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

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

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

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

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

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

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

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

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

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

Elasticsearch CCR allows real-time data replication for faster disaster recovery.

Cascading failures occur when one service's failure impacts others, causing widespread issues.

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

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

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

Graceful degradation allows apps to function partially during service failures.

The Saga Pattern manages distributed transactions using local transactions and compensating actions.

Queues distribute tasks to one consumer, while Pub/Sub broadcasts events to multiple subscribers.

Request-Response asks for a result, while Events notify that something has happened.

Crash failures stop a service, while network failures disrupt communication.

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

Quorum Reads ensure data consistency by querying multiple replicas in distributed systems.

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

A Circuit Breaker helps prevent system failures by stopping calls to unhealthy services.

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

The Circuit Breaker pattern controls service calls to prevent failures from spreading.

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

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

Kafka uses retry topics and delayed retries to manage message failures efficiently.

Synchronous communication waits for a response, while asynchronous continues without waiting.

Kafka uses different strategies to assign partitions to consumers in a group efficiently.

Older offsets can overwrite newer ones in Kafka if not handled properly.

Redis is a fast in-memory data store used for caching and low-latency applications.

Backpressure helps manage message flow in Kafka during traffic spikes.

Kafka rebalance can lead to lost or duplicated work if not handled carefully.