Metoro
Kubernetes native observability with eBPF telemetry and an AI SRE agent, Guardian, that finds root cause and opens fix pull requests.
Metoro is an AI SRE for teams running on Kubernetes, built on its own observability platform. An eBPF collector installed with a single Helm command captures logs, metrics, traces, profiles and Kubernetes events with no code changes, and its agent, Guardian, starts on its own on new deployments, detected anomalies and firing alerts.
Guardian verifies deployments against pre deployment behavior, investigates alerts and anomalies into a root cause with supporting evidence, follows runbooks customers write in natural language, and inspects code changes to open fix pull requests for review. Guardian requests approval before it takes an action. Metoro runs as Metoro Cloud, BYOC or on premises, carries SOC 2 Type II, and offers an API, webhook events and an MCP server. Customers can run Guardian's model calls on their own AWS Bedrock account. Metoro is backed by Y Combinator.
Vendor details
Canonical URL
https://metoro.io
Category
SRE / DevOps agent
Company status
independent
Use cases & customers
Primary use cases
Target customers
Deployment options
Integrations
eBPF telemetry, OpenTelemetry and Prometheus, GitHub (code fixes), Slack, PagerDuty, Rootly, webhooks, event ingestion and KEDA; API and MCP server.
In practice
A team ships a new release to its Kubernetes cluster. Guardian starts on the new deployment, compares telemetry, log patterns and latency before and after the rollout, and reports what changed with supporting evidence.
An alert fires on an error rate spike at night. Guardian follows the runbook the team wrote in natural language for that alert, investigates to a root cause and posts its findings to Slack.
A bad code change caused the incident. Guardian inspects the change through the GitHub integration and opens a fix pull request for review, and it asks for approval before it takes any other action.
Sources & related URLs
Research sources
Agentic Index coverage score
9.0 / 14 capabilities · 64%
| Integrations & Tool Calling | Full |
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Guardian inspects code changes and creates pull requests through the GitHub integration and posts findings to Slack, beside PagerDuty, Rootly, webhook and event ingestion integrations and its own eBPF, OpenTelemetry and Prometheus telemetry. Sourcemetoro.io/docs/ai-sre/overviewread 2026-09-29 |
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| Workflow Orchestration | Full |
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Customers write runbooks for each alert in natural language, as numbered investigation steps Guardian follows when the alert fires, so the customer edits the flow. Guardian also chains deployment verification, root cause and fix pull requests. Metoro does not describe branching or conditions. Sourcemetoro.io/docs/ai-sre/runbooksread 2026-09-29 |
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| Knowledge Grounding & RAG | Full |
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Guardian investigates over Metoro's own persisted store of the customer's eBPF logs, traces, metrics, profiles and Kubernetes resources, with a service map and deployment history, compared before and after each rollout. Sourcemetoro.io/docs/ai-sre/overviewread 2026-09-29 |
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| Human Oversight & Guardrails | Full |
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Guardian asks for approval before it takes an action, and a webhook event is sent when it does. Code fixes arrive as pull requests for review. Sourcemetoro.io/docs/api-reference/webhooks/agent-action-approval-requestedread 2026-09-29 |
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| Security, Identity & Governance | Full |
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SSO and SAML, RBAC and audit logs come with the Scale and Enterprise tiers, with setup pages for RBAC, SSO, SAML and API keys. Every tier is SOC 2 Type II certified. Sourcemetoro.io/pricingread 2026-09-29 |
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| Observability & Auditability | Partial |
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Each investigation produces an investigation document with all gathered data, and findings come with supporting evidence. That is evidence for each run, but there is no record of the queries, tools or steps Guardian took. Metoro's telemetry of the customer's cluster is what the product does, not a record of the agent. Sourcemetoro.io/docs/ai-sre/alert-investigationsread 2026-09-29 |
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| Memory & State Persistence | Not documented |
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There is no memory the agent reads across runs. The Issues Catalog tracks recurring issues with the root cause, symptoms, impact and resolution steps, which is a record of the customer's incidents, not agent memory. Sourcemetoro.io/docs/ai-sre/overviewread 2026-09-29 |
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| Deployment & Data Residency | Full |
