GitHub Copilot Tutorial | How useful is it for Cloud and DevOps?

TechWorld with Nana

27 Mar 202443:42

TLDRThe video tutorial explores the utility of GitHub Copilot for software engineers and Cloud/DevOps engineers. It explains that GitHub Copilot is an AI assistant for coding integrated into code editors like Visual Studio Code, which suggests code based on the current context of the files open in the editor. The video demonstrates common use cases, such as generating code for creating multiple AWS S3 buckets or EC2 instances, and highlights the limitations, including the tool's outdated information as of September 2021. The host also compares GitHub Copilot with Pulumi AI, showing that while Copilot can assist with code generation, it is not up-to-date with the latest infrastructure as code tools and practices. The video concludes by emphasizing that Copilot is a valuable tool for speeding up certain coding tasks but should not replace a developer's knowledge and understanding of the tools and technologies they are working with.

Takeaways

🤖 GitHub Copilot is an AI assistant for coding that integrates into code editors like Visual Studio Code, providing code suggestions and autocompletion based on the context of the current files open in the editor.
🔍 Copilot uses an open AI large language model trained on billions of lines of code and text, allowing it to offer suggestions aligned with best practices.
📚 The context provided to GitHub Copilot is limited to the files currently open in the editor, which is an advantage as it focuses on the relevant code without needing the entire workspace.
🚀 GitHub Copilot can be particularly useful for writing code, but it may have limitations when it comes to infrastructure as code, due to the rapid pace of development in that domain.
🆓 For certain groups like open-source maintainers, teachers, and students, GitHub Copilot is available for free, which is checked on a monthly basis.
💻 To use GitHub Copilot, you need a GitHub account, and it can be integrated into Visual Studio Code via an extension.
📝 Copilot can help translate code from one language or framework to another, although the output may vary and requires validation against current documentation.
⏱️ One of the key benefits of GitHub Copilot is the ability to generate code based on natural language descriptions, speeding up the coding process.
🗓️ A significant limitation of GitHub Copilot is that its information may be outdated, particularly for rapidly evolving tools and languages, which requires developers to verify the suggestions against the latest documentation.
🗣️ GitHub Copilot can also be used with voice commands through extensions like Visual Studio Code Speech, allowing for a hands-free coding experience.
✅ It's important to note that GitHub Copilot is designed to assist rather than replace a developer's knowledge and expertise, acting as a co-pilot rather than a pilot in the coding process.

Q & A

What is GitHub Copilot and how does it assist in coding?
-GitHub Copilot is an AI assistant for coding that integrates with code editors or integrated development environments like Visual Studio Code. It helps users write code within the editor by providing code suggestions, autocomplete, and even comments based on the context of the current files open in the editor and the code that has been written.
How does GitHub Copilot's context-aware feature work?
-GitHub Copilot's context-aware feature works by considering the existing code that the user has written and the current code being written as context. It does not upload the entire workspace to maintain privacy and relevance, but rather uses the files currently open in the editor and the active file where the user is working.
What are some limitations of using GitHub Copilot for infrastructure as code?
-GitHub Copilot has limitations when used for infrastructure as code because its knowledge base may be outdated. It is trained with data up to a certain date, and since infrastructure as code tools evolve rapidly, the suggestions provided by Copilot may not reflect the latest best practices or features.
How does GitHub Copilot ensure privacy when using code suggestions?
-GitHub Copilot allows users to configure privacy settings. Users can choose whether to allow GitHub Copilot to generate code suggestions based on public repositories on GitHub and decide if the prompts and context used by Copilot can be collected, retained, and processed by GitHub and Microsoft to improve the tool.
What are the prerequisites for using GitHub Copilot with Visual Studio Code for infrastructure as code projects?
-To use GitHub Copilot with Visual Studio Code for infrastructure as code projects, you need an AWS account, Pulumi installed locally, Python installed locally, Visual Studio Code, and the GitHub Copilot extension for Visual Studio Code. You also need a GitHub account to access GitHub Copilot.
How can GitHub Copilot help in translating Terraform code to Pulumi code?
-GitHub Copilot can assist by generating Pulumi code that replicates the functionality of the provided Terraform code. It can help in understanding and translating configurations from one infrastructure as code language to another, which can be beneficial for migration projects.
What is the significance of the date mentioned in the context of GitHub Copilot's knowledge base?
-The date mentioned, September 2021, signifies the last update to GitHub Copilot's knowledge base. This means that any changes, updates, or new features released after this date will not be reflected in the suggestions provided by Copilot.
How does Pulumi AI compare to GitHub Copilot in terms of providing up-to-date configurations?
-Pulumi AI is specifically designed for Pulumi and is more up-to-date than GitHub Copilot, providing configurations that reflect the latest features and best practices of Pulumi. It is a more suitable tool for generating current and accurate Pulumi configurations.
What is the role of GitHub Copilot in explaining complex code?
-GitHub Copilot can analyze complex code and provide explanations for what the code is doing. This can be particularly useful for developers who are new to a codebase or need to understand unfamiliar code quickly.
What are some additional features of GitHub Copilot when used with Visual Studio Code?
-In addition to code suggestions and autocomplete, GitHub Copilot can also be used for voice commands through an extension like Visual Studio Code Speech, allowing users to dictate commands to the editor.
How does GitHub Copilot handle the execution of infrastructure as code configurations?
-GitHub Copilot does not execute infrastructure as code configurations. It provides suggestions and code snippets that the user can incorporate into their code. The execution of the code is done through the respective infrastructure as code tool, such as Pulumi, which will then interact with the cloud platform to provision resources.

