aws-embedded-metrics (original) (raw)

aws-embedded-metrics

Generate CloudWatch Metrics embedded within structured log events. The embedded metrics will be extracted so you can visualize and alarm on them for real-time incident detection. This allows you to monitor aggregated values while preserving the detailed event context that generated them.

Use Cases

Installation

npm install aws-embedded-metrics

ImportantVersions 4.1.1+, 3.0.2+, 2.0.7+ are required for usage in Lambda with JSON log format. Using previous versions in such Lambda environments will lead to metric loss.

Usage

To get a metric logger, you can either decorate your function with a metricScope, or manually create and flush the logger.

Using the metricScope decorator without function parameters:

const { metricScope, Unit, StorageResolution } = require("aws-embedded-metrics");

const myFunc = metricScope(metrics => async () => { metrics.putDimensions({ Service: "Aggregator" }); metrics.putMetric("ProcessingLatency", 100, Unit.Milliseconds, StorageResolution.Standard); metrics.putMetric("Memory.HeapUsed", 1600424.0, Unit.Bytes, StorageResolution.High); metrics.setProperty("RequestId", "422b1569-16f6-4a03-b8f0-fe3fd9b100f8"); // ... });

await myFunc();

Using the metricScope decorator with function parameters:

const { metricScope, Unit, StorageResolution } = require("aws-embedded-metrics");

const myFunc = metricScope(metrics => async (param1: string, param2: number) => { metrics.putDimensions({ Service: "Aggregator" }); metrics.putMetric("ProcessingLatency", 100, Unit.Milliseconds, StorageResolution.Standard); metrics.putMetric("Memory.HeapUsed", 1600424.0, Unit.Bytes, StorageResolution.High); metrics.setProperty("RequestId", "422b1569-16f6-4a03-b8f0-fe3fd9b100f8"); // ... });

await myFunc('myParam', 0);

Manually constructing and flushing the logger:

const { createMetricsLogger, Unit, StorageResolution } = require("aws-embedded-metrics");

const myFunc = async () => { const metrics = createMetricsLogger(); metrics.putDimensions({ Service: "Aggregator" }); metrics.putMetric("ProcessingLatency", 100, Unit.Milliseconds, StorageResolution.Standard); metrics.putMetric("Memory.HeapUsed", 1600424.0, Unit.Bytes, StorageResolution.High); metrics.setProperty("RequestId", "422b1569-16f6-4a03-b8f0-fe3fd9b100f8"); // ... await metrics.flush(); };

await myFunc();

Lambda

If you are running on Lambda, export your function like so:

const { metricScope } = require("aws-embedded-metrics");

const myFunc = metricScope(metrics => async () => { // ... });

exports.handler = myFunc;

API

MetricLogger

The MetricLogger is the interface you will use to publish embedded metrics.

Adds a new metric to the current logger context. Multiple metrics using the same key will be appended to an array of values. Multiple metrics cannot have same key and different storage resolution. The Embedded Metric Format supports a maximum of 100 values per key. If more metric values are added than are supported by the format, the logger will be flushed to allow for new metric values to be captured.

Requirements:

Storage Resolution

An OPTIONAL value representing the storage resolution for the corresponding metric. Setting this to High specifies this metric as a high-resolution metric, so that CloudWatch stores the metric with sub-minute resolution down to one second. Setting this to Standard specifies this metric as a standard-resolution metric, which CloudWatch stores at 1-minute resolution. If a value is not provided, then a default value of Standard is assumed. See Cloud Watch High-Resolution metrics

Examples:

// Standard Resolution example putMetric("Latency", 200, Unit.Milliseconds) putMetric("Latency", 201, Unit.Milliseconds, StorageResolution.Standard)

// High Resolution example putMetric("Memory.HeapUsed", 1600424.0, Unit.Bytes, StorageResolution.High);

Adds or updates the value for a given property on this context. This value is not submitted to CloudWatch Metrics but is searchable by CloudWatch Logs Insights. This is useful for contextual and potentially high-cardinality data that is not appropriate for CloudWatch Metrics dimensions.

Requirements:

Examples:

setProperty("RequestId", "422b1569-16f6-4a03-b8f0-fe3fd9b100f8") setProperty("InstanceId", "i-1234567890") setProperty("Device", { Id: "61270781-c6ac-46f1-baf7-22c808af8162", Name: "Transducer", Model: "PT-1234" });

Adds a new set of dimensions that will be associated to all metric values.

WARNING: Every distinct value will result in a new CloudWatch Metric. If the cardinality of a particular value is expected to be high, you should consider using setProperty instead.

Requirements:

Examples:

putDimensions({ Operation: "Aggregator" }) putDimensions({ Operation: "Aggregator", DeviceType: "Actuator" })

Explicitly override all dimensions. This will remove the default dimensions unless the useDefault parameter is set to true (defaults to false).

WARNING: Every distinct value will result in a new CloudWatch Metric. If the cardinality of a particular value is expected to be high, you should consider using setProperty instead.

Requirements:

Examples:

// Overwrites custom dimensions - keeps default dimensions setDimensions({Operation: "Aggregator"}, true)

// Overwrites custom dimensions - removes default dimensions setDimensions([ { Operation: "Aggregator" }, { Operation: "Aggregator", DeviceType: "Actuator" } ])

Explicitly clear all custom dimensions. Set useDefault to true to keep the default dimensions.

