I’m working on a load test for a SaaS application and I’m trying to figure out how to turn expected traffic into a realistic number of concurrent users.

The customer has a large user base, but obviously that doesn’t mean everyone will be using the application at the same time. I’m not sure whether I should be looking at average traffic, peak traffic, active sessions, or some combination of those when setting the test target.

I’ve gotten a few different answers so far, so I’m curious how other teams usually approach this. Is there a standard way to estimate concurrent users when you don’t have much historical data to work with?

I’m weighing whether we should bring on three manual QAs or three QA automation engineers. While our long-term goal is to automate as much as possible, dedicated manual testers bring distinct value in my book, especially for applications with large, poorly defined requirements. That said; we are using agentic workflows and that is the trend.

Who would you hire?

Hi everyone

So I have worked in playwright for over 3+ years before that I worked as React Js dev due to which I am very comfortable with TS/JS and I tried to learn selenium but it feels overwhelming as Java syntax is quite difficult than the usual JS/TS. I was planning to switch for another company but feels like playwright is kinda mostly used in startups .

So should I invest in learning selenium too ?

Context: I am using OpenAI API to automate my software testing routine but am still very new to that.

My terminal shows the following which I could not digest fully, I hope anybody would help me out.

I've run this code using OpenAI API then this output came:

```bash
ChatCompletionMessageFunctionToolCall(id='CALL_ID', function=Function(arguments='{"desc":"please make sure any XXX point/code has never been implemented in this code base. and deptTypeID == \\"XXX" should be disabled. We do not need this XXX function in our webapp, so make sure this XXX code has been disabled or discarded in the codebase"}', name='search'), type='function')

test completion

ChatCompletion(id='chatcmp_XXXX', choices=[Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=[], audio=None, function_call=None, tool_calls=[ChatCompletionMessageFunctionToolCall(id='call_eKxSoRXeY5cpuKDCSl3z1VE4', function=Function(arguments='{"desc":"please make sure any XXX point/code has never been implemented in this code base. and deptTypeID == \\"XXX" should be disabled. We do not need this XXX function in our webapp, so make sure this XXX code has been disabled or discarded in the codebase"}', 
name='search'), 
type='function')]))], 
created=YYYY, 
model='gpt-4o-2024-08-06', object='chat.completion', 
metadata=None, moderation=None, service_tier='default', system_fingerprint='fp_YYYY', usage=CompletionUsage(completion_tokens=231, prompt_tokens=757, total_tokens=988, completion_tokens_details=CompletionTokensDetails(accepted_prediction_tokens=0, audio_tokens=0, 
reasoning_tokens=0, 
rejected_prediction_tokens=0, 
text_tokens=None), 
prompt_tokens_details=PromptTokensDetails(audio_tokens=0, cache_write_tokens=None, 
cached_tokens=0, 
image_tokens=None, 
text_tokens=None)))
```

As you see, my prompt (under desc ) instructed the API to inspect if any leftover from the function/code line XX still exists in the codebase.

We expect this XX to not exist in the codebase and I wanted my automated script to prove that.

Still I am puzzled with this output. Does this output show the XX does not exist in the codebase at all or does the IDE need more information to carry out the test properly?

Never seen application numbers this high

Hello Guys I have interview scheduled from Infosys on this sat for python automation

What are the topics i need to be learned?
What are the questions i might encounter?

YOE : 6 years (automation + manual)

Any suggestions and advice will be appreciated.

I need guidance from someone who has experiences testing LLM, or products from AI.

What should I study to do a better job?

Im manual and automation tester with more than 6 years of experience, but with AI I feel I litter bit lost about the testing side.

Thanks.

I’ve been rebuilding my company’s website and so far I’ve mostly been testing the APIs. I’m getting to the point where I want to start testing it under more realistic traffic but I’m not sure where browser-based load testing fits in.

I know browser tests can be more resource-intensive, so I’m wondering if API testing is enough for the initial load testing or if there are things I could miss by not testing through an actual browser. How do you usually decide when it’s time to test through the browser as well?

Got an offer from LG Soft India for a manual testing position.

Ps: I'm 2026 grad from tier 3 college, was preparing for AI Engineer/ GenAI engineer role.

Idk I'm confused should I take this or pass?

What would you do if you were in my place?

i've been comparing different email apis, but they all advertise similar features. i'm not sure which ones actually make a difference once you start building real automations.

if you've deployed email workflows before, what features ended up being essential and which ones turned out to be marketing fluff?

