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

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

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

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

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

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

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

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

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

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.

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

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

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

Availability is about access; reliability is about correct performance.

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

Graceful degradation allows apps to function partially during service failures.

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

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

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

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

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

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

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

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.

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

Elasticsearch uses distributed architecture to search data quickly across multiple servers.

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

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

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

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

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

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

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

ZooKeeper coordinates distributed systems using an ensemble of servers and the ZAB protocol.

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

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

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

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

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

Synchronous replication waits for confirmation from replicas, while asynchronous allows faster writes without waiting.