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

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

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

Choose Elasticsearch for complex text searches, but use databases for structured queries.

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

HLD provides an overview of system architecture, while LLD details implementation specifics.

FAANG engineers use high-level design principles to create scalable systems.

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

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

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

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

Choosing the right boundaries for microservices is crucial for effective architecture.

Database replication helps keep data available and allows systems to handle more read requests.

Microservices and modular monoliths differ mainly in deployment and communication methods.

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

Functional requirements define what a system does, while non-functional requirements define how it performs.

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