Amazon Lambda

Crawler

This page is limited to documentation for ingesting AWS Lambda metrics from Amazon CloudWatch. See the Datadog Serverless documentation for more details.

Overview

Amazon Lambda is a compute service that runs code in response to events and automatically manages the compute resources required by that code.

Enable this integration to begin collecting CloudWatch metrics. This page also describes how to set up custom metrics, logging, and tracing for your Lambda functions.

Setup

Installation

If you haven’t already, set up the Amazon Web Services integration first.

Metric collection

architecture diagram for collecting runtime metrics from AWS Lambda

AWS Lambda metrics

In the AWS integration tile, ensure that Lambda is checked under metric collection.

Add the following permissions to your Datadog IAM policy to collect Amazon Lambda metrics. For more information, see the Lambda policies on the AWS website.

AWS Permission	Description
`lambda:List*`	List Lambda functions, metadata, and tags.
`tag:GetResources`	Get custom tags applied to Lambda functions.
`cloudtrail:LookupEvents`	Use CloudTrail History to detect changes to lambda functions

Install the Datadog - AWS Lambda integration.

Once this is completed, view all of your Lambda Functions in the Datadog Serverless view. This page brings together metrics, traces, and logs from your AWS Lambda functions running serverless applications into one view. Detailed documentation on this feature can be found in the Datadog Serverless documentation.

Data Collected

Metrics

aws.lambda.duration (gauge)	Measures the average elapsed wall clock time from when the function code starts executing as a result of an invocation to when it stops executing. Shown as millisecond
aws.lambda.duration.maximum (gauge)	Measures the maximum elapsed wall clock time from when the function code starts executing as a result of an invocation to when it stops executing. Shown as millisecond
aws.lambda.duration.minimum (gauge)	Measures the minimum elapsed wall clock time from when the function code starts executing as a result of an invocation to when it stops executing. Shown as millisecond
aws.lambda.duration.sum (gauge)	Measures the total execution time of the lambda function executing. Shown as millisecond
aws.lambda.duration.p50 (gauge)	Measures the p50 elapsed wall clock time from when the function code starts executing as a result of an invocation to when it stops executing. Shown as millisecond
aws.lambda.duration.p80 (gauge)	Measures the p80 elapsed wall clock time from when the function code starts executing as a result of an invocation to when it stops executing. Shown as millisecond
aws.lambda.duration.p95 (gauge)	Measures the p95 elapsed wall clock time from when the function code starts executing as a result of an invocation to when it stops executing. Shown as millisecond
aws.lambda.duration.p99 (gauge)	Measures the p99 elapsed wall clock time from when the function code starts executing as a result of an invocation to when it stops executing. Shown as millisecond
aws.lambda.duration.p99.9 (gauge)	Measures the p99.9 elapsed wall clock time from when the function code starts executing as a result of an invocation to when it stops executing. Shown as millisecond
aws.lambda.timeout (gauge)	Measures the amount of allowed execution time for the function before the Lambda runtime stops it. Shown as second
aws.lambda.memorysize (gauge)	Measures the amount of allocated memory available to the function during execution. Shown as mebibyte
aws.lambda.errors (count)	Measures the number of invocations that failed due to errors in the function. Shown as error
aws.lambda.invocations (count)	Measures the number of times a function is invoked in response to an event or invocation API call. Shown as invocation
aws.lambda.throttles (count)	Measures the number of Lambda function invocation attempts that were throttled due to invocation rates exceeding the customer's concurrent limits (error code 429). Failed invocations may trigger a retry attempt that succeeds. Shown as throttle
aws.lambda.iterator_age (gauge)	Measures the age of the last record for each batch of records processed Shown as millisecond
aws.lambda.iterator_age.minimum (gauge)	Measures the minimum age of the last record for each batch of records processed Shown as millisecond
aws.lambda.iterator_age.maximum (gauge)	Measures the maximum age of the last record for each batch of records processed Shown as millisecond
aws.lambda.iterator_age.sum (gauge)	Measures the sum of the ages of the last record for each batch of records processed Shown as millisecond
aws.lambda.dead_letter_errors (count)	Measures the sum of times Lambda is unable to write the failed event payload to your configured Dead Letter Queues. Shown as error
aws.lambda.concurrent_executions (gauge)	Measures the average of concurrent executions for a given function at a given point in time. Shown as execution
aws.lambda.concurrent_executions.minimum (gauge)	Measures the minimum of concurrent executions for a given function at a given point in time. Shown as execution
aws.lambda.concurrent_executions.maximum (gauge)	Measures the maximum of concurrent executions for a given function at a given point in time. Shown as execution
aws.lambda.concurrent_executions.sum (gauge)	Measures the sum of concurrent executions for a given function at a given point in time. Shown as execution
aws.lambda.concurrent_executions_global (gauge)	Measures the average of concurrent executions for all functions in an account at a given point in time. Shown as execution
aws.lambda.concurrent_executions_global.minimum (gauge)	Measures the minimum of concurrent executions for all functions in an account at a given point in time. Shown as execution
aws.lambda.concurrent_executions_global.maximum (gauge)	Measures the maximum of concurrent executions for all functions in an account at a given point in time. Shown as execution
aws.lambda.concurrent_executions_global.sum (gauge)	Measures the sum of concurrent executions for all functions in an account at a given point in time. Shown as execution
aws.lambda.unreserved_concurrent_executions (gauge)	Measures the sum of the concurrency of the functions that don't have a custom concurrency limit specified. Shown as execution
aws.lambda.post_runtime_extensions_duration (gauge)	Measures the average amount of time that the runtime spends running code for extensions after the function code has completed. Shown as millisecond
aws.lambda.post_runtime_extensions_duration.maximum (gauge)	Measures the maximum amount of time that the runtime spends running code for extensions after the function code has completed. Shown as millisecond
aws.lambda.post_runtime_extensions_duration.minimum (gauge)	Measures the minimum amount of time that the runtime spends running code for extensions after the function code has completed. Shown as millisecond
aws.lambda.post_runtime_extensions_duration.sum (gauge)	Measures the cumulative amount of time that the runtime spends running code for extensions after the function code has completed. Shown as millisecond
aws.lambda.post_runtime_extensions_duration.p50 (gauge)	Measures the p50 elapsed wall time that the runtime spends running code for extensions after the function code has completed. Shown as millisecond
aws.lambda.post_runtime_extensions_duration.p99 (gauge)	Measures the p90 elapsed wall time that the runtime spends running code for extensions after the function code has completed. Shown as millisecond
aws.lambda.provisioned_concurrent_executions (gauge)	Measures the average number of events that are being processed on provisioned concurrency Shown as execution
aws.lambda.provisioned_concurrent_executions.minimum (gauge)	Measures the minimum number of events that are being processed on provisioned concurrency Shown as execution
aws.lambda.provisioned_concurrent_executions.maximum (gauge)	Measures the maximum number of events that are being processed on provisioned concurrency Shown as execution
aws.lambda.provisioned_concurrency_invocations (count)	Measures the number of invocations that are run on provisioned concurrency Shown as invocation
aws.lambda.provisioned_concurrency_spillover_invocations (count)	Measures the number of invocations that are run on non-provisioned concurrency when all provisioned concurrency is in use Shown as invocation
aws.lambda.provisioned_concurrency_utilization (gauge)	Measures the average fraction of provisioned concurrency in use for a given function at a given point in time Shown as percent
aws.lambda.provisioned_concurrency_utilization.minimum (gauge)	Measures the minimum fraction of provisioned concurrency in use for a given function at a given point in time Shown as percent
aws.lambda.provisioned_concurrency_utilization.maximum (gauge)	Measures the maximum fraction of provisioned concurrency in use for a given function at a given point in time Shown as percent
aws.lambda.signature_validation_errors (count)	Measures the number of times a function is successfully deployed but fails a signature check Shown as error
aws.lambda.enhanced.invocations (count)	Measures the number of times a function is invoked in response to an event or invocation API call. Shown as invocation
aws.lambda.enhanced.errors (count)	Measures the number of invocations that failed due to errors in the function. Shown as error
aws.lambda.enhanced.max_memory_used (gauge)	Measures the maximum amount of memory (mb) used by the function. Shown as mebibyte
aws.lambda.enhanced.duration (gauge)	Measures the elapsed seconds from when the function code starts executing as a result of an invocation to when it stops executing. Shown as second
aws.lambda.enhanced.billed_duration (gauge)	Measures the billed amount of time the function ran for (100ms increments). Shown as second
aws.lambda.enhanced.init_duration (gauge)	Measures the initialization time (second) of a function during a cold start. Shown as second
aws.lambda.enhanced.estimated_cost (gauge)	Measures the total estimated cost of the function invocation (US dollars). Shown as dollar
aws.lambda.enhanced.timeouts (count)	Measures the number of times a function times out. Shown as timeout
aws.lambda.enhanced.out_of_memory (count)	Measures the number of times a function runs out of memory. Shown as error

