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-powered coding assistant integrated into code editors like Visual Studio Code. The tool uses context from the user's current codebase to provide suggestions and auto-complete features, which can speed up the coding process. However, the video highlights that GitHub Copilot may not be fully up-to-date, especially for rapidly evolving tools like infrastructure as code platforms. It also demonstrates the tool's ability to translate Terraform code into Pulumi Python code, though with the caveat that the user must verify the suggestions against current documentation. The video concludes by noting that while GitHub Copilot can expedite certain coding tasks, it is not a replacement for a developer's expertise and should be used as a co-pilot rather than a pilot in the coding process.

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 context.
  • 🔍 Copilot uses an open AI large language model trained on billions of lines of code and text, offering suggestions aligned with best practices.
  • 📚 The context for GitHub Copilot is limited to the currently open files in the editor, which is an advantage as it doesn't require the entire workspace to be uploaded.
  • 🚀 Copilot is particularly useful for writing code, but it has limitations when it comes to infrastructure as code, where tools and libraries can become outdated quickly.
  • 🆓 For certain groups like open-source maintainers, teachers, and students, GitHub Copilot is available for free, checked on a monthly basis.
  • 💻 To use Copilot, you need a GitHub account, and it can be integrated into Visual Studio Code via an extension.
  • ✅ Copilot can generate code snippets that match public repositories on GitHub and provide details about the matching code, including license and source.
  • 📝 It's important to review and validate code suggestions from Copilot, as the tool may provide outdated information or configurations.
  • 🔄 For migrating projects, Copilot can assist in translating code from one infrastructure as code tool to another, like from Terraform to Pulumi.
  • 📈 Pulumi AI is a more up-to-date tool for generating Pulumi configurations, which might be more beneficial for certain tasks compared to Copilot.
  • 🎤 An interesting feature of Visual Studio Code is the ability to use voice commands with extensions like Visual Studio Code Speech, which can interact with Copilot.

Q & A

  • What is GitHub Copilot and how does it function within a code editor?

    -GitHub Copilot is an AI assistant for coding that integrates into a code editor or an integrated development environment, such as Visual Studio Code. It assists in writing code within the editor, providing context-aware suggestions based on the existing code and the current file being worked on. It uses an open AI large language model trained with billions of lines of code and text to offer suggestions and complete code based on best practices.

  • How does GitHub Copilot handle the context of the code it is assisting with?

    -GitHub Copilot considers the existing code, whatever has been written, and the current file open in the editor as context. It does not upload the entire workspace, but rather the relevant files currently being worked on, to provide accurate and context-aware assistance.

  • What are some limitations of using GitHub Copilot for infrastructure as code scenarios?

    -GitHub Copilot may provide outdated information since its knowledge base is not always up to date with the latest developments in infrastructure as code languages or tools. It is also less consistent for infrastructure as code due to the rapid pace of change in the field compared to more established programming languages.

  • How can GitHub Copilot be beneficial for someone who is new to a codebase or a programming language?

    -GitHub Copilot can help new developers by providing code suggestions, explanations, and even translations from one programming language or framework to another. It can also explain complex code segments, making it easier for newcomers to understand and work with existing code.

  • 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 installed in Visual Studio Code. You also need a GitHub account to access GitHub Copilot.

  • How does GitHub Copilot ensure privacy and security when retaining the context used for code suggestions?

    -Users can configure GitHub Copilot to decide whether the prompts and context used to generate code are collected, retained, and processed by GitHub and shared with Microsoft. This is an important consideration for maintaining the privacy and security of sensitive code or data.

  • What is the role of GitHub Copilot in helping with the migration from one infrastructure as code tool to another?

    -GitHub Copilot can assist in translating code from one infrastructure as code tool to another. For example, it can help convert Terraform code to Pulumi code, although the user must validate the translated code against the latest documentation due to potential outdated information in GitHub Copilot's knowledge base.

  • How does Pulumi AI compare to GitHub Copilot in terms of providing up-to-date configurations for infrastructure as code?

    -Pulumi AI is specifically designed for use with Pulumi and provides more up-to-date configurations compared to GitHub Copilot. It is informed with the latest state of Pulumi and can generate configurations that include default settings automatically, making it a better choice for Pulumi users.

  • What is the process of installing the GitHub Copilot extension in Visual Studio Code?

