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Disaster recovery ensures systems can restore services and data after major disruptions.

Alerting helps notify the right people about production issues quickly.

Elasticsearch CCR allows real-time data replication for faster disaster recovery.

The RED Method helps monitor microservices using Rate, Errors, and Duration metrics.

Disaster Recovery Testing verifies that your recovery plan works effectively in real situations.

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

Dependency failures can disrupt applications, but resilience patterns can help manage them.

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

Active-passive architecture ensures a standby system takes over if the main system fails.

The dual-write trap in Elasticsearch can cause data inconsistency during reindexing.

Replicas keep your system available, while snapshots allow for data recovery.

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

Late-arriving events can be dropped, updated, or routed based on system needs.

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

Timeouts in distributed systems indicate suspicion, not confirmed failure.

Point-in-Time Recovery allows databases to be restored to a specific moment before data loss.

The USE Method helps find and analyze infrastructure bottlenecks in software systems.