Table: oci_database_autonomous_db_metric_cpu_utilization - Query OCI Database Autonomous DB Metric CPU Utilization using SQL

An Autonomous DB Metric CPU Utilization is a resource in Oracle Cloud Infrastructure's (OCI) Database service. It provides metrics related to the CPU utilization of autonomous databases within an OCI environment. These metrics can be used to monitor the performance and efficiency of the databases, helping to identify any potential issues or areas for improvement.

Table Usage Guide

The oci_database_autonomous_db_metric_cpu_utilization table provides insights into the CPU utilization of autonomous databases within the OCI Database service. As a Database Administrator, explore database-specific details through this table, including CPU utilization, average active sessions, and associated metadata. Utilize it to uncover information about autonomous databases, such as those with high CPU utilization, the performance of the databases, and the efficiency of resource usage.

Examples

Basic info

Explore the performance of your autonomous databases by analyzing their CPU utilization metrics. This query helps you assess the minimum, maximum, and average CPU usage over time, allowing you to optimize resources and improve database performance.

select
  id,
  timestamp,
  minimum,
  maximum,
  average,
  sample_count
from
  oci_database_autonomous_db_metric_cpu_utilization
order by
  id,
  timestamp;

select
  id,
  timestamp,
  minimum,
  maximum,
  average,
  sample_count
from
  oci_database_autonomous_db_metric_cpu_utilization
order by
  id,
  timestamp;

CPU Over 80% average

Identify instances where the average CPU utilization exceeds 80% in your autonomous database. This allows you to monitor system performance and manage resources effectively.

select
  id,
  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
  oci_database_autonomous_db_metric_cpu_utilization
where
  average > 80
order by
  id,
  timestamp;

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

Schema for oci_database_autonomous_db_metric_cpu_utilization

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.
compartment_id	text		The ID of the compartment.
id	text		The OCID of the Autonomous Database.
maximum	double precision		The maximum metric value for the data point.
metric_name	text		The name of the metric.
minimum	double precision		The minimum metric value for the data point.
namespace	text		The metric namespace.
region	text		The OCI region in which the resource is located.
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.
sum	double precision		The sum of the metric values for the data point.
tenant_id	text	=, !=, ~~, ~~, !~~, !~~	The OCID of the Tenant in which the resource is located.
tenant_name	text		The name of the Tenant in which the resource is located.
timestamp	timestamp with time zone		The time stamp used for the data point.
unit	text		The standard unit for the data point.

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)" -- oci

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

steampipe_export_oci --config '<your_config>' oci_database_autonomous_db_metric_cpu_utilization