Technical Discussion

We recently deployed a feature that passed all tests in our Acceptance environment (functional tests, regression, smoke tests), but after deployment to Production, we encountered issues such as broken functionality, unexpected errors, and performance slowdowns.Here’s the setup:Acceptance and Production environments are as close to identical as possible (same configurations, database versions, and server setups). Automated and manual tests ran successfully in Acceptance. The feature in question interacts with both third-party APIs and a legacy system.However, after deployment to Production, users are facing:API timeouts and failed calls to third-party services. Slower performance in certain areas of the application. Data inconsistencies when interacting with the legacy system.Has anyone experienced a similar issue where everything works fine in Acceptance, but things fall apart in Production? What are some potential causes or overlooked areas that could explain this discrepancy?I’m part

What conferences are you attending this Year?Tell the community so that we may see each other there.

1️⃣ Automated Testing - Let the machines do the work, but at what cost?2️⃣ Manual Testing - Human touch is invaluable, or is it?3️⃣ CI/CD Pipeline Testing - Seamless integration or overkill?4️⃣ Exploratory Testing - Creative freedom or chaotic mess?5️⃣ Test-Driven Development (TDD) - Code-first or test-first?🎯 Vote and defend your choice in the comments!What would you sacrifice, and why? Let the debate begin!

Since we are testers we tend to spot pattern and issues even when we do not want to :smiley: .So i was wondering how do you spot a text that is generated by an LLM/AI.Please do not say I use a scanner.For me the tells are usually these 3* Using the prashe "In the world of"* Using words that one does not usually use in a day to day conversation like delve* The post is marked with emojis all the way.What about you?

In scenarios where your application integrates with real-time data feeds (e.g., stock prices, sensor data), how do you approach automated testing? What tools or frameworks help simulate or validate such real-time interactions?

When running automated tests in parallel, what are the most common challenges you've faced, and how did you overcome issues such as test data dependency or browser state? Do you have any strategies for efficiently managing resources?

AI models often operate as black boxes, making their decisions opaque. How do testers ensure they understand and trust AI-driven test results?

Flaky tests can undermine confidence in automated testing. How do testers identify the root causes and resolve these issues?

I want to share how I use a database for storing results of my database comparison which makes them easy filterable.I started with reports in files (and still have them for sharing and long-term storage), each run typically covering multiple subtopics and creating by that multiple files. And that twice for the new and the old database.Going through each file and looking for the same patterns again and again became laborious. Especial because filtering by fatality was demanding (I marked error classes by different colors while going through the files) . Even more when I wanted to see if similar failures happend over multiple subtopics.Now I can filter and sort for anything I want. By regexes!I also show them to others to discuss my findings.If you haven’t done something similar: Feel inspired to do something similar for yourself! Any question?If you have done something similar: How do you do and use it?This reports seldom last longer than some days. When I changed the report tables (esp

 “LinkedIn Posting Made Easy with API" is a concise and informative video by @IOan. It explores the power of using an Application Programming Interface (API) to simplify and streamline the process of posting content on LinkedIn. With the rise of social media and the importance of professional networking, LinkedIn has become an invaluable platform for individuals and businesses alike. However, manually posting content on LinkedIn can be time-consuming and tedious. In this video, we delve into the benefits of leveraging an API to automate and optimize LinkedIn posting. From integrating your existing systems to seamlessly pushing content updates, the video demonstrates how APIs can enhance efficiency, save time, and expand your reach on LinkedIn. Whether you're a developer, a marketing professional, or an entrepreneur, "LinkedIn Posting Made Easy with API" provides valuable insights and practical tips for leveraging this powerful tool to maximize your LinkedIn presence.

I am experimenting with a new video format and wanted to share it with the community.Here is a video with a really simple yet smart Cypress tricks. 

Hey everyone,Guess what's happening in just two days? Yup, we're hosting a super cool webinar with @danielknott all about AI! 🤖💻 If you've got burning questions about AI and how it's shaking up the testing world, drop them in this chat. We'll make sure Daniel tackles them during the webinar.Get hyped and get those questions flowing! See you there!

In the digital age, passwords have become the first line of defense against cyber threats.Yet, many of us still fall into the trap of using weak and easily guessable passwords.But how easy is it to make a password, you just have to follow the password rules, right? Well…how good are you at following rules?  Have a look at the above video and try the followingWell first try to actually beat the game :) Write in the comment if you were stuck Write how you found the answer to the different rulesWould you use such a password in your daily life?

