Observability & Monitoring Arena
Datadog vs New Relic
Datadog
Datadog, Inc.
Datadog wins · 18–13 (23 drawn)
Agenticness — how well agents can access and operate the productAgenticness
How well agents can access and operate the product
Agent access
ai-native userPoint an agent at llms.txt or agent-oriented docs
weight 2 · round to DatadogDatadog hosts a live llms.txt at docs.datadoghq.com confirmed by direct HTTP 200 probe, explicitly indexing observability documentation for agent consumption, alongside a documented MCP server for agentic tool access. Missing for 10: no independent/community corroboration of agents actually using llms.txt, and no broader agent-oriented docs structure beyond the single file.
- [probe] “PROBE llms.txt: HTTP 200 at https://docs.datadoghq.com/llms.txt # Datadog documentation > Documentation index for the Datadog observability…”
- [claimed-docs] “Datadog MCP Server”
- [probe] “official MCP server documented at https://docs.datadoghq.com/mcp_server/”
New Relicnone0/10A 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.
ai-native userRun the product headlessly / in CI for automation
weight 2 · round drawnDatadog documents an official CLI (datadog-ci) and API reference that support headless/CI automation (e.g., CI Visibility, uploading test/coverage data, deployment tracking), and integrations with CI platforms are referenced. However, there's no first-party evidence of a comprehensive 'run headlessly' story specifically for AI-native automation (e.g., no CI-specific quickstart guide walkthrough, no independent hands-on confirmation of CI reliability). missing for 10: dedicated documentation/tutorial on headless CI automation workflows for AI agents, independent/community validation of CLI use in CI pipelines, and details on authentication/config for non-interactive automated runs.
- [probe] “official CLI documented at https://github.com/DataDog/datadog-ci”
- [claimed-docs] “CI Visibility”
- [claimed-docs] “API Reference”
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”
ai-native userPlug MCP servers into this product so it can use their tools
weight 3 · round drawnDatadognone0/10Evidence only shows Datadog exposing its own official MCP server so external agents can call Datadog's tools (datadog-docs-3, datadog-probe-3) — the reverse direction of this story, which asks whether a user can plug external MCP servers into Datadog so Datadog's own AI features (e.g., Bits AI) can consume their tools. No documentation shows Datadog acting as an MCP client or supporting configurable MCP server connections for its own AI assistant.
- [claimed-docs] “Datadog MCP Server”
- [probe] “official MCP server documented at https://docs.datadoghq.com/mcp_server/”
- [claimed-docs] “Bits AI”
New Relicnone0/10Evidence 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.”
ai-native userConnect an agent via an official MCP server
weight 3 · round drawnDatadog publishes an official MCP Server with dedicated documentation, allowing AI agents to connect to Datadog data natively, and this is corroborated by a direct probe confirming the doc page exists. Missing for 10: independent/hands-on third-party validation of the MCP server's real-world behavior and details on scope/tooling coverage.
- [claimed-docs] “Datadog MCP Server”
- [probe] “official MCP server documented at https://docs.datadoghq.com/mcp_server/”
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/”
ai-native userUse an official CLI
weight 2 · round to DatadogDatadog ships an official open-source CLI (datadog-ci) documented on GitHub, usable for CI/CD, uploading source maps, tracking deployments, etc., which supports automation/agentic workflows. Missing for 10: no independent hands-on review of the CLI's AI-native usability, and no first-party docs page (only GitHub repo) confirming ongoing maintenance depth.
- [probe] “official CLI documented at https://github.com/DataDog/datadog-ci”
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.
ai-native userDrive the product through a documented public API
weight 3 · round to DatadogDatadog publishes a comprehensive public API Reference (datadog-docs-24) covering the platform's functionality, plus an official CLI (datadog-ci) and MCP server for programmatic/agentic access, indicating a mature documented API surface. Missing for 10: independent third-party corroboration of API completeness/reliability beyond vendor docs.
- [claimed-docs] “API Reference”
- [probe] “official CLI documented at https://github.com/DataDog/datadog-ci”
- [probe] “official MCP server documented at https://docs.datadoghq.com/mcp_server/”
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”
ai-native userIssue scoped/least-privilege API credentials for an agent
weight 2 · round drawnDatadognone0/10The evidence pack mentions an API Reference, MCP Server, and general docs, but nothing describes scoped or least-privilege API credential issuance for agents (e.g., restricted API keys, granular permission scopes tied to agent identity). Missing for 10: documentation on restricted/scoped API keys, role-based key permissions for AI agents, or any agent-specific credential-issuance workflow.
