Grafana vs New Relic

Agent access

1. ai-native userPoint an agent at llms.txt or agent-oriented docs

   weight 2 · round to Grafana
   Grafana✓fullprobed9/10

   Direct probe confirms llms.txt exists and returns HTTP 200 with structured content, and docs pages are served in markdown format via .md suffix, both directly satisfying the agent-oriented docs story. Missing for 10: independent third-party confirmation of agents actually consuming these formats successfully in the wild.

   • [probe] “PROBE llms.txt: HTTP 200 at https://grafana.com/llms.txt # Grafana documentation > Grafana Labs builds open and composable observability so…”
   • [probe] “PROBE docs-md: HTTP 200 at https://grafana.com/docs/grafana/latest/.md --- title: "Grafana OSS and Enterprise | Grafana documentation" descr…”

   proof ↗⚑ flag

   New Relic—none0/10

   A direct probe confirms llms.txt returns 404, and there's no evidence of agent-oriented docs designed for AI consumption; the MCP server is a separate integration mechanism, not agent-readable documentation. Missing for 10: an llms.txt file, any agent-oriented/markdown docs format, or evidence of AI agents successfully consuming New Relic docs directly.

   • [probe] “PROBE llms.txt: HTTP 404 at https://docs.newrelic.com/llms.txt”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.newrelic.com/openapi.json, https://docs.newrelic.com/swagger.json, https://docs.newreli…”

   proof ↗⚑ flag

2. ai-native userRun the product headlessly / in CI for automation

   weight 2 · round to Grafana
   Grafana✓fullprobed8/10

   Grafana explicitly documents a CLI/observability-as-code workflow 'suitable for CI/CD pipelines, local development' with authentication and admin tasks from the terminal, plus provisioning via version-controlled config files for GitOps, and exposes an OpenAPI-based API for programmatic/headless automation. These combine to give clear first-party support for running Grafana headlessly in CI. Missing for 10: independent/community corroboration of actual CI usage or hands-on reports validating headless automation workflows.

   • [claimed-docs] “You can authenticate, manage multiple environments, and perform administrative tasks from the terminal. It’s suitable for CI/CD pipelines, l…”
   • [claimed-docs] “Grafana has an active provisioning system that uses configuration files. You can define data sources and dashboards using files that can be …”
   • [claimed-docs] “You can define data sources and dashboards using files that can be version controlled, making GitOps more natural.”
   • [claimed-docs] “define dashboards, data sources, and other configurations in code, enabling version control, automated testing, and reliable deployments thr…”
   • [probe] “PROBE openapi: HTTP 200 at https://grafana.com/api/openapi.json — contains "openapi" key”
   • [probe] “official CLI documented at https://grafana.com/docs/grafana/latest/administration/cli/”

   proof ↗⚑ flag

   New Relic~partialprobed6/10

   New Relic ships an official CLI (newrelic-cli) for deployment markers and entity search, plus a GraphQL-based NerdGraph API, both of which are inherently scriptable/headless and usable in CI pipelines (e.g. recording deployment markers on release). However, there is no explicit CI/CD integration guide, pipeline example, or documented automation workflow tying these together for AI-native/agentic use. Missing for 10: explicit CI/CD pipeline documentation or examples, evidence of headless operation being a first-class supported workflow, and independent confirmation of CLI use in automated pipelines.

   • [github] “Entity Search: Search for entities across all your New Relic accounts”
   • [github] “Deployment Markers: Easily record an APM Application deployment within New Relic.”
   • [claimed-docs] “NerdGraph is our GraphQL-format API that lets you query New Relic data and configure some New Relic features.”
   • [claimed-docs] “An easy way to experiment with the NerdGraph API is to use the NerdGraph API explorer.”
   • [probe] “official CLI documented at https://github.com/newrelic/newrelic-cli”

   proof ↗⚑ flag

3. ai-native userPlug MCP servers into this product so it can use their tools

   weight 3 · round drawn
   Grafana—none0/10

   The evidence shows Grafana ships an MCP *server* (Cloud MCP Server / self-managed grafana-mcp) that lets external AI agents call Grafana's own tools — this is the reverse direction of the story, which asks whether Grafana itself can plug in and consume external MCP servers' tools. No evidence describes Grafana acting as an MCP client that connects to and uses external MCP servers.

   • [claimed-docs] “Connect AI agents to Grafana through the fully hosted Cloud MCP Server or the self-managed open source MCP Server.”
   • [probe] “official MCP server documented at https://github.com/grafana/mcp-grafana”

   proof ↗⚑ flag

   New Relic—none0/10

   Evidence shows New Relic ships an official MCP server so external AI tools can connect to New Relic's data (new-relic-docs-11, new-relic-docs-22, new-relic-probe-3) — this is the reverse direction (New Relic as MCP server, not MCP client). No evidence indicates New Relic's own AI assistant or platform can consume/plug in external MCP servers to use their tools.

   • [claimed-docs] “This update provides a standardized, scalable way to connect your favorite AI development tools directly to the rich context of the New Reli…”
   • [claimed-docs] “Ask questions in plain English, and the MCP server converts them to NRQL to get results—even if you're not a NRQL expert.”
   • [probe] “official MCP server documented at https://docs.newrelic.com/whats-new/2025/11/whats-new-11-05-mcp-server/”
   • [claimed-docs] “It allows you to ask questions, troubleshoot issues, and explore telemetry data using plain language.”

   proof ↗⚑ flag

4. ai-native userConnect an agent via an official MCP server

   weight 3 · round to Grafana
   Grafana✓fullprobed9/10

   Grafana documents official MCP server support explicitly: both a fully hosted Cloud MCP Server and a self-managed open source MCP Server, confirmed by first-party docs and a dedicated GitHub repo (grafana/mcp-grafana). This directly satisfies connecting an agent via an official MCP server. Missing for 10: independent hands-on third-party review of the MCP server's reliability/functionality beyond vendor docs and repo existence.

   • [claimed-docs] “Connect AI agents to Grafana through the fully hosted Cloud MCP Server or the self-managed open source MCP Server.”
   • [probe] “official MCP server documented at https://github.com/grafana/mcp-grafana”
   • [claimed-docs] “Understand production systems faster using natural language”

   proof ↗⚑ flag

   New Relic✓fullprobed8/10

   New Relic ships an official MCP server (documented Nov 2025) that connects AI development tools to New Relic's platform context, including converting plain-English questions into NRQL queries. This is first-party vendor documentation with a dedicated release note and probe-confirmed URL, but lacks independent/hands-on corroboration of the MCP server's reliability. Missing for 10: independent or hands-on validation of the MCP server, detail on setup/auth flow and supported tool integrations.

   • [claimed-docs] “This update provides a standardized, scalable way to connect your favorite AI development tools directly to the rich context of the New Reli…”
   • [claimed-docs] “Ask questions in plain English, and the MCP server converts them to NRQL to get results—even if you're not a NRQL expert.”
   • [probe] “official MCP server documented at https://docs.newrelic.com/whats-new/2025/11/whats-new-11-05-mcp-server/”

   proof ↗⚑ flag

5. ai-native userUse an official CLI

   weight 2 · round to Grafana
   Grafana✓fullprobed6/10

   Grafana ships an official CLI (grafana-probe-5) with documented capabilities for authentication, multi-environment management, and administrative/CI-CD tasks from the terminal (grafana-docs-26), which an AI-native/agentic user could script against. Missing for 10: no evidence of AI-specific CLI features (e.g., natural-language CLI commands, agent-oriented output formats) and no independent/hands-on corroboration of the CLI's usability in agentic workflows.

   • [probe] “official CLI documented at https://grafana.com/docs/grafana/latest/administration/cli/”
   • [claimed-docs] “You can authenticate, manage multiple environments, and perform administrative tasks from the terminal. It’s suitable for CI/CD pipelines, l…”

   proof ↗⚑ flag

   New Relic~partialprobed6/10

   New Relic ships an official open-source CLI (newrelic-cli) supporting entity search, deployment markers, and platform configuration, confirmed via GitHub repo and probe. However, the evidence doesn't show AI-native features specific to the CLI itself (e.g., natural-language query support, agentic workflows are only documented for the separate MCP server/AI assistant, not the CLI). Missing for 10: documentation of AI-native/agentic capabilities within the CLI itself, independent hands-on reviews of the CLI, and details on how it integrates with AI coding agents.

   • [github] “Entity Search: Search for entities across all your New Relic accounts”
   • [github] “Deployment Markers: Easily record an APM Application deployment within New Relic.”
   • [probe] “official CLI documented at https://github.com/newrelic/newrelic-cli”

   proof ↗⚑ flag

6. ai-native userDrive the product through a documented public API

   weight 3 · round drawn
   Grafana✓fullprobed8/10

   Grafana exposes a documented public HTTP API confirmed by a live OpenAPI spec (grafana-probe-3), plus provisioning/as-code docs and a CLI for automation (grafana-docs-2, grafana-docs-26, grafana-probe-5), and even an official MCP server and llms.txt for AI-agent access (grafana-docs-7, grafana-probe-4, grafana-probe-1). This gives strong first-party and probe-verified evidence of a documented, machine-drivable API surface. Missing for 10: independent hands-on developer confirmation of API completeness/stability and rate-limit/versioning details.

   • [probe] “PROBE openapi: HTTP 200 at https://grafana.com/api/openapi.json — contains "openapi" key”
   • [claimed-docs] “Grafana has an active provisioning system that uses configuration files. You can define data sources and dashboards using files that can be …”
   • [claimed-docs] “You can authenticate, manage multiple environments, and perform administrative tasks from the terminal. It’s suitable for CI/CD pipelines, l…”
   • [probe] “official CLI documented at https://grafana.com/docs/grafana/latest/administration/cli/”
   • [claimed-docs] “Connect AI agents to Grafana through the fully hosted Cloud MCP Server or the self-managed open source MCP Server.”
   • [probe] “official MCP server documented at https://github.com/grafana/mcp-grafana”
   • [probe] “PROBE llms.txt: HTTP 200 at https://grafana.com/llms.txt # Grafana documentation > Grafana Labs builds open and composable observability so…”

   proof ↗⚑ flag

   New Relic✓fullprobed8/10

   New Relic documents NerdGraph, a GraphQL API for querying data and configuring features, with an interactive explorer, plus an official CLI (newrelic-cli) that wraps API functionality for entity search and deployment markers. This constitutes a documented public API surface that can be driven programmatically outside the UI. Missing for 10: no discoverable OpenAPI/Swagger spec (probe found 404s) and no independent hands-on developer corroboration of NerdGraph usage beyond docs.

   • [claimed-docs] “NerdGraph is our GraphQL-format API that lets you query New Relic data and configure some New Relic features.”
   • [claimed-docs] “An easy way to experiment with the NerdGraph API is to use the NerdGraph API explorer.”
   • [github] “Entity Search: Search for entities across all your New Relic accounts”
   • [github] “Deployment Markers: Easily record an APM Application deployment within New Relic.”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.newrelic.com/openapi.json, https://docs.newrelic.com/swagger.json, https://docs.newreli…”
   • [probe] “official CLI documented at https://github.com/newrelic/newrelic-cli”

   proof ↗⚑ flag

7. ai-native userIssue scoped/least-privilege API credentials for an agent

   weight 2 · round drawn
   Grafana—none0/10

   The evidence pack shows Grafana has an MCP server for agent connectivity (grafana-docs-7, grafana-probe-4) but contains no mention of scoped or least-privilege API keys, service accounts, or role-based credential issuance for agents. Absence of evidence for this applicable capability means it cannot be credited as delivered.

   • [claimed-docs] “Connect AI agents to Grafana through the fully hosted Cloud MCP Server or the self-managed open source MCP Server.”
   • [probe] “official MCP server documented at https://github.com/grafana/mcp-grafana”

   proof ↗⚑ flag

   New Relic—none0/10

   New Relic offers API access (NerdGraph, user keys) and an MCP server for AI tools, but no evidence describes scoped/least-privilege credential issuance specifically for agents (e.g., fine-grained API key scoping, role-based agent tokens). Missing for 10: documentation of scoped API key creation, least-privilege permission models for agent credentials, or agent-specific token management.

   • [claimed-docs] “NerdGraph is our GraphQL-format API that lets you query New Relic data and configure some New Relic features.”
   • [claimed-docs] “This update provides a standardized, scalable way to connect your favorite AI development tools directly to the rich context of the New Reli…”
   • [claimed-docs] “Ask questions in plain English, and the MCP server converts them to NRQL to get results—even if you're not a NRQL expert.”

   proof ↗⚑ flag

8. ai-native userBuild against official SDKs

   weight 2 · round to New Relic
   Grafana—none0/10

   The evidence shows an OpenAPI spec (grafana-probe-3) and a CLI (grafana-probe-5), but no evidence of official client SDKs (e.g., Python/Go/JS SDKs) that AI-native developers could build against programmatically. Missing for 10: documented official SDK packages/libraries, SDK usage examples, or client-library release notes.

