* Transactions* This document describes how to support transactions in the domain of workflow engine and subsystems.
The use cases for transactions in workflows is to enable consistency during workflow executions. * Constraints * The constraints for this are related to different types of transaction problems: Workflow transaction execution should be in one single transaction (until idle elements are reached or there are no more elements to process) Process state should be consistent in storage in one single transaction. In the case of database multiple tables should be written in an atomic transaction Reactive code should be removed as it does not behave properly with transactions. Transactions Policy among workflow runtime and subsystems should be consistent in terms of configuration (no subcomponent should start a transaction if there is already one on the go, but they should mandate to be in a transaction) Error handling should still produce an event that can be stored. Subsystems execution should be included during transactions Async execution will spawn its own transaction. * Architecture * The architecture of the solution impacts some areas: Components with reactive that are involved in transaction refactor. So far, the only subsystem using reactive code job service. Process Code generation should change in order to reflect the transactions of the workflow engine Error handling should be modified in a way the error is captured outside the transaction and handled in a different one to avoid event loss. Exchange information among runtime and subsystems should be in a way that those elements are involved in a transaction or they can be rolled back. At the moment the communication is being done with a rest call that is not part of the transaction and cannot be rolled back. Events produced within the transaction should be part of the transaction as well to avoid phantom events (events producing during workflow execution that are sent at the end of the unit of work) * Risk Assessment * The risks identified for this work are the following: Error handling can be problematic depending where we set the boundaries of the transaction. There are two different approaches: Boilerplate code for each task to start / commit / rollback the transaction and deail with error in the rest call tier itself Use the runtime environment to install error handling for doing the operation. Exchange information among systems in a non-transactional way. There are a couple of approaches Install every time a transaction sync listener whenever the rest call is made against the subsystem and doing a compensation when it fails Wrap the rest call in a XAResource that can be enlisted in the transaction. The use of Kafka clients for stream that does not belong to the transactions Wrap with XAResource (Kafka client support transactions, but does not offer XAresource) Install a transaction sync for each transaction. Performance impact with transactions. Different transaction methods in quarkus and spring boot
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