Telemetry
Integration guide

Sidekiq Job Telemetry

Track Sidekiq execution outcomes, attempts, queue wait, errors, and releases from server middleware without copying job arguments.

Reviewed by the Telemetry product team on . Instrumentation contract, privacy boundaries, and implementation guidance. Review standards and ownership

Useful for
  • Sidekiq retry monitoring
  • Queue latency analysis
  • Background job reliability
Implementation evidence

Sidekiq Job Telemetry: from boundary to verified row

Use Sidekiq Job Telemetry at a controlled application boundary, keep the event contract small, and verify a known outcome before building aggregate views.

  1. 1

    Choose the outcome

    Sidekiq retry monitoring

  2. 2

    Define the contract

    job_id, job_name, queue_name, status, and attempt

  3. 3

    Instrument the boundary

    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. 4

    Verify the evidence

    Exercise a known fixture, then inspect job_attempt_completed for one correctly typed terminal row.

Before you start

Prerequisites and boundaries

  • 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.

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

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 contract

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

Implementation checkpoints

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 events are emitted per attempt, build terminal-success and retry-exhaustion metrics explicitly 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.

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.

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.

Related product capability

Continue this workflow in Alerts

Promote the reviewed reliability query into an owned threshold and response workflow.

Related SQL recipes

Answer the next question with SQL

Run the query against the structured fields from this workflow, inspect the example result, and turn a useful answer into a dashboard or alert.

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