Any concept.
clear in 60 seconds.

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.

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.

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.

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.

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.

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

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

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

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.

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.

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.

Distributed tracing helps track requests across microservices to find delays.

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

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

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

Timeouts in distributed systems indicate suspicion, not confirmed failure.

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

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