Example:

resetDimensions(false) // this will clear all custom dimensions as well as disable default dimensions

Sets the CloudWatch namespace that extracted metrics should be published to. If not set, a default value of aws-embedded-metrics will be used.

Requirements:

Example:

setNamespace("MyApplication");

Sets the CloudWatch timestamp that extracted metrics are associated with. If not set a default value of new Date() will be used.

If set for a given MetricsLogger, timestamp will be preserved across calls to flush().

Requirements:

Examples:

setTimestamp(new Date()) setTimestamp(new Date().getTime())

Flushes the current MetricsContext to the configured sink and resets all properties and metric values. The namespace and default dimensions will be preserved across flushes. Custom dimensions are preserved by default, but this behavior can be changed by setting logger.flushPreserveDimensions = false. Timestamp will be preserved if set explicitly via setTimestamp().

Examples:

logger.flush() // custom and default dimensions will be preserved after each flush

logger.flushPreserveDimensions = false logger.flush() // only default dimensions will be preserved after flush()

logger.flushPreserveDimensions = false logger.resetDimensions(false) logger.flush() // default dimensions are disabled - no dimensions will be preserved after flush()

Configuration

All configuration values can be set using environment variables with the prefix (AWS_EMF_). Configuration should be performed as close to application start up as possible.

ServiceName: Overrides the name of the service. For services where the name cannot be inferred (e.g. Java process running on EC2), a default value of Unknown will be used if not explicitly set.

Requirements:

Example:

// in process const { Configuration } = require("aws-embedded-metrics"); Configuration.serviceName = "MyApp";

// environment AWS_EMF_SERVICE_NAME=MyApp

ServiceType: Overrides the type of the service. For services where the type cannot be inferred (e.g. Java process running on EC2), a default value of Unknown will be used if not explicitly set.

Requirements:

Example:

// in process const { Configuration } = require("aws-embedded-metrics"); Configuration.serviceType = "NodeJSWebApp";

// environment AWS_EMF_SERVICE_TYPE=NodeJSWebApp

LogGroupName: For agent-based platforms, you may optionally configure the destination log group that metrics should be delivered to. This value will be passed from the library to the agent in the Embedded Metric payload. If a LogGroup is not provided, the default value will be derived from the service name: -metrics

Requirements:

Example:

// in process const { Configuration } = require("aws-embedded-metrics"); Configuration.logGroupName = "LogGroupName";

// environment AWS_EMF_LOG_GROUP_NAME=LogGroupName

LogStreamName: For agent-based platforms, you may optionally configure the destination log stream that metrics should be delivered to. This value will be passed from the library to the agent in the Embedded Metric payload. If a LogGroup is not provided, the default value will be derived by the agent (this will likely be the hostname).

Requirements:

Example:

// in process const { Configuration } = require("aws-embedded-metrics"); Configuration.logStreamName = "LogStreamName";

// environment AWS_EMF_LOG_STREAM_NAME=LogStreamName

AgentEndpoint: For agent-based platforms, you may optionally configure the endpoint to reach the agent on.

Example:

// in process const { Configuration } = require("aws-embedded-metrics"); Configuration.agentEndpoint = "udp://127.0.0.1:1000";

// environment AWS_EMF_AGENT_ENDPOINT="udp://127.0.0.1:1000"

EnvironmentOverride: Short circuit auto-environment detection by explicitly defining how events should be sent. This is not supported through programatic access due to #43.

Valid values include:

Example:

AWS_EMF_ENVIRONMENT=Local

EnableDebugLogging: Enable debug logging for the library. If the library is not behaving as expected, you can set this to true to log to console.

Example:

// in process const { Configuration } = require("aws-embedded-metrics"); Configuration.debuggingLoggingEnabled = true;

// environment AWS_EMF_ENABLE_DEBUG_LOGGING=true

Namespace: Sets the CloudWatch namespace that extracted metrics should be published to. If not set, a default value of aws-embedded-metrics will be used.

Requirements:

Example:

// in process const { Configuration } = require("aws-embedded-metrics"); Configuration.namespace = "Namespace";

// environment AWS_EMF_NAMESPACE=Namespace

Examples

Check out the examples directory to get started.

Testing Examples

Check out the unit test examples directory to get started. Here we provide a few examples to help you write tests against code that depends on this package.

Development

Building

This project uses Volta to pin the currently supported version of node.

npm i && npm run build

Running Locally

If you are running the CW agent locally, you can test the workflow:

npm i && npm link
cd examples/agent && npm link aws-embedded-metrics

After linking you'll need to rebuild any changes:

npm run build

Testing

We have 2 different types of tests:

  1. Unit tests which can be run using the following commands:

npm test

or

npm run watch

  1. Integration tests. These tests require Docker to run the CloudWatch Agent and valid AWS credentials. Tests can be run by:
export AWS_ACCESS_KEY_ID=
export AWS_SECRET_ACCESS_KEY=
export AWS_REGION=us-west-2
npm run integ

Formatting

We use Prettier for auto-formatting. You should install the plugin for your editor-of-choice and enabled format-on-save.

License

This project is licensed under the Apache-2.0 License.