How to address deadlock issues between microservices in SQL Server during concurrent transactions
I'm migrating some code and Currently developing a set of microservices that heavily interact with a SQL Server 2019 database, and I’ve run into persistent deadlock issues that seem to arise under load. The architecture involves several services concurrently accessing shared resources, and it appears that concurrent updates are leading to deadlock scenarios. In my investigations, I’ve identified that two services, Service A and Service B, frequently attempt to update the same records during a high-traffic period. Here’s a simplified illustration of one of the transactions from Service A: ```sql BEGIN TRANSACTION; UPDATE Orders SET Status = 'Processing' WHERE OrderID = @OrderID; -- Some processing logic COMMIT; ``` While Service B executes a similar transaction: ```sql BEGIN TRANSACTION; UPDATE Orders SET Status = 'Shipped' WHERE OrderID = @OrderID; -- Additional logic COMMIT; ``` To mitigate this, I've tried implementing a retry mechanism within my service clients, but that hasn’t proven effective enough. Adding indexes to the `Orders` table didn't help either, and it seems to just escalate the number of deadlocks observed in the SQL Server logs. The deadlock graph analysis points to a resource contention issue. I’m considering a couple of alternatives: 1. **Optimizing Transaction Scope**: Reducing the locking scope by making the transaction as short as possible. However, I’m unsure how to break down the operations without risking data integrity. 2. **Implementing Explicit Locking**: Using table hints like `UPDLOCK` or `ROWLOCK` to control lock escalation. I’ve read that this could reduce contention but might lead to other performance issues. 3. **Using Snapshot Isolation**: Enabling snapshot isolation to provide a versioned view of the data for readers, which could minimize blocking. Still, I need clarity on how this might affect my service’s transactional consistency. My questions are: What strategies have others implemented to resolve deadlocks in microservices architectures specifically with SQL Server? Are there best practices for transaction management in a concurrent environment that could help reduce these issues? Any insights or examples would be greatly appreciated. I'm working with Sql in a Docker container on Ubuntu 22.04. I appreciate any insights! This is part of a larger web app I'm building.