Upskilling Quality Engineers for the New Age: A Success Story in SDET Transformation

The full transcript

Kavya (Director of Product Marketing, LambdaTest) - Hi, everyone. Welcome to another exciting session of the LambdaTest Experience (XP) Series. Through XP Series, we dive into a world of insights and innovations featuring renowned industry experts and business leaders in the testing and QA ecosystem.

I'm your host, Kavya, Director of Product Marketing at LambdaTest, and it's a pleasure to have you all with us today. In today's session, we'll delve into how organizations can adapt to the evolving demands of test automation through effective upskilling and innovation.

But before we dive into the discussion further, let me introduce you to our guest on the show, Samuele Moscatelli, Test Automation Team Lead at Accenture. Samuele is a seasoned professional proficient in Java, JavaScript, and Python.

His deep understanding of the full-stack development processes, combined with key certifications in AWS, SDET, and Master Technology Architects, underscores his expertise.

So, let's jump straight into the heart of today's discussion. Samuele, how did you build and maintain a strong, inclusive community of testers with varying skill levels and ensure that knowledge sharing happens across all experience levels?

Samuele Moscatelli (Test Automation Team Lead, Accenture) - So, first of all, thanks a lot for having me here. It's an honor and a privilege to have the opportunity of speaking in one of the LambdaTest Experience sessions and I'm really grateful for that.

So to answer the question, I have to admit that building and maintaining such a community has been a multi-faced endeavor that requires a blend of strategic planning, empathy, and also continuous engagement. But let me try to break down the approach into a few key areas.

So, first of all, it has been important for us to cultivate our common environment and to foster a culture where every tester feels valued, regardless of their experience level.

This started with a clear communication about the importance of diversity in terms of both skills and perspectives. We, in fact, celebrate every kind of contribution, from the keen insights of our more seasoned testers to the fresh perspectives of newcomers.

Then secondly, for us it has been important to establish structured onboarding and also mentorship programs. We, in fact, developed a comprehensive onboarding program that allows new testers to join our community and also ensures that they have all the resources and the support they need in order to succeed.

Paired with this, we have also a mentorship program that connects less experienced testers with more seasoned ones, thus creating this natural flow of knowledge between them and meanwhile also fostering a strong and supporting relationship between them.

Third, we also facilitated open knowledge sharing, and in particular, we utilized a variety of platforms and methods. Examples are groundwork sessions, regular workshops, or even webinars. These allowed testers to collaborate with each other and to learn in an end and zone environment.

Together with this, we also maintained an accessible repository of resources that included documentation, tutorials, and even recorded sessions, thus being able to cater to different learning styles and different learning bases.

The fourth point is continuous feedback and adaptation. In fact, regular feedback loops are crucial, and we are aware of this, of course. And for this reason, we conducted surveys or also open forums where testers and our team members can voice their own ideas and also voice their own concerns.

This feedback was really important for us because it helped us continuously adapt our strategies to meet the evolving needs of our community thus ensuring that everyone feels heard and also valued.

Fifth and last point, for sure not least, is recognizing and rewarding contribution. So as we all may know, recognition is a very powerful motivator and for this reason we have decided to regularly highlight individual and team achievements.

And to do this with both formal rewards and more casual kudos. These, of course, have reinforced the value of each tester's contribution and have also inspired other testers to share their knowledge and to also share their expertise.

So, in conclusion, by blending these elements together, we have been able to create this vibrant and inclusive community where testers of all skill levels feel empowered to learn, share, and also grow together. Of course, this is still an ongoing journey, but it's one that pays off in terms of a dynamic and innovative testing community.

Kavya (Director of Product Marketing, LambdaTest) - Thank you so much, Samuele, because that is a fantastic approach to how you can basically cultivate a collaborative environment. Because I think culture begins within the team, within smaller teams before it sort of spreads across the organization.

And it is interesting to hear how you have managed to, in a way, bring together testers who have different skill levels and skill sets together in such an effective manner.

Thank you so much for breaking down those points for us. Moving on to the next question, what was the biggest challenge that you faced in transforming the team, and how did you overcome it?

