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.
Ask any SRE what slows them down in a Kubernetes incident, and the answer is usually too much information in too many different places.
One of the most visible ways organizations bring platform engineering to life is through Internal Developer Platforms (IDPs). But at the same time, not every developer portal qualifies as a true platform.
Port gives teams the tools to build IDPs that are usable, governed, and extensible. Komodor brings Kubernetes into that equation—not as another silo, but as a native part of the experience.
The Essential Survival Guide for Platform Engineers: Navigating Kubernetes Challenges with Komodor
In this blog post, I want to focus on the exciting new features that v1.33 brings and what it means for all of us.
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.
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.
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.
Gain instant visibility into your clusters and resolve issues faster.
