Table: aws_elasticache_redis_metric_cache_hits_hourly - Query Amazon ElastiCache Redis Cache Hits using SQL
The Amazon ElastiCache Redis is a web service that makes it easy to set up, manage, and scale a distributed in-memory data store or cache environment 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. The 'Cache Hits' metric specifically provides the number of successful read-only key lookups in the main dictionary on an hourly basis.
Table Usage Guide
The aws_elasticache_redis_metric_cache_hits_hourly
table in Steampipe provides you with information about the cache hits metrics of Amazon ElastiCache Redis instances on an hourly basis. This table allows you as a system administrator or a DevOps engineer to monitor and analyze the performance of Redis cache nodes by querying the cache hits metrics. You can utilize this table to gather insights on cache hits, such as the number of successful lookup of keys in the cache, and to understand the efficiency of your cache configurations. The schema outlines the various attributes of the cache hits metrics for you, including the timestamp, cache hits, dimensions, and more.
The aws_elasticache_redis_metric_cache_hits_hourly
table provides you with metric statistics at 1 hour intervals for the most recent 60 days.
Examples
Basic info
Determine the efficiency of your AWS ElastiCache Redis instances by analyzing cache hit metrics over time. This can help optimize performance and resource utilization.
select cache_cluster_id, timestamp, minimum, maximum, average, sum, sample_countfrom aws_elasticache_redis_metric_cache_hits_hourlyorder by cache_cluster_id, timestamp;
select cache_cluster_id, timestamp, minimum, maximum, average, sum, sample_countfrom aws_elasticache_redis_metric_cache_hits_hourlyorder by cache_cluster_id, timestamp;
CacheHit sum below 10
The query is used to monitor the performance of your AWS ElastiCache Redis clusters by identifying instances where the sum of cache hits falls below 10 in an hour. This can help you pinpoint potential issues and optimize your cache usage for improved application performance.
select cache_cluster_id, timestamp, round(sum :: numeric, 2) as sum_cachehits, round(average :: numeric, 2) as average_cachehits, sample_countfrom aws_elasticache_redis_metric_cache_hits_hourlywhere sum < 10order by cache_cluster_id, timestamp;
select cache_cluster_id, timestamp, round(sum, 2) as sum_cachehits, round(average, 2) as average_cachehits, sample_countfrom aws_elasticache_redis_metric_cache_hits_hourlywhere sum < 10order by cache_cluster_id, timestamp;
CacheHit hourly average < 100
Explore the performance of your AWS ElastiCache Redis clusters by identifying instances where the hourly average of cache hits is less than 100. This can help pinpoint potential areas of concern and optimize the usage of your cache clusters.
select cache_cluster_id, timestamp, round(minimum :: numeric, 2) as min_cachehits, round(maximum :: numeric, 2) as max_cachehits, round(average :: numeric, 2) as avg_cachehits, sample_countfrom aws_elasticache_redis_metric_cache_hits_hourlywhere average < 100order by cache_cluster_id, timestamp;
select cache_cluster_id, timestamp, round(minimum, 2) as min_cachehits, round(maximum, 2) as max_cachehits, round(average, 2) as avg_cachehits, sample_countfrom aws_elasticache_redis_metric_cache_hits_hourlywhere average < 100order by cache_cluster_id, timestamp;
Schema for aws_elasticache_redis_metric_cache_hits_hourly
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_cache_hits_hourly