Feed Prometheus with Locust: performance tests as a metrics’ source

How to use load test results as a Prometheus metrics’ source and graph them against cluster resource consumption in Grafana.

#locust #kubernetes #prometheus #load-testing #monitoring #testing

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Feed Prometheus with Locust: performance tests as a metrics’ source

How to use load test results as a Prometheus metrics’ source and graph them against cluster resource consumption in Grafana.

#locust #kubernetes #prometheus #load-testing #monitoring #testing

How to Do API Testing?

Nowadays API testing is an integral part of testing. There are a lot of tools like postman, insomnia, etc. There are many articles that ask what is API, What is API testing, but the problem is How to do API testing? What I need to validate.

Note: In this article, I am going to use postman assertions for all the examples since it is the most popular tool. But this article is not intended only for the postman tool.

Let’s directly jump to the topic.

Let’s consider you have an API endpoint example http://dzone.com/getuserDetails/{{username}} when you send the get request to that URL it returns the JSON response.

My API endpoint is http://dzone.com/getuserDetails/{{username}}

The response is in JSON format like below

JSON

{
  "jobTitle": "string",
  "userid": "string",
  "phoneNumber": "string",
  "password": "string",
  "email": "user@example.com",
  "firstName": "string",
  "lastName": "string",
  "userName": "string",
  "country": "string",
  "region": "string",
  "city": "string",
  "department": "string",
  "userType": 0
}

In the JSON we can see there are properties and associated values.

Now, For example, if we need details of the user with the username ‘ganeshhegde’ we need to send a **GET **request to **http://dzone.com/getuserDetails/ganeshhegde **

Now there are two scenarios.

1. Valid Usecase: User is available in the database and it returns user details with status code 200

2. Invalid Usecase: User is Unavailable/Invalid user in this case it returns status with code 404 with not found message.

#tutorial #performance #api #test automation #api testing #testing and qa #application programming interface #testing as a service #testing tutorial #api test

Where To Learn Test Programming — July 2020 Edition

What do you do when you have lots of free time on your hands? Why not learn test programming strategies and approaches?

When you’re looking for places to learn test programming, Test Automation University has you covered. From API testing through visual validation, you can hone your skills and learn new approaches on TAU.

We introduced five new TAU courses from April through June, and each of them can help you expand your knowledge, learn a new approach, and improve your craft as a test automation engineer. They are:

These courses add to the other three courses we introduced in January through March 2020:

• IntelliJ for Test Automation Engineers (3 hrs 41 min)
• Cucumber with JavaScript (1 hr 22 min)
• Python Programming (2 hrs)

Each of these courses can give you a new set of skills.

Let’s look at each in a little detail.

Mobile Automation With Appium in JavaScript

Orane Findley teaches Mobile Automation with Appium in JavaScript. Orane walks through all the basics of Appium, starting with what it is and where it runs.

“Appium is an open-source tool for automating native, web, and hybrid applications on different platforms.”

In the introduction, Orane describes the course parts:

• Setup and Dependencies — installing Appium and setting up your first project
• Working with elements by finding them, sending values, clicking, and submitting
• Creating sessions, changing screen orientations, and taking screenshots
• Timing, including TimeOuts and Implicit Waits
• Collecting attributes and data from an element
• Selecting and using element states
• Reviewing everything to make it all make sense

The first chapter, broken into five parts, gets your system ready for the rest of the course. You’ll download and install a Java Developer Kit, a stable version of Node.js, Android Studio and Emulator (for a mobile device emulator), Visual Studio Code for an IDE, Appium Server, and a sample Appium Android Package Kit. If you get into trouble, you can use the Test Automation University Slack channel to get help from Orane. Each subchapter contains the links to get to the proper software. Finally, Orane has you customize your configuration for the course project.

Chapter 2 deals with elements and screen interactions for your app. You can find elements on the page, interact with those elements, and scroll the page to make other elements visible. Orane breaks the chapter into three distinct subchapters so you can become competent with each part of finding, scrolling, and interacting with the app. The quiz comes at the end of the third subchapter.

