PostgreSQL on Azure Flexible metrics and alerts

This documentation contains a list of metrics and alerts that are available when monitoring PostgreSQL on Azure Flexible Server.  Send us feedback if there are additional metrics or alerts you'd find valuable. 

If you can't find a specific metric or alert you would like to use when monitoring your Azure Flexible instances, send us feedback.

Metrics

The following lists the metrics Redgate Monitor collects and exposes on the Analysis page:

Host machine metrics

To get access to host machine metrics for Azure Flexible Server, you need to set up authentication with the Azure metrics API. You can find out more about how to set it up in our guide on enabling advanced monitoring for Azure Flexible Server.

These are the metrics that are queried from the Azure Monitor API:

  • Machine: processor time
  • Machine: memory used
  • Network utilization
  • Disk used
  • Disk read bytes/sec
  • Disk write bytes/sec
  • Disk throughput bytes/sec
  • Disk transfers/sec

PostgreSQL metrics 

Available at the instance level as an aggregate, and at the individual database level:

  • Number of connections
  • Transactions committed / rolled back 
  • Query overflow to temp data bytes sec
  • Block write time
  • Block read time
  • Transactions committed / second 
  • Transactions rolled back / second 
  • Deadlocks / sec
  • Cache hit ratio 

Alerts

The following is a list of alerts available for PostgreSQL on Azure Flexible Server:

  • PostgreSQL specific alerts
    • Configuration change
    • Database unavailable
    • Internal Redgate Monitor error (instance)
    • Long-running query
    • Long-running transaction
    • Long-running idle transaction
    • Monitoring error (data collection)
    • Monitoring stopped (credentials)
    • Instance unreachable
    • Low cache hit ratio
  • Host machine alerts (requires advanced monitoring enabled with Azure API credentials)
    • Disk space
    • Internal Redgate Monitor error (host)
    • Monitoring error (host machine data collection)
    • Monitoring stopped (host machine credentials)
    • Physical memory
    • Processor under-utilization
    • Processor utilization

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