we can offer - contact us, and we will set something up!