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Choosing between single and multi-region architecture affects system resilience and cost.

Active-Active Architecture uses multiple regions to serve traffic simultaneously for better resilience.

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

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

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

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

Containers share the host OS kernel, while VMs virtualize hardware with separate OS.

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.

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

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

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

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

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

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

OLTP handles transactions while OLAP is for data analysis and reporting.

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

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

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

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.

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

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

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

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

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

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

DNS resolution translates a URL into an IP address for web access.

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

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

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

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

Availability is about access; reliability is about correct performance.

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

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

2-Phase Commit helps maintain data consistency in transactions across multiple databases.

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

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

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

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

Message queues allow services to communicate asynchronously, improving scalability and reliability.

Authentication verifies who you are, while authorization determines what you can do.