Datadog Integration
Parent: MongoDB Monitoring and Observability · Published reference · snapshot 2026-10-23 · skill mongodb-cohort-e4e31a146993
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Source-anchored research for Datadog Integration. Run status: COMPLETED.
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Problems, failure modes and limitations
- The Agent MongoDB check supports custom find, count and aggregate metrics. Database Monitoring adds query snapshots, slow-query metrics, execution plans and collection insights beyond the standard integration. (low confidence) (verified as of 2026-10-23) [source]
- Datadog's standard MongoDB integration distinguishes Database Monitoring as an additional product for query snapshots, slow-query metrics, database load and execution plans. (low confidence) (verified as of 2026-10-23) [source]
Comparisons and alternatives
- Atlas provides cluster, replica-set and database tags on relevant metrics. Custom tags require opt-in and apply to metrics rather than alerts. (low confidence) (verified as of 2026-10-14) [source]
- Atlas warns that mongodb.atlas.replstatus.health can remain healthy when nodes stop sending pings, or become inaccurate during partitions and Datadog ingestion problems. Configure no-data monitoring rather than treating health=1 alone as proof of availability. (low confidence) [source]
- Atlas exposes organization, project, cluster and database tags. User-defined resource tags are optional and apply to metrics rather than alerts. (medium confidence) (verified as of 2026-10-14) [source]
Facts and statements
- Atlas pushes metrics into Datadog; setup uses a Datadog API key in Atlas project integrations. Both vendors document an M10+ cluster requirement. (high confidence) (verified as of 2026-10-14) [source]
- Atlas setup requires a Datadog API key. The CLI command atlas integrations create DATADOG creates or updates the project integration. (high confidence) [source]
- Atlas can deliver alerts as Datadog events through the same integration used for project metrics. (high confidence) [source]
- Atlas disables high-cardinality database, collection-latency and query-shape metric exports by default; enable sendDatabaseMetrics, sendCollectionLatencyMetrics and sendQueryShapeMetrics explicitly. (high confidence) (verified as of 2026-10-14) [source]
- The MongoDB check ships with the Datadog Agent. Its configuration uses mongo.d/conf.yaml and a monitoring user with clusterMonitor plus read permissions for the databases being monitored. (high confidence) (verified as of 2026-10-23) [source]
- MongoDB APM requires instrumentation in the application making database requests. OneUptime illustrates initializing Node.js dd-trace before importing the MongoDB client; installing the database metric check alone does not establish application tracing. (high confidence) [source]
- The Agent integration collects low-level metrics per mongod node, while higher-level collection/index statistics require topology-aware placement. Datadog documents separate replica-set and sharded-cluster layouts. (low confidence) [source]
- The MongoDB integration changelog records safeguards against monitoring overhead and failures: skipping explain on $mergeCursors pipelines to prevent potential crashes, and removing queryStats server-side sorting to avoid sort-memory failures. (low confidence) (verified as of 2026-07-08) [source]
- A February 2023 Terraform user reported INTEGRATION_FIELDS_INVALID and INVALID_ENUM_VALUE errors while configuring Datadog region values through the Atlas API. The captured thread records differing Atlas and Terraform documentation values and no follow-up confirming a fix. (low confidence) [source]
- A Datadog-authored Chef guest post shows automated Agent deployment and configuration of the MongoDB integration through Chef roles; this remains vendor-origin evidence. (low confidence) [source]
- Atlas requires Project Owner access for this integration; an Organization Owner must first add themselves to the project with that role. (low confidence) (verified as of 2026-10-14) [source]
- Datadog recommends an Agent on each replica-set host, connecting to its local member. Low-level metrics require collection from every mongod, while higher-level collection/index statistics should be collected once. (low confidence) [source]
- MongoDB logs require a separate Agent configuration: enable logs_enabled in datadog.yaml and configure the MongoDB log source. Log collection is disabled by default. (low confidence) (verified as of 2026-10-23) [source]
Children
- Atlas metric export configuration (frontier)
- Agent topology and collection permissions (frontier)
- MongoDB application tracing (frontier)
- Datadog Database Monitoring (frontier)
Frontier under this node: Agent topology and collection permissions, Atlas metric export configuration, Datadog Database Monitoring, MongoDB application tracing