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

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

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

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

High Availability ensures your application remains operational even during server failures.

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

Data residency is crucial for compliance with laws about where data can be stored.

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

Fault domains help prevent multiple servers from failing together in an architecture.

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

A single component's failure can take down your entire application, even with redundancy.

Availability is about access; reliability is about correct performance.

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

Database replication enhances data availability and read performance but has challenges like replication lag.

Timeouts in distributed systems indicate suspicion, not confirmed failure.

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

Classifying failures and using controlled retries in Kafka prevents outages.

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.