   • [probe] “PROBE openapi: HTTP 200 at https://grafana.com/api/openapi.json — contains "openapi" key”
   • [probe] “official CLI documented at https://grafana.com/docs/grafana/latest/administration/cli/”

   proof ↗⚑ flag

   New Relic✓fullprobed7/10

   New Relic ships official first-party agents/SDKs for Go, Java, .NET, Node.js, PHP, Python, and Ruby, plus a GraphQL-based NerdGraph API with an interactive API explorer, OpenTelemetry instrumentation support, and an official CLI (newrelic-cli), giving developers multiple official, documented ways to build against the platform. Missing for 10: independent/hands-on corroboration of SDK developer experience and no explicit AI-native SDK features (e.g., no OpenAPI spec found, llms.txt 404).

   • [claimed-docs] “Monitor application performance across your stack. We've got agents for Go, Java, .NET, Node.js, PHP, Python, and Ruby.”
   • [claimed-docs] “NerdGraph is our GraphQL-format API that lets you query New Relic data and configure some New Relic features.”
   • [claimed-docs] “Instrument your service with OpenTelemetry and gain platform-agnostic observability.”
   • [claimed-docs] “An easy way to experiment with the NerdGraph API is to use the NerdGraph API explorer.”
   • [github] “Entity Search: Search for entities across all your New Relic accounts”
   • [probe] “official CLI documented at https://github.com/newrelic/newrelic-cli”
   • [probe] “PROBE llms.txt: HTTP 404 at https://docs.newrelic.com/llms.txt”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.newrelic.com/openapi.json, https://docs.newrelic.com/swagger.json, https://docs.newreli…”

   proof ↗⚑ flag

9. ai-native userSubscribe to events via webhooks

   weight 2 · round drawn
   Grafana—none0/10

   The evidence pack covers Grafana alerting, dashboards, and MCP integration, but nothing documents webhook-based event subscription (e.g., outgoing alert webhooks or webhook triggers for agents). Missing for 10: any citation describing webhook contact points/notifiers or an event subscription API.

   ⚑ flag

   New Relic—none0/10

   The evidence pack shows alerts, dashboards, NerdGraph API, MCP server, and CLI capabilities, but no mention of webhook subscriptions for events or any pub/sub-style event notification mechanism for external systems. Alerts docs mention notifications but do not describe webhook subscription APIs. Missing for 10: any documentation of a webhooks feature, webhook configuration API, or event subscription endpoint.

   • [claimed-docs] “You define the data to watch, the thresholds that if exceeded mean an issue, who is notified, and how.”
   • [claimed-docs] “NerdGraph is our GraphQL-format API that lets you query New Relic data and configure some New Relic features.”

   proof ↗⚑ flag

Agentic features

1. ai-native userGet AI-generated insights and suggestions from my data inside the product

   weight 2 · round to New Relic
   Grafana~partialclaimed5/10

   Grafana Cloud markets natural-language driven understanding of production systems and provides an official MCP server so AI agents can query Grafana data (grafana-docs-7, grafana-docs-8), which implies AI-generated insights are emerging in the product. However, evidence is thin marketing copy with no concrete feature walkthrough, no independent/hands-on confirmation, and no detail on what 'insights and suggestions' actually look like. Missing for 10: detailed documentation of specific AI-insight features (e.g., anomaly detection, auto-generated explanations), independent/hands-on validation, and confirmation this is generally available rather than early-access marketing.

   • [claimed-docs] “Connect AI agents to Grafana through the fully hosted Cloud MCP Server or the self-managed open source MCP Server.”
   • [claimed-docs] “Understand production systems faster using natural language”

   proof ↗⚑ flag

   New Relic✓fullclaimed7/10

   New Relic AI (docs-9, docs-10) provides in-product AI assistant for plain-language querying, troubleshooting suggestions, and query help, plus an MCP server (docs-11, docs-22) that converts natural language to NRQL for insights. This is first-party documented but lacks independent/hands-on corroboration of quality or depth of insights generated. Missing for 10: independent user validation of AI insight quality, detail on proactive/automated insight generation beyond query assistance, and depth of anomaly-detection or automated root-cause AI features.

   • [claimed-docs] “It allows you to ask questions, troubleshoot issues, and explore telemetry data using plain language.”
   • [claimed-docs] “If you're struggling to get a query to work, ask our AI assistant to help you.”
   • [claimed-docs] “This update provides a standardized, scalable way to connect your favorite AI development tools directly to the rich context of the New Reli…”
   • [claimed-docs] “Ask questions in plain English, and the MCP server converts them to NRQL to get results—even if you're not a NRQL expert.”

   proof ↗⚑ flag

2. ai-native userSet up automations that run autonomously in the background

   weight 2 · round to Grafana
   Grafana~partialclaimed5/10

   Grafana Alerting, on-call escalation, and incident workflows run continuously and autonomously once configured (grafana-docs-1, grafana-docs-6, grafana-docs-19, grafana-docs-24), and provisioning/as-code lets users automate deployment of these configs via CI/CD (grafana-docs-2, grafana-docs-16, grafana-docs-26). However, this is traditional monitoring automation, not an AI-native agentic automation framework—there's no evidence of AI agents autonomously executing multi-step tasks or scheduled agent runs beyond the MCP connector letting external agents query Grafana. Missing for 10: evidence of AI-driven autonomous task execution/orchestration, scheduled agent workflows, or an agent framework beyond alert/escalation rules.

   • [claimed-docs] “you create queries and expressions from multiple data sources, no matter where you store your data... create, manage, and take action on you…”
   • [claimed-docs] “Use it to create on-call schedules, escalate alerts to the people who are on call, and coordinate incidents from declaration through post-in…”
   • [claimed-docs] “create on-call schedules, escalate alerts to the people who are on call, and coordinate incidents from declaration through post-incident rev…”
   • [claimed-docs] “Grafana Alerting allows you to learn about problems in your systems moments after they occur.”
   • [claimed-docs] “Grafana has an active provisioning system that uses configuration files. You can define data sources and dashboards using files that can be …”
   • [claimed-docs] “define dashboards, data sources, and other configurations in code, enabling version control, automated testing, and reliable deployments thr…”
   • [claimed-docs] “You can authenticate, manage multiple environments, and perform administrative tasks from the terminal. It’s suitable for CI/CD pipelines, l…”
   • [claimed-docs] “Connect AI agents to Grafana through the fully hosted Cloud MCP Server or the self-managed open source MCP Server.”

   proof ↗⚑ flag

   New Relic~partialclaimed4/10

   New Relic's alerting system lets you define thresholds and notification rules that run continuously in the background without further manual intervention (new-relic-docs-5, new-relic-docs-21/25), which is a basic autonomous background automation. However, the 'ai-native/agentic' framing (AI assistant, MCP server) is described as an interactive query/troubleshooting helper (new-relic-docs-9/10) or a connector for external AI tools (new-relic-docs-11/22) rather than an autonomous agent that itself sets up and runs background tasks. Missing for 10: evidence of AI-driven workflows/agents that autonomously configure or execute actions (not just user-defined alert rules), a documented automation/workflow engine beyond alerting, and independent corroboration that these run unattended reliably.

   • [claimed-docs] “You define the data to watch, the thresholds that if exceeded mean an issue, who is notified, and how.”
   • [claimed-docs] “NRQL can help you: Create a new chart ... Set up NRQL-based alerts (our primary and most powerful type of alert)”
   • [claimed-docs] “Set up NRQL-based alerts (our primary and most powerful type of alert)”
   • [claimed-docs] “It allows you to ask questions, troubleshoot issues, and explore telemetry data using plain language.”
   • [claimed-docs] “This update provides a standardized, scalable way to connect your favorite AI development tools directly to the rich context of the New Reli…”
   • [claimed-docs] “Ask questions in plain English, and the MCP server converts them to NRQL to get results—even if you're not a NRQL expert.”

   proof ↗⚑ flag

3. ai-native userDelegate tasks to a built-in AI assistant inside the product

   weight 3 · round to New Relic
   Grafana~partialprobed3/10

   Grafana's docs mention 'Understand production systems faster using natural language' on its Cloud AI-tools page, hinting at some built-in AI assistant capability, but the pack's concrete AI evidence is almost entirely about the MCP Server letting external AI agents connect TO Grafana (docs-7, probe-4) — the opposite direction of a user delegating tasks to an assistant embedded in the product. There is no documentation of assistant UI, task types it can perform, or hands-on validation of such a feature. Missing for 10: description of an actual built-in assistant interface, concrete examples of delegated tasks/actions it performs, and independent/community confirmation it works.

   • [claimed-docs] “Understand production systems faster using natural language”
   • [claimed-docs] “Connect AI agents to Grafana through the fully hosted Cloud MCP Server or the self-managed open source MCP Server.”
   • [probe] “official MCP server documented at https://github.com/grafana/mcp-grafana”

   proof ↗⚑ flag

   New Relic✓fullclaimed7/10

   New Relic docs describe a built-in AI assistant (New Relic AI) that lets users ask questions in plain language, troubleshoot issues, explore telemetry data, and get help building NRQL queries directly inside the product. This matches the story of delegating tasks to an in-product AI assistant, though evidence is vendor-documentation only with no independent hands-on verification of task delegation depth or reliability. Missing for 10: independent/community corroboration of the assistant's real-world task delegation capability and quality, and more detail on the scope of tasks it can autonomously perform beyond Q&A/query help.

   • [claimed-docs] “It allows you to ask questions, troubleshoot issues, and explore telemetry data using plain language.”
   • [claimed-docs] “If you're struggling to get a query to work, ask our AI assistant to help you.”

   proof ↗⚑ flag

4. ai-native userOperate the product with natural-language commands

   weight 2 · round to New Relic
   Grafana~partialprobed6/10

   Grafana Cloud markets natural-language understanding of systems and ships both a hosted and self-managed MCP Server that lets AI agents connect and act on Grafana data (querying, dashboards, alerts) via natural language, which is the main enabler of this story. However, this is delivered through a separate MCP layer/agent integration rather than a native NL command interface built into the core product, and there's no first-party or community evidence of end-to-end hands-on validation of NL commands actually working reliably. Missing for 10: native in-product NL command bar/assistant, independent hands-on reports confirming NL-driven actions succeed reliably, broader coverage beyond MCP-mediated access.

   • [claimed-docs] “Connect AI agents to Grafana through the fully hosted Cloud MCP Server or the self-managed open source MCP Server.”
   • [claimed-docs] “Understand production systems faster using natural language”
   • [probe] “official MCP server documented at https://github.com/grafana/mcp-grafana”

   proof ↗⚑ flag

   New Relic✓fullprobed8/10

   New Relic AI lets users ask questions, troubleshoot, and explore telemetry in plain language, and the new MCP server explicitly converts natural-language questions into NRQL queries to retrieve results without requiring NRQL expertise. This directly delivers natural-language operation of the product for querying and troubleshooting. Missing for 10: independent/hands-on validation of the natural-language assistant's accuracy and broader coverage beyond querying (e.g., configuring alerts or dashboards via NL commands).

   • [claimed-docs] “It allows you to ask questions, troubleshoot issues, and explore telemetry data using plain language.”
   • [claimed-docs] “If you're struggling to get a query to work, ask our AI assistant to help you.”
   • [claimed-docs] “Ask questions in plain English, and the MCP server converts them to NRQL to get results—even if you're not a NRQL expert.”
   • [claimed-docs] “This update provides a standardized, scalable way to connect your favorite AI development tools directly to the rich context of the New Reli…”
   • [probe] “official MCP server documented at https://docs.newrelic.com/whats-new/2025/11/whats-new-11-05-mcp-server/”

   proof ↗⚑ flag

Api quality

1. ai-native userExplore an interactive API reference with runnable examples

   weight 2 · round to New Relic
   Grafana—none0/10

   Evidence shows Grafana exposes an OpenAPI spec (grafana-probe-3) but nothing indicates an interactive reference UI with runnable/try-it-out examples; docs excerpts focus on dashboards, alerting, and data sources, not API exploration tooling.

   • [probe] “PROBE openapi: HTTP 200 at https://grafana.com/api/openapi.json — contains "openapi" key”

   proof ↗⚑ flag

   New Relic~partialprobed5/10

   New Relic documents a NerdGraph API explorer for experimenting with its GraphQL API (new-relic-docs-20), which functions as an interactive, runnable reference for that API, but there's no evidence of a broader interactive API reference (e.g., REST API explorer/Swagger UI) covering the full platform, and probes show no OpenAPI spec or llms.txt exposed. Missing for 10: a comprehensive interactive reference across all New Relic APIs (not just NerdGraph), OpenAPI/Swagger-based explorer, and independent/hands-on confirmation of the explorer's usability.

   • [claimed-docs] “An easy way to experiment with the NerdGraph API is to use the NerdGraph API explorer.”
   • [claimed-docs] “NerdGraph is our GraphQL-format API that lets you query New Relic data and configure some New Relic features.”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.newrelic.com/openapi.json, https://docs.newrelic.com/swagger.json, https://docs.newreli…”

   proof ↗⚑ flag

2. ai-native userDownload a machine-readable API spec (OpenAPI or equivalent)

   weight 2 · round to Grafana
   Grafana✓fullprobed8/10

   A probe confirms Grafana exposes a machine-readable OpenAPI spec at /api/openapi.json (HTTP 200, contains 'openapi' key), directly satisfying the story. Missing for 10: first-party docs explicitly documenting/linking this spec for API consumers and independent developer corroboration of using it.

