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!
Discover our events, webinars and other ways to connect.
Here’s what they’re saying about Komodor in the news.
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Komodor’s new add-on support for autoscalers provides unparalleled visibility into the behavior of autoscalers in your K8s environments. This ensures they perform efficiently and avoid common pitfalls while integrating effectively within your Kubernetes systems. By offering real-time insights, automated troubleshooting and proactive optimization, Komodor enhances your understanding of autoscaler dynamics and helps prevent costly mistakes.
KubeCon is packed with cutting-edge content, especially for seasoned Kubernetes practitioners. With hundreds of sessions spanning operations, observability, platform engineering, and AI-driven automation (AIOps)
Komodor introduces Drift Management, which allows organizations to detect, analyze, and resolve drift at scale—eliminating uncertainty, reducing downtime, and strengthening governance across their clusters.
New full-cycle capabilities detect, investigate, and remediate configuration drift across Kubernetes cluster fleets; ensuring consistency, reliability and security at scale.
Although IaC (and CaC) bring immense value, they can also lead to a major problem: configuration drift. In this article, we will take a closer look at this issue and explore different methods of keeping systems in their intended state.
This article will present the steps involved in running AI workloads on Kubernetes. We will explore the different steps, from data preparation to serving AI models, and see how several tools can help as well as discuss their drawbacks.
With the recent rise of AI and the advent of tools like Kubeflow and Argo Workflows, Kubernetes is also becoming a first-class citizen when it comes to running AI workloads.
We tested DeepSeek’s models head-to-head against industry leaders in solving real-world Kubernetes challenges.
Company posts 200% increase in revenue and 400% jump in Fortune 500 customers TEL AVIV and SAN FRANCISCO, Feb. 5, 2025 — Komodor, the company that automates Kubernetes operations, health, performance and cost management, today announced that over the past twelve months ended January 31, it increased annual recurring revenue (ARR) by 200% and grew […]
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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