Sidekiq job telemetry

Test the integration

Send and verify events with Sidekiq job telemetry

Use Sidekiq job 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
Sidekiq retry monitoring
2
Define the contract
job_id, job_name, queue_name, status, and attempt
3
Log the final result
Wrap yield in server middleware so each execution attempt has one outcome; use jid as the logical identifier and retry_count plus one as the attempt.
4
Check the stored event
Exercise a known fixture, then inspect job_attempt_completed for one correctly typed terminal row.

Before you start

A reusable Ruby HTTP wrapper with explicit open and read timeouts
Sidekiq server middleware registered in every worker process
Stable job class and queue names plus an approved error taxonomy

Delivery setup

Install and initialize server-side

Use a small Net::HTTP wrapper with a server-side key plus explicit open and read timeouts. Keep ingestion credentials out of browser bundles, client-visible environment variables, source control, logs, and exception messages.

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.

sidekiq

Sidekiq job telemetry event

ruby

class TelemetryOutcomeMiddleware
  include Sidekiq::ServerMiddleware

  def call(_job_instance, job, queue)
    started_at = Process.clock_gettime(Process::CLOCK_MONOTONIC)
    status = "success"
    error_type = nil

    begin
      yield
    rescue => error
      status = "failed"
      error_type = classify_error(error)
      raise
    ensure
      TelemetryHttp.log(
        table: "job_attempt_completed",
        data: {
          job_id: job["jid"],
          job_name: job["class"],
          queue_name: queue,
          attempt: job.fetch("retry_count", -1) + 2,
          status: status,
          duration_ms: ((Process.clock_gettime(Process::CLOCK_MONOTONIC) - started_at) * 1000).round,
          error_type: error_type,
          release: ENV["APP_RELEASE"]
        }
      )
    end
  end
end

Event schema

job_id, job_name, queue_name, status, and attempt

queue_wait_ms, duration_ms, error_type, retry_exhausted, and release

item_count or approved account context derived by the job, never serialized arguments

Check your setup

Checkpoint 1

Wrap yield in server middleware so each execution attempt has one outcome; use jid as the logical identifier and retry_count plus one as the attempt.

Checkpoint 2

Do not rescue without re-raising because Sidekiq must observe the exception to apply its retry policy.

Checkpoint 3

If you log each attempt, count final successes and exhausted retries separately so retries do not inflate job totals.

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.

sidekiq-verification

Sidekiq job telemetry verification query

sql

SELECT *
FROM job_attempt_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.

Ruby HTTP integration Queue worker guide Retry-storm SQL Sidekiq middleware Sidekiq error handling

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.

Async reliability11 fields