   • [probe] “PROBE openapi: HTTP 200 at https://grafana.com/api/openapi.json — contains "openapi" key”

   proof ↗⚑ flag

   New Relic—none0/10

   New Relic's primary API is NerdGraph (GraphQL), and explicit probes show no OpenAPI/swagger spec is served at any standard path (404s), with no other evidence of a downloadable machine-readable spec.

   • [claimed-docs] “NerdGraph is our GraphQL-format API that lets you query New Relic data and configure some New Relic features.”
   • [claimed-docs] “An easy way to experiment with the NerdGraph API is to use the NerdGraph API explorer.”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.newrelic.com/openapi.json, https://docs.newrelic.com/swagger.json, https://docs.newreli…”

   proof ↗⚑ flag

3. ai-native userTest against a sandbox environment without touching production data

   weight 1 · round drawn
   Grafana—none0/10

   There is no evidence of a dedicated sandbox/test environment feature isolated from production data; the closest is a suggestion to run Loki locally in monolithic mode for experimentation, which is a self-hosted local dev setup rather than a documented sandbox/testing environment for AI-native workflows. missing for 10: an official sandbox/staging environment offering, documentation on isolating test data from production, and any AI-agent-specific sandbox testing guidance.

   • [claimed-docs] “Try it locally. The fastest way to experiment is to run Loki in monolithic (single-binary) mode with a local filesystem backend and send log…”

   proof ↗⚑ flag

   New Relic—none0/10

   No evidence in the pack of a sandbox/test environment, free trial account isolation, or any mechanism to test New Relic's features without touching production telemetry data; all references are to production monitoring, alerting, dashboards, and the MCP server connecting to real platform data. Missing for 10: any documented sandbox account, test-mode API, synthetic data environment, or explicit separation between test and production data ingestion.

   ⚑ flag

4. ai-native userRely on versioned APIs with a documented deprecation policy

   weight 2 · round drawn
   Grafana—none0/10

   There's an OpenAPI spec probe confirming an API exists, but no evidence of API versioning scheme or a documented deprecation policy for that API; no changelog/deprecation policy citations appear anywhere in the pack.

   • [probe] “PROBE openapi: HTTP 200 at https://grafana.com/api/openapi.json — contains "openapi" key”

   proof ↗⚑ flag

   New Relic—none0/10

   Evidence shows NerdGraph API and NerdGraph explorer exist, but there is no documented API versioning scheme or deprecation policy; probes confirm no OpenAPI spec is discoverable, and no docs mention version numbers, sunset timelines, or breaking-change guarantees. Missing for 10: documented API versioning scheme, explicit deprecation/sunset policy, changelog or migration guide for breaking changes.

   • [claimed-docs] “NerdGraph is our GraphQL-format API that lets you query New Relic data and configure some New Relic features.”
   • [claimed-docs] “An easy way to experiment with the NerdGraph API is to use the NerdGraph API explorer.”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.newrelic.com/openapi.json, https://docs.newrelic.com/swagger.json, https://docs.newreli…”

   proof ↗⚑ flag

Agent integration

1. ai-native userHave an external agent query metrics, logs, and traces through documented APIs to debug production

   weight 3 · round drawn
   Grafana✓fullprobed9/10

   Grafana provides documented APIs/query languages for metrics, logs, and traces (LogQL, Tempo tracing, OpenAPI spec) plus an official MCP server (mcp-grafana and hosted Cloud MCP Server) explicitly built to let external AI agents query this telemetry for production debugging, and marketing copy confirms natural-language production troubleshooting. Missing for 10: independent hands-on report of an agent successfully debugging a real production incident via MCP.

   • [claimed-docs] “Connect AI agents to Grafana through the fully hosted Cloud MCP Server or the self-managed open source MCP Server.”
   • [claimed-docs] “Understand production systems faster using natural language”
   • [claimed-docs] “enables you to query, visualize, alert on, and explore your metrics, logs, and traces wherever they're stored”
   • [claimed-docs] “LogQL is Grafana Loki's query language. LogQL uses labels and operators for filtering.”
   • [claimed-docs] “Tempo lets you search for traces, generate metrics from spans, and link your tracing data with logs and metrics.”
   • [probe] “PROBE openapi: HTTP 200 at https://grafana.com/api/openapi.json — contains "openapi" key”
   • [probe] “official MCP server documented at https://github.com/grafana/mcp-grafana”

   proof ↗⚑ flag

   New Relic✓fullprobed9/10

   New Relic exposes NerdGraph, a documented GraphQL API for querying metrics, logs, and traces, plus NRQL for structured queries, and now an official MCP server that lets external AI agents connect and convert natural-language questions into NRQL for troubleshooting production issues. This directly matches the story of an external agent querying telemetry through documented APIs to debug production. Missing for 10: independent hands-on validation of the MCP server/API reliability from third parties beyond vendor docs.

   • [claimed-docs] “NerdGraph is our GraphQL-format API that lets you query New Relic data and configure some New Relic features.”
   • [claimed-docs] “An easy way to experiment with the NerdGraph API is to use the NerdGraph API explorer.”
   • [claimed-docs] “This update provides a standardized, scalable way to connect your favorite AI development tools directly to the rich context of the New Reli…”
   • [claimed-docs] “Ask questions in plain English, and the MCP server converts them to NRQL to get results—even if you're not a NRQL expert.”
   • [claimed-docs] “NRQL can help you: Create a new chart, Answer a specific question for the purpose of troubleshooting or business analysis, Set up NRQL-based…”
   • [probe] “official MCP server documented at https://docs.newrelic.com/whats-new/2025/11/whats-new-11-05-mcp-server/”

   proof ↗⚑ flag

Ai investigation

1. ai-native userGet AI-generated summaries of incidents and alert context for responders

   weight 2 · round to New Relic
   Grafana~partialclaimed3/10

   Grafana markets natural-language understanding of production systems and offers an official MCP server for connecting AI agents to Grafana data, which could enable AI-generated incident summaries, but no evidence explicitly documents an AI summarization feature for incidents or alert context (e.g., no mention of an 'explain this alert' or auto-generated incident report capability). Incident management docs describe manual investigation workflows, not AI-generated summaries. Missing for 10: explicit product feature/docs describing AI-generated incident summaries, hands-on or docs evidence of alert-context summarization, independent corroboration of this specific capability.

   • [claimed-docs] “Understand production systems faster using natural language”
   • [claimed-docs] “Connect AI agents to Grafana through the fully hosted Cloud MCP Server or the self-managed open source MCP Server.”
   • [claimed-docs] “create on-call schedules, escalate alerts to the people who are on call, and coordinate incidents from declaration through post-incident rev…”
   • [claimed-docs] “During an incident, you can investigate with the same metrics, logs, and traces that fired the alert.”

   proof ↗⚑ flag

   New Relic~partialclaimed5/10

   New Relic AI (docs-9, docs-10) lets users ask questions and troubleshoot issues in plain language, and the MCP server (docs-11, docs-22) exposes platform context to AI tools, which supports AI-assisted incident triage — but no evidence explicitly shows auto-generated incident summaries or alert-specific responder context. Missing for 10: explicit incident-summary generation feature, alert-context packaging for responders, and independent/hands-on confirmation of this specific workflow.

   • [claimed-docs] “It allows you to ask questions, troubleshoot issues, and explore telemetry data using plain language.”
   • [claimed-docs] “If you're struggling to get a query to work, ask our AI assistant to help you.”
   • [claimed-docs] “This update provides a standardized, scalable way to connect your favorite AI development tools directly to the rich context of the New Reli…”
   • [claimed-docs] “Ask questions in plain English, and the MCP server converts them to NRQL to get results—even if you're not a NRQL expert.”

   proof ↗⚑ flag

2. ai-native userHave the platform's AI investigate an alert or error and propose a probable root cause

   weight 3 · round to New Relic
   Grafana~partialprobed4/10

   Grafana docs mention natural-language understanding of production systems and MCP server integration that lets AI agents query Grafana data (alerts, dashboards, logs, traces), which could support an AI investigating an issue, but there is no explicit evidence of a built-in feature that automatically investigates an alert and proposes a probable root cause. Missing for 10: dedicated root-cause-analysis/investigation feature (e.g. an 'AI incident investigator'), first-party documentation of automated root-cause proposals, and independent/hands-on confirmation that this workflow works in practice.

   • [claimed-docs] “Connect AI agents to Grafana through the fully hosted Cloud MCP Server or the self-managed open source MCP Server.”
   • [claimed-docs] “Understand production systems faster using natural language”
   • [probe] “official MCP server documented at https://github.com/grafana/mcp-grafana”
   • [claimed-docs] “During an incident, you can investigate with the same metrics, logs, and traces that fired the alert.”

   proof ↗⚑ flag

   New Relic~partialclaimed5/10

   New Relic AI is documented to let users 'ask questions, troubleshoot issues, and explore telemetry data using plain language' and the MCP server converts natural-language questions into NRQL queries, which supports AI-assisted investigation of issues, but the evidence never explicitly describes an AI that proactively investigates a specific alert/error and outputs a proposed root cause. Missing for 10: explicit documentation of an automated root-cause-analysis workflow tied to alerts/errors, hands-on/independent confirmation that the AI assistant produces accurate root-cause conclusions rather than just query help.

   • [claimed-docs] “It allows you to ask questions, troubleshoot issues, and explore telemetry data using plain language.”
   • [claimed-docs] “If you're struggling to get a query to work, ask our AI assistant to help you.”
   • [claimed-docs] “Ask questions in plain English, and the MCP server converts them to NRQL to get results—even if you're not a NRQL expert.”
   • [claimed-docs] “This update provides a standardized, scalable way to connect your favorite AI development tools directly to the rich context of the New Reli…”

   proof ↗⚑ flag

Ai querying

1. ai-native userAsk questions of my telemetry in natural language and get a real query or chart back

   weight 2 · round to New Relic
   Grafana~partialprobed5/10

   Grafana docs mention an official MCP server for connecting AI agents to Grafana and marketing copy claiming 'understand production systems faster using natural language,' suggesting some NL-to-query/chart capability exists via its AI/MCP integrations. However there is no concrete documentation, demo, or independent confirmation showing an end-to-end natural-language question producing an actual query or chart. Missing for 10: detailed docs/demo of the NL-to-query/chart workflow, hands-on or community validation that it works reliably, and clarity on which product tier/tool actually performs the translation.

   • [claimed-docs] “Connect AI agents to Grafana through the fully hosted Cloud MCP Server or the self-managed open source MCP Server.”
   • [claimed-docs] “Understand production systems faster using natural language”
   • [probe] “official MCP server documented at https://github.com/grafana/mcp-grafana”

   proof ↗⚑ flag

   New Relic✓fullclaimed8/10

   New Relic AI explicitly lets users ask questions, troubleshoot, and explore telemetry in plain language, and can help generate/fix NRQL queries; the new MCP server converts natural-language questions directly into NRQL and returns results, tying into chart/dashboard capabilities. missing for 10: independent/hands-on validation of natural-language-to-chart accuracy and no community corroboration of the AI assistant's real-world reliability.

   • [claimed-docs] “It allows you to ask questions, troubleshoot issues, and explore telemetry data using plain language.”
   • [claimed-docs] “If you're struggling to get a query to work, ask our AI assistant to help you.”
   • [claimed-docs] “Ask questions in plain English, and the MCP server converts them to NRQL to get results—even if you're not a NRQL expert.”
   • [claimed-docs] “NRQL can help you: Create a new chart, Answer a specific question for the purpose of troubleshooting or business analysis, Set up NRQL-based…”
   • [claimed-docs] “Through our UI you can build and share tailored user-friendly charts and visualizations.”

   proof ↗⚑ flag

Alert automation

1. ai-native userPoint alert notifications at webhooks that trigger automated remediation or agents

   weight 2 · round drawn
   Grafana—none0/10

   The evidence pack documents Grafana Alerting broadly (querying, notification management, on-call escalation) but never explicitly mentions webhook contact points/notifiers as a delivery mechanism for triggering automated remediation or agent-driven actions. Missing for 10: explicit documentation of webhook-based contact points/notification channels, evidence of configuring alerts to call external automation/agent endpoints, and any hands-on confirmation of this remediation workflow.

   ⚑ flag

   New Relic—none0/10

   The evidence pack describes generic alerting configuration (thresholds, notification recipients) and a GraphQL API (NerdGraph) for configuring some features, but nowhere explicitly mentions webhook notification channels or integration with remediation/automation agents via webhooks. Given New Relic is an observability/alerting platform, this is a fair and applicable axis, but no direct evidence confirms webhook-triggered automation exists.

   • [claimed-docs] “You define the data to watch, the thresholds that if exceeded mean an issue, who is notified, and how.”
   • [claimed-docs] “NerdGraph is our GraphQL-format API that lets you query New Relic data and configure some New Relic features.”

   proof ↗⚑ flag

Alerting

1. sreAlert on any telemetry signal with routing, grouping, and silencing of notifications

   weight 3 · round to Grafana
   Grafana✓fullcommunity8/10

   Grafana Alerting supports querying/alerting across many data sources with consolidated management, and Grafana Cloud adds on-call scheduling, escalation, and incident coordination (routing/grouping analog to Alertmanager). SLO features let SREs define SLIs/SLOs to alert on reliability signals, and community evidence confirms multi-datasource alerting works in production (albeit with added complexity from needing separate services like Alertmanager). Missing for 10: explicit first-party documentation of silencing/grouping mechanics and independent confirmation of routing granularity beyond general alerting docs.

