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.
Cost and Performance Optimization
Komodor autonomously slashes between 40–70% of cloud compute costs while improving reliability and performance. The platform continuously searches for opportunities to optimize cloud native resources – overprovisioned nodes, autoscaler inefficiencies, underutilized GPU instances and more.
In complex cloud native environments, reliability and cost are inseparable. Overprovisioning ensures uptime but drives waste, while aggressive cost-cutting risks performance. Komodor enables SRE and platform teams to maintain reliability for business-critical applications while saving money through reduced cloud costs.
Komodor makes autoscaling faster, smarter, and more reliable through intelligent bin-packing. The technology maximizes node utilization by placing pods more efficiently, resolving fragmentation, and minimizing scheduling restrictions. This enables autoscalers to scale down safely and deliver significant compute cost savings.
Komodor eliminates guesswork by analyzing actual CPU and memory usage along with historical performance data, then recommending and applying safe, performance-aware requests and limits. It automatically right-sizes workloads to eliminate waste from overprovisioning and prevent performance issues caused by underprovisioning.
Komodor provides a unified view of the Kubernetes spend across the organization – incorporating actual cloud pricing that includes discounts, usage-based rates, and custom on-prem unit costs. It enables precise cost allocation by business unit, team, or application to identify trends, detect anomalies, and uncover inefficiencies before they affect the budget.
“By cutting down overspend without compromising performance, we could reinvest those savings into our creative operations. Komodor didn’t just save us money; it made our Kubernetes architecture smarter.”
Mark
Head of Cloud Platforms, Travel Technology Company
Komodor’s autopilot feature automatically adjusts resource consumption in real-time to meet performance requirements. It can be customized to align with organizational policies and standards via configurable thresholds and guardrails – ensuring smooth, optimized scaling as infrastructure grows.
Komodor accelerates scaling with Smart Headroom, a pre-allocated capacity buffer that allows new workloads to be scheduled instantly without waiting for node cold starts. It ensures burst-ready capacity and consistent performance during traffic spikes while avoiding the waste of blanket overprovisioning.
PodMotion enables zero-downtime migration of Kubernetes stateful workloads, automatically moving pods across nodes without disrupting availability. It allows teams to reduce costs, boost efficiency, and manage infrastructure events like upgrades without affecting applications, while also taking advantage of spot instances and better bin packing for additional savings.
Faster incident management with Komodor’s AI SRE platform helps SRE teams focus and reduces incident impact on customers.
Operational friction slows development and degrades productivity. Komodor gives developers the self-service capabilities they need to resolve issues independently, sharply reducing TicketOps for SRE teams.
Improved performance and uptime protect the bottom line and maintain customer trust.
Gain instant visibility into your clusters and resolve issues faster.
