Agentic Index
Metoro vs Middleware (2026)
Both vendors last verified
Metoro and Middleware both pair observability with an AI SRE agent that opens fix pull requests, both are self serve with a free tier, and they differ on scope and on how they charge. That verdict is the Agentic Index coverage score, graded from each vendor's own published materials.
Metoro is Kubernetes native, collecting telemetry with eBPF, and its Guardian agent finds root cause and opens fixes. It is free for up to two nodes and $20 per node a month on Scale. Middleware is full stack observability whose OpsAI agent detects issues across APM, RUM, logs and Kubernetes, traces errors to the line through GitHub MCP and opens or applies fix pull requests. Its Free Forever tier covers 100 GB, and Pay As You Go is $0.30 per GB. Metoro adds an API with an OpenAPI spec and runbooks for each alert written as numbered steps. Choose Metoro for Kubernetes estates priced by node. Choose Middleware for full stack observability priced by data volume.
On the Agentic Index production ops ranking, neither Metoro nor Middleware clears the bar, which asks for all five resolution loop capabilities documented in full. Metoro does not document observability and auditability in full; Middleware does not document workflow orchestration in full, nor observability and auditability. 15 of the 38 vendors in the lane clear it. See the production ops ranking
This comparison is published by Agentic Index, an independent agentic AI vendor research platform. Metoro and Middleware are each graded against the same 14 capability Agentic Index taxonomy, from the vendor's own public materials under the Agentic Index verification standard, alongside 1,084 researched vendors. No vendor pays for placement and no vendor has reviewed this page. How this evidence is graded
Choose Metoro if
- Your estate is Kubernetes, and you want eBPF telemetry without instrumenting code.
- A per node price suits how your costs grow.
- Your developers want an OpenAPI spec for logs, alerts and dashboards.
Choose Middleware if
- You need APM, real user monitoring and logs as well as Kubernetes.
- Errors should be traced to the line through GitHub.
- A per GB price, with 100 GB free, suits how your costs grow.
| Feature | M Metoro |
M Middleware |
|---|---|---|
| Action & orchestration | ||
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Integrations & Tool Calling Ability to connect agents to real systems through native integrations, OAuth-authenticated actions, custom tools, APIs, webhooks, or MCP-compatible tools. |
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MetoroIntegrations & Tool Calling 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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MiddlewareIntegrations & Tool Calling OpsAI acts in outside systems. For Kubernetes it can apply fixes directly, and it connects to the repo through GitHub MCP and opens pull requests. It ingests alerts from Datadog and Grafana beside Middleware's own telemetry, investigating with their metrics, logs and traces without a migration. Vercel is supported as a source too, and Slack carries conversations with OpsAI. SourceMiddleware, middleware.io/product/ops-ai and docs.middleware.io OpsAI overviewread 2026-10-05 |
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Workflow Orchestration Ability to sequence, branch, retry, route, and combine deterministic workflow nodes with autonomous agent steps. |
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MetoroWorkflow Orchestration 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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MiddlewareWorkflow Orchestration OpsAI runs its own fixed sequence of detection, root cause and then a proposed fix, an automatic Kubernetes fix or a pull request. The Auto RCA or Auto Fix mode is the only setting. There is no workflow builder, branching or multiple agents. Auto Investigation runs the root cause step on its own across Kubernetes, APM and RUM using the telemetry already collected. SourceMiddleware, docs.middleware.io OpsAI overviewread 2026-10-05 |
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Triggers & Channel Coverage How agents wake up and where they work: schedules, webhooks, message events, CRM events, inbox events, chat, email, voice, and collaboration tools. |
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MetoroTriggers & Channel Coverage 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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MiddlewareTriggers & Channel Coverage OpsAI starts on automatic issue detection across APM, RUM and Kubernetes and on alerts from Middleware or integrated platforms, taking the alert and pulling in stack traces and logs, as well as from a conversation. Alerts appear in the OpsAI listing, and teams can also start a conversation by mentioning @Middleware in Slack. SourceMiddleware, docs.middleware.io OpsAI overviewread 2026-10-05 |
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| Knowledge & context | ||
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Knowledge Grounding & RAG Ability to ground agent behavior in company data through document ingestion, retrieval, external knowledge APIs, semantic search, or RAG layers. |
