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

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

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

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

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

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

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

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

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

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

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

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

Graceful degradation allows apps to function partially during service failures.

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

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

Vertical scaling means upgrading one server, while horizontal scaling means adding more servers.

API Gateway, Proxy, and Load Balancer serve different roles in managing requests and traffic in systems.

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

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

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

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

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

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

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

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

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

A reverse proxy routes client requests to different backend services efficiently.

Load balancers distribute traffic across multiple servers to enhance performance and reliability.

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

Availability is about access; reliability is about correct performance.

Fail Fast means stopping quickly on errors, while Fail Safe ensures safety in failures.

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

Sharding splits databases into smaller parts to improve performance and scalability.

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

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

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

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

Distributed caching spreads data across multiple servers for better performance and reliability.