steampipe plugin install aws

Table: aws_ecs_cluster_metric_cpu_utilization_hourly - Query AWS ECS Cluster Metrics using SQL

The AWS ECS Cluster Metrics is a feature of Amazon Elastic Container Service (ECS) that provides CPU utilization data. It allows you to monitor and troubleshoot your applications running on ECS. The CPU Utilization metric represents the percentage of total CPU units that are currently in use on a cluster for an hour.

Table Usage Guide

The aws_ecs_cluster_metric_cpu_utilization_hourly table in Steampipe gives you information about the CPU utilization metrics of AWS ECS (Elastic Container Service) clusters on an hourly basis. This table allows you, as a DevOps engineer, data analyst, or other technical professional, to query cluster-specific details, including the average, maximum, and minimum CPU utilization percentages. You can utilize this table to monitor the performance of your ECS clusters, identify potential resource bottlenecks, and optimize resource allocation. The schema outlines the various attributes of the ECS cluster CPU utilization for you, including the cluster name, timestamp, average utilization, maximum utilization, and minimum utilization.

The aws_ecs_cluster_metric_cpu_utilization_hourly table provides you with metric statistics at 1 hour intervals for the most recent 60 days.

Examples

Basic info

Explore the performance of various AWS ECS clusters by tracking their CPU utilization over time. This allows for effective resource management and helps in identifying potential performance issues.

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

CPU Over 80% average

Discover the instances where the average CPU utilization exceeds 80% in your AWS ECS clusters, allowing you to identify potential performance issues and optimize resource allocation.

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_hourly
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_hourly
where
average > 80
order by
cluster_name,
timestamp;

CPU hourly average < 1%

Determine the areas in which AWS ECS clusters are underutilized, by pinpointing instances where the average CPU usage is less than 1% on an hourly basis. This allows for efficient resource management and cost optimization by identifying potential opportunities for downsizing.

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_hourly
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_hourly
where
average < 1
order by
cluster_name,
timestamp;

Schema for aws_ecs_cluster_metric_cpu_utilization_hourly

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_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.
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_hourly