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Three deployment models are offered, Metoro Cloud, Metoro BYOC and Metoro On-Prem, and there are on premises installation guides for the Metoro Hub (On-Premises 11.x). Sourcemetoro.io/pricingread 2026-09-29 |
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| Prebuilt Agents, Templates & Packs | Partial |
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Deployment verification, anomaly detection and root cause, alert investigations, runbook following and code fixes are capabilities of one agent, Guardian, not separately adoptable agents. The dashboard templates are not agents either. Sourcemetoro.io/docs/ai-sre/overviewread 2026-09-29 |
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| Triggers & Channel Coverage | Full |
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Guardian starts on its own on a new_deployment event, on anomalies it detects such as error rate spikes, and when an alert fires from a known threshold or condition, and runbooks run when a configured alert triggers. Sourcemetoro.io/docs/ai-sre/overviewread 2026-09-29 |
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| Model Flexibility & Routing | Not documented |
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The model is Metoro's choice, named as Claude Opus 4.5, a single named maker. Customers may optionally run Guardian's model calls on their own AWS Bedrock account, and otherwise Metoro's default credentials are used. That decides where the calls run, not which model maker serves them. Sourcemetoro.io/docs/ai-sre/aws-bedrock-setupread 2026-09-29 |
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| APIs, SDKs & MCP Extensibility | Full |
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There is an API with an OpenAPI spec (query logs, create environments, create or update alerts and dashboards) and webhook events. The Metoro MCP server runs on the workspace URL with API key auth and offers tools such as create_investigation and create_ai_issue. Sourcemetoro.io/docs/integrations/metoro-mcp-serverread 2026-09-29 |
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| Testing, Debugging & Optimization | Not documented |
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Deployment verification compares telemetry, log patterns and latency before and after each rollout, which validates the customer's change, not Guardian's own behavior. There is no evaluation of the agent's investigations or fixes. Sourcemetoro.io/docs/ai-sre/overviewread 2026-09-29 |
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| Browser & Computer Use | Not documented |
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There is no browser, desktop or computer control. Guardian works through Metoro's telemetry, GitHub and Slack integrations. Sourcemetoro.io/docs/ai-sre/overviewread 2026-09-29 |
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The Agentic Index coverage score grades every vendor Full, Partial or Not documented against the same 14 buyer facing capabilities, from public evidence only. Each capability links to how all vendors in the index score on it. How this evidence is graded
Pricing
Hobby free (up to 2 nodes); Scale $20 per node per month plus $0.20 per GB over 100 GB per node; Enterprise custom
Per node per month, with data overage per GB above 100 GB per node; LLM usage passed through at cost
What is public
The Hobby limits, the Scale per node price and data overage rate, retention, deployment models and security inclusions by tier; Enterprise is custom.
Cost watchouts
Data above 100 GB per node is billed at $0.20 per GB, and AI investigations add LLM usage at cost unless the customer brings its own Bedrock keys.
Variable cost rationale
Cost scales with node count and data volume above the per node allowance, plus LLM usage passed through at cost.
Overage / add-ons
$0.20 per GB above 100 GB per node
Sales call required
Mixed (some tiers require a call)
Free / trial
Free Hobby tier: 1 cluster, 1 user, up to 2 nodes
Lowest paid plan
Scale, $20 per node per month
Key ambiguities
Enterprise is quoted on contact, so the price of the tier that carries the BYOC and on premises options is not public.
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Alternatives to Metoro
The closest documented capability profiles to Metoro among SRE and DevOps agents tracked by Agentic Index, ordered by similarity on the same 14 point evidence the rankings use. No vendor pays for placement.
- Middleware8.0 / 14A lighter documented profile than MetoroMetoro vs Middleware →
- Better Stack9.5 / 14Adds documented Memory & State Persistence
- Bluebricks10.5 / 14Adds documented Memory & State Persistence and Testing, Debugging & Optimization
- Causely9.5 / 14Fuller documented coverage on Observability & Auditability and Prebuilt Agents, Templates & Packs
- Harness7.5 / 14A lighter documented profile than Metoro
- PagerDuty10.5 / 14Adds documented Memory & State Persistence and Testing, Debugging & Optimization
Similarity is computed from each vendor's Agentic Index coverage score evidence, axis by axis, not from the totals. How this evidence is graded