Azure IoT Edge
Azure IoT Edge moves analytics and logic out of the cloud and onto your on-premises devices. Using a cloud interface, you can deploy either Azure service logic or your own code to devices without having to physically access them. And offline capabilities mean that you can extract business insights anywhere, without worrying about maintaining constant communication with a cloud service.
More details about the services are available in the documentation.
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Make IoT-Edge (V2+) usable (again) in products which require both OnPrem and OnDemand deploy
In many industries (e.g. medical, energy, aeronautics) companies must produce products that can also be installed in environments where no internet connectivity is available/permitted. These same products however, are also often installed in places where they can leverage cloud (OnDemand) capabilities. If IoT-Edge ist to be applicable for such products, it must (by design) provide for:
1. Installation from download or USB-stick including configuration via config file or local API (as did Edge V1)
2. Provide and abstraction layer to the external communication (as was done via Edge V1 Modules) enabling a configurable routing to use OnPremises endpoits (REST) or…56 votesHi Richard, item #3 has been addressed with the public preview of extended offline feature work. You can find out more about it at the blog post below. The rest of the issues you raise will take longer for us to add to the product.
https://azure.microsoft.com/en-us/blog/extended-offline-operation-with-azure-iot-edge/
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Store Private key for X.509 based DPS securely on HSM
Use the X.509-based enrollment in DPS in IoTEdge without storing the private key on file system.
The idea is to store the Private Key in a HSM and let it never leave.
At this moment, the x.509 provisioning mode only supports a private key on the file system...
23 votes -
(Cloud-triggered) IoT Edge Runtime Updates
Provide a way of an (automatic) cloud-triggered update mechanism for the IoT Edge Runtime through IoT Hubs Device Management. Providing update capabilities not only for the containers but for the runtime and even the underlying OS is crucial for IoT Scenarios.
16 votes -
ARM Python SDK for Azure IoT Edge
Make the Python SDK for creating IoT Edge Modules also available for ARM cpu's and Windows.
The vast selection of python libraries, and ARM devices with python support, makes it an ideal choice for rapid development of Edge Modules.
7 votesThe Python SDK is going through a rewrite at the moment. Once that is complete it will be supported on both Linux and Windows. You can find a preview of the rewrite at – github.com/Azure/azure-iot-sdk-python-preview
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Low bandwidth / partially connected: message delivery priority
For scenarios with low bandwidth and connectivity issues sending messages in the FIFO order of the message cache after being offline is not working. We need a way to specify "important" messages (delivery priority) that needs to be sent before trying to send all other messages from the msg cache. Specifying different TTL values for different priorities would be necessary as well.
6 votes -
Issue iotedge commands from Azure
It would be great to issue iotedge commands from Azure on specific devices. Especially the "iotedge logs" command to see what is happening on a device remotely.
6 votesHere are a couple logging related commands that you can run from the cloud.
https://docs.microsoft.com/en-us/azure/iot-edge/how-to-edgeagent-direct-method
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Any plans to support Yocto on ARM32?
This post: https://docs.microsoft.com/en-us/azure/iot-edge/support indicates that Yocto on ARM32 is not supported. Will it be? And, if so, will the ARM Python SDK for IoT Edge (suggested here: https://feedback.azure.com/forums/907045-azure-iot-edge/suggestions/34976278-arm-python-sdk-for-azure-iot-edge) work on Yocto?
6 votesWe have published preview layers for IoT Edge on Yocto – https://github.com/azure/meta-iotedge. There is still work to be done before this becomes a Tier 1 OS; however you can start playing with it and providing feedback now.
As far as Python support, you should probably be able to build a Yocto image that supports Python. You’ll have to include the layers required by the Python SDK. This SDK is going through a rewrite at the moment; however you can see a preview at – https://github.com/Azure/azure-iot-sdk-python-preview
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Support for aarch64 based platforms
It would be great if support could be extended for deploying the run time on aarch64 based platforms, a lot of industrial platforms being launched on the market are based on Cortex-A53.
5 votesPreview support for ARM64 is available in the 1.0.8 release.
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Log a Warning if messages are deleted from the StoreAndForward/offline cache (because of TTL)
Currently there is no way to figure out that messages were deleted because of the Time To Live/TTL StoreAndForward configuration. There should be a warning in the Logs if this happens to hint the deletion of messages that were not sent to IoT Hub. Ideally there is a configurable second warning before this happens (e.g. 10 minutes before messages get deleted because of TTL).
In addition it would be great to add more control to the StoreAndForward/Caching/Queuing functionality of messaging - refer to ideas https://feedback.azure.com/forums/907045-azure-iot-edge/suggestions/33534802-more-options-or-configuration-parameters-of-stor and https://feedback.azure.com/forums/907045-azure-iot-edge/suggestions/36632884-low-bandwidth-partially-connected-message-deliv3 votesWe are currently adding the ability to pull metrics from the runtime so that customers can understand how their Edge devices are performing in the field. Message drops due to TTL is one of the metrics we’ll be exposing. I do not expect this feature for a few months, likely 1.0.10.
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Local Edge N+M high availability and scalability (no cloud connection required after setup)
1) Deploy Edges as local clusters such that they can suffer failure and there is a high availability strategy that doesn't require a cloud connection.
2) Edge scalability to horizontally add nodes to the Local Edge Cluster. Maybe it kind of behaves like Docker Swarm. i.e. Say I have a pretty intense preprocessor for data prep before handing it to ML Inference. That could get scaled out across multiple nodes in a Local Edge Cluster.
3 votesOur public preview of IoT Edge integration with Kubernetes is the first step towards running IoT Edge on clusters.
https://docs.microsoft.com/en-us/azure/iot-edge/how-to-install-iot-edge-kubernetes
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