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@Stability(value=Experimental)

Package software.amazon.awscdk.services.cloudwatch

Amazon CloudWatch Construct Library

See: Description

Package software.amazon.awscdk.services.cloudwatch Description

Amazon CloudWatch Construct Library

Stability: Experimental

This is a developer preview (public beta) module. Releases might lack important features and might have future breaking changes.

This API is still under active development and subject to non-backward compatible changes or removal in any future version. Use of the API is not recommended in production environments. Experimental APIs are not subject to the Semantic Versioning model.

Metric objects represent a metric that is emitted by AWS services or your own application, such as CPUUsage, FailureCount or Bandwidth.

Metric objects can be constructed directly or are exposed by resources as attributes. Resources that expose metrics will have functions that look like metricXxx() which will return a Metric object, initialized with defaults that make sense.

For example, lambda.Function objects have the fn.metricErrors() method, which represents the amount of errors reported by that Lambda function:

const errors = fn.metricErrors();

Aggregation

To graph or alarm on metrics you must aggregate them first, using a function like Average or a percentile function like P99. By default, most Metric objects returned by CDK libraries will be configured as Average over 300 seconds (5 minutes). The exception is if the metric represents a count of discrete events, such as failures. In that case, the Metric object will be configured as Sum over 300 seconds, i.e. it represents the number of times that event occurred over the time period.

If you want to change the default aggregation of the Metric object (for example, the function or the period), you can do so by passing additional parameters to the metric function call:

const minuteErrorRate = fn.metricErrors({
     statistic: 'avg',
     periodSec: 60,
     label: 'Lambda failure rate'
 });

This function also allows changing the metric label or color (which will be useful when embedding them in graphs, see below).

Rates versus Sums

The reason for using Sum to count discrete events is that some events are emitted as either 0 or 1 (for example Errors for a Lambda) and some are only emitted as 1 (for example NumberOfMessagesPublished for an SNS topic).

In case 0-metrics are emitted, it makes sense to take the Average of this metric: the result will be the fraction of errors over all executions.

If 0-metrics are not emitted, the Average will always be equal to 1, and not be very useful.

In order to simplify the mental model of Metric objects, we default to aggregating using Sum, which will be the same for both metrics types. If you happen to know the Metric you want to alarm on makes sense as a rate (Average) you can always choose to change the statistic.

Alarms

Alarms can be created on metrics in one of two ways. Either create an Alarm object, passing the Metric object to set the alarm on:

new Alarm(this, 'Alarm', {
     metric: fn.metricErrors(),
     threshold: 100,
     evaluationPeriods: 2,
 });

Alternatively, you can call metric.newAlarm():

fn.metricErrors().newAlarm(this, 'Alarm', {
     threshold: 100,
     evaluationPeriods: 2,
 });

The most important properties to set while creating an Alarms are:

Dashboards

Dashboards are set of Widgets stored server-side which can be accessed quickly from the AWS console. Available widgets are graphs of a metric over time, the current value of a metric, or a static piece of Markdown which explains what the graphs mean.

The following widgets are available:

Graph widget

A graph widget can display any number of metrics on either the left or right vertical axis:

dashboard.add(new GraphWidget({
     title: "Executions vs error rate",
 
     left: [executionCountMetric],
 
     right: [errorCountMetric.with({
         statistic: "average",
         label: "Error rate",
         color: "00FF00"
     })]
 }));

Alarm widget

An alarm widget shows the graph and the alarm line of a single alarm:

dashboard.add(new AlarmWidget({
     title: "Errors",
     alarm: errorAlarm,
 }));

Single value widget

A single-value widget shows the latest value of a set of metrics (as opposed to a graph of the value over time):

dashboard.add(new SingleValueWidget({
     metrics: [visitorCount, purchaseCount],
 }));

Text widget

A text widget shows an arbitrary piece of MarkDown. Use this to add explanations to your dashboard:

dashboard.add(new TextWidget({
     markdown: '# Key Performance Indicators'
 }));

Dashboard Layout

The widgets on a dashboard are visually laid out in a grid that is 24 columns wide. Normally you specify X and Y coordinates for the widgets on a Dashboard, but because this is inconvenient to do manually, the library contains a simple layout system to help you lay out your dashboards the way you want them to.

Widgets have a width and height property, and they will be automatically laid out either horizontally or vertically stacked to fill out the available space.

Widgets are added to a Dashboard by calling add(widget1, widget2, ...). Widgets given in the same call will be laid out horizontally. Widgets given in different calls will be laid out vertically. To make more complex layouts, you can use the following widgets to pack widgets together in different ways:

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