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

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

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

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

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

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

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

Data residency is crucial for compliance with laws about where data can be stored.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Kafka Schema Evolution allows safe changes to message structures without breaking existing consumers.

CDC with Kafka allows real-time updates from databases to multiple services.

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

Availability is about access; reliability is about correct performance.

Cache breakdowns can overwhelm databases, but request coalescing solves this issue.

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

Container data can be lost unless stored in persistent volumes.

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

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

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

Global failover ensures applications remain available by redirecting traffic from failed regions to functioning ones.