This glossary focuses on terms and concepts specific to serverless architectures, cloud platform providers, and Datadog Serverless monitoring.
General serverless concepts
| Concept | Description |
|---|
| Serverless | A development model in which a cloud provider allocates backend resources on demand. This paradigm enables developers to build, run, and deploy applications and services without having to manage infrastructure. |
| Function | In a serverless paradigm, a function is a self-contained application that runs in the cloud. |
| Cloud-based development | A workflow where developers run their code in the cloud during the development process, instead of just on their local machines. Generally, building serverless applications requires cloud-based development. |
| Cold start | The first time you invoke a particular function, it may take a longer time to run than in subsequent invocations. This phenomenon is known as a cold start, and may be caused by different factors: for instance, the cloud provider may need some time to provision underlying resources. |
| Event-driven architecture | An architectural pattern in which events drive communication between decoupled services. |
| Function-as-a-Service (FaaS) | A subset of serverless functions. FaaS refers explicitly to event-driven paradigms. |
Cloud-specific concepts
Datadog Serverless provides monitoring for serverless applications in multiple cloud environments.
AWS Lambda is the FaaS platform provided by Amazon Web Services. See the AWS Lambda documentation for more details.
| Concept | Description |
|---|
| Amazon Resource Name (ARN) | A naming convention for resources in AWS. |
| AWS CloudFormation | An AWS service that uses templates to create and delete AWS resources. You can create and delete collections of resources as a unit; these collections are called “stacks.” |
| AWS Identity and Access Management (IAM) | An AWS service for managing users and user permissions in AWS. |
| AWS Lambda | AWS’s FaaS offering. Alternately, “a Lambda” is often used as a shorthand for “a Lambda function”. |
| Step Functions | Step Functions is a service provided by AWS which offers a way of orchestrating common workflows composed of multiple Lambda functions or cloud service events, without needing to write plumbing code to handle the workflow state and retry logic, etc. |
| Deployment package | Lambda function code can be deployed using a deployment package: either a ZIP archive that contains the function code and dependencies, or a container image that is compatible with the Open Container Initiative (OCI) specification. |
| Edge location | An AWS data center used to perform service-specific operations. |
| Event | A JSON document that contains data for a Lambda function to process. |
| Lambda function | A serverless function in Lambda. Each function had code to process events and can be invoked to run. |
| Lambda layer | A ZIP archive that contains additional code—for example, libraries, a custom runtime, configuration files, or other dependencies. You can use Lambda layers to use libraries in your serverless functions without having to include these libraries in your deployment package. |
| Managed policy | An IAM policy that can be attached to multiple users, groups, and roles. These can be created and managed by AWS or by a customer. |
| Resource | An S3 bucket, EC2 instance, IAM user, or other entity that can be used in AWS. |
| Resource property | When including a resource in an AWS CloudFormation stack, each resource can have one or more associated properties. |
| Serverless Application Model (SAM) | SAM is an Infrastructure as Code framework developed by AWS specifically focused on serverless applications. |
Datadog serverless for AWS Lambda concepts
| Concept | Description |
|---|
| Enhanced Lambda metrics | Enhanced Lambda metrics give you a view above and beyond the default Lambda metrics enabled with the AWS Lambda integration. These metrics are distinguished by being in the aws.lambda.enhanced.* namespace, and are Datadog’s best practice for setting real-time monitors on your serverless application health. |
| Lambda library | The Datadog Lambda library collects data (such as enhanced Lambda metrics and traces) from your Lambda function runtime. The Lambda library then submits this data either to logs (for the Forwarder to pick up) or to the Lambda extension. The Datadog Lambda library is often bundled together with the Datadog tracing library into a Lambda layer for easy installation. |
| Forwarder | An AWS Lambda function that parses and ships serverless monitoring data from CloudWatch logs to Datadog. |
| Lambda extension | A lightweight Datadog Agent that runs within the Lambda execution environment and ships serverless monitoring data to Datadog with minimal performance overhead. The extension is distributed as a Lambda layer for easy installation. |
| Serverless CLI | The CLI enables instrumentation by modifying existing Lambda functions’ configuration. It is the quickest way to get started with Datadog serverless monitoring. |
| Serverless Macro | The Datadog Serverless CloudFormation macro automatically enables instrumentation for serverless applications by transforming the CloudFormation template. |
| Serverless Plugin | The Serverless plugin automatically enables instrumentation for your applications managed by the Serverless Framework by modifying the Lambda functions’ configuration. |
| Serverless CDK Construct | The Serverless plugin automatically enables instrumentation for your applications managed by the AWS CDK by modifying the Lambda functions’ configuration. |
| Trace merging | Serverless trace merging is required to see a single, connected trace when you configure both Datadog’s tracing libraries (dd-trace) and AWS X-Ray tracing libraries in your application. |
| Trace propagation | The Datadog trace context needs to be propagated over AWS managed services, such as SQS, Kinesis and Lambda functions, to generate a single, connected trace for serverless applications. |
| Serverless Insights | Datadog automatically generates suggestions to resolve errors and performance problems and optimizes cost for your serverless applications. |
Azure Functions is the FaaS platform provided by Microsoft Azure. See the Microsoft Azure Functions documentation for more details.
| Concept | Description |
|---|
| Azure Functions | Microsoft’s FaaS offering. |
| Azure App Service | A hosting service for building web applications, services, and APIs. |
| Azure Resource Manager (ARM) template | A JSON document that defines the infrastructure and configuration for your project. |
Datadog serverless for Azure Functions concepts
Cloud Functions is Google’s serverless execution environment. See the Google Cloud Functions documentation for more details.
| Concept | Description |
|---|
| Cloud Functions | Google’s FaaS offering. |