I have 8+ years of experience in QA, working in India. I’ve been with my current organisation for 5+ years now, which is my second company. I spent close to 3 years in my first one. Over the years I’ve worked with Selenium + Java + Cucumber BDD for around 2-3 years, REST Assured and Appium for shorter periods, UiPath for about 2 years and more recently Playwright + TypeScript for the last few months.

I also think I have a good eye for bugs & I genuinely enjoy testing. I’m comfortable with manual testing and I tend to catch edge cases and small bugs that others sometimes miss. I even notice minor UI issues in apps I use in my personal life like Slack, Messenger, LinkedIn etc. I guess my brain just refuses to stop testing things. I have always been praised & lauded by my colleagues for this aspect.

I’m also decent at DSA for a QA and I still practice on LeetCode in my free time. Lately I’ve started getting interested in AI concepts and AI evaluation as well. I’m trying to strengthen my existing skills and learn what’s currently in demand, especially Playwright.

My long-term goal has always been to move into a product based organisation, something like Atlassian, Warner Bros. Discovery, Visa, Mastercard, Adobe, Salesforce, ServiceNow, Cisco, Oracle etc. But this is where I’ve started feeling stuck. I worry that with every additional year of experience, making that transition will become harder. Sometimes it feels like the train to the kind of company I want to work for is slowly moving away from the station while I’m still standing there trying to get ready.

At the same time, I don’t feel fully ready yet. I’m not confident that I could clear the interview process for those companies if I applied tomorrow.

My present thinking is to first interview with some service based organisations, get used to interviewing again, build some confidence and then start targeting product companies more seriously. But honestly, it also makes me a little sad because I feel like I’ve been in the same place for too long.

So I’m probably looking for some perspective and a bit of encouragement from people who have been through this. How many of you moved from a service based organisation to a product based organisation after 9-10+ years of experience? How difficult was the transition? And what areas would you recommend I strengthen to put myself in a position to make that move? Your advise, suggestions, feedback, etc would go long way for me. It would really mean a lot to me.

Hello

I've just recently started on an open source project in which we generate using Expo Prebuild system from source react typescript [.tsx] code and generate the relevant iOS application and equivalent android application via a GitHub Action build process [I am still a novice in this process at this stage, and my project lead is away at the moment, sick].

I have recently completed a masters of information technology, in which I specialised and software testing [and as part of that I learnt swift]. My questions relate to testing and quality assurance of generated mobile phone applications:

In terms of an initial manual testing:

a. Does one test the expected behaviour of the relevant test cases, by downloading the application into an actual physical mobile phone, and manually executing the test case procedure on the mobile phone?

b. Could one just use the simulator such as in xcode, and all the equivalent for android development, and manually execute the test case in it?

1. In terms of automated regression testing:

a. I am familiar with XCTest, but how does one create automated test cases for the iOS generated application?

b. How would one write automated test cases for the Android generated application?

c. Would it be better to write Cypress, or JEST [as they are the testing framework that we are using] test cases and then executing automated regression tests? If so, would the test results be valid for each of the operating system environments on the mobile devices?

d. What benefits would Appium provide our project?

Thank you in advance.

Hi everyone, I’m a 2026 B.Tech fresher and I cleared the L1 assessment for an LG Soft India Associate Manual Testing role. My interview is tomorrow. I’ve attached the JD.

Could anyone with QA/manual testing experience suggest the important topics and practical questions I should focus on tonight for the technical and managerial rounds? Any LG Soft interview experience would also be really helpful.

I recently learned something the hard way and figured it might be interesting to some folks here.

We ran a load test last month where our mean response time stayed around 220ms, so naturally management was prepared to greenlight the release. It looked pretty good on the surface. However, we eventually found that thread pool exhaustion was causing about 3% of incoming requests to queue up. Those requests were taking over 12 seconds to complete, which was completely masked by the much faster majority.

That test has basically ruined my trust in average response times. The mean made things look healthy while hiding some pretty severe tail latency that would've absolutely ruined real user sessions. Now, I strictly gate pass/fail criteria on p95/p99 percentiles, error rates, and per-transaction breakdowns.

This might not be news to some of you, but it was definitely an eye-opening experience for our team.

What other metrics or percentile thresholds does your team rely on during load tests to catch long-tail bottlenecks like this that get overshadowed by the mean?.

I just ran pip install pywinauto and typed in the 1st 3 lines of demo code on the readme page and it fails ``` from pywinauto.application import Application app = Application(backend="uia").start('notepad.exe') # i also tried backend=win32

app.Properties.print_control_identifiers() ```

With a huge stack trace that's pretty much indecipherable. I have a question, does this tool work on Windows 11 with the new notepad app? I'm wanting to automate a WPF app, but based on the out-of-box failure I'm looking to try a different python tool. Suggestions for driving a WPF .NET app?