Each of the metrics retrieved from AWS is assigned the same tags that appear in the AWS console, including but not limited to function name, security-groups, and more.

Custom metrics are only tagged with function name.

Events

The AWS Lambda integration does not include any events.

Service Checks

The AWS Lambda integration does not include any service checks.

Serverless

Real-time enhanced Lambda metrics

Datadog generates real-time Lambda runtime metrics out-of-the-box for Node.js, Python, and Ruby runtimes. See the Serverless documentation to learn more.

Enabling enhanced real-time Lambda metrics

See the Serverless documentation to learn more.

Log collection

See the Serverless documentation to learn more.

Trace collection

Datadog supports distributed tracing for your AWS Lambda functions using either Datadog APM or AWS X-Ray. You can use either set of client libraries to generate traces, and Datadog APM connects traces from applications running on hosts, containers, and serverless functions automatically. See the Serverless documentation to learn more.

Tracing with Datadog APM

The Datadog Node.js, Python, and Ruby tracing libraries support distributed tracing for AWS Lambda, with more runtimes coming soon. The easiest way to add tracing to your application is with the Datadog Lambda Library, which includes the Datadog tracing library as a dependency. See the Serverless documentation to learn more.

Tracing across AWS Lambda and hosts

When applicable, Datadog merges AWS X-Ray traces with native Datadog APM traces. This means that your traces show the complete picture of requests that cross infrastructure boundaries, whether it be AWS Lambda, containers, on-prem hosts, or managed services. See the Serverless documentation to learn more.

Organizing your infrastructure with tags

Any tag applied to your Lambda function automatically becomes a new dimension on which your can slice and dice your traces. See the Serverless documentation to learn more.

Serverless integrations

The following Lambda function integrations provide additional functionality for monitoring serverless applications. See the corresponding Serverless documentation to learn more:

Custom metrics

Install the Datadog Lambda Library to collect and send custom metrics. See the Serverless documentation to learn more.

Upgrading to distribution metrics

With distribution metrics, you select the aggregation when graphing or querying it instead of specifying it at submission time. See the Serverless documentation to learn more.

Custom metrics sample code

In your function code, you must import the necessary methods from the Lambda Layer and add a wrapper around your function handler. See the Serverless documentation to learn more.