Outlines

00:00

🤖 Introduction to GitHub Copilot

The video begins with an introduction to GitHub Copilot, an AI assistant for coding that integrates into code editors like Visual Studio Code. It discusses the tool's ability to make the work of software and cloud DevOps engineers easier and faster. The focus is on how GitHub Copilot can assist in cloud and DevOps engineering tasks, and it is compared to other AI tools like Cat GPT. The video also explains how GitHub Copilot uses context from the user's current code files to provide suggestions and answers.

05:02

🚀 Setting Up GitHub Copilot and Prerequisites

The second paragraph outlines the setup process for using GitHub Copilot, including the need for an AWS account, Pulumi installation, Python, Visual Studio Code, and the GitHub Copilot extension. It also covers the process of signing up for GitHub Copilot with a free trial and configuring privacy settings regarding code suggestions and data retention.

10:03

🔧 Activating GitHub Copilot in Visual Studio Code

This section details the steps to activate GitHub Copilot within Visual Studio Code. It includes installing the GitHub Copilot extension and signing in to link the extension with the user's GitHub Copilot account. The paragraph also covers initializing a new Pulumi project using the Pulumi CLI and setting up a Python environment for AWS infrastructure provisioning.

15:03

📝 Using GitHub Copilot for Coding Assistance

The video demonstrates how to use GitHub Copilot for generating code snippets and writing infrastructure configurations. It shows how to request code generation for creating multiple S3 buckets and EC2 instances within a loop. The paragraph also highlights the convenience of inline suggestions and the ability to control the flow of suggestions using comments.

20:04

🧩 Translating Terraform to Pulumi with GitHub Copilot

The speaker discusses the limitations of GitHub Copilot when used for translating Terraform code to Pulumi, given that the tool's information may be outdated. It shows an attempt to translate a Terraform script that provisions a VPC and EKS cluster into Pulumi code, noting the importance of validating configurations against up-to-date documentation.

25:05

📚 Understanding and Translating Terraform Code with GitHub Copilot

This part of the video focuses on using GitHub Copilot to understand and translate Terraform code into Pulumi Python code. It emphasizes the importance of checking the generated configurations against the latest documentation due to the potential for outdated information from GitHub Copilot. The video also compares GitHub Copilot's output to that of Pulumi AI, noting that Pulumi AI provides more up-to-date configurations.

30:08

🗣️ Using GitHub Copilot with Voice Commands

The final paragraph explores a unique use case for GitHub Copilot: using voice commands to interact with the AI. Although the official GitHub extension for voice commands has been discontinued, the video demonstrates using a third-party extension called Visual Studio Code Speech to dictate commands to GitHub Copilot. This feature is presented as a potential time-saver for complex or lengthy code requests.

35:09

📉 Executing Pulumi Code and Reflecting on GitHub Copilot's Utility

The video concludes with the execution of Pulumi code using Pulumi AI's configurations, which are more up-to-date than those provided by GitHub Copilot. It reflects on the limitations and utility of GitHub Copilot, particularly for rapidly evolving tools and languages in the DevOps field. The speaker encourages viewers to share their experiences with AI tools in the comments section.

Mindmap

Keywords

💡GitHub Copilot

GitHub Copilot is an AI assistant for coding that integrates with code editors or integrated development environments (IDEs) like Visual Studio Code. It assists developers by providing code suggestions and autocompletions based on the context of the code being written. In the video, it is discussed in the context of its utility for software engineers, Cloud DevOps engineers, and its limitations when used for infrastructure as code.

