How do you manage concurrency at the Saga level?
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what is saga in microservices Informational
- How do you maintain backward compatibility when making changes to Sagas? What are some common use cases where the Saga pattern is particularly well-suited?
- What are the trade-offs between these different retry strategies?
- How do you configure retry policies for different types of failures? How does the Saga pattern handle the need for integrating with caching mechanisms to improve the performance and reduce the load on microservices involved in a Saga?
- Can you use a state machine to model the lifecycle of a Saga?
- How do teams collaborate on the design and implementation of Sagas that span multiple services?
- What are some common patterns for managing local transactions in microservices?
- How do you manage concurrency at the Saga level?
- How can these vulnerabilities be mitigated? How does the Saga pattern handle the need for supporting different approaches to handling the rollback or compensation of a distributed transaction that has partially completed, especially in scenarios where some steps have succeeded and others have failed?
- How do you prevent data corruption due to concurrent Saga executions? How does the Saga pattern integrate with different messaging technologies, such as Kafka, RabbitMQ, or message brokers?
- What are some auto-scaling strategies for microservices? How does the Saga pattern handle the need for supporting different approaches to handling data migration or schema changes in microservices that participate in long-running Sagas, ensuring that in-flight transactions are not disrupted?
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