AWS IoT Greengrass FAQs

“Local resource” refers to buses and peripherals that are physically present on the AWS IoT Greengrass host, or a file system volume on the AWS IoT Greengrass host OS. For example, to communicate with devices connected via Modbus/CANbus, an AWS IoT Greengrass Lambda function would need to access the serial port on the device. A local resource is defined at AWS IoT Greengrass group scope, and all Lambdas in the AWS IoT Greengrass group can use the defined local resources.

AWS IoT Greengrass local resource allows your Lambda functions to securely interact with hardware such as sensors and actuators. For example, your Lambda function can read video streams from the camera on the device or send command and control to GPIO.

Hardware roots of trust provide tamper-protected trusted execution environments where a true random number generator can produce the private keys used for encryption functions. These hardware “secure elements” are resistant to malware tampering and are physically tied to a given IoT device, establishing a strong root of trust upon which software can be deployed safely.

First, you must run your AWS IoT Greengrass Core software on an edge device with a secure element. Following the hardware vendor’s directions, generate a private key on that secure element. Next, follow our documentation to update the config.json file settings to use the secure element private key.

For a current list of integrated hardware, visit the AWS Partner Device Catalog.

Secure element vendors have configured their secure elements to use a set of PKCS#11 standard APIs to integrate with AWS IoT Greengrass. Vendors use a set of testing tools to qualify that their hardware is configured correctly.

On AWS IoT Greengrass devices, you can perform ML inference on locally-generated data using models optimized with Amazon SageMaker Neo. To prepare your device for inference, you can follow the instructions on installing the Neo DLR runtime on your device. For more information, see Installing DLR.

You can compile a model in Amazon SageMaker Neo for your target hardware platform and store it in an Amazon Simple Storage Service (Amazon S3) bucket. Then you can configure AWS IoT Greengrass to use the Amazon S3 bucket to deploy the Neo optimized model for local inference on the device.

You can bring your ML model trained elsewhere by placing it in .tar.gz and .zip format in Amazon S3. You will then let AWS IoT Greengrass know the Amazon S3 URI and AWS IoT Greengrass will deploy to target devices.

AWS IoT Greengrass ML Inference is currently available in all Regions AWS IoT Greengrass is available in. Please refer to the AWS Regions Table for the most updated information regarding Region availability of AWS IoT Greengrass.

You can use AWS IoT Greengrass ML Inference regardless of your geographic location, as long as you have access to one of these AWS Regions.

AWS IoT Greengrass components are building blocks that enable easy creation of complex workflows such as machine learning inference, local processing, messaging, and data management. AWS IoT Greengrass also offers prebuilt components such as Stream Manager that supports data export to local and cloud targets. These components help accelerate application development so you don't have to worry about understanding device protocols, managing credentials, or interacting with external APIs, and you can interact with AWS services and third-party applications without writing code. In addition, you can also build your own components on top of AWS IoT Greengrass. All components are designed to enable ease of use, as they can configured and managed through the AWS Greengrass console. These components enable you to reuse common business logic from one AWS IoT Greengrass device to another, as you can easily discover, import, configure, and deploy components at the edge.

AWS IoT Greengrass components can be added via the “components” section for each group in the AWS IoT Greengrass console. Once added, you can configure the AWS IoT Greengrass components parameters and deploy the group to add them to your AWS IoT Greengrass Core device.

Any AWS IoT Greengrass customer can use AWS IoT Greengrass components from within the AWS IoT Greengrass Console, which is accessible through the AWS Management Console.

You can find available AWS IoT Greengrass components in our documentation.

Since Lambda functions running on AWS IoT Greengrass Cores have access to network resources, you can use Lambda to implement support for any protocol that is implemented on top of TCP/IP. In addition, you can also take advantage of AWS IoT Greengrass Local Resource Access to implement support for protocols that need access to hardware adapter/drivers.

AWS IoT Greengrass also provides Modbus-RTU, Modbus-TCP, and EtherNet/IP Protocol Adapter connectors that can help you connect to edge devices. For more information, refer to the connector documentation here.

You can use the IoT SiteWise connector to ingest device data from OPC UA servers, the Modbus-TCP connector to ingest device data from Modbus-TCP servers, and the EtherNet/IP connector to ingest device data from EtherNet/IP servers. Data export to AWS IoT SiteWise is enabled by default and you can use custom streams to export data to AWS IoT Analytics, Amazon Kinesis, and Amazon S3. You can also use custom streams to send data to Lambda functions to conduct local processing before you export the data. Alternatively, you can create a custom implementation that uses locally deployed Lambda functions to ingest and process device data and then deliver the data to local or cloud targets.

From time to time, AWS will publish updated versions of the AWS IoT Greengrass Core software to provide the following benefits:

• Introduce new or improved features
• Bug fixes
• Security improvements

With AWS IoT Greengrass Over the Air Updates (OTA), customers can get all these benefits without having to manually download and reinstall the AWS IoT Greengrass Core software.

No. You can always choose to download and install updates manually or follow a different software deployment process.

When new versions of AWS IoT Greengrass Core become available, we will announce it on the AWS IoT Greengrass software developer forum. You can find a link to that forum here.

