steampipe plugin install aws

Table: aws_redshift_cluster_metric_cpu_utilization_daily - Query AWS Redshift Cluster Metrics using SQL

The AWS Redshift Cluster is a fully managed, petabyte-scale data warehouse service in the cloud. It allows you to analyze all your data using your existing business intelligence tools. The CPU Utilization metric provides the percentage of CPU utilization for the Amazon Redshift cluster.

Table Usage Guide

The aws_redshift_cluster_metric_cpu_utilization_daily table in Steampipe gives you information about the CPU utilization metrics for AWS Redshift clusters, calculated on a daily basis. This table allows you, as a data engineer or administrator, to query CPU usage details, including maximum, minimum, average, and sample count values. You can utilize this table to gather insights on cluster performance, such as identifying clusters with high CPU usage, tracking CPU usage trends over time, and optimizing cluster configurations for better performance. The schema outlines the various attributes of the CPU utilization metrics, including the cluster identifier, region, timestamp, and the aforementioned statistical values.

The aws_redshift_cluster_metric_cpu_utilization_daily table provides you with metric statistics at 24-hour intervals for the last year.

Examples

Basic info

Analyze the daily CPU utilization patterns of your AWS Redshift clusters to understand their performance and resource usage trends. This information can help optimize resource allocation and improve overall system efficiency.

select
cluster_identifier,
timestamp,
minimum,
maximum,
average,
sample_count
from
aws_redshift_cluster_metric_cpu_utilization_daily
order by
cluster_identifier,
timestamp;
select
cluster_identifier,
timestamp,
minimum,
maximum,
average,
sample_count
from
aws_redshift_cluster_metric_cpu_utilization_daily
order by
cluster_identifier,
timestamp;

CPU Over 80% average

Determine the areas in which your AWS Redshift clusters are experiencing high CPU utilization, specifically where the average daily usage exceeds 80%. This can help in identifying potential performance issues and planning for capacity upgrades.

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

CPU daily average < 2%

This example helps to identify instances where the average daily CPU utilization is less than 2% in your AWS Redshift clusters. This can be useful to pinpoint underutilized resources, potentially leading to cost savings by downsizing or eliminating these clusters.

select
cluster_identifier,
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
aws_redshift_cluster_metric_cpu_utilization_daily
where
average < 2
order by
cluster_identifier,
timestamp;
select
cluster_identifier,
timestamp,
round(minimum, 2) as min_cpu,
round(maximum, 2) as max_cpu,
round(average, 2) as avg_cpu,
sample_count
from
aws_redshift_cluster_metric_cpu_utilization_daily
where
average < 2
order by
cluster_identifier,
timestamp;

Schema for aws_redshift_cluster_metric_cpu_utilization_daily

NameTypeOperatorsDescription
_ctxjsonbSteampipe context in JSON form, e.g. connection_name.
account_idtextThe AWS Account ID in which the resource is located.
averagedouble precisionThe average of the metric values that correspond to the data point.
cluster_identifiertextThe friendly name to identify the DB Instance.
maximumdouble precisionThe maximum metric value for the data point.
metric_nametextThe name of the metric.
minimumdouble precisionThe minimum metric value for the data point.
namespacetextThe metric namespace.
partitiontextThe AWS partition in which the resource is located (aws, aws-cn, or aws-us-gov).
regiontextThe AWS Region in which the resource is located.
sample_countdouble precisionThe number of metric values that contributed to the aggregate value of this data point.
sumdouble precisionThe sum of the metric values for the data point.
timestamptimestamp with time zoneThe time stamp used for the data point.
unittextThe 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)" -- aws

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

steampipe_export_aws --config '<your_config>' aws_redshift_cluster_metric_cpu_utilization_daily