Appium Money, AI Test Generation, Kubernetes Trends and More TGNS122

Do you know what open source tool now has a contribution payment program? Have you seen the first OpenAI Test Generation LLM? And what are some of the hottest trends in kubernetes? Find out in this episode of the Test Guild News show for the week of May 26th. So grab your favorite cup of coffee or tea and let's do this before we get into it. If you haven't already, please make sure to subscribe to Our Test Guild LinkedIn New Show Newsletter that I'll have a link for down below and never miss another episode. So exciting news in Appium. Appium has just introduced a sponsorship program for its contributors and recognized partner companies. Through open Collective, individuals and organizations can donate various tiers receiving benefits like recognition, Appium's documentation and websites and the funds will be distributed monthly to project maintainers, contributors and upstream projects, fostering community growth. So for testers, you're going to benefit from enhanced support and resources, improving project stability and recognition for your contributions. And as you probably know, financial incentives can motivate active participation and innovation within the Appium community. So really great sign from Appium. If you do anything with Appium, check that out in the comments down below. So, want to know more about an open source AI test gen LLM? Let's check it out. So last week Codeum announced that it has developed and released the first open source implementation of Meta's TestGen LLM, a tool aimed at enhancing automated unit test coverage. And this follows the February publication by Meta researchers of a paper on automating unit tests improving large language models that we covered back in February. And the new tool integrates with Codium AI's open source project Cover Agent, promising to improve test coverage with assured improvement over existing code bases. So this is really cool because now you can use TestGen LLM to generate tests that compile, run correctly and help you increase code coverage. It also can help you with tool validation tests, then updates the test suite until the code meets coverage criteria or reaches maximum iterations. It also helps you with challenges like languages like Python, which require precise indentation of code. AI's open source implementation of Meta's test gen LLM offers a really great tool for testers to check out to maybe enhance or maybe augment their test case generation and coverage. Obviously not to replace it, but but also help foster community collaboration for ongoing advancements. What works and what doesn't to help you test better? Definitely check this out as well. Let me know your thoughts. And also another company has availed more AI technology and this one is with Smart Beer. So Smart Beer has unveiled Halo AI, which is a new AI driven technology designed to help software developers and testers. This article goes over how Halo AI aims to automate repetitive and complex tasks, significantly boosting productivity and innovation within development teams and some key points in this article is in beta testing, Halo AI reduced test times by 98% and automated half of QA tests, saving 20 hours per regression cycle. It also goes over how Halo AI integrates with Gen AI technology to address talent shortages and enhance team capabilities. SMAPYA emphasizes improved customer experiences by enabling teams to work faster and and more efficiently. And the technology is part of smartphone broad AI strategy which includes previous innovations in automated regression tests and AI powered test management and you can find out more about this in the links down below. So can you use APIs as an alternative to end to end tests? Maybe so let's check out this next article and Ivan let me know. They just released this article if you don't know Ivan is a principal QA engineer and test automation coach and in this article he highlights a new approach to testing APIs offering an alternative to the traditional end to end test. And instead of relying solely on external tests that mimic real world API consumptions, developers can now implement internal tests using Node js, Express JS and the Supertest library. And he goes into detail how this approach grants greater control over the testing environments by allowing the API to be tested from within its code base and this enables the use of mocking for various components, enhancing the flexibility and accuracy of test. And while traditional end to end tests remain crucial for validating API functionality in real environments, combining them with internal tests like this can provide a more comprehensive testing strategy. Really cool technique that you should definitely check out if you're doing anything with API testing. So you want to know about trends and predictions for 2024 when it comes to Kubernetes. If so, here's an article you definitely should read as well. And this is how in 2024 Kubernetes management is evolving with new trends and predictions that aims to streamline, secure and optimize container orchestration. So some trends you need to know is number one is GitOps adoption. GitOps uses Git for declarative infrastructure and applications, enhancing version control and automation. Number two is kubernetes native tools Specialized tools for Kubernetes are becoming more popular. Policy as code defining security policies as code that ensures consistent enforcement and reduces human error. Number four is automated vulnerability scanning five is service mesh usage six is AI machine learning integrations to help you with predictive management, resource allocation and security anomaly detection. Number seven they go over is edge computing and number eight is resource optimization and sustainability. And these developments really ensure that testers can maintain high standards of security efficiency and flexibility and managing and testing kubernetes environments. I know a lot of you are dealing with, so definitely check out this article and see if it helps you so I was really excited when I saw this next article. It's all about a Java based load testing tool you all should be using, but I think you may not have been using it for this exact reason. Now you have no excuse. So Gatling, which is a popular open source load testing tool, has launched a new JavaScript and TypeScript SDK doubling its accessibility for developers. This new SDK allows developers to write load test in JavaScript and compile them and run on Java virtual machines, leveraging Gatling's powerful multi threading capabilities. And this update I think really broadens Gatling's user base by enabling JavaScript developers to to utilize familiar syntax and tools from the NPM registry while harnessing the performance features of gatling. And the JavaScript SDK integrates seamlessly with Gatling's robust code base and supports the Gatling Recorder, an application that captures browser based user actions and converts them into load testing scripts. And this tool simplifies the process for new users and enhances the script capabilities for more complex scenarios. So if you're using JavaScript and you haven't checked out Gatling yet, this is your chance to do so. And you can find a link for this in the links down below. All right, I came across this new announcement scrolling through my LinkedIn feed where I saw this by Amjad who talked about how Hound Dog has officially launched Emerging from Stealth Mode, which announced its first series seed round of funding. So what is Hound Dog AI? Well, this new platform aims to help data security by offering proactive measures to prevent personal identification information. And as you know, traditional reactive approaches often fail to keep up with the rapid code based changes leading to costly data breaches and compliance issues. With Hound Dog AI, they created to address this by using advanced AI to detect sensitive data flows and generate records of processing activities for GDPR compliance. So it helps you with a bunch of things. So the first one is the AI powered scanner identifies PII leaks before they reach production, reducing the risk of data breaches. It also has comprehensive data mapping which allows the platform to provide detailed data flow reports which are essential as you know for GDPR and also has seamless integrations within your CICD pipelines. So I'm always curious about companies that acquire other companies because it gives me a signal of where we're going in certain industries and this next article goes over how bugcrowd acquired Informer to boost attack service management. So bugcrowd is one of the leading crowd security platforms and it has acquired Informer, which is an external attack surface management vendor, to enhance its visibility and security capabilities for customers. This article goes over how this acquisition aims to integrate Informa's advanced technology into bugcrowd's platform, providing better insights into digital assets and improving the scope of penetration testing and bug bounty programs. And Informa's technology, which goes beyond simple DNS scans, will help understand and secure their attack service more effectively, particularly benefiting sectors like healthcare that rely heavily on third party assets. All right, for links of everything of value we covered in this news episode, head on over to the links in that comment down below. So that's it for this episode of the Test Guild News Show. I'm Joe. My mission to help you succeed in creating end to end full stack pipeline automation awesomeness. As always, test everything and keep the good. Cheers.