Solutions
Solutions
Komodor partnered with a leading AI Cloud Provider to tackle their operational hurdles. Here's how our AI SRE, Klaudia, successfully bridged the visibility gaps in their highly customized CAPI infrastructure.
At KubeCon Europe 2026, Komodor is unveiling a new extensible multi-agent architecture for Klaudia AI. To understand why it matters, it helps to start with why building AI for infrastructure is so fundamentally hard.
Out-of-the-box and bring-your-own AI agents that encode operational knowledge boost troubleshooting speed and accuracy across cloud native infrastructure
Platform teams find themselves caught in the middle, trying to optimize shared infrastructure while both sides insist their priorities are non-negotiable. This conflict plays out across enterprises constantly, and it reveals a fundamental problem with how cost optimization works in cloud-native environments. The typical FinOps model, where a centralized team identifies savings opportunities and pushes recommendations to engineering, assumes that cost and operations are separate domains that can be optimized independently. In Kubernetes, that assumption breaks down completely.
Komodor, the autonomous AI SRE company for cloud-native infrastructure, today announced the launch of the Komodor Partner Program, designed to enable and reward partners delivering AI-driven cloud-native infrastructure reliability and optimization services to enterprise customers. Foundational partners include Cloud Bazaar, Matrix DevOps, Trace3 and others.
Part 8 of our AI SRE in Practice Series. This scenario walks through how AI-augmented troubleshooting enables engineers without Kubernetes expertise to diagnose and resolve complex issues, using a real example from a team onboarding non-experts to platform operations.
We recently wrote about how AI-generated code is overwhelming SRE teams with production complexity they can't manage. Turns out that's only half the problem. The other half shows up on the cloud bill.
Company doubled its share of Fortune 500 customers with surging demand for AI-powered reliability and cost control.
Overprovisioning is draining your cloud budget. Kubernetes cost optimization done right means fixing root causes, not just reading dashboards.
