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

Komodor

Hyground vs Dash0

Hyground vs Komodor: AI SRE that runs inside your own cluster

Komodor is a Kubernetes operations platform, and Klaudia is the AI SRE agent inside it. A Komodor agent runs in your cluster and streams to Komodor's cloud, in either a US or an EU instance, and that cloud is where Klaudia itself runs. Hyground keeps the whole platform inside your cluster instead: the investigation, the knowledge base, and the connection to your model. Nothing egresses to us.

A fair starting point

Komodor's Kubernetes operations platform is mature, and Klaudia no longer stops when a root cause leads outside Kubernetes: it queries Datadog and Grafana mid-investigation, opens pull requests in GitHub, and routes to specialist agents for Argo, Istio, Postgres, Kafka and NVIDIA GPUs. It also ships a real cost-optimisation product, which Hyground does not. Two questions still separate the products, and both are about location rather than features. Where does the platform itself run, and so where does your cluster data end up? And who picks the model that reasons over it?

Side by side

Hyground vs

Komodor

at a glance

What matters

Hyground

Komodor

Where it runs

Entirely in your own Kubernetes cluster, from your own cloud to a fully air-gapped site.

An agent in your cluster, with the platform hosted as SaaS in AWS, in a US or an EU instance. Komodor's own documentation says a strictly air-gapped cluster would not work.

Where your cluster data goes

No data egress to Hyground, because no Hyground-operated data plane exists. With a self-hosted model, nothing crosses the network at all.

The agent streams cluster metadata and telemetry to Komodor's cloud over TLS. Komodor states it collects metadata only and blocks secrets automatically.

LLM choice

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

Klaudia runs on AWS Bedrock in Komodor's environment. No documented way to bring or self-host your own model.

Observability reach

First-party connectors for Prometheus, Loki, Elasticsearch, OpenSearch, Jaeger and InfluxDB, all queried from inside your cluster.

Datadog and Grafana, covering Prometheus, Loki, Tempo and Pyroscope, through MCP servers. Read-only, and configured per tool.

Your documentation and runbooks

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

Uploaded files today. Their documentation lists Confluence and Slack sync as coming soon.

Fixing things

Hyground diagnoses and recommends. It does not restart, scale or reconfigure anything.

One-click remediation, kubectl execution for admins, and autonomous self-healing once you authorise a policy, under their RBAC and audit trail.

Cost optimisation

Right-sizing observations come out of an investigation. There is no cost product.

A cost product: allocation, dynamic pod right-sizing, bin-packing and savings tracking, on the Enterprise tier.

Pricing model

Priced on infrastructure size, not seats. Quote on request.

Priced per node, on the average node count across the year. A Teams tier covers 50 nodes and 25 users with a trial; Enterprise is custom and adds single sign-on, cost optimisation and 24x7 support.

Swipe to compare

Why teams choose Hyground

Where Hyground differs

The whole platform runs in your cluster

Hyground installs by Helm into your own Kubernetes cluster, and the platform stays there: the agents, the knowledge base, the audit trail, and the connection to your model. Nothing egresses to Hyground, because there is no Hyground-operated data plane to egress to. Komodor puts an agent in your cluster and hosts the platform itself as SaaS in AWS. Its own installation guide says that a cluster with zero outbound access would not work.

Any model, including one you host yourself

Hyground connects to any LLM provider through LiteLLM: a cloud model in your own tenant, a self-hosted model, or any OpenAI-compatible endpoint, with automatic fallback across a model list. Klaudia runs on AWS Bedrock in Komodor's environment, and Komodor's documentation describes no way to bring, swap or self-host the model.

Read-first, and every write is gated

Hyground adapters default to read-only and verify it at startup. The few writes that exist are narrow and sit behind explicit configuration, and an infrastructure write needs a human approval bound to that exact command. Komodor offers one-click remediation from the analysis, and has pull-request generation and fully automated self-healing in beta, governed by policies you configure.

Your runbooks and wikis, indexed inside the cluster

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. Komodor's knowledge base takes uploaded files today; its documentation lists Confluence and Slack sync as coming soon.

Where each integration runs

Komodor now reaches Datadog and Grafana during an investigation, so the gap is no longer which tools get read. It is which side of your perimeter reads them. Hyground queries Prometheus, Loki, Elasticsearch, OpenSearch, Jaeger and InfluxDB from inside your cluster, under one gateway with platform-managed credentials and one audit trail. Komodor reaches them from its own cloud, with credentials you hand over per tool.

They fix things today, and we do not

Worth saying plainly: Komodor closes the loop and Hyground does not. Klaudia runs one-click remediation from its own analysis, executes kubectl for admins, and will resolve recurring issues on its own once you authorise a policy, all under their RBAC and audit trail. Hyground diagnoses and recommends, and a person makes the change. If you are buying automated resolution today, that is theirs.

Decision

When each platform fits

Komodor and Hyground now overlap on a lot of ground. What still separates them is where the platform runs, and whether your cluster data and your model choice stay on your side of the perimeter.

Choose Hyground when

Sovereignty is a requirement where you work rather than a preference, your environments are regulated, on-premises or air-gapped, you want to pick the model that reasons over your infrastructure or to host it yourself, and you want investigation, ticketing and your own documentation in one platform that never phones home.

Choose

Komodor

when

You are comfortable with a SaaS control plane, Kubernetes cost optimisation is one of the reasons you are buying, and you want a mature operations UI with autonomous remediation behind it.