Samuele Moscatelli (Test Automation Team Lead, Accenture) - So, thanks for the question. I think in my opinion, the biggest challenge that we faced was that of managing the varying skill set and knowledge levels of our team members.

And in order to address this, we decided to implement a two-pronged strategy. In particular, the first thing that we have done is that of developing a comprehensive self-study program that allowed our team members to gain foundational knowledge at their own pace.

This included a personalized learning path with a mix of online courses, interactive tutorials, and also some projects that made the learning process more flexible and more accessible.

In this way, fact, our team members were able to focus on the areas where they needed the most improvement and also they, in this way, ensured to gain a strong foundational understanding of these concepts. The second thing that we have done is structure the team into smaller and more focused mini-teams.

Of course, each is composed of both junior and senior members. This allowed us to facilitate mentorship and continuous learning among the team members because the more senior members of the smaller teams provided guidance and shared the best practices with their more junior counterparts.

These mini-teams also encouraged closer communication and stronger relationships among the members and have, in this way, enhanced collaboration and mutual support between testers. This dual approach of course, has facilitated skill development and knowledge sharing at the same time as promoted a collaborative and supportive team environment.

And also it has fostered stronger communication between our colleagues and accelerated skill acquisition and team cohesion. And although it required an investment, of course, in terms of time and resources, the results have been outstanding because it significantly improved our team performance and our team morale, and it also allowed us to enhance the project efficiency.

So, in summary, addressing the challenge of having varying skill sets among our team members through this guided self-study training and through these smaller and more focused mini-teams led to a more cohesive and efficient team that proved the strategy's effectiveness and the long-term benefits of this upskilling initiative.

Kavya (Director of Product Marketing, LambdaTest) - Thank you so much, Samuele. I was about to summarize it, but you've done it wonderfully. It is also interesting on how you have navigated through it. There is a lot that enterprises and organizations out there can learn from your experience for sure.

What I can also notice as a recurring theme is how important mentorship is within the Accenture testing teams because it definitely creates a lot of value, especially when there are senior team members who are guiding the junior team members, not just when it comes to projects, but also when it comes to upskilling as well as learning.

So yeah, that is pretty interesting. Moving on to the next question that we have, how can we replicate and scale this upskilling and community-building approach in organizations of different sizes and testing maturity?

From what I can understand right now, the testing teams that you might have might have already achieved a certain level of maturity. So, how would you suggest that organizations that are at varied scales can implement this?

Samuele Moscatelli (Test Automation Team Lead, Accenture) - Yes, so I think that's a really good question and also a bit complex one because replicating and scaling these kinds of approaches requires a tailored strategy usually. However, I think there are some core principles we can call them.

like them that remain consistent and that we can talk about. In particular, I think that the first fundamental thing is to create a culture that values continuous learning. And in order to achieve this, it's important to ensure that the leadership at all levels champions the importance of upskilling.

And this does not only include time and resources, but also includes recognition for the learning initiatives. Secondly, I think it's important to encourage a culture of collaboration and knowledge sharing because this would allow us to make the journey a team effort.

And in particular, as mentioned also earlier, I think it's important to have different levels of experience among the participants because this could ensure that the knowledge would flow naturally among them and also to ensure that there is someone with the experience to guide a project in the right direction and to keep it on track, of course.

Then I also think it's important to provide the right training and learning resources. And in particular, I think it's important to really provide a variety of those resources because this enables team members to learn with different styles and with different spaces also.

And the result is that they are able to feel in better control of the concepts that they are learning and thus in a better position to be able to put this concept in practice in a more easy and effectively manner.

An example is, in my opinion, it is possible to provide both guided and self -paced training and also accompany this with resource libraries so that you could really cater to different learning styles and different learning places.

Then, as you know, these first three concepts that I mentioned are quite complex to achieve. And in particular, it's important in order to achieve them to adapt to the organizational context. So, in particular, in order to be able to scale the approach, it is important to tailor it to the organization's size and to the organization's testing maturity.

For smaller organizations, in fact, it is usually better to create a strong learning culture first and, thus to build more flexible and cost-effective training solutions. While for larger organizations, it is better usually to develop more comprehensive and even multi-tiered training programs, thus being able to cater to different teams and, in some cases, even to different departments.

