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

The Saga Pattern manages distributed transactions using local transactions and compensating actions.

Microservices can communicate using five key patterns based on their needs.

Kafka Schema Evolution allows safe changes to message structures without breaking existing consumers.

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

A Circuit Breaker helps prevent system failures by stopping calls to unhealthy services.

The Circuit Breaker pattern controls service calls to prevent failures from spreading.

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

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

Elasticsearch offers Data Streams for simplicity and Time-Based Indices for control in managing time-series data.

Backpressure helps manage message flow in Kafka during traffic spikes.

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

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

Elasticsearch index templates automatically apply settings to new indices based on patterns.

Elasticsearch Data Streams simplify time-series data management with one name for many indices.