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.
Who we are, and our promise for the future of K8s.
Have a question for us? Write us.
Come aboard the K8s ship – we’re hiring!
Here’s what they’re saying about Komodor in the news.
Day 1 Kubernetes tasks, such as provisioning clusters and setting up CI/CD pipelines, are now well-charted waters. However, the true test of operational maturity begins after deployment. Day 2 operations are where organizations unlock the full potential of Kubernetes, but they also introduce exponential complexity that often outpaces human capacity.
“Mastering Day 2 Kubernetes with AI SRE” is your guide to bridging the gap between complexity and reliability. By integrating Artificial Intelligence into Site Reliability Engineering, you can transform how you troubleshoot, scale, and govern cloud-native environments.
Understand the critical shift from standard Day 1 provisioning to Day 2’s dynamic ecosystem. Learn how AI agents move beyond simple automation to provide autonomous oversight, reducing the cognitive load on your engineering teams.
Discover how AI-driven analysis addresses the heart of Kubernetes’ operational hurdles:
Intelligent Troubleshooting: Moving from “hunting for logs” to automated Root Cause Analysis (RCA).
Predictive Scaling: Leveraging machine learning to anticipate resource spikes rather than reacting to them.
Automated Governance: Enforcing policy and security guardrails in real-time without human intervention.
Discover how platforms like Komodor serve as a virtual SRE team member. By leveraging full-stack visibility and contextual AI, you can:
Democratize Knowledge: Allow developers to solve complex K8s issues using natural language queries.
Automate Remediation: detailed remediation workflows that fix issues before they impact the end-user.
Optimize Reliability: Receive proactive recommendations to improve system health based on historical data patterns.
Hear how leading tech organizations utilized AI-enhanced operations to conquer Day 2 challenges, resulting in drastically reduced MTTR (Mean Time to Repair) and improved developer velocity.
Day 2 is where the rubber meets the road. Without an AI SRE strategy, teams are condemned to a cycle of constant firefighting, escalating cloud costs, and burnout.
By leveraging AI SRE, you do more than just maintain stability; you evolve from reactive incident management to proactive, autonomous operations. This guide equips you with the insights needed to stop debugging and start innovating.
Gain instant visibility into your clusters and resolve issues faster.
