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

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

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

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

Graceful degradation allows apps to function partially during service failures.

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

Availability is about access; reliability is about correct performance.

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

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

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

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

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

The retry pattern helps systems recover from temporary failures but can cause overload if misused.

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

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

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

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

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

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

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

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

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

Latency, throughput, and response time are key metrics in system performance.

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

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

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

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

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

SLIs measure service performance, SLOs set reliability targets, and SLAs are customer agreements.

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

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

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

Alerting helps notify the right people about production issues quickly.

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

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

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

Timeouts in distributed systems indicate suspicion, not confirmed failure.

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

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

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

In distributed systems, timestamps don't always reflect the true order of events.

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

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

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

Logs, metrics, and traces help engineers debug issues in software systems.

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

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.

Cascading failures occur when one service's failure impacts others, causing widespread issues.

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

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

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

Latency is the time for one request, while throughput is how many requests are processed.

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

Transactions ensure database operations are reliable using ACID properties.

Fail-stop means a system stops and stays down, while fail-recover means it can come back but needs to be ready.

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

DNS helps microservices find each other, but it has limitations that may require a service registry.

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

Load shedding helps systems reject excess requests to maintain performance during high demand.