💡Infrastructure as Code (IaC)

Infrastructure as Code refers to the practice of defining and provisioning IT infrastructure using machine-readable files instead of manual processes. Tools like Pulumi and Terraform are used for IaC. The video explores the use of GitHub Copilot for writing IaC, highlighting its advantages and the challenges due to the rapid pace of change in IaC tools.

💡Pulumi

Pulumi is an IaC tool that allows users to define cloud resources using programming languages like Python. In the video, Pulumi is used to create AWS infrastructure, and the integration of GitHub Copilot with Pulumi is demonstrated to show how it can assist in writing Pulumi code.

💡Visual Studio Code

Visual Studio Code (VS Code) is a popular source-code editor developed by Microsoft that supports debugging, Git control, and syntax highlighting. It is used as the IDE for integrating GitHub Copilot in the video, showcasing how developers can use it to enhance their coding workflow.

💡Code Suggestions

Code suggestions are a feature of GitHub Copilot that provides developers with proposed code snippets based on the context of their current work. The video demonstrates how GitHub Copilot offers code suggestions, which can speed up the coding process by predicting what the developer might want to write next.

💡Autocomplete

Autocomplete is a feature that predicts and suggests the completion of a line of code as a developer types. GitHub Copilot uses this feature to enhance productivity by reducing the amount of typing required and by providing suggestions that fit the current context of the code.

💡Security Group

A security group in AWS is a virtual firewall that controls inbound and outbound traffic to AWS resources like EC2 instances. The video discusses how GitHub Copilot can suggest creating security groups with specific configurations, which is a critical aspect of setting up infrastructure securely.

💡Amazon Machine Image (AMI)

An Amazon Machine Image is a pre-configured virtual machine image, provided by AWS, that can be used to launch EC2 instances. The video mentions AMIs in the context of creating EC2 instances and how GitHub Copilot can help in suggesting the use of specific AMIs for different instance types.

💡Outdated Information

The video points out that one of the limitations of GitHub Copilot is that its information may be outdated, particularly for rapidly evolving tools like Pulumi. This can lead to developers using older versions of libraries or functions that may not be best practice or even supported.

💡EKS Cluster

EKS stands for Amazon Elastic Kubernetes Service, which is a managed service that makes it easy to run Kubernetes clusters. The video demonstrates the process of creating an EKS cluster using Pulumi and how GitHub Copilot can assist in translating Terraform code into Pulumi code for an EKS cluster.

💡Voice Assistant

The video mentions a feature of Visual Studio Code called 'Speech', which acts as a voice assistant. It allows users to speak commands to their editor, and GitHub Copilot can respond to these commands. This feature is showcased as a unique way to interact with the code editor, although it may not be commonly used in a team setting.

Highlights

GitHub Copilot is an AI assistant for coding that integrates within code editors like Visual Studio Code.

Copilot uses an open AI large language model trained on billions of lines of code and text.

It provides code suggestions and autocomplete features as you type, predicting your next steps based on context.

GitHub Copilot takes the currently open files in your editor as context for its suggestions.

For infrastructure as code, Copilot can be more helpful for writing code rather than specific configurations.

GitHub Copilot can generate code for simple tasks, like creating multiple S3 buckets in a loop.

It can suggest code comments and block configurations, aiding in explaining or writing code.

Copilot's suggestions can be influenced and directed using comments within the code.

GitHub Copilot has a limitation as it may provide outdated information, especially for rapidly evolving tools.

It is essential to verify Copilot's suggestions against the latest documentation to ensure they are up-to-date.

GitHub Copilot can assist in translating code from one infrastructure as code tool to another, like Terraform to Pulumi.

Pulumi AI is a more up-to-date tool for generating Pulumi configurations, compared to GitHub Copilot.

Copilot can be used to explain complex code snippets, which is beneficial for understanding unfamiliar code.

GitHub Copilot is not a replacement for knowledge but a tool to speed up the coding process.

The tool can be particularly useful for generating boilerplate code and explaining logic in a human language.

Visual Studio Code Speech extension can be used with GitHub Copilot for voice commands, offering an alternative interaction method.

GitHub Copilot is free for open source maintainers, teachers, and students, with a monthly verification check.

Users can control GitHub Copilot's data retention policies, deciding whether their code context is collected and processed.

Copilot provides a chat interface within the editor for asking questions and receiving code suggestions.

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