  In this short video, @IOan provides a concise introduction to accessibility testing, offering clear explanations and key insights.Everything may seem correct at first glance, but Ioan reveals that appearances can be deceiving. Stay tuned as we explore why accessibility testing is crucial, what areas you can test, and how to get started with it. Let's dive into the world of software inclusivity!

Having recently concluded our webinar with David Colwell (link below) I thought it would be good to get opinions from the community about the role of testing in an industry that is rapidly incorporating AI. What do you guys think things are going to look like moving forward? We’re in the early stages of AI integration, but I’m sure everyone expects huge changes over the next few years, and definitely decades. My biggest question is are there any major changes you think will take place that the average person isn’t thinking about? Do you have any hot takes on AI and the way it’s impacting testing and software development? The closest thing I have to a hot take is that I think the AI explosion may end up being more of a sigmoid curve than continual exponential growth:  We’ve seen huge development throughout 2023 with generative AI, but I think it’s possible we see a sort of cooling period instead of the insane jump we saw this year. What do you think? Don’t forget to check out the webina

Hi All,Has anyone integrated ai with testing as for testing the video we would need to use python with deeplearning algorithm.Thanks,Harish n

The general public often conflates various skill sets and abilities found in the tech industry. Many seem to think that in order to be a tester (or to fit in anywhere in the tech sector) you need to know how to code. I myself have found that regardless of what role you’re in, basic knowledge of code and some of its fundamental principles help serve just about any position in a tech environment. It may not be necessary to write or execute in every role, but having some degree of familiarity with how things work under the hood is often helpful in the day-to-day encounters in the field. What do you think? How much coding knowledge does your role require? And are there areas in tech where you don’t think it’s necessary? 

I’ve been wondering lately how much crossover there is in the technologies that testers use. Is the software you use specific to your company, or is it more broad/general use? What have you seen in the industry or in your experience? 

Over the past 10 days, we witnessed an incredible display of skill, dedication, and commitment to the world of DevOps. Let's congartulate the 2 winners of 10 Days of DevOps Challenge.🥇 Winner 1: @IOan  🥇 Winner 2: @hungoboss  Ioan and Hung consistently showcased their deep understanding of DevOps principles and innovative problem-solving. Their contributions have not only elevated their own skills but have also inspired the entire community.But, let's not forget that it's not just about the winners. The entire community that participated in the challenge has grown, learned, and connected over the past 10 Days. Special thanks to @sabarish, @mmario.ffrohlich and @sarmistha for your contributions. Keep challenging yourselves, keep innovating, and keep pushing the boundaries of what's possible in DevOps. Congratulations once again to our champions, and thank you to everyone who made the 10 Days of DevOps Challenge an unforgettable experience! 🚀

Question: How do comprehensive test reports and metrics benefit testers and developers in identifying issues?  Answer in the comments below. Next task will be live tomorrow on Oct.14. 

Question: How does code review help in maintaining high-quality test scripts and fostering collaboration?  Answer in the comments below. Next task will be live tomorrow on Oct. 11.

Question: How does continuous integration help in the DevOps lifecycle, and what are some common CI best practices? Answer in the comments below. Next task will be live tomorrow on Oct. 9.

The topic of "Feature Flags and Feature Toggles: A Strategy for Controlled Rollouts" is a valuable discussion point for developers interested in optimizing their release processes.  What are Feature Flags and Toggles Feature flags (also known as feature toggles) are a development technique that allows you to turn specific features or parts of your application on or off at runtime. They are essentially conditional statements in your code that determine whether a particular feature should be visible or active for end-users. This enables developers to have granular control over feature releases and updates.Do you use features flags?What is your experience with them?Any benefits/drawbacks that you want to share?

What would be considered the similiarities and differences between DevOps and DevSecOps. Will DevSecOps replace DevOps in future?

Some time ago about what is SAST and DAST emerged in one of the community threads which inspired me to write this short article explaining the difference between SAST, DAST, IAST and RASP using a clever analogy.Before we start explaining the terms, try to imagine yourself as a castellan who is concerned about protecting his castle (your computer system) from the savage raiders (cyber threats).Our application is like a castle we have to protect SAST - Static Application Security TestingNaturally, you would want to prevent most of the issues when the castle is not yet built. I mean, it's much easier to change the design of a certain wall before it is built rather than after it's already standing. And how to spot the potential issues? By carefully examining the blueprints and looking for the issues. This is when SAST (Static Application Security Testing) comes into play. When looking for flaws using SAST, the castellan should ask himself questions such as: "Do the walls have the right thi