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MetoroKnowledge Grounding & RAG 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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MiddlewareKnowledge Grounding & RAG OpsAI works over Middleware's persisted store of the customer's APM traces, RUM data, logs and Kubernetes telemetry, and reads only the files related to a specific error through GitHub MCP for source context. It can also investigate with the metrics, logs and traces held in Datadog and Grafana, and teams can query their observability data by talking to OpsAI. SourceMiddleware, middleware.io/product/ops-ai and docs.middleware.io OpsAI overviewread 2026-10-05 |
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Memory & State Persistence Ability to persist context across a run, conversation, workflow, user, team, or longer-term memory layer. |
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MetoroMemory & State Persistence 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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MiddlewareMemory & State Persistence OpsAI keeps no memory or context from one issue to the next. It does not store the customer's source code, and error context is not stored either. Each investigation draws on the telemetry already collected for that issue. SourceMiddleware, middleware.io/product/ops-ai and docs.middleware.io OpsAI overviewread 2026-10-05 |
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| Control & trust | ||
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Human Oversight & Guardrails Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls. |
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MetoroHuman Oversight & Guardrails 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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MiddlewareHuman Oversight & Guardrails In Auto RCA mode, OpsAI suggests fixes for review and users apply the proposed fix with a single click, so a person commits each Kubernetes fix unless the team opts into Auto Fix, which modifies the Kubernetes object directly. Code changes arrive as pull requests with the suggested changes and the context needed for review, so developers keep control of code. SourceMiddleware, middleware.io/product/ops-ai, docs.middleware.io OpsAI overview and OpsAI for Kubernetesread 2026-10-05 |
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Security, Identity & Governance RBAC, SSO, auditability, encryption, least-privilege tool access, compliance posture, and data handling policy. |
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MetoroSecurity, Identity & Governance 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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MiddlewareSecurity, Identity & Governance SSO and security features come with the Pay As You Go plan, OpsAI's GitHub reads are scoped to the files related to an error, and Middleware displays SOC 2 Type II, ISO 27001, HIPAA and GDPR badges for OpsAI. OpsAI never reads the full codebase, and Middleware stores neither the source code nor the error context. SourceMiddleware, middleware.io/pricing, middleware.io/product/ops-ai and docs.middleware.io OpsAI overviewread 2026-10-05 |
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Observability & Auditability Traces, logs, execution histories, metrics, audit events, and debugging detail for production agent behavior. |
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MetoroObservability & Auditability 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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MiddlewareObservability & Auditability Each issue carries OpsAI's root cause analysis and a proposed fix with a side by side diff, and each pull request carries the context a reviewer needs. There is no record of the steps, queries or actions OpsAI took, and Middleware does not say whether Auto Fix actions are logged. SourceMiddleware, docs.middleware.io OpsAI overviewread 2026-10-05 |
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Deployment & Data Residency Deployment modes and options, including SaaS, dedicated cloud, VPC, on-prem, hybrid, local runtime, and self-hosting. |
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MetoroDeployment & Data Residency 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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MiddlewareDeployment & Data Residency A BYOC plan offers Bring Your Own Cloud deployment with custom data retention and custom pricing, beside the hosted plans, which keep data 14 days on the free tier and 30 days by default on Pay As You Go. For Kubernetes, the Middleware agent runs inside the customer's own cluster. SourceMiddleware, middleware.io/pricing and docs.middleware.io OpsAI for Kubernetesread 2026-10-05 |
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| Solution readiness | ||
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Prebuilt Agents, Templates & Packs Ready-made workflows, packaged employees, templates, blueprints, industry solutions, and role-specific agents that reduce time-to-value. |
