Any concept.
clear in 60 seconds.

Classifying failures and using controlled retries in Kafka prevents outages.

Fallbacks allow systems to handle failures safely and maintain user experience.

Timeouts in distributed systems indicate suspicion, not confirmed failure.

Fail Fast means stopping quickly on errors, while Fail Safe ensures safety in failures.

Graceful degradation allows apps to function partially during service failures.

Alerting helps notify the right people about production issues quickly.

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

Kafka uses Dead Letter Topics to handle messages that repeatedly fail processing.

Crash failures stop a service, while network failures disrupt communication.

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

Cascading failures occur when one service's failure impacts others, causing widespread issues.

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

Kafka uses retry topics and delayed retries to manage message failures efficiently.

An error budget shows how much downtime is acceptable while meeting reliability goals.

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

Cache breakdowns can overwhelm databases, but request coalescing solves this issue.

Graceful shutdown in Kafka ensures no data loss during consumer termination.

HTTP methods tell the server what to do, and status codes tell us the result.

Backpressure helps manage message flow in Kafka during traffic spikes.

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

Failover ensures systems remain operational by managing leader changes during failures.

Cache penetration occurs when requests for non-existent data overload the database.