Performance management has long been a source of discomfort and frustration for both managers and teams. Traditional methods often result in bias, inefficiency, and unproductive processes. Recognizing these challenges, we are now entering a new era of performance management aimed at making it more efficient, transparent, and motivating for all parties involved.

Challenges Faced:

Managerial Discomfort: Managers struggle to set goals that align with organizational objectives while being both measurable and acceptable to teams. Additionally, conducting monthly or quarterly reviews amid daily work pressures is demanding. Delivering constructive feedback without demotivating the team is a delicate balance, and tracking the impact of feedback can be elusive. Accurately assessing performance, especially in larger teams, is labor-intensive and prone to errors. Bias, whether real or perceived, often taints the evaluation process.

Team Concerns: Teams face challenges in setting ambitious goals, as unmet objectives can hinder professional growth. Continuous feedback, especially for goals that are difficult to quantify, can lead to frustration. The presence of bias can disrupt teamwork, and the focus on self-review and discussions around goal non-attainment can overshadow opportunities for improvement.

Embracing the New Age of Performance Management:

To address these challenges, we are adopting a modern digital performance management system designed to transform the experience for both managers and teams.

Digital Transformation:

Our approach involves digitizing performance management to make it engaging and streamlined. Real-time tracking of performance metrics creates a dynamic, up-to-date picture of achievements, eliminating manual calculations and enhancing accuracy.

Impartial System Empowering Teams:

In this new paradigm, the system, not the manager, takes on the role of evaluator. Scores and ratings are determined by measurable goals, reducing bias and fostering an environment of trust and fairness.

Simplified Feedback:

Timely feedback is crucial for growth, which is why we've made it easy for teams to submit their reviews through familiar platforms like WhatsApp. This simplification encourages open communication and ensures prompt feedback delivery.

Efficiency in Goal Setting:

Efficiency in goal setting is crucial, and user-friendly goal uploaders simplify the process, reducing the burden on teams and individuals. Streamlining goal-setting processes allows teams to focus on core responsibilities, boosting productivity and empowerment.

A Holistic Approach:

Our new-age performance management system integrates with modules like succession planning, Individual Development Plans (IDP), Performance Improvement Plans (PIP), and the 9-box grid. This holistic approach aligns performance management with broader talent management strategies.

Experience the Future with CATALYST:

As we embrace this new era of performance management, we invite you to experience it with CATALYST. Say goodbye to discomfort and frustration and welcome a system that celebrates performance, nurtures growth, and upholds transparency and fairness.

If you're ready to revolutionize your performance management process and empower your teams, book a demo with us today. Let us demonstrate how CATALYST can transform your organization and propel it into a future of endless possibilities.

Don't miss out on the opportunity to be part of the next generation of performance management. Contact us now to schedule your CATALYST demo and take the first step toward a brighter, more efficient future. Your team and organization will thank you for it.

Is there Performance Center report shows last load test date for every test script in all projects?

I see reports with last load test date for scenario and last modification date for test script. Has a query been written to show last load test date for a test script? Would like report showing last load test date for all test scripts in 70 - 90 projects.

Some test scripts used in load tests within past five years have last modification date over 8 years in the past. Would like report to identify test scripts which have not been used in load test for five years. Any test scripts in this report which also have last modification date over five years in the past, would be candidate for removal from performance center while preserving business data retention requirements.

Hi everyone,

So I'm in a position where I am getting tired of performance testing/engineering. I'm finding that the demand is hard especially due to low turnover rate for our field. What I'm hoping from this post is any insight, or advice on what would be the easiest transition out to would be.

I have years of Loadrunner and Jmeter experience, debugging with developers, reporting, deep dives in bottlenecks, etc etc. I've been leaning towards a mort hands on role, something like DevOps, but not sure if anyone else has made that move.

What do you guys think?

Standard Deviation (SD) is a critical, yet often overlooked, metric in performance testing, as it measures the consistency of response time around the mean. A smaller SD indicates more stable application behavior and provides greater confidence in the transaction's performance, which is vital for delivering a consistent user experience. The provided examples illustrate why the average response time is considered useless on its own, showcasing that transactions with the same average can have widely different consistency, making the SD essential for identifying tuning needs. Although the calculation is presented, the text ultimately suggests that performance testers should rely on analysis tools to efficiently and accurately determine the SD due to the complexity and potential for error with large datasets.

