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

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

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

Classifying failures and using controlled retries in Kafka prevents outages.

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

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

Timeouts in distributed systems indicate suspicion, not confirmed failure.

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

You can update Elasticsearch indices without downtime using alias switching.

Kafka uses different strategies to assign partitions to consumers in a group efficiently.

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