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Token Bucket allows burst traffic, while Leaky Bucket smooths out traffic flow.

Classifying failures and using controlled retries in Kafka prevents outages.

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

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

L4 and L7 load balancers differ in how they route network traffic based on layers of the OSI model.

Backpressure helps manage message flow in Kafka during traffic spikes.

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

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

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

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

Alerting helps notify the right people about production issues quickly.