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Virtual metrics in Splunk Infrastructure Monitoring 🔗

The following topic provides an overview of virtual metrics in Splunk Infrastructure Monitoring, list of available virtual metrics, and some current limitations.

Note

Virtual metrics is a beta feature. While in beta, virtual metrics might be periodically updated or removed when new dimensions, such as host.name, are introduced.

About virtual metrics 🔗

When you get data in from different sources such as AWS CloudWatch, Google Cloud Platform, Azure Monitor, and Splunk OpenTelemetry Connector, infrastructure metrics for the same host can vary in naming conventions and value scale. To make it easier for you to find and work with metrics coming in from different sources, Splunk Infrastructure Monitoring pulls data from different sources, transforms them, and returns them in a unified format called virtual metrics.

Virtual metrics remove the complexity of choosing the most appropriate metric source among various available options. With virtual metrics, you can use a generic metric name, such as ^aws.ec2.cpu.utilization, and let Infrastructure Monitoring select the best metric source for each host.

Each virtual metric time series (MTS) has two data sources: a Splunk OpenTelemetry Connector and a public cloud such as AWS, GCP, or Azure. For a single host, if metrics from both sources are present, Infrastructure Monitoring uses data from Splunk OpenTelemetry Connector because it has higher resolution and faster updates.

Virtual metrics power different built-in host navigators, including AWS EC2 navigator, GCP Compute Engine navigator, Azure Virtual Machine navigator, and the My Data Center hosts navigator. You can also use virtual metrics in your custom charts and detectors.

List of virtual metrics 🔗

The following table shows available virtual metrics in Splunk Infrastructure Monitoring:

Virtual metric

Description

^aws.ec2.cpu.utilization

Uses best available data from CPUUtilization (namespace:EC2, stat:mean) from AWS CloudWatch and cpu.utilization from Splunk OpenTelemetry Connector.

^aws.ec2.disk.io.read.total

Uses best available data from DiskReadBytes (namespace:EC2, stat:sum) from AWS CloudWatch and system.disk.io.total (direction:read) from Splunk OpenTelemetry Connector.

^aws.ec2.disk.io.write.total

Uses best available data from DiskWriteBytes (namespace:EC2, stat:sum) from AWS CloudWatch and system.disk.io.total (direction:write) from Splunk OpenTelemetry Connector.

^aws.ec2.disk.ops.read.total

Uses best available data from DiskReadOps (namespace:EC2, stat:sum) from AWS CloudWatch and system.disk.operations.total (direction:read) from Splunk OpenTelemetry Connector.

^aws.ec2.disk.ops.write.total

Uses best available data from DiskWriteOps (namespace:EC2, stat:sum) from AWS CloudWatch and system.disk.operations.total (direction:write) from Splunk OpenTelemetry Connector.

^aws.ec2.network.io.receive.total

Uses best available data from NetworkIn (namespace:EC2, stat:sum) from AWS CloudWatch and system.network.io.total (direction:receive) from Splunk OpenTelemetry Connector.

^aws.ec2.network.io.transmit.total

Uses best available data from NetworkOut (namespace:EC2, stat:sum) from AWS CloudWatch and system.network.io.total (direction:transmit) from Splunk OpenTelemetry Connector.

^azure.vm.cpu.utilization

Uses best available data from Percentage CPU from Azure Monitoring and cpu.utilization from Splunk OpenTelemetry Connector.

^azure.vm.disk.io.read.total

Uses best available data from Disk Read Bytes from Azure Monitoring and cpu.utilization from Splunk OpenTelemetry Connector.

^azure.vm.disk.io.write.total

Uses best available data from Disk Write Bytes from Azure Monitoring and cpu.utilization from Splunk OpenTelemetry Connector.

^azure.vm.disk.ops.read.total

Uses best available data from Disk Read Operations/Sec from Azure Monitoring and cpu.utilization from Splunk OpenTelemetry Connector.

^azure.vm.disk.ops.write.total

Uses best available data from Disk Write Operations/Sec from Azure Monitoring and cpu.utilization from Splunk OpenTelemetry Connector.

^azure.vm.network.io.receive.total

Uses best available data from Network In from Azure Monitoring and cpu.utilization from Splunk OpenTelemetry Connector.

^azure.vm.network.io.transmit.total

Uses best available data from Network Out from Azure Monitoring and cpu.utilization from Splunk OpenTelemetry Connector.

^gcp.gce.cpu.utilization

Uses best available data from instance/cpu/utilization from Google Cloud Monitoring and cpu.utilization from Splunk OpenTelemetry Connector.

^gcp.gce.disk.io.read.total

Uses best available data from instance/disk/read_bytes_count from Google Cloud Monitoring and system.network.io.total from Splunk OpenTelemetry Connector.

^gcp.gce.disk.io.write.total

Uses best available data from instance/disk/write_bytes_count from Google Cloud Monitoring and system.network.io.total from Splunk OpenTelemetry Connector.

^gcp.gce.disk.ops.read.total

Uses best available data from instance/disk/read_ops_count from Google Cloud Monitoring and system.disk.operations.total from Splunk OpenTelemetry Connector.

^gcp.gce.disk.ops.write.total

Uses best available data from instance/disk/write_ops_count from Google Cloud Monitoring and system.disk.operations.total from Splunk OpenTelemetry Connector.

^gcp.gce.network.io.receive.total

Uses best available data from instance/network/received_bytes_count from Google Cloud Monitoring and system.network.io.total from Splunk OpenTelemetry Connector.

^gcp.gce.network.io.transmit.total

Uses best available data from instance/network/sent_bytes_count from Google Cloud Monitoring and system.network.io.total from Splunk OpenTelemetry Connector.

Limitations of virtual metrics 🔗

Virtual metrics have the following limitations:

  • You can’t use non-exact searches on virtual metric names. For example, you can’t query for sf_metric:^aws.ec2.disk.ops.*.total to get both read and write ops.

  • Virtual metric results don’t get a guaranteed boost in results from the Metric Finder. Searching for a substring or full virtual metric name might not show matching virtual metrics.

  • Virtual MTS contains only dimensions that are present on both underlying data sources:

    • For AWS, virtual MTS has dimension AWSUniqueId.

    • For GCP, virtual MTS has dimension gcp_id.

    • For Azure, virtual MTS has dimension azure_resource_id.

  • Virtual metrics support only default rollup and rate rollup.

  • Virtual metric queries don’t support partition filters.