Komodor is a Kubernetes management platform that empowers everyone from Platform engineers to Developers to stop firefighting, simplify operations and proactively improve the health of their workloads and infrastructure.
Proactively detect & remediate issues in your clusters & workloads.
Automatically analyze and reconcile drift across your fleet.
Easily operate & manage K8s clusters at scale.
Reduce costs without compromising on performance.
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Hear’s what they’re saying about Komodor in the news.
Many organizations operate multiple clusters within the same environment—such as production clusters distributed across regions—for high availability, disaster recovery, or compliance.
While these clusters are intended to remain identical, configuration drifts can still occur. These drifts can be caused by manual changes, inconsistencies in automation, or variations between infrastructure providers.
With Komodor, you can compare deployments of the same application across clusters and instantly spot inconsistencies. Instead of manually checking YAML files or running kubectl diff across clusters, Komodor automates this process and presents a clear diff view.
kubectl diff
Users can easily analyze the drift. In this example, we can see there was a failed deployment that caused the drift. We can even dive deeper to investigate the reason for the deployment failure. In this case, it’s an ImagePullBackOff error due to issues connecting to the container image repository.
Komodor highlights this discrepancy, helping teams ensure all clusters are configured consistently. This helps avoid unexpected behavior, detect rollbacks or failed deployments that may have gone unnoticed, troubleshoot drifts, and analyze the applicative performance of different versions.
Organizations can define the desired state and specify target clusters, packages, and services to detect configuration drifts in real time automatically.
With automated multi-cluster drift detection, teams can ensure consistency across regions by proactively identifying and resolving discrepancies before they lead to actual incidents.
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