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.
Proactively prevent issues before they occur.
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 cloud-native.
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.
Join the Komodor partner program and accelerate growth.
Enter a few high-level cluster inputs and generate a concise savings estimate. Unlock the technical report to see the optimization mechanisms, assumptions, and prioritized next steps.
Nodes, compute footprint, monthly spend, lifecycle mix, and basic governance posture.
A lightweight popup summarizes estimated monthly and annual savings, plus top optimization categories.
Submit a business email to view detailed mechanisms and export the report as a PDF.
Keep this lightweight. The goal is to estimate the opportunity quickly, then use the full report to inspect the underlying assumptions.
Across all node pools.
Total vCPU capacity.
Total memory capacity.
Use your current monthly infrastructure run rate.
Used to estimate lifecycle-weighted monthly spend.
Percentage of nodes running on spot instances.
Automatically capped so it does not overlap with spot.
60% on-demand · 20% spot · 20% reserved
The next step opens a concise result summary. No email is needed for the initial estimate.
Estimates are directional and based on conservative benchmark assumptions. Validate against workload-level telemetry before remediation.
Estimated optimization opportunity
Your immediate estimate is ready. Unlock the full technical report to see the optimization mechanics and assumptions.
Understand the full picture: bin-packing assumptions, rightsizing mechanics, lifecycle mix exposure, workload governance risks, and the step-by-step remediation plan.
Gain instant visibility into your clusters and resolve issues faster.
May 12 · 9:00EST / 15:00 CET · Live & Online
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