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CloudWatch metrics

CloudWatch metrics continuously pulls metrics that have tags applied to them from CloudWatch, and pushes these metrics to your Grafana Cloud hosted metrics instance. Then you can drill into your data and identify issues.

With CloudWatch metrics, you can:

  • Pull CloudWatch metrics from multiple AWS accounts and regions, without installing the Grafana Agent.
  • Create multiple configurations called scrape jobs to separate data. A scrape job is a set of configurations that dictate which services, regions, and AWS accounts to collect data from.
  • Ingest the tags from your AWS instance and make them available for querying and alerting.
  • Query and alert on metrics data using the Prometheus query language (PromQL).
  • Use out-of-the-box dashboards for different services, so you don’t need to build them.

How it works

CloudWatch metrics uses an open source exporter to continually pull CloudWatch metrics and store them in a Prometheus format. Then you can use PromQL to query metrics later at no additional cost. PromQL allows you to run familiar expressions, such as aws_ec2_cpuutilization_maximum{region=“eu-west-2”, scrape_job=”myEC2Job”}.

You can create any number of scrape jobs. In this way, you can logically split your data into specific jobs, and scrape any number of AWS accounts to better organize your data.

As part of creating a job, Grafana needs access to the CloudWatch data available in your account. To grant access, CloudWatch metrics uses AWS account delegation. Grafana can then assume a role that has access only to your CloudWatch data, with no need to share access and secret keys.

Included services

Use Grafana Cloud to connect over 60 of the most popular AWS services, including EC2, Lambda, EBS, RDS, S3, ECS, ELB, and Billing. To see a complete list of services and what is gathered for each one, refer to Services.

Timestamps in Grafana and CloudWatch metrics

The timestamp of a metric pulled by CloudWatch metrics is set to the time the metric is pulled. This might seem counterintuitive, but its intent is to simplify the writing of alert queries. The timestamps from CloudWatch metrics always appear more delayed than they actually are.

Timestamp example

As an example, assume you are looking at a single metric, CPU Maximum, pulled every five minutes. This leads to CloudWatch metrics pulling data with a CloudWatch period of five minutes.

CloudWatch timestamps mark the beginning of a period, not the end.

Beginning of period starts at 0:00
Beginning of period starts at 0:00

CloudWatch samples are visible at the beginning of a period and aggregated through the period window.

Sample aggregated through 0:08
Sample aggregated through 0:08

CloudWatch metrics pulls on a consistent interval, and only requests data which has been fully aggregated. This results in a Grafana Cloud timestamp of 0:08 for a metric CloudWatch stamped at 0:00.

Sample aggregated through 0:08
Sample aggregated through 0:08

If the CloudWatch timestamp was used instead:

  • Metrics would appear to be eight minutes old when ingested.
  • Any alert queries written would need to consider this extra variable delay.

The pull timestamp gives the appearance of an eight-minute delay. But actually, only three minutes have passed since the value stopped being updated. This means your alert queries can remain simple.