steampipe plugin install aws

Table: aws_ecs_cluster_metric_cpu_utilization_daily - Query AWS ECS Cluster Metrics using SQL

The AWS ECS Cluster is a logical grouping of tasks or services. It allows you to manage and scale a set of services or tasks together in an AWS environment. The CPU Utilization Metric provides data about the CPU usage of the services or tasks in the cluster, helping you monitor and optimize resource allocation on a daily basis.

Table Usage Guide

The aws_ecs_cluster_metric_cpu_utilization_daily table in Steampipe provides you with information about CPU utilization metrics within AWS Elastic Container Service (ECS) clusters. This table allows you, as a DevOps engineer, to query CPU utilization details on a daily basis, including the average, maximum, and minimum utilization. You can utilize this table to monitor and analyze CPU usage trends, identify potential performance issues, and optimize resource allocation. The schema outlines the various attributes of the CPU utilization metric for you, including the timestamp, period, unit, and statistical values.

Examples

Basic info

Explore the daily CPU usage patterns across your AWS ECS clusters. This can help you understand resource utilization trends and plan for capacity adjustments.

select
cluster_name,
timestamp,
minimum,
maximum,
average,
sample_count
from
aws_ecs_cluster_metric_cpu_utilization_daily
order by
cluster_name,
timestamp;
select
cluster_name,
timestamp,
minimum,
maximum,
average,
sample_count
from
aws_ecs_cluster_metric_cpu_utilization_daily
order by
cluster_name,
timestamp;

CPU Over 80% average

Explore instances where the average CPU utilization exceeds 80% in AWS ECS clusters. This can help in identifying potential performance issues and aid in capacity planning.

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

CPU daily average < 1%

Identify instances where the average daily CPU utilization of AWS ECS clusters is less than 1%. This can help in understanding underutilized resources and potentially save costs by downsizing or eliminating unnecessary clusters.

select
cluster_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
aws_ecs_cluster_metric_cpu_utilization_daily
where
average < 1
order by
cluster_name,
timestamp;
select
cluster_name,
timestamp,
round(minimum, 2) as min_cpu,
round(maximum, 2) as max_cpu,
round(average, 2) as avg_cpu,
sample_count
from
aws_ecs_cluster_metric_cpu_utilization_daily
where
average < 1
order by
cluster_name,
timestamp;

Schema for aws_ecs_cluster_metric_cpu_utilization_daily

NameTypeOperatorsDescription
_ctxjsonbSteampipe context in JSON form.
account_idtext=, !=, ~~, ~~*, !~~, !~~*The AWS Account ID in which the resource is located.
averagedouble precisionThe average of the metric values that correspond to the data point.
cluster_nametextA user-generated string that you use to identify your cluster.
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.
sp_connection_nametext=, !=, ~~, ~~*, !~~, !~~*Steampipe connection name.
sp_ctxjsonbSteampipe context in JSON form.
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_ecs_cluster_metric_cpu_utilization_daily