cdk-monitoring-constructs 2.6.1

cdk-monitoring-constructs

CDK Monitoring Constructs

Easy-to-use CDK constructs for monitoring your AWS infrastructure.

• Easily add commonly-used alarms using predefined properties
• Generate concise Cloudwatch dashboards that indicate your alarms
• Extend the library with your own extensions or custom metrics
• Consume the library in multiple languages (see below)

Installation

TypeScript

https://www.npmjs.com/package/cdk-monitoring-constructs

In your package.json:

{
  "dependencies": {
    "cdk-monitoring-constructs": "^2.0.0",

    // peer dependencies of cdk-monitoring-constructs
    "@aws-cdk/aws-apigatewayv2-alpha": "^2.60.0-alpha.0",
    "@aws-cdk/aws-redshift-alpha": "^2.60.0-alpha.0",
    "@aws-cdk/aws-synthetics-alpha": "^2.60.0-alpha.0",
    "aws-cdk-lib": "^2.60.0",
    "constructs": "^10.0.5"

    // ...your other dependencies...
  }
}

Java

See https://mvnrepository.com/artifact/io.github.cdklabs/cdkmonitoringconstructs

Python

See https://pypi.org/project/cdk-monitoring-constructs/

C#

See https://www.nuget.org/packages/Cdklabs.CdkMonitoringConstructs/

Golang

Coming soon!

Features

You can browse the documentation at https://constructs.dev/packages/cdk-monitoring-constructs/

