What is AWS IoT Greengrass?
AWS IoT Greengrass extends AWS to edge devices. The open source runtime enables local data processing, ML inference, and secure communication between devices, even when cloud connectivity is interrupted. Greengrass automatically synchronizes data once the connection is restored.
Greengrass uses a component model: you deploy pre-built AWS components or custom components from the cloud to edge devices. Software can run as a Lambda function, Docker container, native operating system process, or in a custom runtime. Updates are centrally managed and automatically rolled out.
AWS currently recommends AWS IoT Greengrass Version 2; support for Version 1 ends on October 7, 2026.
Core Features
- Run Lambda functions, containers, or native processes locally on edge devices
- ML inference with models optimized for the target hardware (e.g., via SageMaker Neo) and frameworks like TensorFlow Lite
- Local messaging between devices via IPC and MQTT
- Stream Manager for reliable, prioritized data transfer to the cloud
- Centrally managed OTA updates for components
Typical Use Cases
Industrial Automation: Production machines are monitored and controlled locally. Greengrass responds quickly to sensor events, even during cloud outages. Data is buffered locally and synchronized later.
Computer Vision at the Edge: Cameras analyze images locally with ML models. Only relevant results are sent to the cloud, saving bandwidth and reducing latency.
Remote Locations: Offshore platforms, wind farms, or mines with intermittent connectivity use Greengrass for autonomous operation.
Benefits
- Low latency through local processing
- Works offline with automatic synchronization
- Central management of large fleets of edge devices via components and deployments
- Secure OTA updates without physical access
Integration with innFactory
As an AWS reseller, innFactory supports you with AWS IoT Greengrass: edge architecture, component development, ML deployment, fleet management, and migration from Greengrass V1 to V2.
Typical Use Cases
Frequently Asked Questions
What is AWS IoT Greengrass?
AWS IoT Greengrass is an open source edge runtime and cloud service for building, deploying, and managing IoT applications on devices. Devices can process data locally, run ML models, and react autonomously to local events, even without a continuous internet connection.
Which version of Greengrass should I use?
AWS recommends AWS IoT Greengrass Version 2, the current architecture with a component model and flexible runtime support (Lambda, containers, native processes). Support for Greengrass Version 1 ends on October 7, 2026; existing customers should migrate in time.
What does AWS IoT Greengrass cost?
Greengrass is billed on a pay-as-you-go basis per active core device per month, with a limited free tier in the first year. Additional standard costs apply for AWS services used, such as IoT Core connectivity and messaging or data storage. Exact prices are listed on the official AWS pricing page.
Can I run ML models on edge devices?
Yes, Greengrass supports ML inference with models optimized for the target hardware, for example via Amazon SageMaker Neo, as well as frameworks like TensorFlow Lite. Models are deployed from the cloud and run locally with low latency, for example for computer vision or predictive maintenance.
Note: All product information on this page has been compiled with care, but is provided without guarantee and may be outdated or incomplete. Cloud services evolve rapidly — features, pricing, SLAs, and availability change frequently. Authoritative and up-to-date information can only be found on the official product page of AWS (official documentation). This page does not represent an offer by AWS.