    -To install the GitHub Copilot extension in Visual Studio Code, you need to go to the Extensions tab, search for 'GitHub Copilot', select the official extension from GitHub, and install it. After installation, you must sign in to GitHub Copilot to authorize Visual Studio Code to access Copilot.

  • How can GitHub Copilot assist in writing code without using the chat or command line interface?

    -GitHub Copilot provides inline code suggestions as you type in the editor. It can autocomplete code based on the context and your partial input, offering predictions for what you might want to write next. Additionally, it can suggest comments and code blocks based on the current context of your project.

  • What is the importance of checking GitHub Copilot's suggestions against official documentation?

    -It is crucial to verify GitHub Copilot's suggestions against official documentation to ensure that the code and configurations provided are up to date and accurate. This is especially important in rapidly evolving fields like infrastructure as code, where outdated information can lead to errors or suboptimal configurations.

Outlines

00:00

🤖 Introduction to GitHub Copilot for Cloud and DevOps Engineers

The video begins with an introduction to GitHub Copilot, an AI assistant for coding that integrates within code editors like Visual Studio Code. It discusses whether GitHub Copilot is a revolutionary tool that can simplify the work of software engineers or even replace the need for engineers in some cases. The focus is on its application for cloud and DevOps engineers and compares its value to software development. The video outlines the basic functionality of GitHub Copilot, its context-aware code suggestions, and the fact that it uses an open AI model trained on billions of lines of code.

05:02

📋 Setting Up GitHub Copilot and Prerequisites

The second paragraph covers the setup process for using GitHub Copilot. It includes creating an AWS account, installing Pulumi locally, installing Python, and setting up Visual Studio Code. The video also guides viewers on how to sign up for GitHub Copilot, including the availability of free access for certain groups like open-source maintainers, teachers, and students. It explains the configuration options regarding code suggestions and data retention policies.

10:03

🔑 GitHub Copilot's Data Handling and Integration with Visual Studio Code

This part discusses GitHub Copilot's data handling policies, emphasizing security considerations when using the tool. It then demonstrates how to integrate GitHub Copilot into Visual Studio Code by installing the extension and signing in. The video also shows how to create a new Pulumi project using the Pulumi CLI and setting up an access token for Pulumi.

15:03

🚀 Using GitHub Copilot for Coding Assistance

The video demonstrates how to use GitHub Copilot for coding assistance. It shows how to generate code for creating multiple S3 buckets in a loop and how to use inline suggestions for code configuration. The video also illustrates how to ask GitHub Copilot for specific code blocks and how it can provide code suggestions based on comments within the code.

20:04

🧱 Limitations of GitHub Copilot for Infrastructure as Code

The video highlights a significant drawback of using GitHub Copilot for infrastructure as code, which is that its information is outdated as of September 2021. It explains that this can lead to using older versions of operating systems and libraries, which is not ideal for infrastructure provisioning. The video also emphasizes the importance of checking and updating configurations against the latest documentation.

25:05

🔄 Migrate Terraform to Pulumi with GitHub Copilot

The video explores using GitHub Copilot to assist in migrating a project from Terraform to Pulumi. It shows how to ask GitHub Copilot to explain Terraform code and translate it into Pulumi Python code. However, it also points out that the responses from GitHub Copilot can lack consistency and may still require manual updates to be current.

30:08

🗣️ Using GitHub Copilot with Voice Commands

The video concludes with a demonstration of using GitHub Copilot with voice commands through the Visual Studio Code Speech extension. It shows how to dictate commands to GitHub Copilot and receive code suggestions in response. The video also discusses the limitations of using voice commands in a professional setting and the potential benefits for complex scenarios or when a user prefers speech over typing.

35:09

📝 Final Thoughts on GitHub Copilot's Usability

The final paragraph summarizes the video's exploration of GitHub Copilot's capabilities and limitations. It acknowledges that while GitHub Copilot may not be as revolutionary as initially expected, especially for rapidly evolving tools like Pulumi, it still offers some value in specific use cases. The video encourages viewers to share their experiences with GitHub Copilot or other AI assistant tools in the comments section.

