Any concept.
clear in 60 seconds.

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.

SSRF is a vulnerability where an attacker tricks a server into making unintended requests.

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.

Request-Response asks for a result, while Events notify that something has happened.

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

RPO and RTO are key metrics for planning disaster recovery strategies.

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

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

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

Choosing between single and multi-region architecture affects system resilience and cost.

CSRF tricks your browser into making requests without your consent.

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

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

Active-Active Architecture uses multiple regions to serve traffic simultaneously for better resilience.

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.

RPC allows one service to call a function in another service over the network.

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.

Load shedding helps systems reject excess requests to maintain performance during high demand.

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