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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Caching helps applications respond faster by serving data from memory instead of hitting the database.

Availability is about access; reliability is about correct performance.

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