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 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.
Cost and Performance Optimization
Cut cloud waste reactive tools can’t reach, while improving system health and performance. Komodor uses deep cloud-native context to drive intelligent, autonomous optimization that always safeguards reliability. By proactively fixing blockers and misconfigurations, and freeing up locked cloud capacity, you get peak performance at up to 80% lower cost.
In complex cloud-native environments, reliability and cost are impossible to separate. Defensive overprovisioning ensures uptime but drives waste, while aggressive cost optimization risks performance and triggers production incidents. Komodor leverages real-time application health signals and performance context to safely reduce cloud-native spend by up to 80% without threatening production.
Find and remove the optimization blockers that leave nodes unable to consolidate and cluster capacity stranded.
Komodor Capacity Intelligence identifies and fixes the policies and misconfigurations such as Pod Disruption Budgets and anti-affinity rules that block evictions and pin workloads to nodes that can’t be drained.
AI-powered investigation connects the technical dots to deliver clear, actionable recommendations that outline both reliability impact and savings opportunities.
Reclaim cluster capacity other tools don’t reach with AI-driven scheduling that optimizes for node consolidation before pods land.
Predictive Placement acts as a proactive layer between the Kubernetes scheduler and your autoscaler, evaluating every incoming pod against current node state, expected scaling moves, and known unevictable workloads before it’s scheduled. Cloud waste caused by inefficient scheduling is prevented before it happens.
Optimize cloud resource utilization without compromising on performance. Komodor analyzes real-time and historical CPU and memory data, application behavior, and health signals to recommend and maintain optimal resource settings. It continuously rightsizes workloads to cut waste from overprovisioning and prevent issues caused by underprovisioning, ensuring efficiency and reliability across changing demand.
Komodor also aligns KEDA and HPA scaling triggers, allowing event-driven and horizontal autoscaling to work seamlessly as one adaptive scaling system.
Mark
Head of Cloud Platforms, Travel Technology Company
Give workloads burst-ready capacity without paying for the privilege. Cold starts force teams to overprovision defensively — paying for idle capacity that may never burst. Smart Headroom maintains a dynamic, pre-allocated buffer sized to actual workload behavior, so pods schedule on demand without waiting for nodes to spin up. Spikes get absorbed instantly. Blanket overprovisioning disappears.
Komodor supports both fully-autonomous and co-pilot operation modes, giving teams full control over how optimization decisions are applied to meet performance requirements. Fine-grained policies let you define what should run automatically and what requires review, along with guardrails like buffers, ranges, and scopes to align with organizational policies and standards.
Komodor works with any node autoscaler (including Karpenter and Cluster Autoscaler) to make scaling faster, smarter, and more reliable. The result is an intelligent, self-optimizing autoscaling layer that keeps your infrastructure lean, balanced, and dependable. Every recommendation is evaluated by Klaudia AI SRE for production-stability impact before it surfaces.
Komodor provides a unified view of cloud-native spend across the organization – incorporating actual cloud pricing that includes discounts, and custom on-prem unit costs. It enables cost allocation by business unit, team, environment, or application to identify trends, detect anomalies, and uncover inefficiencies. With clear mapping of cost and optimization opportunities, Komodor enables engineering, platform and FinOps teams to align and collaborate effectively to achieve the ideal balance of reliability and efficiency.
Cut Root Cause Analysis from hours to minutes and safely automate remediation with Klaudia multi-agentic AI SRE.
Achieve cloud cost savings of up to 70% with contextually aware, reliability-first cost optimization trusted by enterprise platform teams in production.
Free SREs from the burden of TicketOps by providing a self-serve platform that empowers developers to operate Kubernetes and resolve issues independently.
Gain instant visibility into your clusters and resolve issues faster.
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