Utilizing ZBL object Store
This page provide details about modifying you docker images of micrservices which are to be onboarded onto ZBL AI-Microcloud in order to utilize and interact with ZBL object storage through them.
Ai-MicroCloud has a feature called Datasets. This feature uses respective object storage technology provided by the cloud providers in the backend. Users can upload their data and use it for development and production. Here is the link https://computationaldocs.zeblok.com/info/data-and-metrics/datalake/datasets of how to use the dataset feature using UI. Also, you can check the video at the end of the link on mounting the dataset with Ai-Workstation.
To mount the dataset with Ai-Microservices, follow the steps below:
User needs to use the following "shell script" inside the microservice to access the datasets within Ai-MicroCloud. Please copy the script to the machine where you will create your docker image.
Create a Dockerfile User needs to use the given environment variables, install required packages and include the above script inside your existing dockerfile.
Below is the example of Dockerfile:
All the env values will be picked up from backend. User doesn’t have to add env variables while spawning the microservice
Check whether dataset is mounted "Once you onboard the microservice and spawn it, you should see the dataset on path /app/bucket"
Before the last step once the image is created please follow the link to onboard your newly created microservice onto the ZBL AI-Microcloud
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