Flask and SQLAlchemy telemetry

Test the integration

Send and verify events with Flask and SQLAlchemy telemetry

Use Flask and SQLAlchemy telemetry where your app knows the final result. Collect only the fields you need, then verify a test event before building charts.

1
Choose the outcome
Flask API reliability
2
Define the contract
request_id, endpoint, route_template, method, and status_code
3
Log the final result
Use Flask's matched url_rule instead of request.path so identifiers do not create cardinality or privacy problems.
4
Check the stored event
Exercise a known fixture, then inspect api_request_completed for one correctly typed terminal row.

Before you start

telemetry-sh initialized once in each Flask worker process
A stable Flask endpoint taxonomy and monotonic request timer
SQLAlchemy event listeners limited to counts, durations, and safe operation metadata

Delivery setup

Install and initialize server-side

Initialize Telemetry for synchronous code or TelemetryAsync for asyncio code once per process with a server-side key. Keep ingestion credentials out of browser bundles, client-visible environment variables, source control, logs, and exception messages.

flask-sqlalchemy-install

pip installation

bash

python -m pip install telemetry-sh

1Create one reusable server-side client. Set its timeout and retry limit.
2Log an event when the operation succeeds, fails, retries, or times out.
3Send test events with known results and inspect the stored rows before enabling an alert.

Snippet

Start with one structured event

Add this shape where the workflow completes, fails, or retries. Then build the dashboard from real fields.

flask-sqlalchemy

Flask and SQLAlchemy telemetry event

python

from flask import g, request
from time import monotonic

@app.before_request
def start_request_timer():
    g.request_started_at = monotonic()
    g.db_query_count = 0

@app.after_request
def record_request_outcome(response):
    route = request.url_rule.rule if request.url_rule else "unmatched"
    telemetry.log("api_request_completed", {
        "request_id": request.headers.get("X-Request-ID"),
        "endpoint": request.endpoint or "unmatched",
        "route_template": route,
        "method": request.method,
        "status_code": response.status_code,
        "status": "failed" if response.status_code >= 500 else "success",
        "latency_ms": round((monotonic() - g.request_started_at) * 1000),
        "db_query_count": g.db_query_count,
        "release": app.config.get("APP_RELEASE"),
    })
    return response

Event schema

request_id, endpoint, route_template, method, and status_code

status, latency_ms, db_query_count, rollback_count, and error_type

service, environment, release, and approved tenant context

Check your setup

Checkpoint 1

Use Flask's matched url_rule instead of request.path so identifiers do not create cardinality or privacy problems.

Checkpoint 2

Store per-request counters in flask.g and update them from reviewed SQLAlchemy hooks; never send SQL text, bound parameters, connection strings, or ORM objects.

Checkpoint 3

A teardown exception can occur after a response is constructed, so model request outcome and transaction rollback as distinct events when both questions matter.

Verification

Prove the event arrived

Run this after exercising known success and failure cases. Replace the fallback table name if your final event contract differs from the snippet.

flask-sqlalchemy-verification

Flask and SQLAlchemy telemetry verification query

sql

SELECT *
FROM api_request_completed
ORDER BY timestamp_utc DESC
LIMIT 20;

Confirm one terminal row per logical outcome, with the expected status, identifiers, units, and UTC time.

Inspect the inferred schema and verify that retries do not change field types or generate a new logical event ID.

Search the stored fields for credentials, raw payloads, prompts, private content, and unbounded error messages.

Exercise a provider timeout, ingestion rejection, and process shutdown before treating the dashboard as complete.

Implementation references

Review the event contract, data-safety guidance, and upstream primary documentation before enabling a new production path.

Python SDK Database reliability guide High-cardinality fields Flask request context SQLAlchemy session events

Where to log

Keep the outcome event small and recoverable

This pattern provides

Record the outcome as an event you can query with SQL.
Stable fields for dashboards, alerts, and cross-event correlation.
Test events for checking success, failure, retries, and timeouts.

This pattern does not provide

An OTLP exporter, automatic collection pipeline, or replacement for detailed traces and diagnostic logs.
Exactly-once delivery merely because the payload contains an event ID.
Permission to collect raw provider payloads, user content, credentials, or regulated data.

Delivery and idempotency Batching and shutdown Troubleshoot ingestion

Example event schemas

Check what each event records, when to send it, and which field types it needs. Review the example payload and privacy checklist before using it in production.

API reliability10 fields