AWS IoT Device Tester for AWS IoT Greengrass is a test automation tool that lets you self-test and qualify AWS IoT Greengrass on your Linux-based devices. AWS IoT Device Tester provides a collection of automated tests that enable you to verify whether devices can run AWS IoT Greengrass and be authenticated by and interoperate with AWS IoT services.

You can get AWS IoT Device Tester for AWS IoT Greengrass here.

AWS IoT Device Tester for AWS IoT Greengrass verifies that the combination of a device’s CPU architecture, Linux kernel configuration, and drivers work with AWS IoT Greengrass by testing the following:

• Required software packages have been installed 
• Linux kernel containing AWS IoT Greengrass required kernel configuration (e.g. kernel configured for cgroups)
• Over the air updates
• Device can connect with AWS IoT services and is able to run AWS Lambda functions
• Local resource access functionality
• Device shadow functionality

Use any of the following channels to get support:

AWS Forum for AWS IoT Greengrass

Premium Support

Customer Support

If you are an AWS partner, the AWS Device Qualification Program defines the process to get your device listed in the catalog. A high level overview of the process is as follows:

1. Pass the AWS IoT Device Tester for AWS IoT Greengrass test
    
2. Log into the AWS Partner Network Portal
    
3. Upload the AWS IoT Device Tester report. Once the report is verified by AWS, and other device related artifacts such as picture and data sheet have been submitted, the device is listed in the AWS Partner Device Catalog.

AWS IoT Device Tester for AWS IoT Greengrass is available in all Regions where AWS IoT Greengrass is available.

AWS IoT Device Tester for AWS IoT Greengrass is free to use. However, you will be responsible for any costs associated with AWS usage as part of testing. A single run of AWS IoT Device Tester that tests on a single AWS IoT Greengrass device will cost less than 20 cents.

Operating systems and CPU architectures supported by AWS IoT Greengrass Core and tested for compatibility by AWS are listed here. Other Linux variants that have not have been validated by the AWS IoT Greengrass team can also successfully run AWS IoT Greengrass. You can validate these variants for compatibility using the IoT Greengrass dependency checker on GitHub. Alternatively, you can run IoT Greengrass in “process mode” which lowers the compatibility threshold, but removes support for Linux containers.

You can run AWS IoT Greengrass Core on a device that meets the minimum hardware and software requirements. You can also self-test your devices to see if they will run optimally with AWS IoT Greengrass and other AWS services using AWS IoT Device Tester. You can also discover and evaluate devices that are compatible with AWS IoT Greengrass in the AWS Partner Device Catalog.

To ensure your devices work with AWS IoT Greengrass Core, you can test it using the AWS IoT Device Tester for AWS IoT Greengrass. You can download the tool and read the documentation.

You can connect devices locally to AWS IoT Greengrass Core using FreeRTOS or the AWS IoT Device SDK. AWS IoT Greengrass discovery is available on the AWS IoT Device SDK via C++, Node.js, Java, and Python 2.7, 3.7, and 3.8. For more information, refer to the AWS IoT Greengrass developer guide. You can use the AWS IoT Greengrass discovery library in your FreeRTOS source code to find and connect to an AWS IoT Greengrass Core device.

AWS IoT Greengrass discovery is available on the AWS IoT Device SDK via C++, Node.js, Java, and Python 2.7, 3.7, and 3.8. For more information, refer to the AWS IoT Greengrass developer guide.

Yes. FreeRTOS devices can connect directly to the cloud or connect to AWS IoT Greengrass. FreeRTOS runs on IoT endpoints and is often responsible for the ‘sensing’ and ‘acting’ in an IoT topology.

AWS IoT Greengrass is software that lets you run local compute, messaging, data caching, sync, and machine learning inference capabilities for connected devices in a secure way. With AWS IoT Greengrass, connected devices can run AWS Lambda functions, Docker containers, or both, keep device data in sync, and communicate with other devices securely—even when not connected to the Internet. Using AWS Lambda, AWS IoT Greengrass ensures your IoT devices can respond quickly to local events, use Lambda functions running on AWS IoT Greengrass Core to interact with local resources, operate with intermittent connections, stay updated with over the air updates, and minimize the cost of transmitting IoT data to the cloud.

FreeRTOS is an open source, real-time operating system for microcontrollers that operates on the edge and does not generally support chipsets that could run AWS IoT Greengrass. These microcontroller devices are found on a variety of IoT endpoints such as fitness trackers, pacemakers, electricity meters, automotive transmissions, and sensor networks. FreeRTOS devices cannot run AWS IoT Greengrass Core but can connect, send, and receive messages to and from an AWS IoT Greengrass Core device for local processing at the edge.

The hardware requirements and operating systems are different on both devices.
 

*Based on an AWS study that used the following JDK: JDK version used for the tests: openjdk version "1.8.0_275", OpenJDK Runtime Environment (build 1.8.0_275-8u275-b01-0ubuntu1~18.04-b01), and OpenJDK 64-Bit Server VM (build 25.275-b01, mixed mode). Memory usage may be higher using different inputs.