Table: azure_compute_virtual_machine_metric_cpu_utilization_hourly - Query Azure Compute Virtual Machine Metrics using SQL

Azure Compute is a service within Microsoft Azure that provides scalable and secure virtual machines. It allows users to deploy and manage applications across a global network of Microsoft-managed data centers. Azure Compute provides a variety of virtual machine configurations to handle different workloads and performance requirements.

Table Usage Guide

The azure_compute_virtual_machine_metric_cpu_utilization_hourly table provides insights into the CPU utilization of Azure Compute Virtual Machines on an hourly basis. As a system administrator or DevOps engineer, explore machine-specific details through this table, including CPU usage patterns, peak usage times, and potential performance bottlenecks. Utilize it to monitor and manage resource allocation, ensuring optimal performance and cost-effectiveness of your Azure Compute resources.

Examples

Basic info

Explore the utilization of virtual machine CPU over time to identify patterns or trends. This could help in efficient resource allocation and performance optimization.

select
  name,
  timestamp,
  minimum,
  maximum,
  average,
  sample_count
from
  azure_compute_virtual_machine_metric_cpu_utilization_hourly
order by
  name,
  timestamp;

select
  name,
  timestamp,
  minimum,
  maximum,
  average,
  sample_count
from
  azure_compute_virtual_machine_metric_cpu_utilization_hourly
order by
  name,
  timestamp;

CPU Over 80% average

Determine the areas in which the average CPU utilization exceeds 80% on Azure's virtual machines. This can be useful for identifying potential performance issues and ensuring efficient resource allocation.

select
  name,
  timestamp,
  round(minimum :: numeric, 2) as min_cpu,
  round(maximum :: numeric, 2) as max_cpu,
  round(average :: numeric, 2) as avg_cpu,
  sample_count
from
  azure_compute_virtual_machine_metric_cpu_utilization_hourly
where
  average > 80
order by
  name,
  timestamp;

select
  name,
  timestamp,
  round(minimum, 2) as min_cpu,
  round(maximum, 2) as max_cpu,
  round(average, 2) as avg_cpu,
  sample_count
from
  azure_compute_virtual_machine_metric_cpu_utilization_hourly
where
  average > 80
order by
  name,
  timestamp;

Schema for azure_compute_virtual_machine_metric_cpu_utilization_hourly

Name	Type	Operators	Description
_ctx	jsonb		Steampipe context in JSON form.
average	double precision		The average of the metric values that correspond to the data point.
cloud_environment	text		The Azure Cloud Environment.
maximum	double precision		The maximum metric value for the data point.
minimum	double precision		The minimum metric value for the data point.
name	text		The name of the virtual machine.
resource_group	text		The resource group which holds this resource.
sample_count	double precision		The number of metric values that contributed to the aggregate value of this data point.
sp_connection_name	text	=, !=, ~~, ~~, !~~, !~~	Steampipe connection name.
sp_ctx	jsonb		Steampipe context in JSON form.
subscription_id	text	=, !=, ~~, ~~, !~~, !~~	The Azure Subscription ID in which the resource is located.
sum	double precision		The sum of the metric values for the data point.
timestamp	timestamp with time zone		The time stamp used for the data point.
unit	text		The units in which the metric value is reported.

Export

This table is available as a standalone Exporter CLI. Steampipe exporters are stand-alone binaries that allow you to extract data using Steampipe plugins without a database.

You can download the tarball for your platform from the Releases page, but it is simplest to install them with the steampipe_export_installer.sh script:

/bin/sh -c "$(curl -fsSL https://steampipe.io/install/export.sh)" -- azure

You can pass the configuration to the command with the --config argument:

steampipe_export_azure --config '<your_config>' azure_compute_virtual_machine_metric_cpu_utilization_hourly