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Performance & Caching at Scale
Connection Backpressure
Tune HTTP clients, database pools, worker limits, queues, and timeouts to prevent overload.
What Is Backpressure
Backpressure propagates overload signals from a saturated component to its callers. Without backpressure, a slow database causes goroutine accumulation, memory exhaustion, and cascading failure. Limits and timeouts create backpressure.
HTTP Client Limits
Database Pool Limits
Worker Limits
Queue Backpressure
Message queues provide natural backpressure. Producers block when the queue is full. Consumers process at their own pace. This smooths out traffic spikes.
- Set queue size limits to bound memory usage.
- Use blocking publishes to create backpressure on producers.
- Monitor queue depth to detect processing bottlenecks.
- Use dead-letter queues for messages that cannot be processed.
Timeout Strategy
Without timeouts, a slow database or API call holds a goroutine indefinitely. Under load, this exhausts goroutines and crashes the server. Every outbound call needs a timeout.
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