Sie bauen Ihren eigenen Agenten für die Incident-Behebung?

→

Sie bauen Ihren eigenen Agenten für die Incident-Behebung?

→

Worauf Sie dabei achten sollten.

Sie bauen Ihren eigenen Agenten für die Incident-Behebung?

→

Worauf Sie dabei achten sollten.

Hyground vs.

Metoro

Hyground vs Dash0

Hyground vs Metoro: reason over the observability stack you already run

Metoro runs its own eBPF collector, stores what it gathers, and puts an autonomous Kubernetes agent on top, with cloud, bring-your-own-cloud and air-gapped on-premises deployment options. Hyground collects nothing. It installs into your cluster and reasons over the Prometheus, Loki and cluster data already sitting there.

Ein fairer Start

Metoro is a Kubernetes observability platform with an autonomous SRE agent on top. It installs in about a minute, generates its own eBPF telemetry with no code changes, and then detects issues, verifies deployments and investigates alerts on its own. It runs in their cloud, in your cloud, or fully air-gapped on your own hardware, and you can point its agent at your own AWS Bedrock keys and pay AWS directly for the model. So the two arguments we used to make against them, deployment and model choice, no longer hold. What still separates the products is the data. Metoro asks you to run a second telemetry platform and pay by node and by volume. Hyground reads the observability stack you already run, and stores none of it.

Seite bei Seite

Hyground vs.

Metoro

auf einen Blick

Was eine Rolle spielt

Hyground

Metoro

Where your telemetry lives

In the tools you already run. Hyground queries them in place and stores no telemetry of its own.

In Metoro. Its agent generates eBPF telemetry and ingests it, with 28 days of retention by default.

Instrumentation

None supplied. Hyground reads whatever your stack already emits.

Kernel-level eBPF from a one-minute Helm install, seven signals with no code changes.

LLM choice

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

AWS Bedrock, with your own keys or Metoro's. Their documentation describes no other provider and no self-hosted option.

Scope

Kubernetes plus cloud accounts, databases, ticketing, source control and your own documentation.

Kubernetes, deeply. The product and its documentation are built around the cluster.

Where it runs

Entirely in your own Kubernetes cluster, on-premises and air-gapped included.

Metoro's cloud, your own cloud under their management, or on-premises and air-gapped.

What the agent changes

Nothing in your infrastructure. Hyground diagnoses and recommends.

Detects issues, verifies deployments and proposes code fixes, with an approval step before an agent action runs.

Your documentation and runbooks

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

Runbooks the agent follows during an investigation.

Pricing model

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

Twenty dollars per node per month, plus twenty cents per gigabyte above 100 gigabytes per node. Free up to two nodes.

Zum Vergleichen wischen

Warum Teams Hyground wählen

Wo sich Hyground unterscheidet

No second telemetry platform to run

Hyground reads Prometheus, Loki, Elasticsearch, OpenSearch, Jaeger, InfluxDB and the Kubernetes API in place, and stores none of it. Metoro generates its own eBPF telemetry and ingests it into Metoro, which is a second data platform to operate, secure and pay for by node and by volume. That is a real capability if you have no observability stack, and a duplicate bill if you do.

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. Metoro lets you supply your own AWS Bedrock keys, so the tokens are billed to you rather than to them, which is a genuine option. It is still Bedrock, and nothing self-hosted is documented.

Beyond Kubernetes

Metoro is built around the cluster, and its documentation stays there. Hyground investigates Kubernetes deeply and also reaches AWS and Azure, PostgreSQL, MongoDB, Redis and ClickHouse, Jira and ServiceNow with gated write-back, GitHub and GitLab, and your own Confluence and Git documentation.

Your runbooks and wikis, indexed in your cluster

Hyground ingests Confluence, Cloud and on-premises, up to 100 Git repositories, Artifactory and uploaded files, and embeds them in a vector store that stays in your cluster. Metoro's agent follows runbooks during an investigation, inside the platform that holds your telemetry.

Read-first, with no infrastructure mutation

Both products keep a human in the way of a change: Metoro requests approval before an agent action runs, and proposes code fixes rather than applying them. The difference is scope. Hyground does not restart, scale or reconfigure anything at all, and adapters verify read-only at startup, below the model.

It fits the stack you already bought

If you already run Prometheus, Loki or Elasticsearch, Metoro's value is a second pipeline beside them and a bill that scales with the data you send it. Hyground is additive to what you have: it queries those tools from inside the cluster, adds no storage, and leaves your observability spend where it is.

ENTSCHEIDUNG

Wann welche Plattform passt

Both products investigate Kubernetes autonomously. The question is whether you want the agent to bring its own telemetry platform or to read the one you already run.

Wählen Sie Hyground wenn

You already run an observability stack and have no appetite for a second one. You need the investigation to reach past Kubernetes into cloud accounts, databases and ticketing. Or you want to choose the model yourself, a self-hosted one included.

Wählen Sie

Metoro

wenn

You want the observability and the autonomous agent from the same vendor. eBPF telemetry with no instrumentation work is worth paying for, your world is Kubernetes, and per-node pricing with a free tier suits how you buy.