Developer Guide

Intel® Developer Cloud for the Edge Container Playground

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ID 772269
Date 9/27/2022
Public
Document Table of Contents
Document Table of Contents x
Intel® Developer Cloud for the Edge Container Playground
Intel® Developer Cloud for the Edge Container Playground x
Introduction Marketplace Develop Build Test What’s New? Concepts Marketplace (QuickStart) Test Containers Import Code and Build Containers Develop Containers in JupyterLab Enable Cloud Storage Available Hardware Frequently Asked Questions Known Limitations About containers, helm-charts and docker-compose Notices and Disclaimers Provide Feedback
Test Containers x
Import containers from registries Configure imported containers Select Hardware and Launch Containers Test with helm-charts Test with docker-compose View status, output and performance
Import Code and Build Containers x
Build with dockerfiles Build from application source without dockerfiles
Develop Containers in JupyterLab x
Run OpenVINO™ notebooks Access OpenVINO™ utilities Build containers from terminal
Intel® Developer Cloud for the Edge Container Playground

Intel® Developer Cloud for the Edge Container Playground

This guide is designed to help you get familiar with all the capabilities of the Intel® Developer Cloud for the Edge Container Playground. Use the Notes at the end of each section to try out working examples of each capability.

Introduction

The Intel® Developer Cloud for the Edge Container Playground extension enables you to seamlessly develop, build and test cloud-native container applications on various target deployment hardware.

  • Intel® Xeon® and Intel® Core™ processors

  • Intel® Processor Graphics including Intel® Iris® Xe

The Container Playground can be used to securely test, optimize and enhance your applications before deploying your solution on a cloud service provider or locally on edge devices.

Marketplace

To get started, try out the full-stack reference implementations, configurable AI Solutions, notebooks to learn about OpenVINO™ API or use samples as building blocks for your custom solutions.

Develop

Use the JupyterLab environment to download, convert or optimize pre-trained models from supported deep learning frameworks with the Intel® Distribution of OpenVINO™ Toolkit.

Build

Import your source code hosted in a git repository and build your container images directly from the application source or Dockerfiles.

Test

Benchmark your existing container images imported from container registries. You can also test your multi-container solutions with docker-compose files and helm charts.

Get an overview using the Quick tour option.

NOTE:
  • Current release supports CPUs and integrated GPUs.
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