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MetoroPrebuilt Agents, Templates & Packs 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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MiddlewarePrebuilt Agents, Templates & Packs OpsAI is a single ready to run agent, with detection across APM, RUM, logs and Kubernetes and two modes. There is no set of separate agents or templates to adopt. OpsAI covers Java, Node.js, Python, Go and Next.js on the backend and JavaScript and React in the browser. SourceMiddleware, middleware.io/product/ops-ai and docs.middleware.io OpsAI overviewread 2026-10-05 |
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| Platform extensibility | ||
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Model Flexibility & Routing Ability to work across multiple foundation models, route tasks to different models, or let buyers bring their own providers and keys. |
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MetoroModel Flexibility & Routing 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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MiddlewareModel Flexibility & Routing Middleware names no model provider for OpsAI and offers no model choice. OpsAI is billed in OpsAI tokens by use, error detection is free, and the free tier includes 2 million OpsAI tokens. SourceMiddleware, middleware.io/pricing and docs.middleware.io OpsAI overviewread 2026-10-05 |
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APIs, SDKs & MCP Extensibility Composability layer: stable APIs, SDKs, MCP tool consumption/serving, custom tools, and integration into internal systems. |
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MetoroAPIs, SDKs & MCP Extensibility 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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MiddlewareAPIs, SDKs & MCP Extensibility The platform has a Public API. OpenTelemetry and APM SDKs for Python, Go, Node.js, Next.js and Java send data in, and GitHub MCP is how OpsAI reaches out to the customer's repository, not a way into Middleware. Teams can also talk to OpsAI in Slack by mentioning @Middleware. SourceMiddleware, docs.middleware.io OpsAI overviewread 2026-10-05 |
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Testing, Debugging & Optimization Testing, debugging, scoring, retries, fallbacks, quality gates, and optimization loops for improving agent workflows before and after deployment. |
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MetoroTesting, Debugging & Optimization 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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MiddlewareTesting, Debugging & Optimization OpsAI debugs the customer's application. There is no harness, scored tests, quality gate or improvement loop for the agent itself. In Auto RCA mode, each proposed fix comes with a side by side diff that a person checks before applying it. SourceMiddleware, docs.middleware.io OpsAI overviewread 2026-10-05 |
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| Specialist automation | ||
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Browser & Computer Use Browser, desktop, or remote/local computer control for workflows that cannot be handled through stable APIs alone. |
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MetoroBrowser & Computer Use 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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MiddlewareBrowser & Computer Use OpsAI works through telemetry, Kubernetes and GitHub. The browser test runs in the pricing plans are synthetic monitoring of the customer's site, not an agent operating a browser. Sourcemiddleware.io/product/ops-airead 2026-09-29 |
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Pricing snapshot
Sourced from the Index pricing dataset · open each vendor's profile for full detail.
| Pricing | M Metoro |
M Middleware |
|---|---|---|
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Entry price Lowest public entry point |
Hobby free (up to 2 nodes); Scale $20 per node per month plus $0.20 per GB over 100 GB per node; Enterprise custom | Free Forever tier; Pay As You Go $0.30 per GB of metrics, logs and traces; BYOC custom |
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Pricing confidence How public the numbers are |
Public, exact | Public, exact |
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Billing Primary billing axis |
Per node per month, with data overage per GB above 100 GB per node; LLM usage passed through at cost | Per GB ingested, plus RUM sessions, synthetic checks and browser test runs; OpsAI root cause and fixes in tokens |
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Variable cost Workload / overage exposure |
Medium variable cost | High variable cost |
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Free tier / trial Try before you buy |
Free tier
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Free tier
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Buying motion Self-serve vs sales call |
Mixed | Mixed |
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Pricing verified When this pricing was last checked |
Product updates
Newest first, each linked to its source.
Middleware
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· Agent capability
OpsAI, the SRE agent in Middleware, now comes with built in skills: reusable instructions for investigations such as error analysis, latency troubleshooting, Kubernetes, databases and LLM observability.
Source
Both publish prices. Model your own node count and data volume before comparing.
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