Telemetry
Integration collection

Database and Data-System Telemetry Integrations

Instrument database clients, ORMs, caches, streams, and application-owned query boundaries without storing raw SQL or sensitive parameters.

Reviewed by the Telemetry product team on . Runtime boundaries, shared event fields, verification workflow, and upstream implementation sources. Review standards and ownership

8 implementation guides

Every guide includes a server-side snippet, delivery and privacy boundaries, a verification query, related SQL, and links to upstream documentation.

Browse guides

Selection framework

Choose the boundary that knows the result

Instrument the application boundary

Record the operation fingerprint and final status where the application sees pool wait, execution, transaction, and timeout outcomes.

Do not log raw statements

Normalize operations before collection. SQL text, bound parameters, connection strings, and returned rows can expose secrets or customer data.

Connect pressure to customer impact

Pool saturation, cache misses, or consumer lag become actionable when they affect a service, release, route, job, or account workflow.

Shared event contract

Keep the first schema interoperable

  • database_system, operation, query_fingerprint, status, and duration_ms
  • pool_name, wait_ms, rows_affected, release, and environment
  • account_id, request_id, transaction outcome, and controlled SQLSTATE

Adapt these fields to the workflow, but keep units, status categories, identifiers, and ownership explicit before several services depend on the same table.

Verification

Exercise failure paths before alerts

  1. 1Run one successful query, timeout, rollback, and pool-wait fixture.
  2. 2Confirm no SQL parameters, credentials, or returned data enter events.
  3. 3Compare application duration with the database-adjacent phase durations.
  4. 4Query regressions by operation fingerprint and release.

Implementation guides

Match the framework, provider, or runtime

Sourced implementation guide

Supabase And Postgres App Telemetry

Track product workflows, database-adjacent jobs, API routes, and customer-facing failures from server code.

Open guide
Sourced implementation guide

node-postgres Pool and Query Telemetry

Instrument node-postgres query fingerprints, connection acquisition, pool pressure, timeouts, transaction outcomes, and database errors without logging SQL parameters.

Open guide
Sourced implementation guide

Prisma ORM Database Telemetry

Measure Prisma operation fingerprints, model and method latency, failures, result counts, releases, and database-dependent workflows without collecting raw query parameters.

Open guide
Sourced implementation guide

Flask and SQLAlchemy Telemetry

Measure Flask request outcomes and SQLAlchemy transaction behavior with bounded Python events, stable route templates, and safe error categories.

Open guide
Sourced implementation guide

Redis and node-redis Telemetry

Measure Redis command outcomes, latency, cache behavior, reconnects, and bounded error categories alongside node-redis.

Open guide
Sourced implementation guide

Kafka Consumer Lag and Processing Analytics

Monitor Kafka consumer outcomes, partition lag, processing latency, retries, and poison-message handling with structured events.

Open guide
Sourced implementation guide

MySQL Query and Pool Telemetry

Track normalized MySQL operations, pool wait, transaction outcomes, controlled error categories, and release regressions without storing raw SQL or parameters.

Open guide
Sourced implementation guide

MongoDB Operation Telemetry

Track named MongoDB operations, latency, result counts, retries, transaction outcomes, and release regressions without collecting documents or query values.

Open guide

Verify one end-to-end workflow first

Create a free API key, choose the closest runtime guide, and send one known success and failure before expanding coverage.

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