steampipe plugin install aws

Table: aws_elasticache_redis_metric_engine_cpu_utilization_hourly - Query AWS ElastiCache Redis using SQL

The AWS ElastiCache Redis is a web service that makes it easy to deploy, operate, and scale an in-memory data store or cache in the cloud. It provides a high-performance, scalable, and cost-effective caching solution, while removing the complexity associated with managing a distributed cache environment. This service is primarily used to improve the performance of web applications by retrieving information from fast, managed, in-memory caches, instead of relying entirely on slower disk-based databases.

Table Usage Guide

The aws_elasticache_redis_metric_engine_cpu_utilization_hourly table in Steampipe gives you information about the hourly CPU utilization metrics for AWS ElastiCache Redis. This table enables you, as a DevOps engineer, database administrator, or other technical professional, to query time-series data related to CPU usage. As a result, you can monitor performance, identify potential bottlenecks, and optimize resource allocation. The schema outlines various attributes of the CPU utilization metrics for you, including the timestamp, average, maximum, and minimum CPU utilization, among others.

The aws_elasticache_redis_metric_engine_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 your AWS ElastiCache Redis instances by analyzing CPU utilization over time. This can help optimize resource allocation and identify instances where performance tuning may be required.

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

CPU Over 80% average

Discover instances where your AWS ElastiCache Redis clusters are experiencing high CPU usage, specifically over 80% on average. This can help identify potential performance issues and allow for proactive troubleshooting.

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

CPU hourly average < 2%

Analyze the performance of your AWS ElastiCache Redis clusters by identifying instances where the average CPU usage is less than 2% on an hourly basis. This can help pinpoint potential inefficiencies or underutilized resources, optimizing your cloud infrastructure management and cost efficiency.

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_hourly
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_hourly
where
average < 2
order by
cache_cluster_id,
timestamp;

Schema for aws_elasticache_redis_metric_engine_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.
cache_cluster_idtextThe cache cluster id.
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_elasticache_redis_metric_engine_cpu_utilization_hourly