   • [claimed-docs] “Grafana Alerting allows you to learn about problems in your systems moments after they occur.”
   • [claimed-docs] “you create queries and expressions from multiple data sources, no matter where you store your data, giving you the flexibility to combine yo…”
   • [claimed-docs] “enables you to query, visualize, alert on, and explore your metrics, logs, and traces wherever they're stored”
   • [claimed-docs] “create on-call schedules, escalate alerts to the people who are on call, and coordinate incidents from declaration through post-incident rev…”
   • [claimed-docs] “Use it to create on-call schedules, escalate alerts to the people who are on call, and coordinate incidents from declaration through post-in…”
   • [claimed-docs] “Grafana SLO (Service Level Objective) provides a framework for measuring the quality of service you provide to users.”
   • [community] “I use a combination of Graphite, InfluxDB, PostgreSQL, Timescale, CloudWatch, Prometheus. The alerting in Grafana supporting all those varia…”
   • [community] “Grafana used to be so simple, I don't know if I'm a fan of this direction towards many services. Having to run alertmanager and configure it…”

   proof ↗⚑ flag

   New Relic~partialclaimed5/10

   New Relic docs confirm NRQL-based alerting on any telemetry signal and thresholds with notification routing ("who is notified and how"), but the evidence pack contains no explicit mention of alert grouping or silencing/muting mechanisms. Missing for 10: documented grouping of related alerts, muting/silencing rules, and incident routing workflows with independent corroboration.

   • [claimed-docs] “You define the data to watch, the thresholds that if exceeded mean an issue, who is notified, and how.”
   • [claimed-docs] “NRQL can help you: Create a new chart ... Set up NRQL-based alerts (our primary and most powerful type of alert)”
   • [claimed-docs] “Set up NRQL-based alerts (our primary and most powerful type of alert)”
   • [claimed-docs] “NRQL can help you: Create a new chart, Answer a specific question for the purpose of troubleshooting or business analysis, Set up NRQL-based…”

   proof ↗⚑ flag

2. sreEnable anomaly or outlier detection that surfaces problems without hand-written thresholds

   weight 1 · round drawn
   Grafana—none0/10

   No evidence describes anomaly detection, outlier detection, or ML-based threshold-free alerting; the pack only covers standard rule-based alerting, SLOs, provisioning, and on-call/incident tooling. missing for 10: any mention of anomaly/outlier detection algorithms, forecasting-based alert conditions, or ML-driven baseline detection features.

   ⚑ flag

   New Relic—none0/10

   The evidence pack describes only threshold-based alerting ('you define the thresholds that if exceeded mean an issue') and NRQL-based alerts, with no mention of anomaly/outlier/baseline detection features that surface issues without hand-written thresholds.

   • [claimed-docs] “You define the data to watch, the thresholds that if exceeded mean an issue, who is notified, and how.”
   • [claimed-docs] “NRQL can help you: Create a new chart ... Set up NRQL-based alerts (our primary and most powerful type of alert)”
   • [claimed-docs] “Set up NRQL-based alerts (our primary and most powerful type of alert)”

   proof ↗⚑ flag

Slos

1. sreDefine SLOs with error budgets and burn-rate alerts

   weight 2 · round drawn
   Grafana✓fullclaimed8/10

   Grafana Cloud offers a dedicated SLO product (Grafana SLO) explicitly for defining SLIs/SLOs and reacting when service falls below expected levels, paired with Grafana Alerting for multi-source alert rules and burn-rate style alerting logic. Missing for 10: explicit first-party documentation naming 'burn-rate alerts' or multi-window burn-rate templates, and independent/hands-on confirmation of the SLO burn-rate alerting workflow.

   • [claimed-docs] “With Grafana SLO, you can create metrics to measure the quality of the service you provide users.”
   • [claimed-docs] “By creating SLIs (Service Level Indicators) and SLOs, you define what an acceptable level of service is and how to react if you are not prov…”
   • [claimed-docs] “Grafana SLO (Service Level Objective) provides a framework for measuring the quality of service you provide to users.”
   • [claimed-docs] “Grafana Alerting allows you to learn about problems in your systems moments after they occur.”
   • [claimed-docs] “you create queries and expressions from multiple data sources, no matter where you store your data, giving you the flexibility to combine yo…”

   proof ↗⚑ flag

   New Relic✓fullclaimed8/10

   New Relic's Service Level Management explicitly supports defining and consuming SLIs/SLOs, and NRQL-based alerts (its 'primary and most powerful' alert type) can be layered to implement burn-rate style alerting on top of SLO data. Missing for 10: explicit first-party documentation of a native 'error budget burn-rate alert' template/wizard (as some competitors have) and independent/hands-on confirmation of this specific workflow beyond docs.

   • [claimed-docs] “With New Relic, you can define and consume service level indicators (SLIs) and service level objectives (SLOs) for your applications.”
   • [claimed-docs] “you can define and consume service level indicators (SLIs) and service level objectives (SLOs) for your applications”
   • [claimed-docs] “NRQL can help you: Create a new chart ... Set up NRQL-based alerts (our primary and most powerful type of alert)”
   • [claimed-docs] “Set up NRQL-based alerts (our primary and most powerful type of alert)”
   • [claimed-docs] “You define the data to watch, the thresholds that if exceeded mean an issue, who is notified, and how.”

   proof ↗⚑ flag

1. ai-native userPerform bulk operations across many items at once

   weight 2 · round drawn
   Grafana~partialprobed5/10

   Grafana's provisioning-as-code system, CLI, and OpenAPI-documented API allow scripting bulk creation/management of dashboards, data sources, and alerts (e.g. version-controlled config files, CI/CD deployment, consolidated alert management view), which supports automation-depth bulk workflows. However, there is no explicit documentation of a dedicated bulk-operations API/UI (e.g. batch update/delete across many items in one call) — missing for 10: documented bulk API endpoints or UI multi-select actions, independent hands-on evidence of large-scale bulk operations succeeding, and any AI-native-specific bulk tooling beyond generic as-code/CLI mechanisms.

   • [claimed-docs] “Grafana has an active provisioning system that uses configuration files. You can define data sources and dashboards using files that can be …”
   • [claimed-docs] “This approach lets you define dashboards, data sources, and other configurations in code, enabling version control, automated testing, and r…”
   • [claimed-docs] “You can authenticate, manage multiple environments, and perform administrative tasks from the terminal. It’s suitable for CI/CD pipelines, l…”
   • [claimed-docs] “you create queries and expressions from multiple data sources, no matter where you store your data... create, manage, and take action on you…”
   • [probe] “official CLI documented at https://grafana.com/docs/grafana/latest/administration/cli/”
   • [probe] “PROBE openapi: HTTP 200 at https://grafana.com/api/openapi.json — contains "openapi" key”

   proof ↗⚑ flag

   New Relic~partialclaimed5/10

   NerdGraph GraphQL API and the newrelic-cli support programmatic/bulk operations like entity search across all accounts, and NRQL/dashboards can operate over aggregated data sets, but there's no explicit documentation of bulk create/update/delete operations across many items (e.g., bulk alert config, bulk entity tagging) as a first-class feature. missing for 10: explicit bulk-operation endpoints/examples (batch create/update/delete across many entities), hands-on evidence of bulk workflows succeeding at scale.

   • [claimed-docs] “NerdGraph is our GraphQL-format API that lets you query New Relic data and configure some New Relic features.”
   • [claimed-docs] “An easy way to experiment with the NerdGraph API is to use the NerdGraph API explorer.”
   • [github] “Entity Search: Search for entities across all your New Relic accounts”
   • [claimed-docs] “NRQL can help you: Create a new chart, Answer a specific question for the purpose of troubleshooting or business analysis, Set up NRQL-based…”

   proof ↗⚑ flag

2. ai-native userDefine rules that trigger actions automatically on events

   weight 3 · round drawn
   Grafana✓fullcommunity7/10

   Grafana Alerting lets users define rules on metrics/logs from multiple data sources that trigger notifications, escalate to on-call schedules, and coordinate incident response automatically when conditions are met, directly matching the story. Community evidence corroborates real-world use of Grafana's alerting across heterogeneous data sources. Missing for 10: documented support for arbitrary custom actions beyond notification/escalation (e.g., automated remediation scripts, webhooks triggering external workflows) and independent hands-on validation of complex rule automation.

   • [claimed-docs] “you create queries and expressions from multiple data sources, no matter where you store your data... create, manage, and take action on you…”
   • [claimed-docs] “Use it to create on-call schedules, escalate alerts to the people who are on call, and coordinate incidents from declaration through post-in…”
   • [claimed-docs] “create on-call schedules, escalate alerts to the people who are on call, and coordinate incidents from declaration through post-incident rev…”
   • [claimed-docs] “Grafana Alerting allows you to learn about problems in your systems moments after they occur.”
   • [claimed-docs] “you create queries and expressions from multiple data sources, no matter where you store your data, giving you the flexibility to combine yo…”
   • [community] “I use a combination of Graphite, InfluxDB, PostgreSQL, Timescale, CloudWatch, Prometheus. The alerting in Grafana supporting all those varia…”

   proof ↗⚑ flag

   New Relic✓fullclaimed7/10

   New Relic's alerting system lets users define thresholds/conditions (including powerful NRQL-based conditions) and specify who/how to notify when those conditions are breached, which is the core of automated rule-triggered actions on events (new-relic-docs-5, new-relic-docs-3/21/25). missing for 10: evidence of richer automated remediation/workflow actions (e.g., auto-scaling, ticket creation, custom webhooks) beyond notification routing, and independent/hands-on confirmation that alert rules reliably trigger actions in production.

   • [claimed-docs] “You define the data to watch, the thresholds that if exceeded mean an issue, who is notified, and how.”
   • [claimed-docs] “NRQL can help you: Create a new chart, Answer a specific question for the purpose of troubleshooting or business analysis, Set up NRQL-based…”
   • [claimed-docs] “NRQL can help you: Create a new chart ... Set up NRQL-based alerts (our primary and most powerful type of alert)”
   • [claimed-docs] “Set up NRQL-based alerts (our primary and most powerful type of alert)”

   proof ↗⚑ flag

3. ai-native userSchedule recurring jobs or workflows

   weight 2 · round drawn
   Grafana—none0/10

   The evidence covers alerting rule evaluation, on-call scheduling, and GitOps-style config provisioning, but none of these describe scheduling recurring jobs or automated workflows (e.g., scheduled reports, cron-like task execution) in the AI-native automation sense. Missing for 10: any documentation of scheduled report generation, recurring automated workflows, or job-scheduling APIs.

   • [claimed-docs] “you create queries and expressions from multiple data sources, no matter where you store your data... create, manage, and take action on you…”
   • [claimed-docs] “Use it to create on-call schedules, escalate alerts to the people who are on call, and coordinate incidents from declaration through post-in…”
   • [claimed-docs] “Grafana has an active provisioning system that uses configuration files. You can define data sources and dashboards using files that can be …”

   proof ↗⚑ flag

   New Relic—none0/10

   New Relic's evidence pack shows synthetic monitoring (docs-19) and alerting/dashboards, but there is no documentation of a general job/workflow scheduler, cron-like automation, or AI-native recurring workflow execution capability tied to its MCP server or NerdGraph API. The axis is plausible for a monitoring platform (e.g., scheduled synthetic checks), but no evidence confirms recurring job/workflow scheduling as a user-facing automation feature.

   • [claimed-docs] “Simulate end-user activity and API calls from locations around the world, so you can find problems before your users do.”
   • [claimed-docs] “This update provides a standardized, scalable way to connect your favorite AI development tools directly to the rich context of the New Reli…”
   • [claimed-docs] “NerdGraph is our GraphQL-format API that lets you query New Relic data and configure some New Relic features.”

   proof ↗⚑ flag

4. ai-native userVersion, review, and roll back my automations

   weight 1 · round to Grafana
   Grafana~partialclaimed6/10

   Grafana's provisioning-as-code and 'observability as code' docs let dashboards, data sources, and alert configs be stored in version-controlled files with CI/CD pipelines, which supports versioning and review workflows (grafana-docs-2, grafana-docs-3, grafana-docs-16, grafana-docs-26). However, rollback is only implicit (via standard git revert), and there's no explicit mention of an in-product rollback/version-history UI for alerts or automations, nor of a formal review/approval workflow beyond generic CI/CD mention. Missing for 10: explicit rollback mechanism for automations/alerts, documented review/approval workflow, and independent evidence of these features being used in practice.

   • [claimed-docs] “Grafana has an active provisioning system that uses configuration files. You can define data sources and dashboards using files that can be …”
   • [claimed-docs] “This approach lets you define dashboards, data sources, and other configurations in code, enabling version control, automated testing, and r…”
   • [claimed-docs] “define dashboards, data sources, and other configurations in code, enabling version control, automated testing, and reliable deployments thr…”
   • [claimed-docs] “You can authenticate, manage multiple environments, and perform administrative tasks from the terminal. It’s suitable for CI/CD pipelines, l…”
   • [claimed-docs] “You can define data sources and dashboards using files that can be version controlled, making GitOps more natural.”

   proof ↗⚑ flag

   New Relic—none0/10

   The evidence pack shows NerdGraph API and CLI for configuring alerts/dashboards, but nothing about versioning, reviewing, or rolling back automations (e.g., alert configs, workflows) — no changelog, diff/review UI, or rollback mechanism is documented.

