Amazon IoT Greengrass recently announced a major version release. You can learn more about the new features in our documentation.
Local processing with Amazon Lambda
Amazon IoT Greengrass includes support for Amazon Lambda. With Amazon IoT Greengrass, you can run Amazon Lambda functions right on the device to respond quickly to local events, interact with local resources, and process data on the device to minimize the cost of transmitting device data to the cloud.
Local support for containers
You can deploy, run, and manage Docker containers on Amazon IoT Greengrass devices. Your Docker images can be stored in Docker container registries, such as Amazon Elastic Container Registry (Amazon ECR), Docker Hub, or private Docker Trusted Registries (DTRs).
Local support for Amazon IoT Device Shadows
Amazon IoT Greengrass also includes the functionality of Amazon IoT Device Shadows. The Device Shadow caches the state of your device, like a virtual version or “shadow,” of each device that tracks the device’s current versus desired state and synchronizes that state with the cloud when connectivity is available.
Amazon IoT Greengrass enables messaging between the Amazon IoT Greengrass Core and devices using the Amazon IoT Device SDK on a local network, facilitating communication even when there is no connection to Amazon Web Services. With Amazon IoT Greengrass, your devices can process messages and deliver them to another device or to the cloud based on business rules you define.
Local resource access
Amazon Lambda functions deployed on an Amazon IoT Greengrass Core can access local resources that are attached to the device. This allows you to use serial ports, peripherals such as add-on security devices, sensors and actuators, on-board GPUs, or the local file system to quickly access and process local data.
Amazon IoT Greengrass lets you rapidly develop and debug code on a test device before using the cloud to deploy to your production devices. You can use the Amazon IoT Greengrass command-line interface (CLI) to locally develop and debug applications on your device, and the local debug console to help you visually debug applications.
Amazon IoT Greengrass ML Inference
Amazon IoT Greengrass ML Inference is a feature of Amazon IoT Greengrass that makes it easy to perform machine learning inference locally on Amazon IoT Greengrass devices using models that are built and trained in the cloud. This means you won’t incur data transfer costs or increased latency for your applications that use machine learning inference. Visit our ML Inference page to learn more about this feature.
Amazon IoT Greengrass components
Amazon IoT Greengrass provides pre-built components for common use cases so you can discover and import, configure, and deploy applications and services at the edge without the need to understand different device protocols, manage credentials, or interact with external APIs. You can also create your own components or simply re-use common business logic from one Amazon IoT Greengrass device to another.
Amazon IoT Greengrass is modular. You can add or remove pre-built software components based on your IoT use case, and your device CPU and memory resources. For example, you can choose to include pre-built Amazon IoT Greengrass components such as stream manager only when you need to process data streams with your application, or machine learning components only when you want to perform machine learning inference locally on your devices. To find available Amazon IoT Greengrass components, view our documentation.
Manage IoT applications at scale
Amazon IoT Greengrass makes it easy to remotely deploy and manage device software on millions of devices. You can organize your devices in groups and deploy and manage device software and configuration to a subset of devices or to all devices at once. Amazon IoT thing groups allow you to group multiple Amazon IoT Greengrass devices, and view deployment history, start or stop deployments.
Over the air updates
Amazon IoT Greengrass provides the ability to update the Amazon IoT Greengrass Core software on Amazon IoT Greengrass devices. You can use the Amazon IoT Greengrass console, APIs, or command-line interface to update the version of Amazon IoT Greengrass Cores or components running on your devices in order to deploy security updates, bug fixes, and new Amazon IoT Greengrass features.
Security & hardware integrations
Amazon Web Services has created an ever-expanding selection of industry leading IoT silicon vendors, device manufacturers, and gateway partners who have integrated Amazon IoT Greengrass into their software and hardware offerings. These partners help you move quickly from ideation to prototype to deployment.
Amazon IoT Greengrass Secrets Manager
Amazon IoT Greengrass Secrets Manager allows you to securely store, access, rotate, and manage secrets – credentials, keys, endpoints, and configurations – at the edge. With Amazon IoT Greengrass Connector integration, if an Amazon IoT Greengrass Connector needs a secret to authenticate with an application or service, you can select and deploy a secret to the Amazon IoT Greengrass Core as part of the connector configuration. For example, you can use Amazon IoT Greengrass Secrets Manager to configure credentials for private Docker container registries.
Hardware security integration
Amazon IoT Greengrass offers customers the option to store their device private key on a hardware secure element. You can store sensitive device information at the edge with Amazon IoT Greengrass Secrets Manager and encrypt your secrets using private keys for root of trust security.
Data stream management
Amazon IoT Greengrass Stream Manager
You can use Amazon IoT Greengrass to collect, process, and export data streams from IoT devices and manage the life cycle of that data on the device to minimize development time. Amazon IoT Greengrass provides a standard mechanism to process data streams, manage local data-retention policies, and transmit device data to Amazon Web Services cloud services such as Amazon Simple Storage Service (Amazon S3), Amazon Kinesis, Amazon IoT Core, and Amazon IoT Analytics.