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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.

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

Container data can be lost unless stored in persistent volumes.

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

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

Elasticsearch has different node roles that help manage data and scale clusters effectively.

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

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

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

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

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

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