In both cases, it is fundamental to assess the maturity level of the team. And this is because it is important to begin with foundational knowledge for a less mature team and instead introduce more advanced practices and concepts for a more mature team, thus customizing the training and project complexity based on the maturity level of the team.

Last but not least, again, it's really important to never forget to recognize and celebrate the achievements. This is in order to be able to maintain motivation and to reinforce a positive learning culture inside the team. And in order to do this, for example, it is possible to use newsletters, use tunnels, or even dedicated events and there to really showcase project milestones and also individual contributions.

These, in fact would foster a sense of accomplishment and also a sense of community among the team. And I think by following these principles and of course, as said, adapting them to the context of each organization, we could really and effectively replicate and scale upskilling and community building approach.

This in fact, would not only build a valuable asset, but would also create a sustainable learning journey that enhances both individual and team capabilities, thus fostering a dynamic and innovative testing community.

Kavya (Director of Product Marketing, LambdaTest) - Thank you so much, Samuele, because those are very strategic approaches that testing team sizes of any size could perhaps adopt. In fact, you know, hearing you speak about the initiatives that you have personally implemented, right?

It is also, it also closely resonates with what we do for community at LambdaTest. For instance, we run one of the largest online free testing conferences in the world called Testμ Conference, happened from August 21st-23rd this year.

Apart from that, we offer free certifications and host videos on YouTube. The end goal for us is that of course, you know, testing teams across the world who are at any level of stage or like growth in terms of maturity and so on, can come and access these assets, they can access these content available from leaders such as yourself.

And one thing that also stood out for me was how leaders in all organizations across teams should actually champion the upscaling projects. It sort of tends to begin from top down at times. And even the part about building that culture of collaboration, I think that also needs to be implemented across right from the leadership level itself.

Thank you so much for those insights. Now moving on to the next question that I had was how do you leverage the framework development project so as to upskill the team while building a valuable tool?

Samuele Moscatelli (Test Automation Team Lead, Accenture) - So thanks again for this question. And I am happy to hear that you are also pretty much using a similar approach to our work. And to answer your question, so this was really a transformative experience for us because the project was turned into a comprehensive learning journey for the team where instead of separating trainings and development, we directly integrated learning into the project workflow.

And in particular, the team was really encouraged to learn new skills as soon as they faced new challenges. And for instance, when they had to implement a new feature, they were encouraged to research for best practices first then experiment them and finally directly apply them into the project.

Thus, in this way, ensuring an ensign learning that is really the core of our approach. So ensuring an ensign learning. Of course, we fostered a collaborative atmosphere where knowledge sharing was a core principle.

And for this reason, our more experienced SDETs paired with the less experienced ones, thus creating this kind of mentorship dynamic. And these, of course, not only accelerated skill development for them, but also allowed to build a strong working relationship between our team members and also a cohesive team spirit.

Beside that, regular code reviews were not, of course, missing. And they were used as occasions for expanding and consolidating the knowledge of the team. In this way, in fact, team members were able to have exchanges between them on their code to discuss alternatives and also to collectively learn better approaches.

So, of course, the project has been first designed and planned by our most experienced members and architects, and in particular, really having an experienced team of architects was key in order to achieve the development of a really valuable tool for test automation.

And in this context, I'm also proud to say that I am part of this great architectural team. So the idea was that of implementing an incremental approach in which early tasks focused on more fundamental skills, while later stages tackled more advanced concepts.

So, this scaffolding approach ensured that everyone first would have built a strong foundation before moving on to more challenging tasks. And in addition, in order to follow this approach, we also structured the project as an agile one and thus we introduced task boards, iteration plans, regular meetings, thus making the way of working into the project more familiar for everyone.

And this, of course, allowed to break the project down into smaller tasks that could better fit individual knowledge and also individual learning goals. In fact, each team member, in this way, was able to take the ownership of a specific task and conduct deep dives into the particular technologies that were needed in that task in this way feeling a sense of accomplishment when having to address the task.