The remaining chapters each deal with specific bullets listed above: sessions and screen capture, timing, element attributes, and using element states. The final summary chapter ensures you have internalized the key takeaways from the course. Each of these chapters includes its quiz.

When you complete this course successfully, you will have both a certificate of completion and the code infrastructure available on your system to start testing mobile apps using Appium.

Selenium WebDriver With Python

Andrew Knight, who blogs as The Automation Panda, teaches the course on Selenium WebDriver with Python. As Andrew points out, Python has become a popular language for test automation. If you don’t know Python at all, he points you to Jess Ingrassellino’s great course, Python for Test Programming, also on Test Automation University.

In the first chapter, Andrew has you write your first test. Not in Python, but Gherkin. If you have never used Gherkin syntax, it helps you structure your tests in pseudocode that you can translate into any language of your choice. Andrew points out that it’s important to write your test steps before you write test code — and Gherkin makes this process straightforward.

The second chapter goes through setting up a pytest, the test framework Andrew uses. He assumes you already have Python 3.8 installed. Depending on your machine, you may need to do some work (Macs come with Python 2.7.16 installed, which is old and won’t work. Andrew also goes through the pip package manager to install pipenv. He gives you a GitHub link to his test code for the project. And, finally, he creates a test using the Gherkin codes as comments to show you how a test runs in pytest.

In the third chapter, you set up Selenium Webdriver to work with specific browsers, then create your test fixture in the pytest. Andrew reminds you to download the appropriate browser driver for the browser you want to test — for example, chromedriver to drive Chrome and geckodriver to drive Firefox. Once you use pipenv to install Selenium, you begin your test fixture. One thing to remember is to call an explicit quit for your webdriver after a test.

Chapter 4 goes through page objects, and how you abstract page object details to simplify your test structure. Chapter 5 goes through element locator structures and how to use these in Python. And, in Chapter 6, Andrew goes through some common webdriver calls and how to use them in your tests. These first six chapters cover the basics of testing with Python and Selenium.

Now that you have the basics down, the final three chapters review some advanced ideas: testing with multiple browsers, handling race conditions, and running your tests in parallel. This course gives you specific skills around Python and Selenium on top of what you can get from the Python for Test Programming course.

#tutorial #performance #testing #automation #test automation #automated testing #visual testing #visual testing best practices #testing tutorial

Top 10 Automation Testing Tools: 2020 Edition

The demand for delivering quality software faster — or “Quality at Speed” — requires organizations to search for solutions in Agile, continuous integration (CI), and DevOps methodologies. Test automation is an essential part of these aspects. The latest World Quality Report 2018–2019 suggests that test automation is the biggest bottleneck to deliver “Quality at Speed,” as it is an enabler of successful Agile and DevOps adoption.

Test automation cannot be realized without good tools; as they determine how automation is performed and whether the benefits of automation can be delivered. Test automation tools is a crucial component in the DevOps toolchain. The current test automation trends have increased in applying artificial intelligence and machine learning (AI/ML) to offer advanced capabilities for test optimization, intelligent test generation, execution, and reporting. It will be worthwhile to understand which tools are best poised to take advantage of these trends.****

#automation-testing #automation-testing-tools #testing #testing-tools #selenium #open-source #test-automation #automated-testing

In-house Tool for Performance Testing

In the software development cycle, testing is one of the important criteria. There are many tools available in this space for testing such as Junit, Jmeter, manual, automation, and many performance testing tools. Some of these tools are third-party tools and have a cost-heavy license for the company to manage. For small start-up companies, these license costs can be unbearable. We analyze a tool to make the process easier and more cost effective.

About the Tool

The tool can have two parts. One part can be making a main interface web page where developers/testers can fill in the details and start testing. The other part can be the onboarding template page, where the team can onboard new applications, templates, and stacks so that it appears on the main interface page.

#performance testing #testing tool #performance test tools #testing