Build ML Workflow Pipelines with Flyte and gRPC on Google Cloud C4A Axion processors
Introduction
Understand Flyte and gRPC ML workflows on Google Axion
Create a Google Axion C4A Arm virtual machine
Install Flyte and gRPC tools on Axion
Build a gRPC feature engineering service
Create ML Training Workflow
Execute and validate the ML pipeline
Understand the distributed ML architecture
Next Steps

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Provision Google Axion infrastructure

In this section you’ll create a Google Axion C4A arm64 virtual machine on Google Cloud Platform. You’ll use the c4a-standard-4 machine type, which provides 4 vCPUs and 16 GB of memory. This virtual machine hosts your Flyte ML Workflow with gRPC applications.

Note

For help with GCP setup, see the Learning Path Getting started with Google Cloud Platform .

Provision the virtual machine in Google Cloud Console

To create a virtual machine based on the C4A instance type:

  • Navigate to the Google Cloud Console .
  • Go to Compute Engine > VM Instances and select Create Instance.
  • Under Machine configuration:
    • Populate fields such as Instance name, Region, and Zone.
    • Set Series to C4A.
    • Select c4a-standard-4 for machine type.

Image Alt Text:Screenshot of the Google Cloud Console showing the Machine configuration section. The Series dropdown is set to C4A and the machine type c4a-standard-4 is selectedConfiguring machine type to C4A in Google Cloud Console

  • Under OS and storage, select Change, and then choose an arm64 operating system image.
    • For this Learning Path, select SUSE Linux Enterprise Server.
    • For the license type, choose Pay as you go.
    • Increase Size (GB) from 10 to 100 to allocate sufficient disk space.
    • Select Choose to apply the changes.
  • Under Networking, enable Allow HTTP traffic and Allow HTTPS traffic
  • For some organizations not using the ‘default’ network interface, you may need to select the network appropriate for your organization.
  • Select Create to launch the virtual machine.

After the instance starts, select SSH next to the VM in the instance list to open a browser-based terminal session.

Image Alt Text:Google Cloud Console VM instances page displaying running instance with green checkmark and SSH button in the Connect columnConnecting to a running C4A VM using SSH

A new browser window opens with a terminal connected to your VM.

Image Alt Text:Browser-based SSH terminal window with black background showing Linux command prompt and Google Cloud branding at topTerminal session connected to the VM

What you’ve learned and what’s next

In this section:

  • You provisioned a Google Axion C4A arm64 virtual machine with 4 vCPUs and 16 GB of memory
  • You configured the VM with SUSE Linux Enterprise Server and 100 GB of storage
  • You connected to your VM using SSH through the Google Cloud Console

Your virtual machine is now ready to host Flyte ML Workflow with gRPC.

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