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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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