Slide 8 of 12

MongoDB integration

MongoDB integration

The MongoDB integration provides database monitoring for MongoDB deployments, from simple standalone instances to complex sharded clusters.

What it’s forMonitoring operations, connections, replication, and sharding health
Who uses itDBAs, backend developers, DevOps teams managing MongoDB databases
Under the hoodMakes MongoDB’s internal complexity accessible through clear dashboards

Metrics collected

  • Operations — Queries, inserts, updates, deletes
  • Connections — Current, available, usage
  • Replication — Oplog window, member state
  • Sharding — Chunk distribution, balancer
  • WiredTiger — Cache usage, tickets

Trade-offs

Best for: MongoDB deployments—standalone, replica sets, or sharded clusters

ProsCons
Pre-built dashboards: overview, replication, shardingComplex metrics for large clusters
Pre-built alerts: replication lag, connectionsConnection limit awareness needed
Replica set and sharding visibilityVersion-specific differences
Oplog window monitoring for DR
WiredTiger cache and ticket metrics

Learning path

Deploy this integration step by step.

MongoDB integration

Script

MongoDB deployments range from simple standalone instances to complex sharded clusters, and the integration handles all of them. Operation metrics break down by type (queries, inserts, updates, deletes) showing you workload patterns and write intensity.

Connection tracking matters because MongoDB’s default connection limits are surprisingly low. The integration helps you see when you’re approaching them. Memory metrics are interesting with MongoDB because the WiredTiger storage engine manages its own cache separate from system memory. You need to understand both.

For replica sets, two metrics dominate: oplog window size and member states. The oplog window tells you how far behind a replica can fall before it can no longer catch up, which is critical for disaster recovery. Member states show if replicas are healthy or struggling.

For sharded clusters, you get visibility into chunk distribution across shards and the balancer process that keeps things even. MongoDB’s internal complexity is real, but the dashboards make it accessible without requiring deep MongoDB expertise.