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Request-Response asks for a result, while Events notify that something has happened.

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

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

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

Queues distribute tasks to one consumer, while Pub/Sub broadcasts events to multiple subscribers.

2-Phase Commit helps maintain data consistency in transactions across multiple databases.

Graceful degradation allows apps to function partially during service failures.

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

Vector clocks help track the order and concurrency of events in distributed systems.

Message queues allow services to communicate asynchronously, improving scalability and reliability.

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

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

Older offsets can overwrite newer ones in Kafka if not handled properly.

The Bulkhead Pattern isolates resources to protect critical workloads from failures.

FAANG interviewers evaluate problem understanding, architecture, scalability, and communication skills.

An API Gateway simplifies client access to backend services in microservices.

Distributed backpressure helps manage the flow of work between services to prevent overload.

Backpressure prevents system overload by managing message processing rates in Kafka.

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

Crash failures stop a service, while network failures disrupt communication.

Backpressure helps manage message flow in Kafka during traffic spikes.

Kafka uses retry topics and delayed retries to manage message failures efficiently.

Elasticsearch distributes search queries across shards to find and retrieve results quickly.

Synchronous communication waits for a response, while asynchronous continues without waiting.

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

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

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

Monolithic and microservices architectures each have unique advantages and challenges for software development.

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

Network partitions occur when servers are operational but can't communicate, affecting system performance.

Microservices are useful when you need independent scaling, deployment, and clear boundaries in software design.

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

The CAP Theorem explains the trade-offs in distributed systems during network failures.

Transactions ensure database operations are reliable using ACID properties.

Choosing between a shared database and a database per service affects system design significantly.

Message delivery semantics define how messages are sent in distributed systems and handle failures.

REST, RPC, and gRPC are different methods for communication in software systems.