AI for AIOps: Why Context Matters More Than Models

The AIOps market is crowded with solutions that are not doing so well to the term AI, to say the least. But let's focus on the real challenge: implementing AI in a way that delivers meaningful benefits for your IT operations.

You might think this would lead us down the path of training sophisticated, state-of-the-art models. However, our experience suggests a different approach. Rather than pursuing increasingly complex models, we've found that the secret lies in two key areas:

1. Foundational models are usually the best in class and are hard <or even impossible> to beat.
2. Just like alerts - providing rich, relevant context to the model is the key factor for sound, meaningful, and actionable output.

Context: The Hidden Multiplier

Here's an interesting observation: if you put this incident in front of 9 out of 10 SREs, none of them would immediately turn to ChatGPT. Why? The answer is simple but profound: these models lack the critical context that makes infrastructure troubleshooting effective, that context your top 1% engineers have.

Take a few examples of  what a general-purpose LLM doesn't know about your specific environment:

1. Historical Context: Previous incidents in your infrastructure and their resolution patterns
2. Architectural Understanding: Your system's topology and interconnections
3. Real-time Awareness: Details about correlated alerts and their relationships to the current incident
4. Change management: The latest changes introduced to your system by code or infrastructure
5. … you got it, right?

This is where Keep shines. 

Our platform doesn't just store alerts - it understands your entire infrastructure ecosystem. We've built a system that maintains and leverages this rich contextual knowledge, making our AI assistance truly relevant and actionable.

AI That Takes Initiative

But we've taken context gathering a step further. IT Infrastructure is like a living organism, the data you got 30 minutes ago may quickly become obsolete. What if AI could actively gather the context it needs? What if it will be accurately guardrail to do it with security and privacy in mind? That's what we've built at Keep.

Our AI can perform targeted queries across your connected tools and platforms to gather real-time context about the state of your infrastructure. Instead of an SRE manually piecing this puzzle together, Keep's AI assembles a comprehensive picture and saves time.

Try it yourself on our Open Source platform: https://github.com/keephq/keep/ or log in to our Cloud https://platform.keephq.dev/, where more AI features are available. 

Join us in Keep’s Slack community, where you can find help and a lot of cool use cases: https://slack.keephq.dev/!