Item	Monitoring	Alarms	Notes
AWS API Gateway (REST API) (.monitorApiGateway())	TPS, latency, errors	Latency, error count/rate, low/high TPS	To see metrics, you have to enable Advanced Monitoring
AWS API Gateway V2 (HTTP API) (.monitorApiGatewayV2HttpApi())	TPS, latency, errors	Latency, error count/rate, low/high TPS	To see route level metrics, you have to enable Advanced Monitoring
AWS AppSync (GraphQL API) (.monitorAppSyncApi())	TPS, latency, errors	Latency, error count/rate, low/high TPS
AWS Billing (.monitorBilling())	AWS account cost	Total cost (anomaly)	Requires enabling the Receive Billing Alerts option in AWS Console / Billing Preferences
AWS Certificate Manager (.monitorCertificate())	Certificate expiration	Days until expiration
AWS CloudFront (.monitorCloudFrontDistribution())	TPS, traffic, latency, errors	Error rate, low/high TPS
AWS CloudWatch Logs (.monitorLog())	Patterns present in the log group	Minimum incoming logs
AWS CloudWatch Synthetics Canary (.monitorSyntheticsCanary())	Latency, error count/rate	Error count/rate, latency
AWS CodeBuild (.monitorCodeBuildProject())	Build counts (total, successful, failed), failed rate, duration	Failed build count/rate, duration
AWS DocumentDB (.monitorDocumentDbCluster())	CPU, throttling, read/write latency, transactions, cursors	CPU
AWS DynamoDB (.monitorDynamoTable())	Read and write capacity provisioned / used	Consumed capacity, throttling, latency, errors
AWS DynamoDB Global Secondary Index (.monitorDynamoTableGlobalSecondaryIndex())	Read and write capacity, indexing progress, throttled events
AWS EC2 (.monitorEC2Instances())	CPU, disk operations, network
AWS EC2 Auto Scaling Groups (.monitorAutoScalingGroup())	Group size, instance status
AWS ECS (.monitorFargateService(), .monitorEc2Service(), .monitorSimpleFargateService(), monitorSimpleEc2Service(), .monitorQueueProcessingFargateService(), .monitorQueueProcessingEc2Service())	System resources and task health	Unhealthy task count, running tasks count, CPU/memory usage, and bytes processed by load balancer (if any)	Use for ecs-patterns load balanced ec2/fargate constructs (NetworkLoadBalancedEc2Service, NetworkLoadBalancedFargateService, ApplicationLoadBalancedEc2Service, ApplicationLoadBalancedFargateService)
AWS ElastiCache (.monitorElastiCacheCluster())	CPU/memory usage, evictions and connections	CPU, memory, items count
AWS Glue (.monitorGlueJob())	Traffic, job status, memory/CPU usage	Failed/killed task count/rate
AWS Kinesis Data Analytics (.monitorKinesisDataAnalytics)	Up/Downtime, CPU/memory usage, KPU usage, checkpoint metrics, and garbage collection metrics	Downtime, full restart count
AWS Kinesis Data Stream (.monitorKinesisDataStream())	Put/Get/Incoming Record/s and Throttling	Throttling, throughput, iterator max age
AWS Kinesis Firehose (.monitorKinesisFirehose())	Number of records, requests, latency, throttling	Throttling
AWS Lambda (.monitorLambdaFunction())	Latency, errors, iterator max age	Latency, errors, throttles, iterator max age	Optional Lambda Insights metrics (opt-in) support
AWS Load Balancing (.monitorNetworkLoadBalancer(), .monitorFargateApplicationLoadBalancer(), .monitorFargateNetworkLoadBalancer(), .monitorEc2ApplicationLoadBalancer(), .monitorEc2NetworkLoadBalancer())	System resources and task health	Unhealthy task count, running tasks count, (for Fargate/Ec2 apps) CPU/memory usage	Use for FargateService or Ec2Service backed by a NetworkLoadBalancer or ApplicationLoadBalancer
AWS OpenSearch/Elasticsearch (.monitorOpenSearchCluster(), .monitorElasticsearchCluster())	Indexing and search latency, disk/memory/CPU usage	Indexing and search latency, disk/memory/CPU usage, cluster status, KMS keys
AWS RDS (.monitorRdsCluster())	Query duration, connections, latency, disk/CPU usage	Connections, disk and CPU usage
AWS Redshift (.monitorRedshiftCluster())	Query duration, connections, latency, disk/CPU usage	Query duration, connections, disk and CPU usage
AWS S3 Bucket (.monitorS3Bucket())	Bucket size and number of objects
AWS SecretsManager (.monitorSecretsManagerSecret())	Days since last rotation	Days since last change or rotation
AWS SNS Topic (.monitorSnsTopic())	Message count, size, failed notifications	Failed notifications, min/max published messages
AWS SQS Queue (.monitorSqsQueue(), .monitorSqsQueueWithDlq())	Message count, age, size	Message count, age, DLQ incoming messages
AWS Step Functions (.monitorStepFunction(), .monitorStepFunctionActivity(), monitorStepFunctionLambdaIntegration(), .monitorStepFunctionServiceIntegration())	Execution count and breakdown per state	Duration, failed, failed rate, aborted, throttled, timed out executions
AWS Web Application Firewall (.monitorWebApplicationFirewallAcl())	Allowed/blocked requests	Blocked requests count/rate
Custom metrics (.monitorCustom())	Addition of custom metrics into the dashboard (each group is a widget)		Supports anomaly detection

Getting started

Create monitoring stack and facade

Important note: Please, do NOT import anything from the /dist/lib package. This is unsupported and might break any time.

Create an instance of MonitoringFacade, which is the main entry point:

export interface MonitoringStackProps extends DeploymentStackProps {
  // ...
}

export class MonitoringStack extends DeploymentStack {
  constructor(parent: App, name: string, props: MonitoringStackProps) {
    super(parent, name, props);

    const monitoring = new MonitoringFacade(this, "Monitoring", {
      // Defaults are provided for these, but they can be customized as desired
      metricFactoryDefaults: { ... },
      alarmFactoryDefaults: { ... },
      dashboardFactory: { ... },
    });

    // Monitor your resources
    monitoring
      .addLargeHeader("Storage")
      .monitorDynamoTable({ /* table1 */ })
      .monitorDynamoTable({ /* table2 */ })
      .monitorDynamoTable({ /* table3 */ })
      // etc.
  }
}

Set up your monitoring

Once the facade is created, you can use it to call methods like .monitorLambdaFunction() and chain them together to define your monitors.

You can also use facade methods to add your own widgets, headers of various sizes, and more.