Other than that, again, I think I repeated it multiple times, but I want really to highlight this, but recognizing progress and achievements was really vital to maintain motivation and enthusiasm inside the team.

And each contribution for this reason was recognized and valued, again, with both formal rewards and also informal kudos. This created a positive reinforcement loop that encouraged among the team continuous learning and continuous effort.

So again, by intertwining the framework development with a structured, collaborative and supportive learning environment, we were able to significantly upskill the team.

And also this dual focus on building both a valuable tool for test automation and to enhance the capabilities of the team, ensured that not only we met the project goals, but also prepared the team for future challenges with a robust skill set and also a more confident and innovative mindset.

Kavya (Director of Product Marketing, LambdaTest) - I mean, it is interesting, Samuele, to begin with, thanks for explaining how it all came together and also benefited the team. And of course, congratulations on coming up with the strategy and implementing it in the first place.

It is really interesting how you used even the projects, that is client projects, for dual purposes. On one hand, you're focusing on the learning part of it. And on the other hand, you're using it for code reviews and ensuring that the quality of the code is maintained throughout the process that really helps.

Can you also outline your automation framework's key features and how it ensures modularity, flexibility, reusability, and infrastructure agnosticism throughout?

Samuele Moscatelli (Test Automation Team Lead, Accenture) - Yes, of course. And I'm really happy to do that because, first of all, our automation framework is called Firestarter, so that we give it a name. And its main goal is that of enabling and accelerating test automation. And in order to do this, it provides all the necessary assets, and it provides them in a structured way.

With Firestarter, fact, test automation can be initiated earlier in the project lifecycle and requires less effort to be established. Of course, the framework is under continuous development, and for this reason, it gets regularly extended with new and fresh functionalities.

And in fact, recently, just a few months ago, we have released the version 1 .3 of Firestarter. And these, among the other features, have also introduced, for example, support for Kafka and support for Avro messages that are two functionalities that are really diffused nowadays.

But what really characterizes and differentiates FireStarter framework is its architecture, which has been designed by our architects to be modular. The framework, in fact, is constituted by many functionalities that altogether, let's say, complete the FireStarter puzzle.

But at the same time, these functionalities are independent between each other. And thus, they could be picked singularly without the need of importing the whole framework as a monolith, let's say. So in practice, will never end up having, let's say with Firestarter, you will never end up having code that you don't need and that you don't use.

But let's summarize a bit. I think we can summarize Firestarter peculiarities in eight points. And in particular, the first one is that it has a distributed design because it gives the possibility to always get the latest binaries from a remote location.

Then Firestarter also is developed in-house and thus it comes, of course, with support and the possibility for on-demand features implementation. It has a non-intrusive design because it does not dictate a specific way of test automation. And Firestarter also does not have any licensing fees because it's completely open source.

Also, it already covers all the main and most used features in the field of test automation and consider that being continuously under development, many more are still to come. And also, it is a POC enabler because allows, as also said before, a faster start into test automation also enables a holistic integration with the WAPS pipeline.

And to conclude, Firestarter also brings efficiency by reducing the effort that is needed for test automation. So let's say these eight characteristics put together make our framework modular, flexible, reusable, and also infrastructure agnostic.

Kavya (Director of Product Marketing, LambdaTest) - Thank you so much, Samuele, for sharing about Firestarter. And also to the audience that's listening in, Firestarter is open source to begin with. So in case you want to try, you know you could get in touch with Samuele to understand more about it and probably give it a try.

And good to know that how versatile and robust it is. It is impressive how you have your Accenture team has built it so that it is adoptable across different infrastructures out there. Now, moving on to the next question, coming back to the upskilling initiative, how did you go about measuring the ROI of the upskilling initiative?

And did it also improve the morale, collaboration, or project efficiency? You did mention that recognition and rewards definitely improved it, but know, how did you go about measuring the ROI in its own?

Samuele Moscatelli (Test Automation Team Lead, Accenture) - Yes, so first of all, I want to mention that feel free to reach out to me if you want to know more about Firestarter. I would be very happy to give more concepts about it.

