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

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

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

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

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

Partial failure means some services fail while others keep running, impacting system reliability.

Database replication helps keep data available and allows systems to handle more read requests.

Availability is about access; reliability is about correct performance.

The retry pattern helps systems recover from temporary failures but can cause overload if misused.

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.

Retry storms occur when too many retries overload a failing service.

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

Kafka uses retries and Dead Letter Queues to manage message processing failures.

Kafka uses replication and in-sync replicas to ensure data is always available.

Timeouts in distributed systems indicate suspicion, not confirmed failure.

Classifying failures and using controlled retries in Kafka prevents outages.

Kafka allows safe message reprocessing by resetting consumer positions without altering data.

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

Elasticsearch uses shards for data distribution and replicas for redundancy.

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.

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