Table: oci_core_instance_metric_cpu_utilization_hourly - Query OCI Core Instance Metrics using SQL
Oracle Cloud Infrastructure (OCI) Core instances provide secure, isolated compute environments for applications. They support a wide range of workloads and offer robust performance. CPU Utilization Metrics provide insights into the CPU usage of these instances, helping in performance monitoring and optimization.
Table Usage Guide
The oci_core_instance_metric_cpu_utilization_hourly
table provides insights into the CPU utilization of OCI Core instances on an hourly basis. As a system administrator or DevOps engineer, you can use this table to monitor CPU usage trends, identify potential performance bottlenecks, and make informed decisions about resource allocation and scaling. This table is particularly useful for maintaining optimal performance and ensuring efficient use of resources in your OCI environment.
Examples
Basic info
Explore the performance of your OCI core instances by analyzing their CPU utilization over time. This allows you to understand usage patterns and potentially optimize resource allocation.
select id, timestamp, minimum, maximum, average, sample_countfrom oci_core_instance_metric_cpu_utilization_hourlyorder by id, timestamp;
select id, timestamp, minimum, maximum, average, sample_countfrom oci_core_instance_metric_cpu_utilization_hourlyorder by id, timestamp;
CPU Over 80% average
Analyze the settings to understand instances where the CPU usage exceeds 80% on average. This can help in identifying potential performance issues and optimizing resource allocation.
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_countfrom oci_core_instance_metric_cpu_utilization_hourlywhere average > 80order 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_countfrom oci_core_instance_metric_cpu_utilization_hourlywhere average > 80order by id, timestamp;
Query examples
Schema for oci_core_instance_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. | |
compartment_id | text | The ID of the compartment. | |
id | text | The OCID of the instance. | |
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_core_instance_metric_cpu_utilization_hourly