Dapr v1.18.1

This patch release focuses heavily on the stability and reliability of the Dapr Workflow engine. It resolves critical issues where sidecars could become unresponsive after configuration changes, workflows could indefinitely hang during complex state transitions, and memory leaks occurred during repeated event waiting. It also optimizes sidecar lifecycle management in Kubernetes to prevent unnecessary restarts.

Fix memory leaks in workflows awaiting repeated events — Prevents long-running workflows from leaking memory and avoids 'spurious wake-ups' caused by outdated timers. This ensures that workflows awaiting the same event name repeatedly remain stable and don't trigger unnecessary activities.

Prevent workflow sidecar deadlocks during configuration reloads — Eliminates a critical bug where updating your Dapr configuration could permanently break workflow execution until a manual pod restart. This significantly improves the reliability of Day 2 operations and automated config updates.

Suppressed unnecessary sidecar restarts on Kubernetes resyncs — Reduces unnecessary CPU churn and transient connection drops by stopping sidecars from restarting when the Kubernetes Operator performs routine synchronization tasks that include no actual changes.

Resolved indefinite hangs in workflows using ContinueAsNew — Ensures that parent workflows don't 'hang' or freeze when a child process completes across a boundary where the parent has restarted its state (ContinueAsNew). This is vital for long-lived, agent-like workflows.

Restore workflow concurrency limits for Helm installations — Ensures that performance-tuning settings for workflows—like limiting how many run at once—are actually respected when Dapr is deployed via Helm. Previously, these settings were silently ignored by Kubernetes.