Welcome to the world of NVIDIA Jetson Nano and AGX Xavier, where machine learning and Kubernetes converge for smart IoT solutions! This guide will walk you through setting up and utilizing these powerful edge devices in a bare-metal Kubernetes cluster. Whether you are a student eager to explore machine learning or an experienced developer looking to lower entry barriers, this blog is for you. Let’s dive in!

Mission Objectives

• Evaluate the feasibility and complexity of running Kubernetes with machine learning on edge devices.
• Provide automation patterns for the Jetson community using Ansible and Kubernetes.
• Offer cost-effective alternatives to cloud services for machine learning students.
• Develop a Jupyter-based infrastructure tailored for Stanford’s CS229 course.
• Have fun while brushing up on deep learning skills!

Setup Essentials

Before we jump into some of the more technical aspects, it’s essential to prepare your hardware. Below, you’ll find shopping lists for both Jetson Nano and Jetson AGX Xavier.

Shopping List for Jetson Nano

• Jetson Nano Developer Kit – ca. $110
• Power Supply – ca. $14
• Jumper – ca. $12
• Micro SDHC Card – ca. $10
• Ethernet Cable – ca. $4
• Optional: M.2 SATA SSD Disk – ca. $49
• Optional: USB 3.0 to M.2 SATA Enclosure – ca. $12

Shopping List for Jetson AGX Xavier

• Jetson Xavier Developer Kit – ca. $712
• M.2 NVMe SSD Disk – ca. $65

Bootstrapping Your MacOS Development Environment

Ready to set things up? Follow these steps:

1. Run make bootstrap-environment on your macOS device. This command will install the required software and configure hostnames.
2. Follow the prompts to install any necessary applications, entering your password as needed.

Provisioning Jetson Devices and Joining Kubernetes Cluster

For Jetson Nanos

1. Execute make nano-image-download to download the NVIDIA Jetpack image.
2. Use balenaEtcher to flash the micro SD card.
3. Connect the Nano to the Ethernet switch of your Kubernetes cluster.
4. Insert the micro SD card in the Nano and power it on.
5. Create a user account with the name 'provision'.
6. Run make setup-access-secure to configure SSH access.

For Jetson AGX Xaviers

1. Execute make guest-sdk-manager-download to download the NVIDIA SDK Manager.
2. Run make guest-build to create a custom kernel.
3. Execute make guest-flash to flash the Xavier.
4. Follow on-screen instructions during the oem-setup process to create a user account.
5. Run make setup-access-secure to configure SSH access.

Building and Deploying Docker Images

Congratulations, you’ve set the groundwork! Let’s look at building and deploying your services:

1. Execute make ml-base-build-and-test to build the base Docker image.
2. Run make jupyter-deploy to deploy a Jupyter server as a Kubernetes pod.
3. Deploy TensorFlow Serving using make tensorflow-serving-deploy.

Understanding the Code through Analogy

Imagine setting up your smart IoT environment like assembling a team of superheroes, each with their unique powers:

• Jetson Nano and AGX Xavier: These are the superheroes who possess amazing abilities to process data at the edge.
• Docker Images: These are their suits; without them, they can’t access their powers effectively in the Kubernetes universe.
• Kubernetes: This is the city where our superheroes operate, providing them the organization and resources needed to maintain order (orchestrate containers).
• Jupyter and TensorFlow Servers: Think of these as specialized training grounds for our heroes, where they hone their skills and improve their abilities!

Troubleshooting

If you encounter issues such as intermittent operation, make sure to:

• Verify that your Jetson Nano is adequately powered; ensure you are using a recommended power supply.
• Check DHCP server settings on your Kubernetes cluster to validate device connectivity.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Looking Ahead

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.