Hyground vs K8sGPT
K8sGPT is a free CNCF Sandbox tool that scans Kubernetes objects and explains failures in plain English. Hyground is a commercial platform that investigates incidents across logs, metrics, runbooks, and tickets, with a vendor on the hook.
Both run inside Kubernetes and use a language model to explain what is going wrong. K8sGPT scans cluster objects for known failure signatures and offers a one-shot explanation. Hyground correlates the cluster with Loki and Prometheus, Confluence and Git runbooks, and Jira and ServiceNow history into a single investigation backed by named support.
Architecture
Six differences that show up the moment incident response has to span more than one cluster, one engineer, or one signal.
Hyground covers investigation, RAG over your documentation, multi-cluster fleet view, and post-mortems written back to Confluence. K8sGPT runs roughly thirty analyzers over in-cluster objects plus Trivy and Keptn. No log search, no metric correlation, no document ingestion, no shared session, no UI.
Hyground ships from a funded team with full-time engineering. K8sGPT has 36 commits from 10 contributors in the last six months, with founder Alex Jones working full-time as a Principal Engineer at AWS. Latest release v0.4.33 shipped on 2026-05-13; the project has been CNCF Sandbox since December 2023 with no public move to Incubating.
Hyground ships with named SLAs, an escalation path, and a managed service option. K8sGPT has no commercial entity, no paid support, no SLA, and no compliance attestations. When the operator pod crashes at 2am, the only recourse is community Slack and the GitHub issue tracker.
A manager-and-remote topology correlates evidence across dozens of clusters from one interface. K8sGPT has no fleet view; each cluster runs its own operator and writes its own CRDs.
Hyground ingests Confluence, Git, PDFs, and Word docs into a vector knowledge base that lives inside the cluster, and writes new runbooks and post-mortems back as the team learns. K8sGPT has no RAG, no document ingestion, no organizational memory; every analyzer run starts from zero.
Specialist agents for logs, metrics, alerts, and knowledge work in parallel, converge on a diagnosis, and file the result to Jira or ServiceNow. K8sGPT runs a deterministic analyzer chain plus a single LLM explanation call, with no follow-up.
Decision
K8sGPT and Hyground sit at different tiers of the stack. The fit depends on whether you want a free in-cluster scanner, or a supported platform that an enterprise can adopt as a system of record for operations.
You need a supported platform that goes beyond cluster-config checks and survives an enterprise procurement review.
You prefer pure open source, run a small footprint, and have the engineering depth to assemble the rest of the platform yourself.
Try the sandbox, or book a demo to see sovereign AI for DevOps run on your stack.