- [claimed-docs] “Datadog MCP Server”
- [claimed-docs] “API Reference”
New Relicnone0/10New 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.”
ai-native userBuild against official SDKs
weight 2 · round to New RelicDatadog provides an official API Reference and OpenTelemetry integration that developers can build against programmatically, plus an official CLI (datadog-ci) and MCP server, suggesting a broader SDK/tooling ecosystem exists. However, the evidence pack never explicitly documents a set of official client SDKs (e.g., per-language libraries) or their AI-specific integration patterns. Missing for 10: explicit SDK documentation pages, language coverage, and any AI-agent-specific SDK usage examples.
- [claimed-docs] “API Reference”
- [claimed-docs] “OpenTelemetry in Datadog”
- [probe] “official CLI documented at https://github.com/DataDog/datadog-ci”
- [claimed-docs] “Datadog MCP Server”
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…”
ai-native userSubscribe to events via webhooks
weight 2 · round drawnDatadognone0/10The evidence pack lists many Datadog capabilities (monitors, integrations, API reference, MCP server) but never mentions webhook subscriptions or outbound webhook notifications for events/alerts. Missing for 10: any documentation of webhook configuration, webhook payload format, or webhook-based event subscription mechanism.
New Relicnone0/10The 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.”
Agentic features
ai-native userGet AI-generated insights and suggestions from my data inside the product
weight 2 · round drawnDatadog's Bits AI and Watchdog features are documented as delivering AI-generated insights, anomaly detection, and suggestions directly within the platform's data (monitoring, incidents, APM). This is corroborated by first-party docs, though there's no independent/hands-on validation of quality or breadth of these AI insights. Missing for 10: independent/hands-on evidence of Bits AI or Watchdog output quality, and detail on how comprehensive the 'insights' are across all product surfaces.
- [claimed-docs] “Bits AI”
- [claimed-docs] “Datadog Watchdog™”
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.”
ai-native userSet up automations that run autonomously in the background
weight 2 · round to DatadogDatadog's Monitors let users configure conditions that run continuously and trigger automated actions/alerts without manual intervention, and Watchdog autonomously detects anomalies in the background without configuration, both supporting background automation (datadog-docs-10, datadog-docs-16). However, there's no evidence of AI-native agentic automation (e.g., multi-step autonomous AI workflows or an agent orchestration feature) beyond rule-based monitoring and anomaly detection. Missing for 10: dedicated workflow/automation orchestration product, evidence of AI agents performing autonomous multi-step actions, and independent corroboration of these running unattended long-term.
- [claimed-docs] “Monitors”
- [claimed-docs] “Datadog Watchdog™”
- [claimed-docs] “Bits AI”
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.”
ai-native userDelegate tasks to a built-in AI assistant inside the product
weight 3 · round to New RelicDatadog documents 'Bits AI' as a built-in AI assistant (datadog-docs-4), which matches the story's core requirement, but the evidence pack only shows a title/URL with no detail on what tasks can be delegated or how it behaves in practice, and no independent/hands-on corroboration exists. Missing for 10: detailed documentation of task-delegation capabilities and scope, and community or hands-on validation of Bits AI actually performing delegated tasks.
- [claimed-docs] “Bits AI”
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.”
ai-native userOperate the product with natural-language commands
weight 2 · round to New RelicDatadog documents 'Bits AI' (an AI assistant) and an official MCP server, suggesting natural-language interaction is possible, but the evidence pack gives only a bare doc title with no detail on what commands/actions Bits AI actually supports or how natural-language control works end-to-end. missing for 10: detailed documentation of Bits AI command capabilities, hands-on or community evidence confirming it works, examples of natural-language operations actually performed.
- [claimed-docs] “Bits AI”
- [claimed-docs] “Datadog MCP Server”
- [probe] “official MCP server documented at https://docs.datadoghq.com/mcp_server/”
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/”
Api quality
ai-native userExplore an interactive API reference with runnable examples
weight 2 · round to New RelicDatadognone0/10Datadog has an API Reference doc page, but there's no evidence of an interactive, runnable-example reference (e.g., embedded code sandbox, try-it-now console); the OpenAPI probe even returned 404s across candidate paths, suggesting no discoverable machine-readable spec for interactive tooling.
- [claimed-docs] “API Reference”
- [probe] “PROBE openapi: all candidate paths 404 (https://docs.datadoghq.com/openapi.json, https://docs.datadoghq.com/swagger.json, https://docs.datad…”
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…”
ai-native userDownload a machine-readable API spec (OpenAPI or equivalent)
weight 2 · round to DatadogDatadog publishes a full API Reference (docs-24) which is typically autogenerated from an OpenAPI-style spec, but the evidence pack shows explicit probe attempts for common openapi.json/swagger.json paths on the docs site all returning 404, so a directly downloadable machine-readable spec is not confirmed at any documented URL. Missing for 10: an explicit, working download link/endpoint for the OpenAPI/Swagger file, and confirmation that the API Reference page itself exposes a machine-readable export.
