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Kafka uses state stores to remember previous events in stateful stream processing.

Partition pruning helps databases skip unnecessary data scans, speeding up queries.

Transactions ensure database operations are reliable using ACID properties.

Kafka can help ensure messages are processed once, but requires careful design.

REST API design focuses on creating clean, efficient, and scalable web services.

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

Search engines collect, index, retrieve, and rank documents to provide relevant results.

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

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

Cache penetration occurs when requests for non-existent data overload the database.

Optimistic and pessimistic locking are strategies to manage database access during concurrent transactions.

Kafka consumer reprocessing involves safely replaying events to correct system states.

Database bottlenecks slow down performance, but identifying them helps optimize and scale effectively.

The choice between SQL and NoSQL databases depends on your application's specific needs.

Idempotency ensures that repeated operations in APIs do not cause duplicate effects.

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

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