AWS ECS and Fargate Telemetry Integration

Implementation evidence

AWS ECS and Fargate Telemetry Integration: from boundary to verified row

Use AWS ECS and Fargate Telemetry Integration at a controlled application boundary, keep the event contract small, and verify a known outcome before building aggregate views.

1
Choose the outcome
ECS release reliability
2
Define the contract
service, ecs_task_family, ecs_task_revision, availability_zone, region, and release
3
Instrument the boundary
Read ECS_CONTAINER_METADATA_URI_V4 from the task runtime and request /task locally with a short timeout. Cache the stable family, revision, and availability-zone fields instead of reading metadata per event.
4
Verify the evidence
Exercise a known fixture, then inspect api_request_completed for one correctly typed terminal row.

Before you start

Prerequisites and boundaries

An ECS task with the version 4 metadata endpoint exposed by the runtime
Telemetry initialized once in the trusted application container with a write-scoped key
Stable service, route, job, release, and outcome fields owned by the application

Delivery setup

Install and initialize server-side

Import telemetry-sh in server-only code and initialize it once with process.env.TELEMETRY_API_KEY. Keep ingestion credentials out of browser bundles, client-visible environment variables, source control, logs, and exception messages.

aws-ecs-fargate-install

npm installation

bash

npm install telemetry-sh

1Prepare one reusable server-side delivery client with bounded network behavior.
2Add the outcome event at the success, failure, retry, or timeout boundary.
3Send controlled fixtures 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.

aws-ecs-fargate

AWS ECS and Fargate Telemetry Integration event

javascript

let cachedEcsContext;

async function getEcsContext() {
  if (cachedEcsContext) return cachedEcsContext;
  const baseUrl = process.env.ECS_CONTAINER_METADATA_URI_V4;
  if (!baseUrl) return {};

  const response = await fetch(`${baseUrl}/task`, {
    signal: AbortSignal.timeout(1000),
  });
  if (!response.ok) throw new Error("ecs_metadata_unavailable");

  const task = await response.json();
  cachedEcsContext = {
    ecs_task_family: task.Family,
    ecs_task_revision: task.Revision,
    availability_zone: task.AvailabilityZone,
  };
  return cachedEcsContext;
}

await telemetry.log("api_request_completed", {
  route_template: "/api/projects/:id",
  status: "success",
  status_code: 200,
  duration_ms: 184,
  service: "projects-api",
  release: process.env.APP_RELEASE ?? "development",
  ...(await getEcsContext()),
});

Event contract

service, ecs_task_family, ecs_task_revision, availability_zone, region, and release

route_template or job_name, status, duration_ms, retry_count, and controlled error_type

No task-role credentials, metadata URI, environment dump, container labels, raw ARN, request body, or exception text

Implementation checkpoints

Checkpoint 1

Read ECS_CONTAINER_METADATA_URI_V4 from the task runtime and request /task locally with a short timeout. Cache the stable family, revision, and availability-zone fields instead of reading metadata per event.

Checkpoint 2

Keep ephemeral task and container identifiers out of ordinary group-by fields unless a bounded incident workflow explicitly requires them.

Checkpoint 3

Record application outcomes at the request or worker boundary. The metadata endpoint adds deployment context; it does not replace CloudWatch infrastructure metrics or distributed traces.

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.

aws-ecs-fargate-verification

AWS ECS and Fargate Telemetry Integration 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.

Infrastructure reliability with SQL API reliability by release Missing heartbeat SQL Amazon ECS task metadata endpoint version 4 Fargate task metadata endpoint

Production boundary

Keep the outcome event small and recoverable

This pattern provides

A bounded, SQL-ready outcome beside the upstream workflow.
Stable fields for dashboards, alerts, and cross-event correlation.
A fixture-driven path for validating success, failure, retry, and timeout behavior.

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

Event schema starting points

Review the row grain, emit boundary, required types, privacy classes, example payload, and validation checklist before adapting a query or snippet to production.

API reliability10 fields