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

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

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

Logs, metrics, and traces help engineers debug issues in software systems.

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

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

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

Dependency failures can disrupt applications, but resilience patterns can help manage them.

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

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

Alerting helps notify the right people about production issues quickly.

Graceful degradation allows apps to function partially during service failures.

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

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

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

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

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

Kafka uses state stores to remember previous events in stateful stream processing.

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

Availability is about access; reliability is about correct performance.

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

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

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

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

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

Stemming and normalization help search engines match various word forms for better results.

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

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

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

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

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

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

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

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

A Circuit Breaker helps prevent system failures by stopping calls to unhealthy services.

Latency, throughput, and response time are key metrics in system performance.

An error budget shows how much downtime is acceptable while meeting reliability goals.

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

Kafka commit strategies determine how offsets are managed during message processing.

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

Observability helps engineers understand system behavior to debug production issues effectively.