   ⚑ flag

Cost

1. sreSee what my observability spend is, attribute it to teams or services, and catch usage spikes before the bill

   weight 3 · round to Grafana
   Grafana~partialcommunity4/10

   Grafana Cloud's Adaptive Telemetry is documented as a cost-management feature that 'automatically identifies the data worth your attention and aggregates the rest, cutting telemetry costs by up to 80%,' and a community comment corroborates Grafana Cloud's cost advantage over competitors. However, there is no evidence of per-team/per-service cost attribution or a dedicated spend dashboard/billing-spike alerting workflow. Missing for 10: cost attribution by team/service, usage-spike alerting tied to billing thresholds, first-party dashboards for cost visibility, independent proof of the attribution workflow.

   • [claimed-docs] “Simplify cost management with Adaptive Telemetry”
   • [claimed-docs] “cutting your telemetry costs by up to 80%”
   • [claimed-docs] “Grafana Cloud’s Adaptive Telemetry suite automatically identifies the data worth your attention and aggregates the rest, cutting your teleme…”
   • [community] “Cost really is the big selling point of Grafana Cloud - it's far, far cheaper than most competitors, and good enough. Not as good as NewReli…”

   proof ↗⚑ flag

   New Relic—none0/10

   There is no evidence of a New Relic feature for attributing observability ingest/spend to specific teams or services, nor of proactive spend/usage-spike alerting on New Relic's own billing (the closest hit, new-relic-docs-15, is about monitoring customers' cloud/K8s spend, not New Relic's own consumption). Multiple community reports directly describe the opposite experience — unexpected multi-x ingest spikes and bill surges that were only discovered after the fact (new-relic-comm-4, new-relic-comm-5, new-relic-comm-8, new-relic-comm-9), with no mention of a dashboard or alert that would have caught them beforehand.

   • [claimed-docs] “Gain real-time visibility into multi-cloud and Kubernetes spend.”
   • [community] “New Relic wants to capture as much data as possible so that they can charge you as much as possible. I run a small environment (~20 small VM…”
   • [community] “Reminds me of when they intentionally enabled JFR on every single java process. Roughly sextupled our ingest (and associated costs) until we…”
   • [community] “I love NewRelic, but their pricing always baffled me. When we added it to our QA, UAT, and Staging envs, they started wanting to bill us as …”
   • [community] “We also run our infrastructure with redundancy, so we got billed for every region & availability zone, they wanted it to be crazy expensive.”

   proof ↗⚑ flag

2. srePredict costs from transparent published per-signal pricing without talking to sales

   weight 1 · round to Grafana
   Grafana~partialcommunity5/10

   Evidence confirms a public Grafana Cloud pricing page with a free tier ([grafana-docs-13]) and cost-reduction tooling (Adaptive Telemetry cutting costs up to 80%, [grafana-docs-21],[grafana-docs-28]), and community commentary corroborates that pricing is transparent and favorable compared to competitors ([grafana-comm-7]). However, no evidence details actual per-signal unit pricing (e.g., $/GB logs, $/series metrics, $/span traces) that an SRE would need to model exact costs without sales contact. Missing for 10: concrete per-signal price tables/units, documentation of self-serve cost calculator, and independent confirmation that pricing matches published rates in practice.

   • [claimed-docs] “Perfect for personal projects, exploring new ideas, and early-stage startups. No charges ever.”
   • [claimed-docs] “cutting your telemetry costs by up to 80%”
   • [claimed-docs] “Grafana Cloud’s Adaptive Telemetry suite automatically identifies the data worth your attention and aggregates the rest, cutting your teleme…”
   • [community] “Cost really is the big selling point of Grafana Cloud - it's far, far cheaper than most competitors, and good enough. Not as good as NewReli…”

   proof ↗⚑ flag

   New Relic!disputedcontradicted4/10

   New Relic does publish some pricing info (100GB free ingest tier) on its pricing page, giving a baseline for self-service cost estimation without sales contact, but multiple independent community reports describe billing as opaque and unpredictable in practice—per-user pricing changes causing 20x bill increases, environments/redundant AZs billed as extra 'production' instances, and ingest spikes (e.g. JFR enabled by default) sextupling costs unexpectedly. This directly contradicts the 'predict costs transparently' premise even though a published price list exists. Missing for 10: detailed per-signal (e.g., per-host, per-user, per-GB-by-data-type) pricing breakdown, and evidence that published prices reliably predict actual bills without support intervention.

   • [claimed-docs] “100 GB of free data ingest/month”
   • [claimed-docs] “Sign up for free access with our perpetual free tier and 100 GB/month of data ingest included.”
   • [community] “When they changed their billing to be per user our bill went up 20x for no additional value... APM hasn't seen a single new feature in the 5…”
   • [community] “New Relic wants to capture as much data as possible so that they can charge you as much as possible. I run a small environment (~20 small VM…”
   • [community] “Reminds me of when they intentionally enabled JFR on every single java process. Roughly sextupled our ingest (and associated costs) until we…”
   • [community] “I love NewRelic, but their pricing always baffled me. When we added it to our QA, UAT, and Staging envs, they started wanting to bill us as …”
   • [community] “We also run our infrastructure with redundancy, so we got billed for every region & availability zone, they wanted it to be crazy expensive.”

   proof ↗⚑ flag

Sampling

1. developerControl trace/log sampling and retention tiers to manage data volume deliberately

   weight 2 · round to Grafana
   Grafana~partialcommunity5/10

   Grafana Cloud's Adaptive Telemetry suite explicitly targets cost control by identifying valuable data and aggregating (i.e., sampling down) the rest, cutting telemetry costs up to 80%, and community commentary confirms cost-effectiveness as a differentiator. However, the evidence never details developer-facing controls for trace sampling rates or explicit retention-tier configuration (e.g., per-signal retention periods, sampling rules), leaving the story only partially substantiated. Missing for 10: documented sampling-rate configuration APIs/UI, explicit retention-tier settings per data type, and independent hands-on confirmation of these controls working as described.

   • [claimed-docs] “Simplify cost management with Adaptive Telemetry”
   • [claimed-docs] “cutting your telemetry costs by up to 80%”
   • [claimed-docs] “Grafana Cloud’s Adaptive Telemetry suite automatically identifies the data worth your attention and aggregates the rest, cutting your teleme…”
   • [community] “Cost really is the big selling point of Grafana Cloud - it's far, far cheaper than most competitors, and good enough. Not as good as NewReli…”

   proof ↗⚑ flag

   New Relic~partialcommunity4/10

   There is only indirect evidence: community reports mention disabling automatic log forwarding via env vars and manually turning off JFR-driven ingest spikes, implying some data-volume control exists, and the free tier caps ingest at 100GB/month. However, no first-party documentation describes explicit trace sampling rules, log drop filters, or configurable data retention tiers as a deliberate developer-facing feature. missing for 10: dedicated docs on trace/log sampling rate configuration, NRQL drop-filter rules, and retention tier selection; independent confirmation that these controls work as intended.

   • [community] “Setting NEW_RELIC_APPLICATION_LOGGING_ENABLED=false and NEW_RELIC_APPLICATION_LOGGING_FORWARDING_ENABLED=false disables the newly-default au…”
   • [community] “New Relic wants to capture as much data as possible so that they can charge you as much as possible. I run a small environment (~20 small VM…”
   • [community] “Reminds me of when they intentionally enabled JFR on every single java process. Roughly sextupled our ingest (and associated costs) until we…”
   • [claimed-docs] “100 GB of free data ingest/month”
   • [claimed-docs] “Sign up for free access with our perpetual free tier and 100 GB/month of data ingest included.”

   proof ↗⚑ flag

As code

1. developerDefine dashboards and alerts as code (JSON models, Terraform, or API) and provision them repeatably

   weight 3 · round to Grafana
   Grafana✓fullprobed8/10

   Grafana's provisioning system explicitly supports defining dashboards, data sources, and alerts via version-controlled config files, and the observability-as-code docs describe JSON models, Terraform, and API/CLI-based provisioning for CI/CD pipelines. This is corroborated by an official OpenAPI spec and CLI docs enabling scripted/repeatable provisioning. Missing for 10: independent hands-on developer accounts specifically validating Terraform/JSON-as-code workflows in production, and no community evidence directly confirms this specific workflow (only general provisioning docs).

   • [claimed-docs] “Grafana has an active provisioning system that uses configuration files. You can define data sources and dashboards using files that can be …”
   • [claimed-docs] “This approach lets you define dashboards, data sources, and other configurations in code, enabling version control, automated testing, and r…”
   • [claimed-docs] “define dashboards, data sources, and other configurations in code, enabling version control, automated testing, and reliable deployments thr…”
   • [claimed-docs] “You can authenticate, manage multiple environments, and perform administrative tasks from the terminal. It’s suitable for CI/CD pipelines, l…”
   • [probe] “PROBE openapi: HTTP 200 at https://grafana.com/api/openapi.json — contains "openapi" key”
   • [probe] “official CLI documented at https://grafana.com/docs/grafana/latest/administration/cli/”

   proof ↗⚑ flag

   New Relic~partialclaimed5/10

   NerdGraph is documented as a GraphQL API that can 'configure some New Relic features' and has an API explorer, implying dashboards/alerts could be provisioned programmatically, and the newrelic-cli exists for some automation tasks. However, the evidence pack never explicitly documents JSON dashboard definition files, a Terraform provider, or alerts-as-code workflows — dashboards are described mainly as built through the UI. Missing for 10: explicit Terraform provider docs, JSON dashboard schema/export-import examples, and alert-as-code API examples beyond generic NerdGraph mention.

   • [claimed-docs] “NerdGraph is our GraphQL-format API that lets you query New Relic data and configure some New Relic features.”
   • [claimed-docs] “An easy way to experiment with the NerdGraph API is to use the NerdGraph API explorer.”
   • [claimed-docs] “You define the data to watch, the thresholds that if exceeded mean an issue, who is notified, and how.”
   • [claimed-docs] “Through our UI you can build and share tailored user-friendly charts and visualizations.”
   • [github] “Entity Search: Search for entities across all your New Relic accounts”
   • [github] “Deployment Markers: Easily record an APM Application deployment within New Relic.”

   proof ↗⚑ flag

Dashboards

1. sreBuild shareable dashboards with rich visualization types and template variables

   weight 2 · round to Grafana
   Grafana✓fullcommunity8/10

   Grafana natively supports rich visualization types across metrics/logs/traces (grafana-docs-9, grafana-gh-1/2/4), dashboard template variables as dropdowns (grafana-gh-3), and dashboards can be shared/provisioned and version-controlled (grafana-docs-2, grafana-docs-11). Community feedback corroborates real-world use for dashboarding across diverse data sources (grafana-comm-1, grafana-comm-5) though notes some visualization types (node graph) have datasource limitations (grafana-comm-6). Missing for 10: explicit first-party documentation/demo of dashboard sharing/export links or snapshot feature, and more independent hands-on validation of template variable UX beyond GitHub feature list.

   • [github] “Create dynamic & reusable dashboards with template variables that appear as dropdowns at the top of the dashboard.”
   • [github] “Explore your data through ad-hoc queries and dynamic drilldown. Split view and compare different time ranges, queries and data sources side …”
   • [github] “Mix different data sources in the same graph! You can specify a data source on a per-query basis.”
   • [claimed-docs] “enables you to query, visualize, alert on, and explore your metrics, logs, and traces wherever they're stored”
   • [claimed-docs] “Grafana has an active provisioning system that uses configuration files. You can define data sources and dashboards using files that can be …”
   • [community] “I use a combination of Graphite, InfluxDB, PostgreSQL, Timescale, CloudWatch, Prometheus. The alerting in Grafana supporting all those varia…”
   • [community] “The relatively new Node graph visualization can't be used with any datasource, even if you select data to fit the model, because it needs a …”

   proof ↗⚑ flag

   New Relic~partialclaimed7/10

   Docs confirm New Relic dashboards support rich visualizations built via UI/NRQL and can be publicly shared via live dashboard URLs, satisfying most of the story. However, evidence does not explicitly mention template variables on dashboards, and there is no independent/hands-on corroboration of the dashboard-building experience (community evidence focuses on pricing/UI complaints unrelated to dashboard features). Missing for 10: explicit documentation of template variables support, independent verification of dashboard usability/quality.

