Operations | Monitoring | ITSM | DevOps | Cloud

[WEBINAR] Introducing the Komodor Agentic Operations Platform

Join Komodor CTO and co-founder Itiel Shwartz for a live look at the newly launched Komodor Agentic Operations Platform. Itiel will guide us through where agentic AI operations are headed in 2026 and beyond, and how Komodor got here: years spent resolving incidents in some of the world’s largest production environments, and what that experience revealed about what makes agents valuable in production.

[DEMO] Komodor Agentic Operations Platform

The Komodor Agentic Operations Platform allows enterprises to confidently implement autonomous operations in mission-critical environments, fully governed from the first run. Get started instantly with pre-built, end-to-end agentic workflows, along with the shared infrastructure, tools, MCP gateways and integrations needed to build, run, and optimize your own.

Self-Improving Agents: A Practical Guide to Continuous Learning

We build agents to take work off engineers’ plates. Then we give those engineers a new manual job: reading failed runs and babysitting prompts. Agents will improve themselves automatically. We’re not there yet, but this is the future I’m betting on. We’ve been working on this ourselves at Komodor over the past year. We know how hard it is to turn a failure into an improvement that holds up beyond a few examples.

[WEBINAR] Codifying Tribal Knowledge - How to Build Long Term Memory for AI SRE Agents

In this technical webinar, Komodor’s engineering team unveils Agent Memory – the long-term operational memory behind our AI SRE agents. We’ll go deep into how it works: why we modeled it on human memory research (episodic vs. semantic, consolidation, reinforcement, decay), why off-the-shelf memory frameworks like Mem0 and Graphiti fell short for SRE workloads, and how we built a fast, purpose-built alternative on PostgreSQL and pgvector – one table, three search indexes, and a hybrid retrieval engine that fuses exact, lexical, and semantic search into a single ranked answer.

Building AI SRE Agents, Part 2: Leave the Laptop, Earn Trust

Moving the agent off your machine and pointing it at real clusters — read-only, in shadow mode — then climbing a trust ladder toward carefully scoped action. This is the second article in a three-part series on taking an AI SRE agent from a weekend experiment to enterprise production. Part 1 built a local agent on a throwaway cluster: read-only, propose-only, refined against a small eval set, with portable skills and no production write access.

4 Cloud-Native Challenges AI SRE Is Solving in 2026 and the 3 New Ones to Look Out For

AI SRE is making real strides in resolving some of the greatest pains related to incident response, troubleshooting, and complex root cause analysis. The on-call rotation, the war room, the week-long RCA, and the ticket queue that ate a third of every platform engineer’s week all look different now than they did two years ago.

5 Optimization Blockers You Didn't Know Were Inflating Your Cloud Bill

Most cloud-native cost tools are built to find and address waste reactively. Underutilized nodes, oversized requests, and idle workloads are revealed in the utilization data, the fixes are well documented, and the initial savings these tools drive are very real. But what we’ve seen consistently across clusters is a different category of blocker, one that quietly prevents consolidation and strands capacity your autoscaler can never reach. They don’t surface in dashboards as obvious waste.

The Investigator That Remembers: Inside Klaudia Memory

There is a particular kind of incident every SRE team is familiar with. A common component of your stack, say your Redis database, starts misbehaving. Someone spends two hours tracing it back to a connection pool exhausted by a misconfigured client, the fix goes in, and everyone moves on, for today. The following Tuesday it happens again, and whoever is on call investigates it from scratch, because the person who solved it last week is asleep, on vacation, or working somewhere else now.