Hi !
In my (spanish) podcast I often complain that we always speak about JavaScript and Docker. And, it also applies to my blog. After my yesterday’s post, someone asked
How we can create a folder on the creation process of the Azure IoT module?
This is not an Azure IoT question, is mostly a docker one. And the answer is easy, just add these lines to create and grant permissions to a folder named [fsexchange]
# create folder for file exchange
RUN mkdir /fsexchange
RUN chown 1000 /fsexchange
RUN chmod 700 /fsexchange
RUN chown 1000 /.
RUN chmod 700 /.
And, you need to do this in each one of the docker definition files that you may use. Like
- Dockerfile.amd64
- Dockerfile.arm32v7
- Dockerfile.arm64v8
- Dockerfile.windows-amd64
- Dockerfile.amd64.debug
- Dockerfile.arm32v7.debug
- Dockerfile.arm64v8.debug
And that’s it! super easy!
Happy coding!
Greetings
El Bruno
References
- Give modules access to a device’s local storage
- Mapping a local ☁ Azure IoT Edge folder module with an Edge device folder 📁
Azure ☁ IoT
- Install ☁ Azure IoT on Raspberry Pi
- Deploy ☁ Azure Blob Storage on IoT Edge, lessons learned
- Connect to ☁ Azure Blob Storage on IoT Edge using Microsoft Azure Storage Explorer
- Lesson learned and tips on how to install Azure IoT Edge on Ubuntu on a Raspberry Pi
- Azure IoT Explorer, in preview and awesome
- Mapping a local ☁ Azure IoT Edge folder module with an Edge device folder 📁
- Creating a folder 📂 in the docker definition in an ☁ Azure IoT Edge
- Granting access to Raspberry Pi GPIO from an ☁ Azure IoT Edge Module
Create an Azure IoT Module using Raspberry Pi and Grove Sensors
- Raspberry Pi + Grove Sensors, read temperature and humidity values
- Raspberry Pi + Grove Sensors, send temperature and humidity values as telemetry to Azure IoT Hub
- Raspberry Pi + Grove Sensors, create a Azure IoT Module to send temperature and humidity values as telemetry to Azure IoT Hub
- Raspberry Pi + Grove Sensors, publish and use the Azure IoT Module
Create an Azure IoT Module from Azure Custom Vision project
- Create and export a Custom Vision Project as Docker image
- Analyze the content of the CV Docker image
- Create and analyze an Azure IoT Module
- Merge the CV project as an Azure IoT Module
- Deploy to an Azure IoT device and test the CV module
- Send telemetry for each analyzed image
- Add digital twin configuration to the Azure IoT module (coming soon)
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