Table: alicloud_ecs_instance_metric_cpu_utilization_daily - Query Alibaba Cloud ECS Instance Metrics using SQL

Alibaba Cloud Elastic Compute Service (ECS) provides scalable, on-demand cloud servers for secure, flexible, and efficient application environments. It allows you to operate and manage online applications in a smoother, more reliable, and more secure manner. ECS instances are the fundamental computing unit provided by Alibaba Cloud ECS.

Table Usage Guide

The alicloud_ecs_instance_metric_cpu_utilization_daily table provides insights into ECS Instance Metrics within Alibaba Cloud Elastic Compute Service (ECS). As a system administrator or DevOps engineer, explore instance-specific details through this table, including daily CPU utilization. Utilize it to uncover information about instances, such as CPU usage patterns, which can help in performance optimization and capacity planning.

Examples

Basic info

Explore the daily CPU utilization patterns of your Alicloud ECS instances to monitor their performance and identify any irregularities. This can assist in optimizing resource allocation and identifying potential issues before they escalate.

select
  instance_id,
  timestamp,
  minimum,
  maximum,
  average
from
  alicloud_ecs_instance_metric_cpu_utilization_daily
order by
  instance_id,
  timestamp;

select
  instance_id,
  timestamp,
  minimum,
  maximum,
  average
from
  alicloud_ecs_instance_metric_cpu_utilization_daily
order by
  instance_id,
  timestamp;

CPU Over 80% average

Explore which Alicloud Elastic Compute Service (ECS) instances have an average CPU utilization exceeding 80%, allowing for proactive resource management and performance optimization. This helps in identifying potential bottlenecks and ensuring efficient usage of resources.

select
  instance_id,
  timestamp,
  round(minimum :: numeric, 2) as min_cpu,
  round(maximum :: numeric, 2) as max_cpu,
  round(average :: numeric, 2) as avg_cpu
from
  alicloud_ecs_instance_metric_cpu_utilization_daily
where
  average > 80
order by
  instance_id,
  timestamp;

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

Query examples

Schema for alicloud_ecs_instance_metric_cpu_utilization_daily

Name	Type	Operators	Description
_ctx	jsonb		Steampipe context in JSON form.
account_id	text	=, !=, ~~, ~~, !~~, !~~	The Alicloud Account ID in which the resource is located.
average	double precision		The average of the metric values that correspond to the data point.
instance_id	text		The ID 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.
sp_connection_name	text	=, !=, ~~, ~~, !~~, !~~	Steampipe connection name.
sp_ctx	jsonb		Steampipe context in JSON form.
timestamp	timestamp with time zone		The timestamp used 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)" -- alicloud

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

steampipe_export_alicloud --config '<your_config>' alicloud_ecs_instance_metric_cpu_utilization_daily