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API pagination helps manage large datasets by breaking them into smaller parts.

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

Deep pagination in Elasticsearch can slow down searches significantly, but there are efficient methods to handle it.

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

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

Kafka uses retention to keep historical data and compaction to keep the latest state.

Observability helps engineers understand system behavior to debug production issues effectively.

Consistency models determine what data reads in distributed systems can see.

Database per Service ensures each microservice owns its data, reducing dependencies.

Kafka consumers can fetch data in batches to improve throughput and reduce latency.

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