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Package software.amazon.awscdk.services.cloudwatch

Amazon CloudWatch Construct Library

See: Description

Package software.amazon.awscdk.services.cloudwatch Description

Amazon CloudWatch Construct Library

---

cfn-resources: Stable

cdk-constructs: Stable


Metric objects

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:

 Function fn;
 
 
 Metric errors = fn.metricErrors();
 

Metric objects can be account and region aware. You can specify account and region as properties of the metric, or use the metric.attachTo(Construct) method. metric.attachTo() will automatically copy the region and account fields of the Construct, which can come from anywhere in the Construct tree.

You can also instantiate Metric objects to reference any published metric that's not exposed using a convenience method on the CDK construct. For example:

 HostedZone hostedZone = HostedZone.Builder.create(this, "MyHostedZone").zoneName("example.org").build();
 Metric metric = Metric.Builder.create()
         .namespace("AWS/Route53")
         .metricName("DNSQueries")
         .dimensionsMap(Map.of(
                 "HostedZoneId", hostedZone.getHostedZoneId()))
         .build();
 

Instantiating a new Metric object

If you want to reference a metric that is not yet exposed by an existing construct, you can instantiate a Metric object to represent it. For example:

 Metric metric = Metric.Builder.create()
         .namespace("MyNamespace")
         .metricName("MyMetric")
         .dimensionsMap(Map.of(
                 "ProcessingStep", "Download"))
         .build();
 

Metric Math

Math expressions are supported by instantiating the MathExpression class. For example, a math expression that sums two other metrics looks like this:

 Function fn;
 
 
 MathExpression allProblems = MathExpression.Builder.create()
         .expression("errors + throttles")
         .usingMetrics(Map.of(
                 "errors", fn.metricErrors(),
                 "faults", fn.metricThrottles()))
         .build();
 

You can use MathExpression objects like any other metric, including using them in other math expressions:

 Function fn;
 MathExpression allProblems;
 
 
 MathExpression problemPercentage = MathExpression.Builder.create()
         .expression("(problems / invocations) * 100")
         .usingMetrics(Map.of(
                 "problems", allProblems,
                 "invocations", fn.metricInvocations()))
         .build();
 

Search Expressions

Math expressions also support search expressions. For example, the following search expression returns all CPUUtilization metrics that it finds, with the graph showing the Average statistic with an aggregation period of 5 minutes:

 MathExpression cpuUtilization = MathExpression.Builder.create()
         .expression("SEARCH('{AWS/EC2,InstanceId} MetricName=\"CPUUtilization\"', 'Average', 300)")
 
         // Specifying '' as the label suppresses the default behavior
         // of using the expression as metric label. This is especially appropriate
         // when using expressions that return multiple time series (like SEARCH()
         // or METRICS()), to show the labels of the retrieved metrics only.
         .label("")
         .build();
 

Cross-account and cross-region search expressions are also supported. Use the searchAccount and searchRegion properties to specify the account and/or region to evaluate the search expression against.

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:

 Function fn;
 
 
 Metric minuteErrorRate = fn.metricErrors(MetricOptions.builder()
         .statistic("avg")
         .period(Duration.minutes(1))
         .label("Lambda failure rate")
         .build());
 

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.

Labels

Metric labels are displayed in the legend of graphs that include the metrics.

You can use dynamic labels to show summary information about the displayed time series in the legend. For example, if you use:

 Function fn;
 
 
 Metric minuteErrorRate = fn.metricErrors(MetricOptions.builder()
         .statistic("sum")
         .period(Duration.hours(1))
 
         // Show the maximum hourly error count in the legend
         .label("[max: ${MAX}] Lambda failure rate")
         .build());
 

As the metric label, the maximum value in the visible range will be shown next to the time series name in the graph's legend.

If the metric is a math expression producing more than one time series, the maximum will be individually calculated and shown for each time series produce by the math expression.

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:

 Function fn;
 
 
 Alarm.Builder.create(this, "Alarm")
         .metric(fn.metricErrors())
         .threshold(100)
         .evaluationPeriods(2)
         .build();
 

Alternatively, you can call metric.createAlarm():

 Function fn;
 
 
 fn.metricErrors().createAlarm(this, "Alarm", CreateAlarmOptions.builder()
         .threshold(100)
         .evaluationPeriods(2)
         .build());
 

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

To create a cross-account alarm, make sure you have enabled cross-account functionality in CloudWatch. Then, set the account property in the Metric object either manually or via the metric.attachTo() method.

Alarm Actions

To add actions to an alarm, use the integration classes from the @aws-cdk/aws-cloudwatch-actions package. For example, to post a message to an SNS topic when an alarm breaches, do the following:

 import software.amazon.awscdk.services.cloudwatch.actions.*;
 Alarm alarm;
 
 
 Topic topic = new Topic(this, "Topic");
 alarm.addAlarmAction(new SnsAction(topic));
 

Notification formats

Alarms can be created in one of two "formats":

For backwards compatibility, CDK will try to create classic, top-level CloudWatch alarms as much as possible, unless you are using features that cannot be expressed in that format. Features that require the new-style alarm format are:

The difference between these two does not impact the functionality of the alarm in any way, except that the format of the notifications the Alarm generates is different between them. This affects both the notifications sent out over SNS, as well as the EventBridge events generated by this Alarm. If you are writing code to consume these notifications, be sure to handle both formats.

Composite Alarms

Composite Alarms can be created from existing Alarm resources.

