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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.

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

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

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

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

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

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

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

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

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

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

Graceful degradation allows apps to function partially during service failures.

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

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

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

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

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

Availability is about access; reliability is about correct performance.

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

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

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

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

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

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

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

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

Transactions ensure database operations are reliable using ACID properties.

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

Alerting helps notify the right people about production issues quickly.

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

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

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

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

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

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

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