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

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

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

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

Graceful degradation allows apps to function partially during service failures.

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

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

The CAP Theorem explains the trade-offs in distributed systems during network failures.

Availability is about access; reliability is about correct performance.

Raft's safety rules guarantee that committed entries are preserved even after leader failures.

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

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

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

Network partitions occur when servers are operational but can't communicate, affecting system performance.

Timeouts in distributed systems indicate suspicion, not confirmed failure.

Classifying failures and using controlled retries in Kafka prevents outages.

Elasticsearch uses shards for data distribution and replicas for redundancy.

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

Alerting helps notify the right people about production issues quickly.

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

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.

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

Redis is a fast in-memory data store used for caching and low-latency applications.

2-Phase Commit helps maintain data consistency in transactions across multiple databases.