 Alarm alarm1;
 Alarm alarm2;
 Alarm alarm3;
 Alarm alarm4;
 
 
 IAlarmRule alarmRule = AlarmRule.anyOf(AlarmRule.allOf(AlarmRule.anyOf(alarm1, AlarmRule.fromAlarm(alarm2, AlarmState.OK), alarm3), AlarmRule.not(AlarmRule.fromAlarm(alarm4, AlarmState.INSUFFICIENT_DATA))), AlarmRule.fromBoolean(false));
 
 CompositeAlarm.Builder.create(this, "MyAwesomeCompositeAlarm")
         .alarmRule(alarmRule)
         .build();
 

A note on units

In CloudWatch, Metrics datums are emitted with units, such as seconds or bytes. When Metric objects are given a unit attribute, it will be used to filter the stream of metric datums for datums emitted using the same unit attribute.

In particular, the unit field is not used to rescale datums or alarm threshold values (for example, it cannot be used to specify an alarm threshold in Megabytes if the metric stream is being emitted as bytes).

You almost certainly don't want to specify the unit property when creating Metric objects (which will retrieve all datums regardless of their unit), unless you have very specific requirements. Note that in any case, CloudWatch only supports filtering by unit for Alarms, not in Dashboard graphs.

Please see the following GitHub issue for a discussion on real unit calculations in CDK: https://github.com/aws/aws-cdk/issues/5595

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 dashboard;
 Metric executionCountMetric;
 Metric errorCountMetric;
 
 
 dashboard.addWidgets(GraphWidget.Builder.create()
         .title("Executions vs error rate")
 
         .left(List.of(executionCountMetric))
 
         .right(List.of(errorCountMetric.with(MetricOptions.builder()
                 .statistic("average")
                 .label("Error rate")
                 .color(Color.GREEN)
                 .build())))
         .build());
 

Using the methods addLeftMetric() and addRightMetric() you can add metrics to a graph widget later on.

Graph widgets can also display annotations attached to the left or the right y-axis.

 Dashboard dashboard;
 
 
 dashboard.addWidgets(GraphWidget.Builder.create()
         // ...
 
         .leftAnnotations(List.of(HorizontalAnnotation.builder().value(1800).label(Duration.minutes(30).toHumanString()).color(Color.RED).build(), HorizontalAnnotation.builder().value(3600).label("1 hour").color("#2ca02c").build()))
         .build());
 

The graph legend can be adjusted from the default position at bottom of the widget.

 Dashboard dashboard;
 
 
 dashboard.addWidgets(GraphWidget.Builder.create()
         // ...
 
         .legendPosition(LegendPosition.RIGHT)
         .build());
 

The graph can publish live data within the last minute that has not been fully aggregated.

 Dashboard dashboard;
 
 
 dashboard.addWidgets(GraphWidget.Builder.create()
         // ...
 
         .liveData(true)
         .build());
 

The graph view can be changed from default 'timeSeries' to 'bar' or 'pie'.

 Dashboard dashboard;
 
 
 dashboard.addWidgets(GraphWidget.Builder.create()
         // ...
 
         .view(GraphWidgetView.BAR)
         .build());
 

Alarm widget

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

 Dashboard dashboard;
 Alarm errorAlarm;
 
 
 dashboard.addWidgets(AlarmWidget.Builder.create()
         .title("Errors")
         .alarm(errorAlarm)
         .build());
 

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 dashboard;
 Metric visitorCount;
 Metric purchaseCount;
 
 
 dashboard.addWidgets(SingleValueWidget.Builder.create()
         .metrics(List.of(visitorCount, purchaseCount))
         .build());
 

Show as many digits as can fit, before rounding.

 Dashboard dashboard;
 
 
 dashboard.addWidgets(SingleValueWidget.Builder.create()
         .metrics(List.of())
 
         .fullPrecision(true)
         .build());
 

Text widget

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

 Dashboard dashboard;
 
 
 dashboard.addWidgets(TextWidget.Builder.create()
         .markdown("# Key Performance Indicators")
         .build());
 

Alarm Status widget

An alarm status widget displays instantly the status of any type of alarms and gives the ability to aggregate one or more alarms together in a small surface.

 Dashboard dashboard;
 Alarm errorAlarm;
 
 
 dashboard.addWidgets(
 AlarmStatusWidget.Builder.create()
         .alarms(List.of(errorAlarm))
         .build());
 

An alarm status widget only showing firing alarms, sorted by state and timestamp:

 Dashboard dashboard;
 Alarm errorAlarm;
 
 
 dashboard.addWidgets(AlarmStatusWidget.Builder.create()
         .title("Errors")
         .alarms(List.of(errorAlarm))
         .sortBy(AlarmStatusWidgetSortBy.STATE_UPDATED_TIMESTAMP)
         .states(List.of(AlarmState.ALARM))
         .build());
 

Query results widget

A LogQueryWidget shows the results of a query from Logs Insights:

 Dashboard dashboard;
 
 
 dashboard.addWidgets(LogQueryWidget.Builder.create()
         .logGroupNames(List.of("my-log-group"))
         .view(LogQueryVisualizationType.TABLE)
         // The lines will be automatically combined using '\n|'.
         .queryLines(List.of("fields @message", "filter @message like /Error/"))
         .build());
 

Custom widget

A CustomWidget shows the result of an AWS Lambda function:

 Dashboard dashboard;
 
 
 // Import or create a lambda function
 IFunction fn = Function.fromFunctionArn(dashboard, "Function", "arn:aws:lambda:us-east-1:123456789012:function:MyFn");
 
 dashboard.addWidgets(CustomWidget.Builder.create()
         .functionArn(fn.getFunctionArn())
         .title("My lambda baked widget")
         .build());
 

You can learn more about custom widgets in the Amazon Cloudwatch User Guide.

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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