Komodor is an autonomous AI SRE platform for Kubernetes. Powered by Klaudia, it’s an agentic AI solution for visualizing, troubleshooting and optimizing cloud-native infrastructure, allowing enterprises to operate Kubernetes at scale.
Proactively detect & remediate issues in your clusters & workloads.
Easily operate & manage K8s clusters at scale.
Reduce costs without compromising on performance.
Guides, blogs, webinars & tools to help you troubleshoot and scale Kubernetes.
Tips, trends, and lessons from the field.
Practical guides for real-world K8s ops.
How it works, how to run it, and how not to break it.
Short, clear articles on Kubernetes concepts, best practices, and troubleshooting.
Infra stories from teams like yours, brief, honest, and right to the point.
Product-focused clips showing Komodor in action, from drift detection to add‑on support.
Live demos, real use cases, and expert Q&A, all up-to-date.
The missing UI for Helm – a simplified way of working with Helm.
Visualize Crossplane resources and speed up troubleshooting.
Validate, clean & secure your K8s YAMLs.
Navigate the community-driven K8s ecosystem map.
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Part 7 of our AI SRE in Practice Series. This scenario walks through how AI-augmented knowledge transfer changes the onboarding experience, using a real example from a containers team implementing changes to HiveMQ infrastructure.
Part 6 of our AI SRE in Practice Series. In this scenario we walk through an AWS CNI IP exhaustion incident where 15 services experienced outages before platform teams identified the root cause.
For an AI SRE to be safe and effective, it cannot rely on generic training data alone. It needs context. Klaudia solves this through a dual-layer approach to context engineering: the Organization Blueprint and the Knowledge Base Integration.
Part 5 of our AI SRE in Practice Series. This scenario walks through a policy enforcement incident where a seemingly minor configuration change caused widespread pod failures that required deep investigation across the cluster to understand the scope and root cause.
This post details how to build an MCP server that connects AI agents (like Claude Desktop or Cursor) to a Kubernetes cluster, enabling natural language control over kubectl operations.
This article explores the technical realities of building Klaudia, an agentic AI solution for Cloud-Native infrastructure.
Komodor Named a Representative Vendor in the 2026 Gartner® Market Guide for AI Site Reliability Engineering Tooling Komodor's AI SRE platform helps organizations maximize uptime, reduce cloud costs, and simplify operations across complex, cloud-native environments
When a new, competing open-source Kubernetes troubleshooting agent was launched, we thought it would be a good idea to put both tools through identical real-world failure scenarios our customers typically encounter. The objective was to benchmark Klaudia Agentic AI and the open-source AI agent, and compare their performance across common Kubernetes failure scenarios.
Part 4 of our AI SRE in Practice Series. In this part we examine what happens when a node terminates unexpectedly, and dealing with the harder question of why it happened and how to prevent it from happening in the future.
Gain instant visibility into your clusters and resolve issues faster.
May 12 · 17:00 CET · Live & Online
🎯 4 Sessions 🎙️ 8 Speakers ⚡ 100% Free
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