   • [claimed-docs] “Through our UI you can build and share tailored user-friendly charts and visualizations.”
   • [claimed-docs] “Share dashboards with stakeholders outside your New Relic organization via publicly accessible live dashboard URLs.”
   • [claimed-docs] “Through our UI you can build and share tailored user-friendly charts and visualizations. Go to our dashboard capability to gather and chart …”
   • [claimed-docs] “Share dashboards with stakeholders outside your New Relic organization via publicly accessible live dashboard URLs”
   • [claimed-docs] “NRQL can help you: Create a new chart, Answer a specific question for the purpose of troubleshooting or business analysis, Set up NRQL-based…”

   proof ↗⚑ flag

Local dev

1. developerSpin up a local or dev instance of the platform to test instrumentation and dashboards

   weight 1 · round to Grafana
   Grafana~partialprobed6/10

   Docs reference an official CLI usable for 'local development' and CI/CD (grafana-docs-26), and provisioning/config-as-code docs describe defining dashboards and data sources in version-controlled files (grafana-docs-2, grafana-docs-16), which supports spinning up and configuring a dev instance for testing instrumentation. There is also a directly analogous local-instance workflow shown for a sibling Grafana Labs product, Loki ('Try it locally... run Loki in monolithic mode with a local filesystem backend', grafana-docs-29), implying the same open-source, self-hostable pattern applies to Grafana itself, though this isn't Grafana-core-specific evidence. Missing for 10: explicit first-party 'docker run grafana/grafana' or local quick-start install docs for Grafana core, and independent/hands-on confirmation of spinning up a local dev instance.

   • [claimed-docs] “You can authenticate, manage multiple environments, and perform administrative tasks from the terminal. It’s suitable for CI/CD pipelines, l…”
   • [claimed-docs] “Grafana has an active provisioning system that uses configuration files. You can define data sources and dashboards using files that can be …”
   • [claimed-docs] “define dashboards, data sources, and other configurations in code, enabling version control, automated testing, and reliable deployments thr…”
   • [claimed-docs] “Try it locally. The fastest way to experiment is to run Loki in monolithic (single-binary) mode with a local filesystem backend and send log…”
   • [probe] “PROBE docs-md: HTTP 200 at https://grafana.com/docs/grafana/latest/.md --- title: "Grafana OSS and Enterprise | Grafana documentation" descr…”

   proof ↗⚑ flag

   New Relic—none0/10

   New Relic is delivered as a hosted SaaS platform; none of the docs describe a way to run a local or self-hosted dev instance, and community evidence explicitly notes the 'removal of development mode & support' as a past feature that is no longer offered, confirming there is no current local/dev instance capability.

   • [community] “Removal of development mode & support. The 'improved' price model. Their new UI is buggy as hell and they refuse to fix it. Every month or s…”

   proof ↗⚑ flag

Self host

1. sreRun the full observability stack self-hosted in production with documented architecture and upgrade path

   weight 2 · round to Grafana
   Grafana~partialprobed7/10

   Grafana OSS is self-hostable with documented provisioning-as-code, GitOps workflows, and Loki upgrade/migration docs, and community evidence confirms it running as core self-hosted infrastructure ('monitoring everything from cloud stuff down to cryogenic fridges'). However, community hands-on feedback notes growing operational complexity requiring separate services (Alertmanager, etc.) and licensing (AGPLv3) concerns that complicate production self-hosting decisions, so the story is delivered with real caveats rather than a single polished architecture/upgrade guide. Missing for 10: a consolidated end-to-end production reference architecture doc, clearer unified upgrade path across the whole stack (not just Loki), and independent verification that complexity concerns have been resolved.

   • [claimed-docs] “Grafana has an active provisioning system that uses configuration files. You can define data sources and dashboards using files that can be …”
   • [claimed-docs] “This approach lets you define dashboards, data sources, and other configurations in code, enabling version control, automated testing, and r…”
   • [claimed-docs] “migrate from previous deployments, and upgrade your Loki environment”
   • [probe] “PROBE docs-md: HTTP 200 at https://grafana.com/docs/grafana/latest/.md --- title: "Grafana OSS and Enterprise | Grafana documentation" descr…”
   • [community] “We have Grafana monitoring everything from cloud stuff down to temperatures of cryogenic fridges. Being able to configure alerts more dynami…”
   • [community] “It's the de facto realtime graph consolidation platform where I work; if the thing you want to use for monitoring doesn't interact with graf…”
   • [community] “Grafana used to be so simple, I don't know if I'm a fan of this direction towards many services. Having to run alertmanager and configure it…”
   • [community] “Even though we use Grafana only internally and there would be no problem with AGPLv3 in theory I see big meetings with legal coming up which…”

   proof ↗⚑ flag

   New Relic—none0/10

   New Relic is documented as a SaaS platform (agents forward data to New Relic-hosted cloud) with no self-hosted deployment architecture, upgrade path, or on-prem installation docs anywhere in the evidence. Community commentary explicitly notes New Relic controls 'where the server is' and that on-prem APM remains an underserved market they don't address, confirming no self-hosted offering exists.

   • [community] “They don’t care that much about open source agent, but they do care about where the server is... there is still a huge underserved market fo…”
   • [claimed-docs] “By default, our APM agents do two things: add metadata to your logs, which gives you logs in context (ability to see logs data in various re…”
   • [claimed-docs] “100 GB of free data ingest/month”

   proof ↗⚑ flag

Change tracking

1. developerCorrelate regressions with deploys and configuration changes via release or change tracking

   weight 2 · round to New Relic
   Grafana~partialclaimed3/10

   Evidence shows Grafana supports investigating incidents with the same metrics/logs/traces that triggered an alert (docs-27) and version-controlled, CI/CD-driven dashboard/config-as-code workflows (docs-2/docs-11/docs-16) which can indirectly tie config changes to observability state, but there is no explicit mention of Grafana's annotation/deploy-marker feature or a dedicated release-tracking view for correlating regressions with specific deploys. missing for 10: explicit deploy/release annotation feature, direct UI for marking deploy events on dashboards, and independent confirmation of this workflow being used for regression correlation.

   • [claimed-docs] “During an incident, you can investigate with the same metrics, logs, and traces that fired the alert.”
   • [claimed-docs] “Grafana has an active provisioning system that uses configuration files. You can define data sources and dashboards using files that can be …”
   • [claimed-docs] “You can define data sources and dashboards using files that can be version controlled, making GitOps more natural.”
   • [claimed-docs] “define dashboards, data sources, and other configurations in code, enabling version control, automated testing, and reliable deployments thr…”

   proof ↗⚑ flag

   New Relic~partialclaimed6/10

   New Relic's CLI supports recording deployment markers (change tracking) that appear alongside APM data, and NRQL/dashboards/alerts can be used to correlate metrics around deploy times, but the evidence pack lacks documentation of a dedicated change-tracking UI feature, automatic regression detection tied to deploys, or config-change tracking beyond deployment markers. missing for 10: dedicated change-tracking/regression-correlation UI docs, evidence of automatic config-change tracking, independent confirmation of deploy correlation workflow.

   • [github] “Deployment Markers: Easily record an APM Application deployment within New Relic.”
   • [claimed-docs] “NRQL can help you: Create a new chart ... Set up NRQL-based alerts (our primary and most powerful type of alert)”
   • [claimed-docs] “NRQL can help you: Create a new chart, Answer a specific question for the purpose of troubleshooting or business analysis, Set up NRQL-based…”

   proof ↗⚑ flag

Incidents

1. sreDeclare and track incidents with timelines, on-call schedules, and escalation policies

   weight 2 · round to Grafana
   Grafana✓fullcommunity8/10

   Grafana Cloud's Incident Response Management (IRM) product explicitly supports on-call schedules, alert escalation, and incident coordination from declaration through post-incident review, with investigation using linked metrics/logs/traces during an incident (timelines). Community evidence corroborates that incident management is a real, priced offering alongside metrics/logs/alerts. Missing for 10: independent hands-on validation of the full timeline/escalation UX and deeper detail on post-incident review workflow beyond the doc summary.

   • [claimed-docs] “Use it to create on-call schedules, escalate alerts to the people who are on call, and coordinate incidents from declaration through post-in…”
   • [claimed-docs] “create on-call schedules, escalate alerts to the people who are on call, and coordinate incidents from declaration through post-incident rev…”
   • [claimed-docs] “During an incident, you can investigate with the same metrics, logs, and traces that fired the alert.”
   • [community] “Cost really is the big selling point of Grafana Cloud - it's far, far cheaper than most competitors, and good enough. Not as good as NewReli…”

   proof ↗⚑ flag

   New Relic~partialclaimed3/10

   New Relic's alerting docs mention defining thresholds and who is notified (new-relic-docs-5, new-relic-docs-25), which touches escalation/notification, but there is no evidence of a dedicated incident timeline view, on-call scheduling, or formal escalation-policy management comparable to a dedicated incident-response tool. Missing for 10: documented incident timeline tracking, on-call schedule configuration, and escalation policy chains/rotations.

   • [claimed-docs] “You define the data to watch, the thresholds that if exceeded mean an issue, who is notified, and how.”
   • [claimed-docs] “Set up NRQL-based alerts (our primary and most powerful type of alert)”

   proof ↗⚑ flag

1. ai-native userDo everything through the API that I can do in the UI

   weight 2 · round to Grafana
   Grafana~partialprobed6/10

   Grafana exposes a documented HTTP/OpenAPI API (grafana-probe-3), a CLI for admin tasks (grafana-docs-26, grafana-probe-5), and code/provisioning workflows for dashboards, data sources and alerts (grafana-docs-2, -3, -11, -16) plus an MCP server for agent access (grafana-probe-4, grafana-docs-7). However, there is no explicit documentation or independent confirmation that every UI capability (e.g., exploration/drilldown UX, node graph, incident workflows) has a full API equivalent, and a community comment notes friction/lack of docs for dashboard/data operations (grafana-comm-3). Missing for 10: an explicit statement or audit confirming 1:1 UI/API feature parity, and evidence covering less common UI features (node graph, incident management) via API/CLI.

   • [probe] “PROBE openapi: HTTP 200 at https://grafana.com/api/openapi.json — contains "openapi" key”
   • [claimed-docs] “You can authenticate, manage multiple environments, and perform administrative tasks from the terminal. It’s suitable for CI/CD pipelines, l…”
   • [probe] “official CLI documented at https://grafana.com/docs/grafana/latest/administration/cli/”
   • [claimed-docs] “Grafana has an active provisioning system that uses configuration files. You can define data sources and dashboards using files that can be …”
   • [claimed-docs] “This approach lets you define dashboards, data sources, and other configurations in code, enabling version control, automated testing, and r…”
   • [claimed-docs] “You can define data sources and dashboards using files that can be version controlled, making GitOps more natural.”
   • [claimed-docs] “define dashboards, data sources, and other configurations in code, enabling version control, automated testing, and reliable deployments thr…”
   • [probe] “official MCP server documented at https://github.com/grafana/mcp-grafana”
   • [claimed-docs] “Connect AI agents to Grafana through the fully hosted Cloud MCP Server or the self-managed open source MCP Server.”
   • [community] “I love using grafana however I abhor creating dashboards and trying to pull data, but that's mostly because of a lack of documentation.”

   proof ↗⚑ flag

   New Relic~partialprobed5/10

   NerdGraph GraphQL API and CLI expose query, alerting, dashboard, and SLO configuration, but New Relic's own docs state NerdGraph lets you 'configure some New Relic features' — explicitly not full UI parity. No evidence every UI workflow (e.g., full dashboard builder, entity management edge cases) is API-exposed, and openapi probes 404 confirming no fully documented spec of complete surface. Missing for 10: explicit confirmation of 1:1 API/UI feature parity, comprehensive OpenAPI spec, and independent verification of coverage gaps.

   • [claimed-docs] “NerdGraph is our GraphQL-format API that lets you query New Relic data and configure some New Relic features.”
   • [claimed-docs] “An easy way to experiment with the NerdGraph API is to use the NerdGraph API explorer.”
   • [github] “Entity Search: Search for entities across all your New Relic accounts”
   • [github] “Deployment Markers: Easily record an APM Application deployment within New Relic.”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.newrelic.com/openapi.json, https://docs.newrelic.com/swagger.json, https://docs.newreli…”
   • [probe] “official CLI documented at https://github.com/newrelic/newrelic-cli”

   proof ↗⚑ flag

2. ai-native userExport all of my data in open formats and leave

   weight 3 · round to Grafana
   Grafana~partialprobed5/10

   Grafana's provisioning/observability-as-code docs show dashboards and data-source configs can be defined in version-controlled files (JSON/YAML) and managed via CLI, which supports exporting configuration in open formats, and Grafana itself is open-source software. However, actual telemetry data (metrics, logs, traces) lives in underlying data sources (Prometheus, Loki, Tempo) rather than Grafana itself, so there's no evidence of a comprehensive 'export all my data and leave' capability for the data layer itself. Missing for 10: explicit dashboard/data export tooling (e.g., JSON model export UI), documentation of bulk data migration/export for metrics-logs-traces, and independent confirmation that exported configs are fully portable without lock-in.

   • [claimed-docs] “Grafana has an active provisioning system that uses configuration files. You can define data sources and dashboards using files that can be …”
   • [claimed-docs] “This approach lets you define dashboards, data sources, and other configurations in code, enabling version control, automated testing, and r…”
   • [claimed-docs] “You can define data sources and dashboards using files that can be version controlled, making GitOps more natural.”
   • [claimed-docs] “define dashboards, data sources, and other configurations in code, enabling version control, automated testing, and reliable deployments thr…”
   • [probe] “official CLI documented at https://grafana.com/docs/grafana/latest/administration/cli/”

   proof ↗⚑ flag

   New Relic~partialcommunity3/10

   New Relic exposes a GraphQL-based NerdGraph API and NRQL query language that could be used to pull data out programmatically, and it supports OpenTelemetry for ingestion, but there is no documented bulk 'export all my data' feature, no data-portability/exit tooling, and community comments note New Relic 'cares about where the server is' implying lock-in to their platform. missing for 10: dedicated bulk export/backup feature, explicit open-format export guarantee, independent confirmation of full data portability on exit.

