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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.

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

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

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

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

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

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

Graceful degradation allows apps to function partially during service failures.

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

gRPC allows efficient communication between services using a structured request-response model.

Stateless servers are easier to scale because they don't store user session data locally.

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

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

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

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

Dependency failures can disrupt applications, but resilience patterns can help manage them.

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

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

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

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

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

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

gRPC supports four communication patterns: Unary, Server Streaming, Client Streaming, and Bidirectional Streaming.

Protobuf schema evolution requires careful changes to avoid breaking existing clients.

Service Discovery helps microservices locate each other dynamically without fixed IP addresses.

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

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

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

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

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.

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

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

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

Availability is about access; reliability is about correct performance.