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New Relic One Programmability Online Training



Join us for this exclusive 90-minute introduction to the fundamentals of New Relic One Programmability. This training will introduce you to the key concepts and walk you through developing New Relic Applications.

The training is based on the self-paced material freely available on New Relic GitHub and delivered by a New Relic facilitator who will guide you through the introduction of the first 3 of the 10 labs available. This session allows for active questions and answers and facilitated troubleshooting when code or environments act unpredictably.


This New Relic One training assumes no specific software engineering or developer experience; each lab comes with a fully completed functional solution that participants can copy into the lab repo to complete the activity. The labs are designed to promote experimentation by changing variables, layouts, data access methods, and UI components allowing each participant to comfortably experiment with the material to gain familiarity. Whether you are new to or rusty at programming or JavaScript, or happen to be an expert React.js developer; this training will provide important context to start you on the journey of developing New Relic Applications. 

Must have:

Permissions to install 

Git installed

Node installed

A text editor or IDE of your choice (we will be using VS Code)

Nerdpack manager role to deploy

Technical exercises include exposure to the following technical topics:

  • Installing the New Relic command-line interface (CLI) on local workstation

  • Setting New Relic API developer access credentials

  • Accessing GitHub repositories and cloning existing NR1 applications

  • Executing New Relic CLI commands

  • Making GraphQL and Web Service requests

  • JavaScript layouts  

During this session we will review the following topics:

  • Installation of New Relic CLI and Environment setup

  • Familiarisation with New Relic One Application component model and lifecycle

  • Advanced UI construction and data processing

  • Individual self paced experimentation and Open Source example deployment

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