Hyground vs
Komodor
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. 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. Our engineers build any other connector that you need with you during onboarding.
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
Nothing by default. Hyground diagnoses and recommends, and changes happen only if you enable them.
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, with Kubernetes and cloud cost optimisation on both tiers.
Pricing model
Priced on infrastructure size, not seats. Quote on request.
Platform fee plus AI tokens.
Why teams choose Hyground
Where Hyground differs
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
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.
FAQ
Hyground vs
Komodor
:
common
questions
Is Hyground an alternative to Komodor?
Yes, when the platform has to run inside your own infrastructure. Hyground keeps the investigation, the knowledge base and the connection to your model inside your cluster. Komodor runs its platform and its model in Komodor's cloud, with an agent in your cluster that streams to it.
Does our cluster data stay in our infrastructure?
With Hyground, yes. No data egresses to us, because Hyground operates no data plane of its own, and with a self-hosted model no data leaves your own infrastructure at all. Komodor's agent streams cluster metadata and telemetry to Komodor's cloud.
Can Hyground run air-gapped or on-premises?
Yes. Hyground installs into any conformant Kubernetes cluster, on-premises ones included, and it runs fully air-gapped when the model is self-hosted. Komodor's installation guide says its agents have to reach its SaaS platform, and that a strictly air-gapped cluster would not work.
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. Klaudia runs on AWS Bedrock in Komodor's environment, with no documented way to bring or host your own model.
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.