   • [claimed-docs] “NerdGraph is our GraphQL-format API that lets you query New Relic data and configure some New Relic features.”
   • [claimed-docs] “Instrument your service with OpenTelemetry and gain platform-agnostic observability.”
   • [claimed-docs] “An easy way to experiment with the NerdGraph API is to use the NerdGraph API explorer.”
   • [community] “They don’t care that much about open source agent, but they do care about where the server is... there is still a huge underserved market fo…”

   proof ↗⚑ flag

3. ai-native userRead the product's source under an open license

   weight 2 · round to Grafana
   Grafana✓fullcommunity8/10

   Grafana's core source code is hosted publicly on GitHub (grafana-gh-1..6) and community discussion explicitly confirms it is licensed under AGPLv3 (grafana-comm-9, grafana-comm-10), an OSI-approved open license, satisfying the ability to read the source under an open license. Missing for 10: explicit first-party license-file citation and clarity on which enterprise-only modules are excluded from the open license.

   • [github] “Explore your data through ad-hoc queries and dynamic drilldown. Split view and compare different time ranges, queries and data sources side …”
   • [community] “Even though we use Grafana only internally and there would be no problem with AGPLv3 in theory I see big meetings with legal coming up which…”
   • [community] “I wonder how many companies will choose to kill off Grafana use as a result of this change. Two companies I've worked for have simply banned…”

   proof ↗⚑ flag

   New Relic—none0/10

   New Relic's core platform is closed-source SaaS; evidence only shows an open-source CLI (newrelic-cli) and agents, not the product's source under an open license, and no evidence of the core platform's source being available.

   • [github] “Entity Search: Search for entities across all your New Relic accounts”
   • [github] “Deployment Markers: Easily record an APM Application deployment within New Relic.”
   • [community] “They don’t care that much about open source agent, but they do care about where the server is... there is still a huge underserved market fo…”

   proof ↗⚑ flag

4. ai-native userSelf-host the core product

   weight 3 · round to Grafana
   Grafana✓fullprobed7/10

   Grafana OSS is well-documented as self-hostable (github.com/grafana/grafana repo, provisioning docs, CLI docs) and even AGPLv3 licensing is discussed by the community confirming open self-hosting, though with some enterprise/legal friction noted. missing for 10: no first-party step-by-step self-hosting/install guide citation in the pack, no independent hands-on report confirming a clean self-hosted deployment experience.

   • [claimed-docs] “Grafana has an active provisioning system that uses configuration files. You can define data sources and dashboards using files that can be …”
   • [claimed-docs] “You can authenticate, manage multiple environments, and perform administrative tasks from the terminal. It’s suitable for CI/CD pipelines, l…”
   • [probe] “official CLI documented at https://grafana.com/docs/grafana/latest/administration/cli/”
   • [community] “Even though we use Grafana only internally and there would be no problem with AGPLv3 in theory I see big meetings with legal coming up which…”
   • [community] “I wonder how many companies will choose to kill off Grafana use as a result of this change. Two companies I've worked for have simply banned…”

   proof ↗⚑ flag

   New Relic—none0/10

   New Relic is documented throughout as a SaaS platform (agents forwarding data to New Relic's cloud, hosted dashboards, cloud-based NRQL/NerdGraph APIs) with no mention of a self-hostable core product. A community comment explicitly notes New Relic doesn't offer on-premise deployment ('they do care about where the server is... huge underserved market for on-premise APMs'), confirming the absence.

   • [community] “They don’t care that much about open source agent, but they do care about where the server is... there is still a huge underserved market fo…”
   • [claimed-docs] “100 GB of free data ingest/month”
   • [claimed-docs] “Sign up for free access with our perpetual free tier and 100 GB/month of data ingest included.”

   proof ↗⚑ flag

Otel

1. developerSend telemetry directly over OTLP with first-class OpenTelemetry support

   weight 3 · round to New Relic
   Grafana—none0/10

   The evidence pack never mentions OTLP, OpenTelemetry SDKs, or native OTLP ingestion endpoints in Grafana; the closest reference is sending logs to Loki via Grafana Alloy, which is an indirect, unrelated mention rather than documentation of first-class OTLP support in Grafana itself. Tracing/metrics docs (Tempo) discuss traces and exemplars but do not describe OTLP as a supported ingestion protocol.

   • [claimed-docs] “Try it locally. The fastest way to experiment is to run Loki in monolithic (single-binary) mode with a local filesystem backend and send log…”
   • [claimed-docs] “Tempo lets you search for traces, generate metrics from spans, and link your tracing data with logs and metrics.”
   • [claimed-docs] “Prometheus exemplars let you jump from Prometheus metrics to Tempo traces by clicking on recorded exemplars.”

   proof ↗⚑ flag

   New Relic~partialclaimed6/10

   New Relic docs explicitly promote OpenTelemetry instrumentation for platform-agnostic observability, confirming OTLP/OTel support as a first-class ingestion path alongside native agents. However, evidence lacks technical detail on OTLP endpoint configuration, semantic-convention mapping fidelity, or independent hands-on validation of OTLP data quality. Missing for 10: detailed OTLP endpoint/setup docs, community/hands-on confirmation of OTLP ingestion working well, and specifics on semantic convention compatibility.

   • [claimed-docs] “Instrument your service with OpenTelemetry and gain platform-agnostic observability.”

   proof ↗⚑ flag

2. sreInstrument once with open standards and switch backends without re-instrumenting my code

   weight 2 · round to Grafana
   Grafana~partialcommunity5/10

   Grafana's evidence strongly supports backend-agnostic querying, visualization, and alerting across many data sources (Prometheus, Loki, Tempo, CloudWatch, etc.) and mixing data sources per-query, which supports the 'switch backends without re-instrumenting' half of the story. However, no evidence explicitly addresses OpenTelemetry-based instrumentation standards or confirms that OTel-instrumented telemetry can be freely repointed across backends without code changes — Grafana Alloy (an OTel collector) is only briefly mentioned once (docs-29) without detail. missing for 10: explicit OTel instrumentation-standard support/documentation, evidence of code-level portability across backends via OTel SDKs, and independent confirmation that switching backends requires no re-instrumentation.

   • [claimed-docs] “you create queries and expressions from multiple data sources, no matter where you store your data... create, manage, and take action on you…”
   • [github] “Mix different data sources in the same graph! You can specify a data source on a per-query basis.”
   • [github] “Mix different data sources in the same graph! You can specify a data source on a per-query basis. This works for even custom datasources.”
   • [claimed-docs] “Tempo lets you search for traces, generate metrics from spans, and link your tracing data with logs and metrics.”
   • [claimed-docs] “Prometheus exemplars let you jump from Prometheus metrics to Tempo traces by clicking on recorded exemplars.”
   • [claimed-docs] “Try it locally. The fastest way to experiment is to run Loki in monolithic (single-binary) mode with a local filesystem backend and send log…”
   • [community] “I use a combination of Graphite, InfluxDB, PostgreSQL, Timescale, CloudWatch, Prometheus. The alerting in Grafana supporting all those varia…”

   proof ↗⚑ flag

   New Relic~partialclaimed4/10

   New Relic docs confirm OpenTelemetry support ('Instrument your service with OpenTelemetry and gain platform-agnostic observability'), which addresses the open-standards instrumentation ask, but the evidence pack otherwise emphasizes proprietary APM agents, NRQL, and NerdGraph as the primary ingestion/analysis path, with no detail on OTLP endpoint configuration, semantic-convention parity, or documented ease of switching backends without re-instrumenting. Missing for 10: detailed OTel onboarding/ingestion docs, evidence of vendor-neutral backend portability, and independent/hands-on confirmation that OTel-instrumented apps get full feature parity vs proprietary agents.

   • [claimed-docs] “Instrument your service with OpenTelemetry and gain platform-agnostic observability.”
   • [claimed-docs] “Monitor application performance across your stack. We’ve got agents for Go, Java, .NET, Node.js, PHP, Python, and Ruby.”
   • [claimed-docs] “Monitor application performance across your stack. We've got agents for Go, Java, .NET, Node.js, PHP, Python, and Ruby.”

   proof ↗⚑ flag

1. ai-native userChoose where my data is stored (region/residency)

   weight 2 · round drawn
   Grafana—none0/10

   The evidence pack covers Grafana's querying, alerting, provisioning, and MCP integration but contains no mention of region selection, data residency options, or where Grafana Cloud stores customer data. While self-hosted Grafana inherently allows control over storage location, no evidence in this pack documents an explicit region/residency choice feature for Grafana Cloud users. missing for 10: any documentation of Grafana Cloud region selection, data residency guarantees, or compliance-driven storage location controls.

   ⚑ flag

   New Relic—none0/10

   The evidence pack contains no mention of region selection, EU/US data center choice, or data residency controls; community comments only note latency issues from non-US access, not an actual data-locality control. Since this is a plausible axis for a SaaS observability platform, absence of evidence yields 'none'.

   • [community] “New Relic is especially slow because of the added latency of the trans-oceanic network hop [for non-US users]. The developers generally avoi…”
   • [community] “They don’t care that much about open source agent, but they do care about where the server is... there is still a huge underserved market fo…”

   proof ↗⚑ flag

2. ai-native userControl data retention and deletion

   weight 2 · round drawn
   Grafana—none0/10

   Grafana is an observability platform, so data retention/deletion controls (e.g., log/metric retention policies, data source deletion) are a plausible axis, but the evidence pack contains no mentions of retention configuration, data deletion APIs, or privacy-oriented data lifecycle controls. Missing for 10: retention policy documentation, deletion/export APIs, GDPR-style data controls, any independent confirmation of these mechanisms.

   ⚑ flag

   New Relic—none0/10

   No evidence pack items address data retention policies, deletion controls, or privacy/compliance configuration for AI-native users; the pack covers monitoring, dashboards, alerts, and MCP/AI query features but nothing on retention/deletion controls.

   ⚑ flag

3. ai-native userOpt out of telemetry and usage tracking

   weight 2 · round drawn
   Grafana—none0/10

   No evidence in the pack addresses telemetry/usage-tracking opt-out settings for Grafana itself (the product's own data collection about users), only observability/monitoring features and cost-reduction telemetry products; this is an applicable axis for any software product but no supporting documentation is present.

   ⚑ flag

   New Relic—none0/10

   No documentation addresses whether New Relic's AI features (New Relic AI assistant, MCP server) track usage/telemetry or provide an opt-out; the only related evidence (community tip on disabling APM log-forwarding via env vars) concerns application log collection, not AI-native usage tracking.

   • [community] “Setting NEW_RELIC_APPLICATION_LOGGING_ENABLED=false and NEW_RELIC_APPLICATION_LOGGING_FORWARDING_ENABLED=false disables the newly-default au…”
   • [claimed-docs] “It allows you to ask questions, troubleshoot issues, and explore telemetry data using plain language.”
   • [claimed-docs] “This update provides a standardized, scalable way to connect your favorite AI development tools directly to the rich context of the New Reli…”

   proof ↗⚑ flag

Analysis

1. developerGroup and filter by high-cardinality fields (user id, request id) without pre-aggregating or defining indexes first

   weight 2 · round to Grafana
   Grafana~partialclaimed5/10

   Grafana's ecosystem (via Loki's LogQL and Tempo's trace search) supports label-based filtering and ad-hoc queries across metrics, logs, and traces without pre-aggregation, and GitHub docs mention ad-hoc queries/drilldown across data sources. However, no evidence explicitly addresses high-cardinality fields like user id or request id, or confirms index-free grouping/filtering at that granularity. Missing for 10: explicit documentation on high-cardinality field handling, benchmarks/examples of filtering by user id/request id without indexing, and independent validation of this specific capability.

   • [claimed-docs] “LogQL is Grafana Loki's query language. LogQL uses labels and operators for filtering.”
   • [github] “Explore your data through ad-hoc queries and dynamic drilldown. Split view and compare different time ranges, queries and data sources side …”
   • [claimed-docs] “Tempo lets you search for traces, generate metrics from spans, and link your tracing data with logs and metrics.”
   • [github] “Mix different data sources in the same graph! You can specify a data source on a per-query basis.”

   proof ↗⚑ flag

   New Relic~partialcommunity3/10

   NRQL is described as a flexible ad-hoc query language for exploring telemetry data and building charts/alerts (new-relic-docs-3, new-relic-docs-21, new-relic-docs-25), which implies some ability to filter/group on arbitrary attributes, but nothing in the evidence explicitly claims support for high-cardinality fields like user id or request id, or states that no pre-aggregation/indexing is required. A community report even notes 'constant problems with metric names exploding' (new-relic-comm-11), hinting at cardinality friction in practice. missing for 10: explicit documentation of high-cardinality attribute support, confirmation that NRQL/NRDB requires no schema/index definition for arbitrary fields, and hands-on evidence of filtering by user id/request id at scale.