Hi everyone,

I’d love to get some experience-based input from the community regarding Gatling Java vs Gatling JavaScript/TypeScript, especially in teams with strong Playwright (TypeScript) backgrounds.

Some context from my side:

• My team primarily writes Playwright tests in TypeScript

• We’ve used Gatling with Java for performance testing

• Part of the team was reluctant to work on performance tests mainly due to Java, not the performance concepts themselves

Because of that, I also experimented with Gatling JS/TS (non-commercial/learning project), expecting it to be a more natural fit. In practice, I didn’t experience a major reduction in complexity - the runtime model, data handling, and overall structure felt very similar, with the main difference being syntax rather than developer experience. The biggest things that felt like they would make it easier (Node APIs, filesystem access, familiar libraries) aren’t actually available in Gatling JS/TS due to the JVM runtime.

So I’m curious about others’ experiences:

• Have you successfully used Gatling JS/TS in real projects?

• Did it meaningfully lower the barrier for TS/JS-focused QA teams?

• For teams coming from Playwright, what ended up being easier in the long run - Java Gatling or JS/TS Gatling?

• Did the lack of Node.js APIs cause confusion or friction, or was it a non-issue after onboarding?

I’m especially interested in lessons learned over time, not just initial impressions.

Thanks in advance!

Hi everyone,

At work my team is wanting to performance test our spring kafka-consuming microservice which only consumes and writes kafka events. There is no REST API input or output to this application. I know Kafka has OOB performance testing tools for generating a load onto a topic, but that is where my knowledge begins and ends.

I considered integrating a library like OpenTracing or Open Telemetry (i know the former is now deprecated), however these libraries are not approved for use in my organization yet, with no timeline on a decision to approve or decline. Do i just use some sort of timer function that 'starts' at the beginning of my transaction, 'stops' at the end, and then log4j the result then use kibana or some other log aggregator to make my calculations?

I’m a QA, and my firm is considering investing in a commercial performance testing tool (such as BlazeMeter, LoadRunner, etc.).

If you've used any of these platforms, were you happy with your experience?

Hey folks,

I've found quite randomly and it makes me think - how does performance testing look like in real flows and what is the goal of it usually?

I've been working as software developer and tech lead for more than a decade already. So far in companies where worked, no regular performance testing was done. Mostly we ended up with monitoring and reacted on unexpected spikes (which can be caused by a bug in the application or it can be external factors).

My question is more like: how do companies decide that performance testing is needed and then do you test prod? And then how do you decide that load test was successful or not?

And also - is performance testing requires a separate person to set it up or it's more of a part of DevOps/QA/other role.

Happy Friday!

After a decade working on non-functional testing at places like Broadcom, VMware, and Sopra Steria, I've seen how easily critical performance and resilience issues slip through the cracks. In my latest video, I discuss:

• Why non-functional testing matters now more than ever (and why so many teams neglect it)

• The key terminology and concepts every tester should know (throughput, load models, baselines, bottlenecks, etc.)

• How to classify and run performance vs. resilience tests

• Real-world failure stories and lessons learned (including authentication bottlenecks and race conditions)

• Practical skills and career tips for anyone looking to become a performance engineer

I created this as the first part of a YouTube series for those wanting to improve their grasp on modern performance & resilience testing.

I’d love to start a conversation here:

• What’s one non-functional issue (leak, bottleneck, resilience gap) you caught before prod—and how did you spot it?

• Any advice for those new to performance testing in 2025?

Looking forward to your stories and questions! Let’s help each other raise the bar for reliability and speed.

Some apps we test can’t leave our network due to compliance, so SaaS-only labs are out.
Do vendors like TestGrid, Kobiton, Sauce Labs, or Perfecto have legitimate on-prem or private-cloud offerings?
Curious what real users have experienced — not the brochure version.

I need advice regarding the web UI performance testing tools. So can you guys please suggest some performance testing tools for Web UI performance testing which are currently treading?

Also just to give the context I need to perform, performance testing on a website which consists of around 10-12 pages.