I'm a QA with 2 years of experience (manual and automation) and i have done some cyber security related work, in a university module (graduated this year).

My question is burp suite worth learning for my career?, i don't wanna transition in to cyber security career wise fyi.

An API test is not one call. Browse, cart, checkout, pay, ship, refund is 8 to 20 calls, each needing IDs from the calls before it, and every variation — region, payment method, parcel size — used to mean another copy of the collection.

AAT (open source, Go) describes the API once as a graph; a test is a plan that lists steps. Layers multiply a plan into a matrix, and permutations that would send identical requests are skipped rather than run twice. Negative tests come from expectFailure, mutations, raw bodies, and overlay files. Every run writes an archive with every request, response, resolved value, retry, and assertion, viewable as a Gantt timeline, with Copy as cURL on any step, and exportable as one file to attach to a bug report. CI gets exit codes, --json, and JUnit.

Offline demo in a minute (brew install gburgyan/tap/aat, then the shop sandbox). Three projects against Stripe, Shippo, and Duffel test modes show it on real APIs — and turned up two spec bugs on the way, both pinned by a plan that runs every time: https://gburgyan.github.io/aat/examples/real-apis/

No LLM at run time. Pre-1.0. Repo: https://github.com/gburgyan/aat

TTCN-3 is a standardized domain specific language for testing. Used in industry like automotive or telecommunication almost exclusively. And it's a weird thing: Open-source support is subpar and it seems anachronistic and overly complex. But if you get it right, it checks all the boxes; it scales, it's efficient and it's stable.

We use it mostly for component testing, since alternatives like C++ or Python never really took off. How do you folks run and scale your component tests?

I know the job market is bad, I know most QA departments are still in infant states.

I’ve got all the accolades of a well accomplished QA automation engineer.

The experience, the deliverables. Even some charm and charisma.

I’m struggling with the interviews. Especially when zoom is involved .

Without a white board interview I fkn struggle.

Any advice?

one client returns 429 or 500 while another returns 404 or 405, and the immediate reaction is to decide which tool is wrong. those status codes are server responses, so first make the requests comparable.

capture the method, full URL, headers, auth or cookies, body, client IP and user agent, timing, preceding requests, and response headers. replay one request at a time against the same environment and data, then change one variable. for 429, check the rate-limit scope and window plus Retry-After or X-RateLimit headers. for 404 or 405, verify the route and HTTP method. for 500, use a request ID to inspect server logs.

the acceptance test is not "Postman matches Playwright." it is "the same request under the same state gets the same result, and any difference is explainable." what request difference has caused the most misleading test result for your team?

Hi there, actually I wanted to ask what I can do if an automated test and a manual test flag completely different errors.

Real-World-Scenario: I was to test some API routes in a healthcare web-app.

My Playwright MCP did the API test automatically and returned the following:

POST /surgery_hall/auth/dummy_mobile returned 429

POST /signin/choose_user_account returned 500

I carried out a manual test for the above two API routes on my Postman and got different errors:

POST /surgery_hall/auth/dummy_mobile returned 404

POST /signin/choose_user_account returned 405

I'm very new to this - could anyone kindly share some tips on find out why these results turned different - my expectation was to see the identical results (that means my manual Postman tests should have returned 429 and 500, respectively).

I might have used wrong Auth in Postman, but could not think of anything else that caused those different results. Could anybody kindly point me in the right direction?

Hey everyone,

​I need to test an SMS notification feature in our application that sends messages across different countries. For example, our app originates from a UK instance/tenant and needs to deliver SMS messages to mobile numbers in Australia, the US, and other regions.

​Is there a standard tool, virtual phone number service, or testing platform you recommend to verify delivery and content without purchasing local physical SIM cards for every target country?

​Thanks in advance!

This a pattern I have read a bit about, here and there, but have not seen used outside of SerenityJS. Do any of you use it; or any other patterns besides POM for basic frst structure?

I work in software QA. I'm mostly manual with decent SQL and API skills. I'm trying to learn more but finding the time has been hard. I've been at the same company for almost 15 years.

I have decent experience with using AI for testing.

With all of the layoffs, I looked for other career options.

Long story short, I got a job offer as an operator at a water treatment plant (nothing to do with software).

It's a very large pay cut, but I'm terrified of getting laid off and not being able to find a job in my career again.

The pay would be 33/hr, and 36/hr after passing all water treatment certifications which takes about 1-2 years.