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Your queue has 50 million unprocessed messages. Consumers are processing 1,000/second. New messages arrive at 5,000/second. The backlog will never drain. Here''s how queue backlogs form, why they''re dangerous, and the patterns to prevent and recover from them.
Master message queue patterns: SQS FIFO for ordered processing, DLQ setup, Kafka for event streaming with consumer groups, BullMQ for in-process jobs, visibility timeout, deduplication, and backpressure.
You split your MVP into 12 microservices before you had 100 users. Now a simple feature requires coordinating 4 teams, 6 deployments, and debugging across 8 services. The architecture that was supposed to scale you faster is the reason you ship slower than your competitors.
The industry consensus has shifted. Here''s why modular monoliths are winning and when microservices still make sense.
You deploy a migration that runs ALTER TABLE on a 40-million row table. PostgreSQL rewrites the entire table. Your app is stuck waiting for the lock. Users see 503s for 8 minutes. Schema changes on large tables require a completely different approach.