Api Performance Testing With K6, Github Copilot, Chatgpt

Api Performance Testing With K6, Github Copilot, Chatgpt
Published 4/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English

| Size: 4.42 GB[/center]
| Duration: 8h 28m
Learn Grafana K6 for REST API performance testing, with the help of Generative AI Assistant (Github Copilot, ChatGPT)

What you'll learn

Learn how AI like ChatGPT and Github Copilot change the software testing landscape

Using AI Assistant (ChatGPT, Github Copilot) on Visual Studio Code to do REST API testing using Grafana K6

Understand performance testing basics

Prompt Engineering for AI, to help you working faster, and more efficient during K6 software testing

Write checks, thresholds, and various Grafana K6 aspects from zero

Requirements

Basic jаvascript knowledge

Basic knowledge of REST API

Description

Explore the frontier of REST API performance testing in this course, designed to empower you with the knowledge to use Grafana K6 for REST API testing enriched with the support of AI assistants. This course covers everything from the basics of K6 to advanced testing techniques, including how to effectively use GitHub Copilot and ChatGPT to improve your automated testing skills with Grafana K6.Start with a warm welcome and an intriguing introduction to AI and Large Language Models. Delve into the course structure and absorb the crucial points guiding your learning path. Your adventure gets more interesting as you explore the integration of AI assistants in software engineering and testing using the capabilities of ChatGPT and GitHub Copilot. With the basics in hand, you'll examine the source code structure, laying the groundwork for comprehensive performance testing. As you progress, the course introduces you to performance testing with K6, starting with installation and your first script execution. Each step, from executing commands on the K6 Command Line with test options flags, is enhanced by AI assistance. The curriculum expands to cover essential tools and concepts like Docker, using software for testing, and using Postman for API interactions. You'll navigate HTTP requests with and without AI support, understand K6 checks and metrics, and learn how to visualize K6 results for insightful analysis. Further refinement of your skills is achieved through lessons on thresholds, tags, and custom tags, each benefiting from AI integration. The course then shifts focus to practical application, guiding you through debugging K6 scripts, adding test data, and mastering data correlation—all with the invaluable support of AI assistants. Advanced topics introduce handling insecure requests, managing HTTP redirects, executing parallel requests, and defining custom metrics. Each module showcases the power of AI to simplify complex tasks. Groups, test lifecycle management, and environmental variables are also discussed, cementing your comprehensive understanding of performance testing. While most of the courses use GitHub Copilot as AI assistance, you will also see how to use ChatGPT with K6, offering a practical application of earlier lessons and presenting advanced strategies in command line usage, test options, HTTP requests, checks, thresholds, and more, all through the lens of AI assistance.This course equips you with the technical skills for API performance testing and empowers you with innovative strategies to harness AI tools for enhanced testing efficiency and effectiveness.Why Buy This Course?Embrace the future of software testing with AI integration.Master Grafana K6, a leading tool in API performance testing.Benefit from hands-on learning with practical projects and examples.Enhance your problem-solving skills in API testing with AI insights.Keep up with industry trends by learning to integrate AI assistants in testing.What You'll Learn:Setting up and configuring Grafana K6 for API testing.Effective use of GitHub Copilot and ChatGPT for writing and optimizing test scripts.Many techniques for performance testing and result analysis.Customizing test environments.Utilizing AI for creating and improving test accuracy and efficiency.Student Requirements:A basic understanding of jаvascript and REST API concepts.Curiosity about AI and its applications in software testing.Interest in enhancing software performance through rigorous testing.Who is This Course For:Developers and Engineers seeking advanced skills in API testing.QA and Testing Professionals want to incorporate AI into their workflows.Tech enthusiasts who are curious about the synergy between AI and REST API performance testing.

Overview

Section 1: Welcome To The Course

Lecture 1 Welcome

Lecture 2 Course Structure & Coverage

Lecture 3 How To Get Maximum Value From This Course

Section 2: AI (Artificial Intelligence) and LLM (Large Language Models)

Lecture 4 About AI & Large Language Models (LLM)

Lecture 5 Important Points on Course With AI Assistant!

Lecture 6 Download Prompts & Source Code

Lecture 7 Prompt Engineering

Section 3: How AI Assistant Change The Way We Work

Lecture 8 AI Assistant in Software Engineering

Lecture 9 AI Assistant in Software Testing

Lecture 10 ChatGPT & Github Copilot

Lecture 11 ChatGPT & Github Copilot - Installation

Section 4: K6 for API Performance Testing

Lecture 12 Source Code Structure

Lecture 13 Performance Testing

Lecture 14 Performance Testing & K6

Lecture 15 K6 Installation

Section 5: K6 Basics

Lecture 16 Hello K6

Lecture 17 Hello K6 - With AI Assistant

Lecture 18 K6 Command Line

Lecture 19 K6 Command Line - With AI Assistant

Lecture 20 Using sleep(n)

Lecture 21 Using sleep(n) - With AI Assistant

Lecture 22 Test Options (Flags)

Lecture 23 Test Options (Flags) - With AI Assistant

Section 6: Other Tools for Software Quality Engineer

Lecture 24 What & Why Docker

Lecture 25 Software To Test

Lecture 26 Trouble on Software To Test?

Lecture 27 Postman

Section 7: K6 For Testing HTTP REST API - The Basic

Lecture 28 Working With HTTP

Lecture 29 Working With HTTP - With AI Assistant

Lecture 30 Checks

Lecture 31 Checks - With AI Assistant

Lecture 32 Metrics

Lecture 33 K6 Result - How To Read

Lecture 34 K6 Result - Output & Visualization

Lecture 35 Tips: Showing p(N) at Output

Lecture 36 Thresholds

Lecture 37 Thresholds - With AI Assistant

Lecture 38 Tags

Lecture 39 Tags - With AI Assistant

Lecture 40 Custom Tags

Lecture 41 Custom Tags - With AI Assistant

Section 8: K6 For Testing HTTP REST API - Intermediate

Lecture 42 Working With AI Assistant

Lecture 43 Modules - With AI Assistant

Lecture 44 Debugging K6 Script

Lecture 45 Adding Test Data - With AI Assistant

Lecture 46 Data Correlation - With AI Assistant

Lecture 47 Tips: Allow Insecure Request

Lecture 48 HTTP Redirect - With AI Assistant

Lecture 49 Parallel Request - With AI Assistant

Lecture 50 Custom Metrics - With AI Assistant

Lecture 51 Groups - With AI Assistant

Lecture 52 Test Lifecycle - With AI Assistant

Lecture 53 Environment Variable - With AI Assistant

Section 9: Using ChatGPT With K6

Lecture 54 Using ChatGPT With K6 - Introduction

Lecture 55 ChatGPT K6 - Hello K6

Lecture 56 ChatGPT K6 - K6 Command Line

Lecture 57 ChatGPT K6 - Test Options

Lecture 58 ChatGPT K6 - Working With HTTP

Lecture 59 ChatGPT K6 - Checks

Lecture 60 ChatGPT K6 - Thresholds

Lecture 61 ChatGPT K6 - Tags Custom Tags

Lecture 62 ChatGPT K6 - Modules

Lecture 63 ChatGPT K6 - Test Data

Lecture 64 ChatGPT K6 - Data Correlation

Lecture 65 ChatGPT K6 - HTTP Redirect

Lecture 66 ChatGPT K6 - Parallel Call

Lecture 67 ChatGPT K6 - Custom Metrics

Lecture 68 ChatGPT K6 - Groups

Section 10: Resources & References

Lecture 69 Resources & References

Lecture 70 Bonus

Software engineers,Software testers / Quality engineers,Technical / QA managers