Building your own DIY agent for incident resolution?

→

Building your own DIY agent for incident resolution?

→

Understand what to look out for.

Building your own DIY agent for incident resolution?

→

Understand what to look out for.

Hyground vs

K8sGPT

Hyground vs K8sGPT: a supported platform, not a cluster scanner

K8sGPT scans your Kubernetes objects and tells you what is broken, on whichever model you point it at, a local one included. It is free, and it lives in the CNCF Sandbox. Hyground is a commercial platform that investigates across logs, metrics, your runbooks and your tickets, and puts a vendor on the hook for the answer.

A fair starting point

K8sGPT does one job well, and it is free. More than thirty analyzers walk your cluster objects, and what they find comes back in plain language. Point it at OpenAI, Azure, Cohere, Amazon Bedrock, Google Gemini or a local model, and with the local one nothing leaves your network. An operator handles continuous scanning and feeds Prometheus and Alertmanager, and an MCP server lets other agents drive it. The project is active. Version 0.4.39 shipped on 2026-09-14, with roughly a hundred commits in the last six months. Hyground is a different kind of thing. It correlates the cluster with your logs, metrics, runbooks and tickets into one investigation, and it comes with a vendor.

Side by side

Hyground vs

K8sGPT

at a glance

What matters

Hyground

K8sGPT

What it looks at

The cluster plus logs, metrics, traces, cloud accounts, databases, your documentation and your tickets. Our engineers build any other connector that you need with you during onboarding.

Kubernetes objects, through more than thirty analyzers, plus Trivy and Keptn integrations.

What an answer is built from

A multi-agent investigation that correlates several sources and converges on a diagnosis.

A deterministic analyzer pass, then one model call to explain the findings.

Your documentation and runbooks

Confluence Cloud and on-premises, up to 100 Git repositories, Artifactory and uploaded files, embedded inside your cluster.

No ingestion of your own documentation. It can attach the official Kubernetes docs to an explanation.

LLM choice

Any provider through LiteLLM: a cloud model in your own tenant, a self-hosted model, or any OpenAI-compatible API.

OpenAI, Azure, Cohere, Amazon Bedrock, Google Gemini or a local model, set per install.

Running it across clusters

A central manager with workers in each cluster, routing to a named cluster and fan-out across all of them.

One operator per cluster, each writing its own custom resources. No fleet view.

Cost and licence

A commercial licence priced on infrastructure size. Quote on request.

Free and open source under Apache 2.0, with no vendor in the supply chain.

Support and accountability

A vendor with a support agreement and a named escalation path.

A CNCF Sandbox project. Support is the community Slack and the GitHub issue tracker.

Compliance posture

ISO/IEC 27001:2022 certified, with a DPA and the usual enterprise paperwork.

An open-source project. There is no entity to hold an attestation.

Swipe to compare

Why teams choose Hyground

Where Hyground differs

More than a cluster scan

K8sGPT reads Kubernetes objects and tells you what is wrong with them, which is a real and useful job. Hyground correlates the cluster with Prometheus, Loki, Elasticsearch, OpenSearch, Jaeger and InfluxDB, with cloud accounts and databases, and with your own runbooks and tickets, into one investigation rather than one explanation.

Grounded in your documentation

Hyground ingests Confluence, Cloud and on-premises, up to 100 Git repositories, Artifactory and uploaded files, and embeds them in a vector store inside your cluster, so an investigation reads your procedures. K8sGPT can attach the official Kubernetes documentation to an explanation, which is a different thing from knowing how your team runs.

One view across every cluster

A central manager orchestrates workers in each cluster, with routing to a named cluster and parallel fan-out across all of them, so evidence from dozens of clusters lands in one place. K8sGPT runs an operator per cluster, each writing its own custom resources, with no view across them.

A vendor on the hook

Hyground comes with a support agreement, a named escalation path and ISO/IEC 27001:2022 certification, which is what an enterprise procurement review asks for. K8sGPT is an Apache 2.0 project in the CNCF Sandbox: no commercial entity, no support agreement and no attestation, because there is no company to give one. Whether that matters depends entirely on your procurement.

Both can keep the model in your network

K8sGPT supports local models, so it can run without sending anything to a provider, and that deserves credit. Hyground reaches any provider through LiteLLM, including a self-hosted model, with automatic fallback across a model list. On sovereignty these two products are closer to each other than to anything else on this site.

An investigation, not an explanation

K8sGPT runs its analyzers and then makes a single model call to explain what they found. Hyground runs specialist agents over logs, metrics, alerts and your knowledge base in parallel, has them converge on a diagnosis, and files the result to Jira or ServiceNow.

Decision

When each platform fits

These are different tiers rather than rivals. One is a free scanner for cluster misconfiguration; the other is a supported platform meant to be a system of record for operations. Plenty of teams run K8sGPT and never need more.

Choose Hyground when

Your investigations have to cross logs, metrics, runbooks and tickets rather than cluster objects alone. You run several clusters and want one place to look. Or procurement wants a vendor, a support agreement and a compliance posture.

You also want the rollout done with you. A forward deployed engineer works with your team from install to daily use. The engineer connects your stack, builds any connector that you are missing, and runs the training and workshops.

Choose

K8sGPT

when

You want open source, free, with no vendor in the supply chain. The question is usually Kubernetes misconfiguration rather than a multi-signal investigation. One cluster is the whole scope, and a community Slack is an escalation path you can live with.

See Hyground in action

Book a demo

Try our sandbox

See Hyground in action

Book a demo

Try our sandbox

See Hyground in action

Book a demo

Try our sandbox

FAQ

Hyground vs

K8sGPT

:

common

questions

Is Hyground an alternative to K8sGPT?

Yes, when you need more than a cluster scan. K8sGPT scans cluster objects and explains what is broken. Hyground pulls the cluster together with logs, metrics, your documentation and your tickets into one investigation, with a vendor standing behind the result.

What does Hyground give us that K8sGPT does not?

Five things. Investigation that reaches past the cluster, your own runbooks and documentation as context, one view across many clusters, findings filed into Jira or ServiceNow, and a vendor carrying a support agreement and ISO/IEC 27001:2022 certification.

Who stands behind the results?

With Hyground, a vendor does, with a support agreement, a named escalation path and ISO/IEC 27001:2022 certification. K8sGPT is an Apache 2.0 project in the CNCF Sandbox, supported through the community Slack and the GitHub issue tracker.

Can we choose the model, or host it ourselves?

Yes. Hyground connects to any LLM provider through LiteLLM, including a cloud model in your own tenant or a model that you host yourself. K8sGPT supports local models too. The difference is what happens next: Hyground runs a multi-agent investigation, where K8sGPT makes one model call to explain its scan.

How do we get Hyground running, and what does it cost?

A forward deployed engineer works with your team from install to daily use. The engineer connects your stack, builds any connector that you are missing, and runs the training and workshops. Hyground is priced on the size of the infrastructure that it covers, not per seat, and you get a quote on request.