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

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

The TCP 3-way handshake ensures reliable connection establishment between a client and server.

RPC allows one service to call a function in another service over the network.

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

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

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

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

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

Distributed locks ensure only one server performs a task, avoiding duplication.

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

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

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

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

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

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

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

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

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

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

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

Cache breakdowns can overwhelm databases, but request coalescing solves this issue.

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

A CDN speeds up web applications by caching content closer to users.

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

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

Consistent hashing helps distribute data across servers with minimal movement.

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

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

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

Timeouts in distributed systems indicate suspicion, not confirmed failure.

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