Introdução

Microservices no Azure requerem sophisticated data management strategies para handle distributed transactions, eventual consistency e data synchronization across service boundaries.

Conceito-chave

Distributed Data Management: Implementation de patterns como Saga, CQRS e Event Sourcing para manage data consistency e transactions across microservices boundaries without sacrificing autonomy.

Tópicos Relevantes

• Saga pattern para distributed transactions
• CQRS para read/write separation
• Event sourcing para audit trail
• Eventually consistent data models
• Service data ownership

Exemplo Prático

E-commerce platform com Order service, Payment service e Inventory service usando Saga pattern para coordenar transactions, Event Hub para event propagation e Cosmos DB para eventual consistency.

Benefícios

• Service autonomy maintained
• Data consistency assured
• Transaction integrity preserved
• Scalability per service
• Resilience improved