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Буллеты про очереди, фоновые задачи, планировщики, асинхронную надёжность, webhooks и внешние доставки.

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Брокеры сообщений

• Built RabbitMQ topic exchanges routing X message types across X services at Xk msg/sec.
• Introduced dead-letter exchanges with X-attempt retry and exponential backoff, recovering X% of failed messages.
• Cut queue backlog from X million to zero by parallelising consumers and raising prefetch to X.
• Replaced RabbitMQ with NATS JetStream for X internal flows, cutting p99 delivery latency from Xms to Xms.
• Configured quorum queues across X nodes, eliminating message loss during broker failover.
• Built priority queues separating X latency-critical flows from bulk work, holding critical p95 at Xms under load.
• Migrated X queues to Amazon SQS with FIFO and deduplication, cutting broker operations toil X hours/week.
• Implemented visibility-timeout tuning and heartbeat extension, removing X duplicate-processing incidents per month.
• Built a message router fanning X inbound events to X consumer groups with per-consumer failure isolation.
• Reduced broker memory pressure X% by capping queue length and offloading overflow to object storage.

Фоновые воркеры

• Built a worker pool processing X jobs/day with bounded concurrency of X and graceful shutdown draining in Xs.
• Cut job processing time from Xmin to Xs by batching X database writes and parallelising I/O-bound stages.
• Implemented at-least-once job execution with idempotency keys, eliminating X duplicate-side-effect defects.
• Built a retry policy with jittered exponential backoff across X job types, cutting downstream thundering herds X%.
• Introduced per-tenant fairness scheduling, preventing X noisy-tenant incidents from starving other customers.
• Added job-level timeouts and cancellation, freeing X% of worker capacity previously lost to hung tasks.
• Built a job dashboard exposing throughput, failure rate and age per queue, cutting incident detection from Xh to Xmin.