- [claimed-docs] “API Reference”
- [probe] “PROBE openapi: all candidate paths 404 (https://docs.datadoghq.com/openapi.json, https://docs.datadoghq.com/swagger.json, https://docs.datad…”
New Relicnone0/10New 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…”
ai-native userTest against a sandbox environment without touching production data
weight 1 · round drawnDatadognone0/10No evidence of a sandbox/test environment feature isolated from production data; Datadog's evidence pack focuses on observability, security, and AI features (Bits AI, MCP server) but never mentions a sandbox mode, test account, or synthetic-data environment for AI-native testing.
New Relicnone0/10No 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.
ai-native userRely on versioned APIs with a documented deprecation policy
weight 2 · round to DatadogDatadog exposes a versioned API (docs-24 references /api/latest/, implying v1/v2 versioning), but the evidence pack contains no documentation of an explicit deprecation policy, sunset timeline, or versioning changelog. Missing for 10: explicit deprecation policy documentation, version support lifecycle, migration guides between API versions, independent confirmation of policy adherence.
- [claimed-docs] “API Reference”
New Relicnone0/10Evidence 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…”
Ai assist — stories about ai assist in this arenaAi assist
Stories about ai assist in this arena
Agent integration
ai-native userHave an external agent query metrics, logs, and traces through documented APIs to debug production
weight 3 · round to New RelicDatadog documents a full REST API reference covering metrics, logs, and traces (datadog-docs-24, datadog-docs-23, datadog-docs-13) plus an official MCP server explicitly designed to let external AI agents query Datadog data (datadog-docs-3, datadog-probe-3), directly matching the story of an external agent debugging production via documented APIs. Missing for 10: independent hands-on validation of an agent successfully using the MCP server/API for real debugging, and no OpenAPI spec was discoverable at expected paths (datadog-probe-2), slightly weakening machine-readable API discoverability.
- [claimed-docs] “Datadog MCP Server”
- [claimed-docs] “API Reference”
- [claimed-docs] “APM”
- [claimed-docs] “Log Management”
- [probe] “official MCP server documented at https://docs.datadoghq.com/mcp_server/”
- [probe] “PROBE openapi: all candidate paths 404 (https://docs.datadoghq.com/openapi.json, https://docs.datadoghq.com/swagger.json, https://docs.datad…”
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/”
Ai investigation
ai-native userGet AI-generated summaries of incidents and alert context for responders
weight 2 · round to DatadogDatadog's Bits AI product page and Incident Management docs indicate AI-assisted incident investigation and responder support, aligning with the story, but the evidence pack lacks detail on the specific 'AI-generated summary' feature depth, independent hands-on validation, or example outputs. missing for 10: detailed documentation of Bits AI incident summary generation workflow, independent/community corroboration of AI summary quality, and specifics on alert-context summarization beyond incident management.
- [claimed-docs] “Bits AI”
- [claimed-docs] “Incident Management”
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.”
ai-native userHave the platform's AI investigate an alert or error and propose a probable root cause
weight 3 · round to DatadogDatadog documents Bits AI and Watchdog, first-party AI features aimed at analyzing alerts/anomalies and assisting investigations, plus an MCP server that could let AI agents query Datadog data for root-cause analysis. However, the evidence pack lacks detailed documentation of Bits AI actually proposing root causes for specific alerts/errors, and there's no independent/hands-on corroboration of this capability working in practice. missing for 10: detailed Bits AI root-cause workflow documentation, hands-on/independent validation of AI-proposed root causes, specifics on Watchdog's automated root-cause analysis output.
- [claimed-docs] “Bits AI”
- [claimed-docs] “Datadog Watchdog™”
- [claimed-docs] “Datadog MCP Server”
- [probe] “official MCP server documented at https://docs.datadoghq.com/mcp_server/”
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…”
Ai querying
ai-native userAsk questions of my telemetry in natural language and get a real query or chart back
weight 2 · round to New RelicDatadog's Bits AI product page ([datadog-docs-4]) is described as an AI assistant, and the MCP server ([datadog-docs-3], [datadog-probe-3]) enables AI agents to query telemetry data, which together suggest natural-language querying capability. However, there is no detailed documentation or independent/hands-on evidence showing it reliably returns a 'real query or chart' from a natural-language question. Missing for 10: concrete examples/screenshots of Bits AI answering telemetry questions with charts/queries, independent user corroboration, and details on scope/limitations of the NLQ feature.
- [claimed-docs] “Bits AI”
- [claimed-docs] “Datadog MCP Server”
- [probe] “official MCP server documented at https://docs.datadoghq.com/mcp_server/”
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.”
Alerting slos — stories about alerting slos in this arenaAlerting slos
Stories about alerting slos in this arena
Alert automation
ai-native userPoint alert notifications at webhooks that trigger automated remediation or agents
weight 2 · round drawnDatadognone0/10Evidence pack lists Monitors/alerting docs but contains no mention of webhook notification integrations or configuring alerts to trigger automated remediation/agent workflows via webhooks.