   • [claimed-docs] “NRQL can help you: Create a new chart, Answer a specific question for the purpose of troubleshooting or business analysis, Set up NRQL-based…”
   • [claimed-docs] “NRQL can help you: Create a new chart ... Set up NRQL-based alerts (our primary and most powerful type of alert)”
   • [claimed-docs] “Set up NRQL-based alerts (our primary and most powerful type of alert)”
   • [community] “I've long preferred New Relic as well - it always seemed the most natural to use; the information that was important was easy to find... I'v…”

   proof ↗⚑ flag

Errors

1. developerSee application errors grouped into issues with stack traces, release tracking, and regression detection

   weight 2 · round drawn
   Grafana—none0/10

   The evidence pack covers Grafana's dashboards, alerting, tracing (Tempo), logs (Loki), and SLOs, but contains no mention of application error grouping into issues, stack trace capture, release tracking, or regression detection—capabilities associated with dedicated error-tracking tools. This is a plausible axis for an observability platform to address, but nothing in the pack demonstrates it.

   ⚑ flag

   New Relic—none0/10

   The evidence pack covers APM agent instrumentation, NRQL querying, dashboards, and deployment markers, but nowhere mentions error grouping into issues, stack trace capture, or regression detection — the core elements of this story. Missing for 10: any documentation of an 'errors inbox' or issue-grouping UI, stack trace capture, or regression detection tied to deployments/releases.

   • [claimed-docs] “Monitor application performance across your stack. We've got agents for Go, Java, .NET, Node.js, PHP, Python, and Ruby.”
   • [github] “Deployment Markers: Easily record an APM Application deployment within New Relic.”
   • [claimed-docs] “Our log management solution provides deeper visibility into application and infrastructure performance data (events, errors, traces, and mor…”

   proof ↗⚑ flag

Query language

1. developerAnalyze telemetry ad hoc with a documented query language

   weight 3 · round to New Relic
   Grafana✓fullcommunity8/10

   Grafana ships Explore for ad-hoc querying/drilldown across data sources (grafana-gh-1, grafana-gh-2) and documents a dedicated query language, LogQL, with syntax details (grafana-docs-15), alongside general docs on querying/exploring metrics, logs, and traces (grafana-docs-9/23). This matches the developer story of ad hoc telemetry analysis with a documented query language. Missing for 10: deeper first-party documentation of PromQL itself (only Loki's LogQL is directly documented in the pack) and independent corroboration free of usability complaints—one community comment notes documentation gaps around pulling/dashboarding data (grafana-comm-3).

   • [github] “Explore your data through ad-hoc queries and dynamic drilldown. Split view and compare different time ranges, queries and data sources side …”
   • [github] “Experience the magic of switching from metrics to logs with preserved label filters. Quickly search through all your logs or streaming them …”
   • [claimed-docs] “LogQL is Grafana Loki's query language. LogQL uses labels and operators for filtering.”
   • [claimed-docs] “enables you to query, visualize, alert on, and explore your metrics, logs, and traces wherever they're stored”
   • [claimed-docs] “enables you to query, visualize, alert on, and explore your metrics, logs, and traces wherever they’re stored”
   • [community] “I love using grafana however I abhor creating dashboards and trying to pull data, but that's mostly because of a lack of documentation.”

   proof ↗⚑ flag

   New Relic✓fullclaimed9/10

   NRQL is a well-documented query language for ad hoc analysis (creating charts, troubleshooting, alerts), with an API explorer for experimentation via NerdGraph, and even an AI assistant to help construct queries. Missing for 10: independent hands-on validation of NRQL usability beyond vendor docs (community comments focus on cost/UI issues rather than the query language itself).

   • [claimed-docs] “NRQL can help you: Create a new chart, Answer a specific question for the purpose of troubleshooting or business analysis, Set up NRQL-based…”
   • [claimed-docs] “NRQL can help you: Create a new chart ... Set up NRQL-based alerts (our primary and most powerful type of alert)”
   • [claimed-docs] “Set up NRQL-based alerts (our primary and most powerful type of alert)”
   • [claimed-docs] “NerdGraph is our GraphQL-format API that lets you query New Relic data and configure some New Relic features.”
   • [claimed-docs] “An easy way to experiment with the NerdGraph API is to use the NerdGraph API explorer.”
   • [claimed-docs] “If you're struggling to get a query to work, ask our AI assistant to help you.”

   proof ↗⚑ flag

Correlation

1. developerJump from a trace span to its correlated logs and metrics to debug a request end to end

   weight 2 · round to Grafana
   Grafana✓fullclaimed8/10

   Grafana/Tempo docs explicitly describe linking traces to logs and metrics, including Prometheus exemplars to jump from metrics to Tempo traces, and Grafana's core UX of switching between metrics/logs/traces ("switching from metrics to logs with preserved label filters"); the incident response flow also confirms investigating with the same metrics/logs/traces that fired an alert, supporting end-to-end debugging. Missing for 10: independent hands-on account of trace-to-log/metric jump specifically (community evidence covers general cross-datasource correlation but not this exact trace-span workflow), and no explicit mention of trace-to-log correlation (only exemplars for metrics->traces).

   • [claimed-docs] “Tempo lets you search for traces, generate metrics from spans, and link your tracing data with logs and metrics.”
   • [claimed-docs] “Prometheus exemplars let you jump from Prometheus metrics to Tempo traces by clicking on recorded exemplars.”
   • [claimed-docs] “During an incident, you can investigate with the same metrics, logs, and traces that fired the alert.”
   • [github] “Experience the magic of switching from metrics to logs with preserved label filters. Quickly search through all your logs or streaming them …”
   • [github] “Experience the magic of switching from metrics to logs with preserved label filters.”

   proof ↗⚑ flag

   New Relic✓fullclaimed7/10

   New Relic's docs explicitly describe 'logs in context' where APM agents add metadata to logs enabling users to 'see logs data in various relevant places in our platform,' directly supporting jumping from traces to correlated logs, and log management ties together events, errors, and traces to reduce MTTR. Missing for 10: no independent/hands-on account specifically demonstrating the trace-span-to-log-and-metric pivot in the UI, and no detail on metrics correlation beyond logs-in-context.

   • [claimed-docs] “By default, our APM agents do two things: add metadata to your logs, which gives you logs in context (ability to see logs data in various re…”
   • [claimed-docs] “Use our APM agents to report logs. ... it lets you easily report application logs, with no additional third-party solutions required.”
   • [claimed-docs] “Our log management solution provides deeper visibility into application and infrastructure performance data (events, errors, traces, and mor…”
   • [claimed-docs] “Get visibility into hosts, containers, providers, network, and infrastructure.”

   proof ↗⚑ flag

Instrumentation

1. sreInstrument hosts, containers, Kubernetes, and cloud services through vendor-maintained agents and integrations

   weight 2 · round to New Relic
   Grafana~partialcommunity5/10

   Evidence shows Grafana ingests data from many sources (Prometheus, CloudWatch, Loki, Tempo) and mentions Grafana Alloy as an agent for sending logs, plus community confirms broad usage across cloud and hardware monitoring, but there is no explicit documentation of a curated integrations library covering hosts/containers/Kubernetes/cloud-specific vendor agents beyond the single Alloy mention. missing for 10: dedicated docs on Grafana Cloud Integrations catalog, Kubernetes-specific agent/exporter guidance, and cloud-provider-specific integration setup instructions.

   • [claimed-docs] “Try it locally. The fastest way to experiment is to run Loki in monolithic (single-binary) mode with a local filesystem backend and send log…”
   • [community] “I use a combination of Graphite, InfluxDB, PostgreSQL, Timescale, CloudWatch, Prometheus. The alerting in Grafana supporting all those varia…”
   • [community] “We have Grafana monitoring everything from cloud stuff down to temperatures of cryogenic fridges. Being able to configure alerts more dynami…”
   • [claimed-docs] “enables you to query, visualize, alert on, and explore your metrics, logs, and traces wherever they're stored”

   proof ↗⚑ flag

   New Relic✓fullcommunity7/10

   New Relic docs confirm vendor-maintained APM agents for major languages, infrastructure monitoring for hosts/containers/providers/network, OpenTelemetry support, Kubernetes/cloud cost visibility, and Lambda serverless monitoring—covering the breadth of hosts, containers, K8s, and cloud services the story asks for. However, community reports flag real friction (fragile in-cluster collection services, a logging-agent bug that dropped logs) suggesting operational rough edges rather than pure vendor-doc perfection. Missing for 10: independent hands-on validation of Kubernetes-specific agent reliability, dedicated K8s integration docs beyond generic infra visibility, and confirmation that in-cluster collection issues have been resolved.

   • [claimed-docs] “Monitor application performance across your stack. We've got agents for Go, Java, .NET, Node.js, PHP, Python, and Ruby.”
   • [claimed-docs] “Instrument your service with OpenTelemetry and gain platform-agnostic observability.”
   • [claimed-docs] “Gain real-time visibility into multi-cloud and Kubernetes spend.”
   • [claimed-docs] “Monitor your serverless AWS Lambda functions using both CloudWatch data and code-level instrumentation.”
   • [claimed-docs] “Get visibility into hosts, containers, providers, network, and infrastructure.”
   • [community] “currently using NR, but it's slow, expensive and the in-cluster collection services are frustratingly fragile.”
   • [community] “New Relic's logging agent had a bug that lost a good portion of our logs for a few months last year. Support were extremely lethargic about …”

   proof ↗⚑ flag

Signals

1. sreCollect metrics, logs, and traces in one platform and pivot between them with shared context

   weight 3 · round to Grafana
   Grafana✓fullcommunity9/10

   Grafana explicitly unifies metrics, logs, and traces from any data source with cross-pivoting features: switching from metrics to logs with preserved label filters, Prometheus exemplars jumping to Tempo traces, mixed data-source graphs, and incident investigation using 'the same metrics, logs, and traces that fired the alert.' Community evidence corroborates it as the de facto consolidation platform supporting many backends (Graphite, InfluxDB, Prometheus, etc.) with unified alerting. Missing for 10: independent hands-on validation specifically of seamless cross-signal pivoting at scale (community comments focus more on alerting/cost than trace-log-metric correlation UX).

   • [claimed-docs] “enables you to query, visualize, alert on, and explore your metrics, logs, and traces wherever they're stored”
   • [github] “Experience the magic of switching from metrics to logs with preserved label filters. Quickly search through all your logs or streaming them …”
   • [claimed-docs] “Prometheus exemplars let you jump from Prometheus metrics to Tempo traces by clicking on recorded exemplars.”
   • [claimed-docs] “During an incident, you can investigate with the same metrics, logs, and traces that fired the alert.”
   • [github] “Mix different data sources in the same graph! You can specify a data source on a per-query basis.”
   • [community] “I use a combination of Graphite, InfluxDB, PostgreSQL, Timescale, CloudWatch, Prometheus. The alerting in Grafana supporting all those varia…”
   • [community] “It's the de facto realtime graph consolidation platform where I work; if the thing you want to use for monitoring doesn't interact with graf…”

   proof ↗⚑ flag

   New Relic✓fullcommunity7/10

   New Relic's docs describe a single platform combining APM metrics (docs-1), OpenTelemetry traces (docs-4), infrastructure metrics (docs-31), and logs explicitly linked 'in context' with APM/trace data via automatic metadata tagging (docs-23, docs-29, docs-30), plus NRQL/dashboards to query and visualize across all these data types from 'anywhere in the platform' (docs-3, docs-7, docs-26). This directly matches the SRE story of unified metrics/logs/traces with cross-navigation. Missing for 10: independent/hands-on confirmation that pivoting between telemetry types is seamless in practice, and community feedback instead raises UI slowness/confusion (comm-13, comm-14) and a past logs-forwarding bug (comm-1) that temper full confidence without rising to a concrete contradiction of the unification claim itself.

   • [claimed-docs] “Monitor application performance across your stack. We've got agents for Go, Java, .NET, Node.js, PHP, Python, and Ruby.”
   • [claimed-docs] “Instrument your service with OpenTelemetry and gain platform-agnostic observability.”
   • [claimed-docs] “Use our APM agents to report logs. ... it lets you easily report application logs, with no additional third-party solutions required.”
   • [claimed-docs] “Our log management solution provides deeper visibility into application and infrastructure performance data (events, errors, traces, and mor…”
   • [claimed-docs] “By default, our APM agents do two things: add metadata to your logs, which gives you logs in context (ability to see logs data in various re…”
   • [claimed-docs] “Get visibility into hosts, containers, providers, network, and infrastructure.”
   • [claimed-docs] “NRQL can help you: Create a new chart, Answer a specific question for the purpose of troubleshooting or business analysis, Set up NRQL-based…”
   • [claimed-docs] “Through our UI you can build and share tailored user-friendly charts and visualizations.”
   • [claimed-docs] “Through our UI you can build and share tailored user-friendly charts and visualizations. Go to our dashboard capability to gather and chart …”
   • [community] “I used New Relic for the first time at my current job, and while the service it provides to our team is invaluable, the UI is slow and very …”
   • [community] “currently using NR, but it's slow, expensive and the in-cluster collection services are frustratingly fragile.”

   proof ↗⚑ flag