What you'll learn
- How to Deploy your Machine Learning Service using the Truefoundry Python SDK.
- How to Enable Autoscaling to ensure optimal service scalability.
Upon completion of this guide, you will have successfully deployed a machine learning service to tackle the MNIST problem. Your service's deployment dashboard will resemble the following:
The MNIST Challenge involves recognizing handwritten digits from images. In this guide, we will use the MNIST dataset, which consists of a large number of labeled handwritten digit images. Our goal is to train a machine learning model that can accurately classify these digits.
To deploy a machine learning service using the Python SDK and follow this guide, let's start by spinning up a Jupyter Lab instance on Truefoundry via the UI. Then, open the mnist-service notebook from the getting started folder in the Jupyter Lab directory navigation and follow along with that notebook.
- On the left panel of the TrueFoundry user interface, locate and click on the "Deployments" tab. From here, navigate to the "Services" tab located in the top bar.
- Click on the "New Deployment" button, and a form will appear with various deployment options. Click on the "Service" button to select service deployment (will be pre-selected)
- In the same form there will be a field "Where would you like to deploy?" option. Click on the "Search Workspace" bar, and select the desired workspace for your deployment.
If you don't have any workspace right now, you can create a new workspace by clicking the Create New Workspace link and following along this Documentation or contact your cluster admin in case of some issues
- Once selected click on the "Next Step" button to continue with the deployment.
Once you initiate the deployment, a form will appear with the configurations for your Jupyter Lab instance. Follow these steps to configure your deployment:
- In the deployment form, you will need to provide a name for your notebook.
- Leave the other configurations as the defaults.
- Click on the "Submit" button.
This action will initiate the process of bringing up your JupyterLab instance. After waiting for a few seconds, your notebook should become available.
- With the notebook successfully launched, you'll see the endpoint URL for accessing your JupyterLab instance. Click on the endpoint URL.
- This action will open the JupyterLab interface in your browser.
- In the JupyterLab navigation, locate the "getting-started" folder, then go to the "mnist-service" subfolder.
- Inside the "mnist-service" subfolder, find and click on the notebook named "python-sdk-mnist.ipynb".
Follow along with the notebook to continue with the deployment process using the Truefoundry Python SDK.
Updated 8 days ago