New Relicnone0/10The 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.”
Alerting
sreAlert on any telemetry signal with routing, grouping, and silencing of notifications
weight 3 · round to DatadogDatadog Monitors support alerting on any metric/log/trace/APM/synthetic signal with configurable notification routing to teams/channels, multi-condition grouping, and mute/downtime (silencing) capabilities, and Monitors doc is the canonical first-party reference for this. Community evidence corroborates strong cross-signal correlation and usability of alerting-adjacent features. Missing for 10: no independent hands-on account specifically validating routing/grouping/silencing workflows, and no detail on advanced silencing scheduling beyond the docs link.
- [claimed-docs] “Monitors”
- [claimed-docs] “Datadog Watchdog™”
- [community] “Their main competitive advantage is being able to correlate data across APM, custom metrics, and logging through the use of tagging, densely…”
- [community] “DD was just easier to use for everybody, has lots of useful baked-in things we liked to use (apdex scores), and was intuitive enough that no…”
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…”
sreEnable anomaly or outlier detection that surfaces problems without hand-written thresholds
weight 1 · round to DatadogDatadog Watchdog provides automated anomaly and outlier detection across metrics, APM, and logs without requiring manual threshold configuration, and Monitors support anomaly-detection algorithms as an alternative to static thresholds. Missing for 10: independent hands-on validation of Watchdog's detection accuracy/false-positive rate and more detail on SLO-specific anomaly alerting.
- [claimed-docs] “Datadog Watchdog™”
- [claimed-docs] “Monitors”
- [claimed-docs] “Service Level Objectives”
New Relicnone0/10The 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)”
Slos
sreDefine SLOs with error budgets and burn-rate alerts
weight 2 · round drawnDatadog has a dedicated Service Level Objectives product with documentation, which integrates with its Monitors system to support error-budget and burn-rate alerting, a standard and well-documented Datadog capability for SRE workflows. Missing for 10: no independent/hands-on corroboration specifically of burn-rate alert configuration, and no community evidence discussing SLO usage in practice.
- [claimed-docs] “Service Level Objectives”
- [claimed-docs] “Monitors”
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.”
Automation depth — how much of the product can run unattendedAutomation depth
How much of the product can run unattended
ai-native userPerform bulk operations across many items at once
weight 2 · round to New RelicDatadog exposes a full REST API and an official CLI (datadog-ci) that could be scripted for bulk actions (e.g., creating/updating many monitors, dashboards, or tags programmatically), but the evidence pack contains no explicit documentation or example of bulk/batch endpoints or AI-native bulk workflows. missing for 10: explicit bulk/batch API endpoints or docs, AI-agent-oriented bulk operation examples, independent confirmation of bulk usage at scale.
- [claimed-docs] “API Reference”
- [probe] “official CLI documented at https://github.com/DataDog/datadog-ci”
- [claimed-docs] “Datadog MCP Server”
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…”
ai-native userDefine rules that trigger actions automatically on events
weight 3 · round to New RelicDatadog's Monitors and Watchdog docs support defining alerting rules that trigger notifications/webhooks/workflows on events (e.g., threshold or anomaly monitors), and Incident Management can be triggered from these events, which supports rule-based automation. However, evidence is thin on AI-native-specific automation (e.g., agentic workflows driven by AI reasoning) beyond standard monitor-to-action pipelines, and no independent/hands-on corroboration of rule-triggered automation depth is present. Missing for 10: evidence of AI-driven/dynamic rule generation, Workflow Automation product specifics, and third-party validation of trigger-action reliability.
- [claimed-docs] “Monitors”
- [claimed-docs] “Datadog Watchdog™”
- [claimed-docs] “Incident Management”
- [claimed-docs] “API Reference”
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)”
ai-native userSchedule recurring jobs or workflows
weight 2 · round drawnDatadognone0/10The evidence pack covers monitoring, APM, security, dashboards, and integrations, but nothing about scheduling recurring jobs or workflows (no cron-like scheduler, workflow orchestration, or automation-trigger documentation). While such automation is a plausible feature for an observability platform, no evidence in this pack demonstrates it.
New Relicnone0/10New 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.”
ai-native userVersion, review, and roll back my automations
weight 1 · round drawnDatadognone0/10No evidence in the pack addresses versioning, review workflows, or rollback capabilities for Datadog automations (e.g., monitors, workflows, or Watchdog). Nothing in docs or community feedback references a version-control, diff, approval, or rollback mechanism for automation configurations.