Mindmap

Keywords

💡GitHub Copilot

GitHub Copilot is an AI-powered code assistant that integrates with code editors or integrated development environments (IDEs), such as Visual Studio Code. It helps developers write code by providing suggestions and auto-complete options based on the context of the code being written. In the video, it is discussed in the context of its usefulness for cloud and DevOps engineers, highlighting its ability to generate code snippets and improve productivity.

💡DevOps

DevOps is a set of practices that combines software development (Dev) and IT operations (Ops) to shorten the system development life cycle and provide continuous delivery with high software quality. In the video, the role of GitHub Copilot in facilitating the work of DevOps engineers is explored, particularly in relation to infrastructure as code.

💡Infrastructure as Code (IaC)

Infrastructure as Code is a DevOps methodology that involves managing and provisioning computing infrastructure through machine-readable definition files, rather than physical hardware configuration. The video discusses the application of GitHub Copilot in writing IaC, especially when using tools like Pulumi and Terraform.

💡Pulumi

Pulumi is an open-source infrastructure as code (IaC) platform that enables developers to create, deploy, and manage cloud infrastructure using familiar programming languages like Python, TypeScript, and Go. The video demonstrates how GitHub Copilot can assist in writing Pulumi code for AWS infrastructure provisioning.

💡Terraform

Terraform is an IaC tool developed by HashiCorp that allows users to define and provision data center infrastructure using a declarative configuration language known as HashiCorp Configuration Language (HCL). The video includes a scenario where GitHub Copilot is used to translate Terraform code into Pulumi code.

💡Code Suggestions

Code suggestions refer to the feature of GitHub Copilot where it provides developers with potential code snippets based on the context of their current work. This feature is highlighted in the video as a significant time-saver and aid in the coding process, especially when writing complex or unfamiliar code.

💡Security Group

A security group in the context of cloud computing, particularly AWS, is a virtual firewall that controls inbound and outbound traffic to AWS resources like EC2 instances. The video script mentions GitHub Copilot suggesting the creation of a security group as part of the infrastructure provisioning process.

💡EKS (Amazon Elastic Kubernetes Service)

Amazon EKS is a fully managed service by AWS that makes it easy to run Kubernetes clusters. The video discusses the use of GitHub Copilot in generating configurations for setting up EKS clusters, which is a common task for cloud engineers and DevOps practitioners.

💡Auto Scaling

Auto Scaling is a feature in cloud environments that automatically adjusts the number of computing resources based on the demand. In the video, the concept is mentioned in the context of configuring EKS node groups to automatically scale the number of instances.

💡Outdated Information

The video points out that one of the limitations of GitHub Copilot is that its training data is outdated, which can lead to the generation of code snippets that use older or unsupported versions of libraries or tools. This is particularly problematic for rapidly evolving fields like cloud computing and DevOps.

💡Pulumi AI

Pulumi AI is a tool within the Pulumi platform that provides up-to-date assistance for creating Pulumi configurations. The video contrasts GitHub Copilot with Pulumi AI, noting that the latter is more current and better suited for generating configurations for Pulumi projects.

Highlights

GitHub Copilot is an AI assistant for coding that integrates within a code editor or IDE, such as Visual Studio Code.

Copilot provides code suggestions and explanations based on the context of your current project files.

It uses an open AI large language model trained with billions of lines of code and text for suggestions.

GitHub Copilot can predict and provide autocomplete suggestions as you type your code.

For infrastructure as code, GitHub Copilot can be more helpful than for writing traditional code due to its context-aware suggestions.

GitHub Copilot can generate code for creating AWS resources, like S3 buckets, based on user prompts.

The tool can suggest code comments and block configurations, enhancing code quality.

GitHub Copilot has limitations, particularly in staying up-to-date with rapidly evolving infrastructure tools.

It is essential to verify Copilot-generated code against the latest documentation due to potential outdated information.

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

Copilot can explain complex code snippets, aiding in understanding and migrating projects.

The tool can be used to generate boilerplate code, speeding up the initial setup process.

GitHub Copilot is not a replacement for in-depth knowledge but a tool to augment the development process.

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

GitHub Copilot can be used for voice commands through extensions like Visual Studio Code Speech, offering an alternative interaction method.

The tool provides a chat interface for requesting specific code or explanations, fostering a more conversational coding experience.

GitHub Copilot is free for open source maintainers, teachers, and students, encouraging wider adoption among these groups.