Hi Patel Krishna,
What you’re seeing is consistent with some of the known challenges when stretching cluster sets across multiple large clusters. Metadata synchronization can lag when you have thousands of endpoints, especially if the control plane is under heavy load. This doesn’t usually break functionality, but it can make management tasks feel inconsistent until replication catches up.
For workload mobility, visibility into resource usage is indeed limited in the current orchestration layer. Many administrators work around this by integrating System Center or Azure Arc monitoring to provide clearer insights into CPU, memory, and storage utilization across clusters. Without that, troubleshooting can feel opaque.
Monitoring and alerting across 10+ clusters is another area where gaps exist. Native tools provide basic health checks, but at scale you’ll want to layer in centralized monitoring solutions that can correlate events across all clusters. This helps avoid blind spots when metadata sync delays occur.
I hope the response provided some helpful insight. If you find this answer useful, please hit “accept answer” so I know it addressed your concern.
Jason.