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Message delivery is dependent on queuing, so if messages on the compute node(s) haven't completed through the production - especially on the outbound send to the Message Bank.  The Message Bank will only "bank" those messages that have been actually sent to it.  If there are still messages queued in the production, they will remain there in the production queues until those pods are restarted or PreStop hooks are used to allow the POD to have a grace period on container shutdown until all queues are empty.  An Interoperability Production is a stateful set, and the queues are required to support message delivery guarantees.  

Hi David,

We make available a large number of metrics from within the IRIS instance via REST API.  The REST APIs can be used to integrate with Azure Monitor or any other 3rd party monitoring solution that supports REST.  The exact metrics to use will be largely dependent on your application along with specific threshold values.  

As a starting point, I would suggest the following as a minimum:  

  • cpu_usage
  • db_freespace
  • db_latency
  • glo_ref_per_sec
  • glo_update_per_sec
  • jrn_block_per_sec
  • license_percent_used
  • phys_mem_percent_used
  • phys_reads_per_sec
  • phys_writes_per_sec
  • process_count
  • system_alerts_new
  • wd_cycle_time

The metrics collected are agnostic to running in Azure, AWS, or on-prem, so they are useful in any deployment scenario.  Here's a link to the all the standard available metrics and their descriptions within IRIS:

https://docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls?KEY=GCM_rest#GCM_rest_metrics

You can also create application specific metrics.  The details can be found here:

https://docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls?KEY=GCM_rest#GCM_rest_metrics_application

I hope this helps.  

Thanks,
Mark B-

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