Cost sampling — stories about cost sampling in this arenaCost sampling
Stories about cost sampling in this arena
Cost
sreSee what my observability spend is, attribute it to teams or services, and catch usage spikes before the bill
weight 3 · round to DatadogDatadogdisputedcontradicted5/10Datadog documents a dedicated Cloud Cost Management product (datadog-docs-15) and tag-based correlation across APM/metrics/logs that could support cost attribution by team/service (datadog-comm-3), but a concrete customer account describes losing a $6M/yr relationship specifically due to 'lack of billing transparency' (datadog-comm-7), and others report costs escalating far beyond expectations without early warning (datadog-comm-13). This is a direct contradiction between the documented cost-visibility capability and hands-on billing-transparency complaints. Missing for 10: first-party documentation/screenshots of per-team/service cost attribution dashboards, evidence of spike/anomaly alerting specifically for Datadog usage costs, and independent confirmation that billing transparency issues have been resolved.
- [claimed-docs] “Cloud Cost Management”
- [community] “Their main competitive advantage is being able to correlate data across APM, custom metrics, and logging through the use of tagging, densely…”
- [community] “Datadog lost our business for two reasons: 1) Lack of billing transparency and 2) an incompetent account rep who managed to piss off our fin…”
- [community] “I like DataDog but it is prohibitively expensive for monitoring serverless applications, even with negotiated rates... Paying for DataDog is…”
New Relicnone0/10There 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.”
srePredict costs from transparent published per-signal pricing without talking to sales
weight 1 · round to New RelicDatadognone0/10The evidence pack contains no published per-signal pricing page or documentation enabling cost prediction without sales contact; instead, community reports explicitly cite 'Lack of billing transparency' as a reason for leaving Datadog and describe pricing as requiring negotiated/account-manager-adjusted rates rather than transparent self-serve figures. Missing for 10: any docs citation of a public pricing/cost calculator page, per-signal unit pricing tables, or evidence that costs can be estimated without sales engagement.
- [community] “Datadog lost our business for two reasons: 1) Lack of billing transparency and 2) an incompetent account rep who managed to piss off our fin…”
- [community] “We spend a few thousand a month with Datadog and our account manager reaches out every quarter to adjust our monthly commit up/down which pr…”
- [community] “I like DataDog but it is prohibitively expensive for monitoring serverless applications, even with negotiated rates... Paying for DataDog is…”
New Relicdisputedcontradicted4/10New 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.”
Sampling
developerControl trace/log sampling and retention tiers to manage data volume deliberately
weight 2 · round to New RelicDatadog lists generic APM/Tracing and Log Management doc pages, which are the general areas where sampling and retention would live, but the evidence pack contains no specific text about trace sampling rules, ingestion controls, or log index/retention tier configuration. missing for 10: explicit documentation of trace sampling rate controls, retention filters, log index/retention tiers, and any independent confirmation these controls work as described.
- [claimed-docs] “Log Management”
- [claimed-docs] “APM”
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.”
Dashboards as code — stories about dashboards as code in this arenaDashboards as code
Stories about dashboards as code in this arena
As code
developerDefine dashboards and alerts as code (JSON models, Terraform, or API) and provision them repeatably
weight 3 · round drawnDatadog exposes an API Reference and dedicated Monitors/Dashboards docs, which imply programmatic definition and provisioning of dashboards and alerts, and a CLI (datadog-ci) exists for automation. However, the evidence pack never explicitly documents a Terraform provider, JSON dashboard/monitor schema, or an 'infrastructure-as-code' workflow for dashboards/alerts. missing for 10: explicit Terraform provider documentation, JSON model schema for dashboards/monitors, and independent confirmation of repeatable IaC provisioning workflows.
- [claimed-docs] “API Reference”
- [claimed-docs] “Monitors”
- [claimed-docs] “Dashboards”
- [probe] “official CLI documented at https://github.com/DataDog/datadog-ci”
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.”
Dashboards
sreBuild shareable dashboards with rich visualization types and template variables
weight 2 · round to New RelicDatadog's official Dashboards docs ([datadog-docs-12]) confirm dashboarding is a core product feature, and community feedback corroborates strong dashboard usability ([datadog-comm-6], [datadog-comm-17]) and notebooks/correlation-based visualization ([datadog-comm-3]). However, the evidence pack lacks specifics on template variables, sharing/permissions mechanics, or a catalog of visualization widget types, and one community voice criticizes dashboard/notebook sprawl and correlation quality ([datadog-comm-5]). Missing for 10: explicit documentation/evidence of template variable support, shareable/public dashboard links, and a breakdown of supported widget/visualization types.
- [claimed-docs] “Dashboards”
- [community] “DD was just easier to use for everybody, has lots of useful baked-in things we liked to use (apdex scores), and was intuitive enough that no…”
- [community] “Their main competitive advantage is being able to correlate data across APM, custom metrics, and logging through the use of tagging, densely…”
- [community] “Datadog's server hexagon map/chart thingie is something else. The kind of innovation that wins prizes.”
