Opinionated conventions for building reliable background job queues and workers.
# Background Jobs taste of a backend reliability engineer - Make every job idempotent so a retry or duplicate delivery never charges a card or sends an email twice. Confidence: 0.95 - Pass IDs in the job payload and load fresh data inside the worker instead of serializing whole records. Confidence: 0.90 - Enqueue jobs in the same database transaction as the write that triggers them, using an outbox table or a Postgres-backed queue. Confidence: 0.85 - Prefer a boring, well-supported queue such as Sidekiq, BullMQ, Celery or a Postgres queue like Graphile Worker over a home-grown one. Confidence: 0.80 - Retry with exponential backoff and jitter, and cap attempts so poison jobs end up in a dead letter queue. Confidence: 0.95 - Classify errors as retryable or permanent and fail permanent ones immediately instead of burning retries. Confidence: 0.85 - Set an explicit timeout on every job and on every network call it makes. Confidence: 0.90 - Keep jobs small and short, and split long batch work into chunks that can resume from a checkpoint. Confidence: 0.85 - Use separate queues for latency-sensitive and bulk work so a backfill never delays password reset emails. Confidence: 0.90 - Rate limit jobs that call third-party APIs per provider, not per worker process. Confidence: 0.80 - Use unique job keys or locks to prevent the same scheduled job from running twice at once. Confidence: 0.85 - Run cron-style schedules from one scheduler with leader election, never from every app instance. Confidence: 0.80 - Version job payloads and keep workers able to read the previous version during deploys. Confidence: 0.80 - Handle SIGTERM gracefully: stop taking new jobs, finish or requeue the current one, then exit. Confidence: 0.90 - Log a job ID, attempt number and correlation ID on every log line from a job. Confidence: 0.85 - Alert on queue depth, oldest job age and dead letter growth, not just on worker crashes. Confidence: 0.90 - Give the dead letter queue an owner and a documented replay command. Confidence: 0.75 - Test jobs by calling the handler directly in unit tests and run one end-to-end test through the real queue in CI. Confidence: 0.80 - Avoid chaining many jobs into hidden workflows; reach for a workflow engine like Temporal when steps need orchestration. Confidence: 0.70 - Store job results and side-effect markers in the database, not only in the queue backend. Confidence: 0.75
Reviews PostgreSQL and MySQL schema migrations (raw SQL or ORM-generated) for table locks, rewrites, data loss, and breaking changes, then proposes safe zero-downtime rewrites with a clear verdict.
Designs and implements AWS cloud architectures with focus on Well-Architected Framework, cost optimization, and security. Use when: 1. Designing or reviewing AWS infrastructure architecture 2. Migrating workloads to AWS or between AWS services 3. Optimizing AWS costs (right-sizing, Reserved Instances, Savings Plans) 4. Implementing AWS security, compliance, or disaster recovery 5. Troubleshooting AWS service issues or performance problems
Reviews bash and POSIX sh scripts before they run in CI, cron or production. Flags missing strict mode, rm -rf on variables that may be empty, curl piped to a shell, eval, unquoted expansions, unchecked cd, parsing ls, chmod 777, hardcoded secrets, predictable /tmp files, ssh eating a read loop, masked exit codes and bashisms under /bin/sh, then returns a fixed script. Includes a stdlib Python linter with --self-test.
Explains every line of a .gitignore, tests it against paths that must be ignored or must stay committable, names the rule that decides each path, and flags mistakes such as negations blocked by an excluded parent folder, inline comments, leading spaces, backslashes, stray **, secrets not covered and .env.example ignored. Returns a fixed file. Includes a stdlib Python checker with --self-test, matched against real git.
