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.
If you haven’t already, set up the Amazon Web Services integration first.
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 on Lambda policies, review the documentation 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.
| 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 (response code 4XX). 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.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 (response code 4XX). 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.
The AWS Lambda integration does not include any events.
The AWS Lambda integration does not include any service checks.
Datadog generates real-time Lambda runtime metrics out-of-the-box for Node.js, Python, and Ruby runtimes. Refer to updated Serverless documentation to learn more.
Refer to updated Serverless documentation to learn more.
Refer to updated Serverless documentation to learn more.
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 will connect traces from applications running on hosts, containers, and serverless functions automatically. Refer to updated Serverless documentation to learn more.
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. Refer to updated Serverless documentation to learn more.
When applicable, Datadog merges AWS X-Ray traces with native Datadog APM traces. This means that your traces will show the complete picture of requests that cross infrastructure boundaries, whether it be AWS Lambda, containers, on-prem hosts, or managed services. Refer to updated Serverless documentation to learn more.
Any tag applied to your Lambda function automatically becomes a new dimension on which your can slice and dice your traces. Refer to updated Serverless documentation to learn more.
The following Lambda function integrations provide additional functionality for monitoring serverless applications. Refer to the corresponding Serverless documentation to learn more.
Install the Datadog Lambda Library to collect and send custom metrics. Refer to updated Serverless documentation to learn more.
With distribution metrics, you select the aggregation when graphing or querying it instead of specifying it at submission time. Refer to updated Serverless documentation to learn more.
Refer to updated Serverless documentation to learn more.
Refer to updated Serverless documentation to learn more.
Refer to updated Serverless documentation to learn more.
In your function code, you must import the necessary methods from the Lambda Layer and add a wrapper around your function handler. Refer to updated Serverless documentation to learn more.
Refer to updated Serverless documentation to learn more.
Refer to updated Serverless documentation to learn more.
Refer to updated Serverless documentation to learn more.
Refer to updated Serverless documentation to learn more.
Refer to updated Serverless documentation to learn more.
Need help? Contact Datadog support.
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