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The retry pattern helps systems recover from temporary failures but can cause overload if misused.

A timeout indicates a deadline was exceeded, not necessarily a failure.

The Transactional Outbox Pattern ensures database updates and event publishing are synchronized to avoid losing events.

The Bulkhead Pattern isolates resources to protect critical workloads from failures.

Timeouts in distributed systems indicate suspicion, not confirmed failure.

Exponential backoff helps manage retries by increasing wait times to reduce system overload.

Jitter helps spread out client retries to avoid traffic spikes.

Kafka Streams uses tumbling and hopping windows for time-based data aggregation.

A Circuit Breaker helps prevent system failures by stopping calls to unhealthy services.

Cache invalidation is about knowing when to refresh cached data.

Cache stampede occurs when many requests hit the database due to a cache miss.

The Circuit Breaker pattern controls service calls to prevent failures from spreading.

Connection pooling reuses database connections but can cause issues if misconfigured.

Kafka's commitSync waits for confirmation, while commitAsync continues immediately.

Microservices can communicate using five key patterns based on their needs.

Kafka uses heartbeats and timeouts to check if consumers are alive.