Design Microservices Architecture with Patterns and Principles - Problem Manage Consistency Across Microservices in Dist

The video tutorial discusses the challenges and solutions related to managing consistency across microservices in distributed transactions. It begins with an overview of the current architecture and identifies new problems. The tutorial recaps data management strategies, emphasizing the importance of choosing the right database and separating read and write operations for scalability. It then delves into considerations for distributed transactions, such as achieving consistency and handling service failures. Finally, it presents solutions like the Saga pattern and change data capture principles to manage distributed transactions effectively.

What is the main challenge introduced in the first section regarding microservices?

• Choosing the right database

• Implementing distributed transactions with consistency

• Managing cross-service queries

• Scaling microservices horizontally

Which of the following is a key consideration when performing distributed transactions across microservices?

• Choosing between NoSQL and relational databases

• Ensuring consistency across multiple microservices

• Applying CQRS and event sourcing patterns

• Optimizing query performance with denormalized data

What should be done if a service is down during a distributed transaction?

• Ignore the failure and proceed

• Retry the transaction indefinitely

• Rollback the transaction and run compensating steps

• Switch to a backup service

Which pattern is suggested for managing distributed transactions in microservices?

• CQRS pattern

• Event sourcing pattern

• Materialized view pattern

• Saga pattern

What does CDC stand for in the context of distributed transactions?

• Consistent Data Capture

• Change Data Capture

• Centralized Data Control

• Concurrent Data Collection