docs/release_notes/v1.12.3.md
This update includes bug fixes:
In HTTP service invocation, in certain cases when a resiliency policy is applied (for example, one that includes timeouts), requests could be interrupted earlier with a "context deadline exceeded" error.
Impacts users running Dapr 1.12.0-1.12.2 that use HTTP service invocation and who have resiliency policies applied
When resiliency policies with timeouts are applied, due to a bug the incorrect context was used while sending the response to the client, and in certain situations it could have been terminated earlier than the request.
We fixed the code that handles HTTP service invocation to make sure the timeout is applied to the entire response.
Placement nodes acquire a lock, disseminate the tables, and release the lock in parallel. The Placement stream disconnects before the dissemination of tables.
Error invoke actor method: failed to invoke target x after 3 retries
Placement server logs:
level=error msg="Stream is disconnected before member is added
Impacts users running Dapr 1.12.0-1.12.2
Dissemination did not use a background context. The logic to acquire a lock, disseminate the tables, and release the lock were all occurring in parallel.
Updated the Dapr Placement service to use a background context and follow a 3 step process to acquire a lock, disseminate the tables, and release the lock.
When using a database with a case-sensitive collation, the SQL Server state store component did not work correctly. Certain operations, including those relied upon by the actor state store, were failing.
Impacts users of Dapr 1.11.0-1.12.2
A stored procedure referenced a column named with the wrong case. This was causing errors on case-sensitive databases.
We updated the stored procedure so it does use the correct case for column names.
When using Dapr with Kafka for Pub/Sub and subscribing to multiple topics, users might see bottlenecks in Kafka message processing and long init times when the Dapr sidecar is starting up.
Impacts users of Dapr 1.11.0-1.12.2
When new topic subscriptions were added, Dapr would close the consumer group and recreate it, leading to partition rebalance across the cluster.
The Kafka consumer logic was changed to not recreate the consumer group every time a new topic subscription is added.