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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

DNS resolution translates a URL into an IP address for web access.

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

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

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

Scaling databases involves deciding whether to enhance read or write capabilities based on traffic patterns.

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

Redis is a fast in-memory data store used for caching and low-latency applications.

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

Database replication helps keep data available and allows systems to handle more read requests.

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

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

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

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.

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

Graceful degradation allows apps to function partially during service failures.

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

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

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

Distributed tracing helps track requests across microservices to find delays.

You can replay Kafka events safely by separating live and replay processes.

HTTPS is a secure version of HTTP that encrypts data for safety.

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

Consistent hashing helps distribute data across servers with minimal movement.

HTTP methods tell the server what to do, and status codes tell us the result.

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

Apache Kafka is a system for managing large volumes of events efficiently.

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

Timeouts in distributed systems indicate suspicion, not confirmed failure.

Kafka uses brokers for data handling and KRaft controllers for metadata management.

Connection pooling reuses database connections but can cause issues if misconfigured.

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

Log replication ensures data consistency by requiring majority acknowledgment before committing changes.

Database isolation levels determine how transactions interact and affect data consistency.