Table: aws_elasticache_redis_metric_engine_cpu_utilization_daily - Query AWS ElastiCache Redis Metrics using SQL

The AWS ElastiCache Redis Metrics service is a tool that allows you to collect, track, and analyze performance metrics for your running ElastiCache instances. It provides valuable information about CPU utilization, helping you understand how your applications are using your cache and where bottlenecks are occurring. This data can help you make informed decisions about scaling and optimizing your ElastiCache instances for better application performance.

Table Usage Guide

The aws_elasticache_redis_metric_engine_cpu_utilization_daily table in Steampipe provides you with daily statistical data about the CPU utilization of an Amazon ElastiCache Redis engine. This table allows you, as a DevOps engineer or data analyst, to query and analyze the CPU usage patterns of your ElastiCache Redis instances. This enables you to identify potential performance bottlenecks and optimize resource allocation. The schema outlines the various attributes of the CPU utilization metrics for you, including the timestamp, minimum, maximum, and average CPU usage, as well as the standard deviation.

The aws_elasticache_redis_metric_engine_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 of AWS ElastiCache Redis clusters to understand their performance trends and capacity planning. This allows you to identify instances where resource usage may be high and adjust accordingly to ensure optimal functioning.

select
  cache_cluster_id,
  timestamp,
  minimum,
  maximum,
  average,
  sample_count
from
  aws_elasticache_redis_metric_engine_cpu_utilization_daily
order by
  cache_cluster_id,
  timestamp;

select
  cache_cluster_id,
  timestamp,
  minimum,
  maximum,
  average,
  sample_count
from
  aws_elasticache_redis_metric_engine_cpu_utilization_daily
order by
  cache_cluster_id,
  timestamp;

CPU Over 80% average

Determine the areas in which your AWS ElastiCache Redis instances are utilizing more than 80% of the CPU on average. This allows you to identify potential performance issues and optimize resource allocation.

select
  cache_cluster_id,
  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_elasticache_redis_metric_engine_cpu_utilization_daily
where
  average > 80
order by
  cache_cluster_id,
  timestamp;

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

CPU daily average < 2%

Identify instances where the daily average CPU utilization is less than 2% in your AWS ElastiCache Redis clusters. This is useful in understanding underutilized resources, which can help optimize costs and resource allocation.

select
  cache_cluster_id,
  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_elasticache_redis_metric_engine_cpu_utilization_daily
where
  average < 2
order by
  cache_cluster_id,
  timestamp;

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

Schema for aws_elasticache_redis_metric_engine_cpu_utilization_daily

Name	Type	Operators	Description
_ctx	jsonb		Steampipe context in JSON form.
account_id	text	=, !=, ~~, ~~, !~~, !~~	The AWS Account ID in which the resource is located.
average	double precision		The average of the metric values that correspond to the data point.
cache_cluster_id	text		The cache cluster id.
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.
partition	text		The AWS partition in which the resource is located (aws, aws-cn, or aws-us-gov).
region	text		The AWS 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.
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)" -- aws

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

steampipe_export_aws --config '<your_config>' aws_elasticache_redis_metric_engine_cpu_utilization_daily