Customize actions

Alarms should have an action setup, otherwise they are not very useful. Currently, we support notifying an SNS queue.

const onAlarmTopic = new Topic(this, "AlarmTopic");

const monitoring = new MonitoringFacade(this, "Monitoring", {
  // ...other props
  alarmFactoryDefaults: {
    // ....other props
    action: new SnsAlarmActionStrategy({ onAlarmTopic }),
  },
});

You can override the default topic for any alarm like this:

monitoring
  .monitorSomething(something, {
    addSomeAlarm: {
      Warning: {
        // ...other props
        threshold: 42,
        actionOverride: new SnsAlarmActionStrategy({ onAlarmTopic }),
      }
    }
  });

Custom metrics

For simply adding some custom metrics, you can use .monitorCustom() and specify your own title and metric groups. Each metric group will be rendered as a single graph widget, and all widgets will be placed next to each other. All the widgets will have the same size, which is chosen based on the number of groups to maximize dashboard space usage.

Custom metric monitoring can be created for simple metrics, simple metrics with anomaly detection and search metrics. The first two also support alarming.

Below we are listing a couple of examples. Let us assume that there are three existing metric variables: m1, m2, m3. They can either be created by hand (new Metric({...})) or (preferably) by using metricFactory (that can be obtained from facade). The advantage of using the shared metricFactory is that you do not need to worry about period, etc.

// create metrics manually
const m1 = new Metric(/* ... */);

const metricFactory = monitoringFacade.createMetricFactory();

// create metrics using metric factory
const m1 = metricFactory.createMetric(/* ... */);

Example: metric with anomaly detection

In this case, only one metric is supported. Multiple metrics cannot be rendered with anomaly detection in a single widget due to a CloudWatch limitation.

monitorCustom({
  title: "Metric with anomaly detection",
  metrics: [
    {
      metric: m1,
      anomalyDetectionStandardDeviationToRender: 3
    }
  ]
})

Adding an alarm:

monitorCustom({
  title: "Metric with anomaly detection and alarm",
  metrics: [
    {
      metric: m1,
      alarmFriendlyName: "MetricWithAnomalyDetectionAlarm",
      anomalyDetectionStandardDeviationToRender: 3,
      addAlarmOnAnomaly: {
        Warning: {
          standardDeviationForAlarm: 4,
          alarmWhenAboveTheBand: true,
          alarmWhenBelowTheBand: true
        }
      }
    }
  ]
})

Example: search metrics

monitorCustom({
  title: "Metric search",
  metrics: [
    {
      searchQuery: "My.Prefix.",
      dimensionsMap: {
        FirstDimension: "FirstDimensionValue",
        // Allow any value for the given dimension (pardon the weird typing to satisfy DimensionsMap)
        SecondDimension: undefined as unknown as string
      }
    }
  ]
})

Search metric does not support setting an alarm, that is a CloudWatch limitation.

Custom monitoring segment

If you want even more flexibility, you can create your own Dashboard Segment.

This is a general procedure on how to do it:

1. Extend the Monitoring class
2. Override the widgets() method (and/or similar ones)
3. Leverage the metric factor and alarm factory, provided by the base class (you can create additional factories, if you will)
4. Add all alarms to .addAlarm() so they are visible to the user and being placed on the alarm summary dashboard

Both of these monitoring base classes are dashboard segments, so you can add them to your monitoring by calling .addSegment().

Monitoring Scopes

With CDK Monitoring Constructs, you can monitor complete CDK construct scopes. It will automatically discover all monitorable resources within the scope (recursively)) and add them to your dashboard.

monitoring.monitorScope(stack);

You can also specify default alarms for any specific resource and disable automatic monitoring for it as well.

monitoring.monitorScope(stack, {
  lambda: {
    props: {
      addLatencyP50Alarm: {
        Critical: { maxLatency: Duration.seconds(10) },
      },
    },
  },

  // Some resources that aren't dependent on nodes (e.g. general metrics across instances/account) may be included
  // by default, but can be explicitly disabled.
  billing: { enabled: false },
  ec2: { enabled: false },
  elasticCache: { enabled: false },
});

Contributing/Security

See CONTRIBUTING for more information.

License

This project is licensed under the Apache-2.0 License.