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

Secure API design requires multiple strategies to protect sensitive data and access.

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

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

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

A single component's failure can take down your entire application, even with redundancy.

Graceful degradation allows apps to function partially during service failures.

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

Disaster Recovery Testing verifies that your recovery plan works effectively in real situations.

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

Container health checks ensure your app is running and ready to serve users.

Disaster recovery ensures systems can restore services and data after major disruptions.

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

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

Zero Trust Architecture ensures that no user or device is trusted by default.

High Availability ensures your application remains operational even during server failures.

Availability is about access; reliability is about correct performance.

Stream Processing Architecture helps turn incoming events into real-time insights efficiently.

Fault domains help prevent multiple servers from failing together in an architecture.

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

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

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

Distributed backpressure helps manage the flow of work between services to prevent overload.

Failover ensures systems remain operational by managing leader changes during failures.

Active-passive architecture ensures a standby system takes over if the main system fails.

Alerting helps notify the right people about production issues quickly.

Dynamo-style databases are designed for high availability and fault tolerance in distributed systems.

Kubernetes uses a Control Plane to manage Worker Nodes and ensure application reliability.

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

Kubernetes uses Pods, ReplicaSets, and Deployments to manage application availability and updates.

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

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

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

Raft and Paxos are protocols that help computers agree on values in distributed systems.

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

RPO and RTO are key metrics for planning disaster recovery strategies.

Timeouts in distributed systems indicate suspicion, not confirmed failure.

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

Structured logging helps in quickly identifying issues by organizing log data consistently.

Fail-stop means a system stops and stays down, while fail-recover means it can come back but needs to be ready.

Paxos is a protocol that helps distributed systems agree on one value despite failures.

The RED Method helps monitor microservices using Rate, Errors, and Duration metrics.

Cassandra uses a masterless architecture to distribute and replicate data efficiently.

CQRS separates how we change data from how we read data, improving scalability.

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

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

Container data can be lost unless stored in persistent volumes.

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

Kubernetes Ingress allows one entry point for multiple applications, simplifying routing.

Availability Zones help prevent downtime by isolating failures across multiple locations.