- [community] “Their data correlation is awful compared to competitors like Honeycomb, Dynatrace and Instana. We shouldn't be sifting through a bunch of ou…”
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…”
Deployment openness — stories about deployment openness in this arenaDeployment openness
Stories about deployment openness in this arena
Local dev
developerSpin up a local or dev instance of the platform to test instrumentation and dashboards
weight 1 · round drawnDatadognone0/10Datadog is a hosted SaaS observability platform; the evidence pack shows no local/self-hosted/dev-instance deployment option, only an OpenAPI-less cloud API, agent-based instrumentation, and integrations — nothing suggesting a way to run the platform itself locally for testing dashboards or instrumentation.
New Relicnone0/10New 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…”
Self host
sreRun the full observability stack self-hosted in production with documented architecture and upgrade path
weight 2 · round drawnDatadognone0/10The axis applies to this product kind (peer products hold positive or none verdicts on this story), so lack of evidence for an applicable capability is "none", never "na". (na/none harmonized at arena bring-up — see pipeline/scripts/na-harmonize.ts.)
New Relicnone0/10New 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”
Incident response — stories about incident response in this arenaIncident response
Stories about incident response in this arena
Change tracking
developerCorrelate regressions with deploys and configuration changes via release or change tracking
weight 2 · round drawnDatadog documents deployment/change tracking via CI Visibility, APM, Monitors, and integrations with GitLab/GitHub that 'Track code changes, deployments, and application performance in real time,' which supports correlating regressions with deploys. However, there's no dedicated first-party doc specifically on 'Deployment Tracking' or 'Change Tracking' markers surfaced in the evidence, and community feedback notes correlation/dashboard experience can be weak compared to competitors. missing for 10: explicit deployment-tracking/change-marker feature docs, hands-on validation of deploy-to-regression correlation workflow.
- [claimed-docs] “CI Visibility”
- [claimed-docs] “APM”
- [claimed-docs] “Monitors”
- [claimed-docs] “Track code changes, deployments, and application performance in real time with integrations across software delivery platforms like GitLab a…”
- [community] “Their data correlation is awful compared to competitors like Honeycomb, Dynatrace and Instana. We shouldn't be sifting through a bunch of ou…”
- [community] “Their main competitive advantage is being able to correlate data across APM, custom metrics, and logging through the use of tagging, densely…”
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…”
Incidents
sreDeclare and track incidents with timelines, on-call schedules, and escalation policies
weight 2 · round to DatadogDatadog has a dedicated Incident Management product (datadog-docs-14) which supports declaring incidents and timelines, plus Monitors/SLOs for alerting. However, the evidence pack does not document native on-call scheduling or escalation policy features (these are often handled via third-party integrations like PagerDuty/Opsgenie rather than natively in Datadog), and no independent/hands-on corroboration of the incident workflow is present. missing for 10: documentation of built-in on-call schedules, escalation policies, and independent verification of the incident timeline/workflow experience.
- [claimed-docs] “Incident Management”
- [claimed-docs] “Monitors”
- [claimed-docs] “Service Level Objectives”
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)”
Openness — open source, data portability, and self-hosting storiesOpenness
Open source, data portability, and self-hosting stories
ai-native userDo everything through the API that I can do in the UI
weight 2 · round to DatadogDatadog offers a comprehensive public API Reference (datadog-docs-24) covering most platform features (monitors, dashboards, logs, SLOs, etc.), plus an official CLI (datadog-ci) and an MCP server, indicating strong API-first design. However, no evidence confirms full UI-API parity — some newer UI features (Bits AI, notebooks, Watchdog insights, hexagon map visualizations) are not confirmed to have full API equivalents, and no independent audit or changelog verifies parity is maintained. missing for 10: explicit parity documentation/audit confirming every UI action has an API equivalent, independent verification of coverage completeness, and confirmation for newer AI/UX features.
- [claimed-docs] “API Reference”
- [probe] “official CLI documented at https://github.com/DataDog/datadog-ci”
- [probe] “official MCP server documented at https://docs.datadoghq.com/mcp_server/”
- [claimed-docs] “Bits AI”
- [claimed-docs] “Datadog Watchdog™”
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”
ai-native userExport all of my data in open formats and leave
weight 3 · round to New RelicDatadognone0/10Datadog exposes an API Reference and supports OpenTelemetry for ingesting data, but there is no evidence of a documented bulk-export capability that lets a customer pull out all stored logs/metrics/traces in an open format and fully migrate away. Missing for 10: documented full-account data export/backup feature, open-format export guarantees, and any evidence of successful data portability/migration by users.
- [claimed-docs] “OpenTelemetry in Datadog”
- [claimed-docs] “API Reference”
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…”
ai-native userRead the product's source under an open license
weight 2 · round drawnDatadognone0/10Datadog is a closed-source SaaS platform; no evidence indicates its core product source is available under an open license (only a CLI and some client libraries/agents are open, and no evidence pack item claims this for the core product).
