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Availability is about access; reliability is about correct performance.

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

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

Load balancers distribute traffic across multiple servers to enhance performance and reliability.

Cache breakdowns can overwhelm databases, but request coalescing solves this issue.

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

Distributed caching spreads data across multiple servers for better performance and reliability.

Timeouts in distributed systems indicate suspicion, not confirmed failure.

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

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

Distributed locks ensure only one server performs a task, avoiding duplication.

Alerting helps notify the right people about production issues quickly.

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

Message queues allow services to communicate asynchronously, improving scalability and reliability.

Elasticsearch uses shards for data distribution and replicas for redundancy.

Elasticsearch aliases allow zero-downtime switching between indices for applications.

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

The Transactional Outbox Pattern ensures database updates and event publishing are synchronized to avoid losing events.

Distributed backpressure helps manage the flow of work between services to prevent overload.

Caching helps applications respond faster by serving data from memory instead of hitting the database.

Vertical scaling means upgrading one server, while horizontal scaling means adding more servers.

A CDN speeds up web applications by caching content closer to users.

The Cache-Aside Pattern speeds up data retrieval by using a cache to store frequently accessed data.

Choosing the right distributed lock depends on your system's needs and existing tools.

You can update Elasticsearch indices without downtime using alias switching.