New Relicnone0/10New 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…”
ai-native userSelf-host the core product
weight 3 · round drawnDatadognone0/10Datadog is a SaaS-only observability platform; no evidence of an on-premise/self-hosted core product offering exists in the pack, and its architecture (cloud dashboards, Watchdog, integrations) presumes a hosted service. This is an applicable axis for infra tools (self-hosted alternatives exist), so absence of evidence yields 'none' rather than 'na'.
New Relicnone0/10New 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.”
Otel standards — stories about otel standards in this arenaOtel standards
Stories about otel standards in this arena
Otel
developerSend telemetry directly over OTLP with first-class OpenTelemetry support
weight 3 · round to DatadogDatadog has a dedicated OpenTelemetry docs page describing OTLP ingestion support alongside its native APM/tracing docs, indicating first-class OTel integration. Missing for 10: no independent/hands-on corroboration of OTLP ingestion behavior, no detail on OTLP endpoint specifics (ports, protocols, semantic convention mapping) or limitations vs native agent.
- [claimed-docs] “OpenTelemetry in Datadog”
- [claimed-docs] “APM”
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.”
sreInstrument once with open standards and switch backends without re-instrumenting my code
weight 2 · round to DatadogDatadog has a dedicated OpenTelemetry docs page (datadog-docs-2) and APM/tracing docs (datadog-docs-23) indicating support for ingesting OTel data via OTLP/Datadog Agent, which supports the 'instrument once with open standards' portion of the story. However, there's no evidence describing seamless backend-switching (e.g., no vendor lock-in avoidance claims, no documentation of using vanilla OTel SDKs without Datadog-specific config, and no independent/hands-on confirmation that switching away from Datadog requires no re-instrumentation). Missing for 10: documentation on portability guarantees when switching backends, independent verification that OTel-only instrumentation works without Datadog-specific exporters/config, and community confirmation of switching experience.
- [claimed-docs] “OpenTelemetry in Datadog”
- [claimed-docs] “APM”
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.”
Privacy posture — data-handling and privacy storiesPrivacy posture
Data-handling and privacy stories
ai-native userChoose where my data is stored (region/residency)
weight 2 · round drawnDatadognone0/10No evidence in the pack mentions data residency, regional data storage, or EU/US site selection for Datadog, despite this being a well-documented capability area for observability platforms generally. Absence of evidence for an applicable capability yields none.
New Relicnone0/10The 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…”
ai-native userPrevent my data from being used to train AI models
weight 3 · round drawnDatadognone0/10No evidence in the pack addresses AI-training data-usage opt-out policies or controls for Datadog's own AI features (e.g., Bits AI); this is an applicable privacy-posture question for an AI-enabled product but is unaddressed by any docs or community citations.
New Relicnone0/10No evidence in the pack addresses data usage for AI model training or an opt-out/data-privacy control for that purpose; the AI-related docs describe New Relic AI assistant features and MCP server, not training data policies. Missing for 10: any privacy policy, data processing agreement, or opt-out mechanism specifically regarding AI training use of customer data.
ai-native userControl data retention and deletion
weight 2 · round drawnDatadognone0/10No evidence pack items address data retention controls, deletion policies, or configurable data lifecycle management for AI-native usage; while Sensitive Data Scanner and Audit Trail are listed, there's no documentation of retention/deletion mechanisms tied to this story.
ai-native userOpt out of telemetry and usage tracking
weight 2 · round drawnDatadognone0/10No evidence in the pack addresses telemetry opt-out or usage-tracking controls for AI-native features (Bits AI, MCP server, etc.); nothing documents a privacy/opt-out mechanism.
New Relicnone0/10No 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…”
Query analytics — stories about query analytics in this arenaQuery analytics
Stories about query analytics in this arena
Analysis
developerGroup and filter by high-cardinality fields (user id, request id) without pre-aggregating or defining indexes first
weight 2 · round to DatadogDatadog's Log Management and APM docs support tag-based filtering and facets, and community evidence (datadog-comm-14) confirms users can click a field like a user id or request id and turn it into a custom search dimension without pre-defining an index, suggesting some high-cardinality ad hoc filtering is possible. However, there's no first-party documentation explicitly addressing high-cardinality field handling (e.g., custom metrics/tags cardinality limits, log facet indexing requirements) or confirmation that grouping/filtering works without any index setup at scale. missing for 10: explicit docs on high-cardinality tag/facet support without pre-indexing, evidence on custom metric cardinality limits, independent benchmarks or hands-on confirmation for user id/request id grouping at scale.
- [claimed-docs] “Log Management”
- [claimed-docs] “APM”
- [community] “If you want my two Datadog favourite features, they were: 1) clicking on a field and making it a custom search dimension in another click, a…”
- [community] “Their main competitive advantage is being able to correlate data across APM, custom metrics, and logging through the use of tagging, densely…”
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…”
Errors
developerSee application errors grouped into issues with stack traces, release tracking, and regression detection
weight 2 · round drawnDatadognone0/10The evidence pack includes APM/tracing docs but no explicit documentation of Datadog's dedicated Error Tracking feature — no mention of errors being grouped into issues, stack trace capture, release tracking, or regression detection algorithms. Only general APM/tracing (datadog-docs-23) and anomaly detection (Watchdog, datadog-docs-16) are cited, which don't concretely evidence this specific issue-grouping/regression workflow.
- [claimed-docs] “APM”
- [claimed-docs] “Datadog Watchdog™”
New Relicnone0/10The 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…”
Query language
developerAnalyze telemetry ad hoc with a documented query language
weight 3 · round to New RelicDatadog's Log Management, Dashboards, and API Reference docs imply a documented query/search syntax for ad hoc telemetry analysis, and community evidence confirms real-world ad hoc querying workflows (e.g., turning a field into a custom search dimension, correlating APM/metrics/logs via tagging). However, no evidence pack item explicitly documents a formal query language reference/spec. Missing for 10: an explicit query-language syntax reference doc, independent hands-on validation of query language depth/expressiveness.
- [claimed-docs] “Log Management”
- [claimed-docs] “Dashboards”
- [claimed-docs] “API Reference”
- [community] “Their main competitive advantage is being able to correlate data across APM, custom metrics, and logging through the use of tagging, densely…”
- [community] “If you want my two Datadog favourite features, they were: 1) clicking on a field and making it a custom search dimension in another click, a…”
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.”
Telemetry unified — stories about telemetry unified in this arenaTelemetry unified
Stories about telemetry unified in this arena
Correlation
developerJump from a trace span to its correlated logs and metrics to debug a request end to end
weight 2 · round drawnDatadog's APM/tracing and log management docs plus community testimony ("correlate data across APM, custom metrics, and logging through tagging") confirm cross-signal correlation from traces to logs/metrics is a core, documented capability. However, one community comment claims their correlation is inferior to competitors, tempering full confidence. Missing for 10: dedicated docs excerpt on trace-to-log deep-linking UI, and independent hands-on verification beyond mixed forum opinions.
- [claimed-docs] “APM”
- [claimed-docs] “Log Management”
- [community] “Their main competitive advantage is being able to correlate data across APM, custom metrics, and logging through the use of tagging, densely…”
- [community] “Their data correlation is awful compared to competitors like Honeycomb, Dynatrace and Instana. We shouldn't be sifting through a bunch of ou…”
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.”
Instrumentation
sreInstrument hosts, containers, Kubernetes, and cloud services through vendor-maintained agents and integrations
weight 2 · round to DatadogDatadog provides vendor-maintained Agent-based instrumentation for hosts/containers/Kubernetes, native OpenTelemetry support, cloud integrations, and a 1,000+ integration marketplace covering major infra and cloud services, corroborated by community praise for ease of collecting metrics/traces. Missing for 10: no independent hands-on validation specifically of Kubernetes/agent deployment depth beyond docs listing.
- [claimed-docs] “OpenTelemetry in Datadog”
- [claimed-docs] “Datadog Integrations: 1,000+ Observability Tools”
- [claimed-docs] “Ably Abnormal Security Active Directory ActiveMQ ActiveMQ XML Adaptive Shield Adobe Experience Manager Adyen Aerospike Aerospike Enterprise …”
- [claimed-docs] “Track code changes, deployments, and application performance in real time with integrations across software delivery platforms like GitLab a…”
- [community] “DD was just easier to use for everybody, has lots of useful baked-in things we liked to use (apdex scores), and was intuitive enough that no…”
- [claimed-docs] “APM”
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 …”
Signals
sreCollect metrics, logs, and traces in one platform and pivot between them with shared context
weight 3 · round to DatadogDatadog is core-built around unified metrics/logs/traces with APM, Log Management, and tracing docs, plus community confirmation that correlation via tagging across APM, metrics, and logs is a key differentiator (datadog-comm-3, datadog-comm-6). Some community pushback exists on correlation quality relative to niche competitors (datadog-comm-5), but this is a comparative gripe, not evidence the capability fails outright, so it counts against quality rather than the verdict. Missing for 10: independent hands-on benchmarking of cross-pillar pivoting UX, and more detail on trace-to-log-to-metric linking mechanics beyond marketing docs.
- [claimed-docs] “APM”
- [claimed-docs] “Log Management”
- [claimed-docs] “Application Performance Monitoring”
- [community] “Their main competitive advantage is being able to correlate data across APM, custom metrics, and logging through the use of tagging, densely…”
- [community] “DD was just easier to use for everybody, has lots of useful baked-in things we liked to use (apdex scores), and was intuitive enough that no…”
- [community] “Their data correlation is awful compared to competitors like Honeycomb, Dynatrace and Instana. We shouldn't be sifting through a bunch of ou…”
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.”