And yes, coming to the question now, I think we could measure the return on investment with two qualitative metrics that are the value that we created for our people and the value that we created for our clients.

So in first instance, we were able to keep our people up with the evolution of innovation, and we were able to allow them to always work with state -of -the -art technologies and with state-of-the-art approaches.

This, of course, affected positively Team Morale because allowed to maintain a dynamic environment where each person could implement a continuous learning culture and thus could never stop growing both personally and professionally.

Along with that, it improved team collaboration since, as also anticipated before, it has been a common effort where people needed to continuously pair with each other in order to accomplish their task and thus to complete the learning journey.

So the result is that each team member has developed an extensive knowledge of the other team members, again both professionally and personally, thus also enabling in this way a better understanding of the organization for everyone.

And last but not least, this Anson-centered learning approach also boosted the efficiency of our team because after following this upskilling approach and upskilling initiative, they were able to bring the experience they gained pretty much everywhere, because this was already a project experience.

On the other side, so going to the second qualitative metrics, this upskilling initiative also unlocked enormous value for our clients. And from a dual perspective, because from one side, they were able to count on people that have a huge and deep knowledge of the field and that also already have experience with different kinds of technologies.

On the other hand, could also count on a valuable and ready-to-use product that enables speed and efficiency in test automation. The result of this was a combination of knowledge and tools that is really key to succeed in this current ever-changing and fast -paced environment.

In fact, this combination can boost project performance and also ensure to reach the goals in a quicker and more robust manner. So let's say that these outcomes are already evident and they are proving the success of this upskilling initiative because people are able to really feel protagonist in the building of a valuable tool while at the same time learning new and useful concepts for their professional lives.

Kavya (Director of Product Marketing, LambdaTest) - That is a very interesting point that you just shared that, you know, the focus that Accenture's testing or quality engineering teams are putting on learning the latest trends in technologies, the focus that you're putting on innovation, right, and keeping up with it is also directly resulting in the clients' project success that their projects performances are important.

That's a very interesting point on how internal upscaling or testing teams upscaling is directly resulting in performance of the end client success. Thanks for breaking that down again, Samuele. We really appreciate it.

Now we are on to the last question of the day, which is based on your experience, right? What are the top three skills estates should develop to stay relevant in the future?

Samuele Moscatelli (Test Automation Team Lead, Accenture) - I'm very happy that you made me this question because I'm actually very active in this context and I'm also, I'm always looking into innovations and new technologies that are coming and trying to, let's say, find the connection with my field of expertise.

So based on my experience in order to stay relevant in the future, I think SDETs should prioritize the development of skills in the context of continuous integration and continuous development into cloud technologies and finally into generative AI. So elaborating a bit and going in the order.

Mastering CI/CD is really critical currently for modern software development in order to ensure rapid and reliable delivery. And the key aspects that an SDET, in my opinion, consider are, first of all, the building and maintenance of CI/CD pipeline.

So having knowledge of tools like Jenkins or GitHub Actions or Azure DevOps or also GitHub GitLab CI, just to name a few of them, I think it's really important in order to be able to seamlessly integrate automated tests into the development lifecycle and thus granting quick feedback and also facilitating continuous improvement into the project.

Then, still in the context of CI/CD, I think it's also important to know the concepts of containerization and orchestration, and thus to have some knowledge towards tools like Docker and Kubernetes, because this would allow to be able to create consistent testing environments and to also be able to scale test executions.

Last, still in CI/CD field, infrastructure as a code. So I think having failure familiarity with like Terraform, Ansible, or CloudFormation is really helpful to be able to automate the environment setup and management. And also this helps in maintaining an infrastructure agnostic approach and in ensuring that tests can run seamlessly across various platforms.

Then the second technical skill that I mentioned is related to cloud technologies because I think that proficiency in cloud technologies is already a must. And actually its importance is increasing even more now that AI technologies are raising. And for this reason, I think really SDETs should develop skills in this direction.

And in particular, I think they should know the main cloud platforms, so those offered by the main cloud providers like AWS, Azure, or even GCP. And in particular, understand the services that they are offering in terms of computing, storage, and networking in order to be able to then leverage these cloud resources.

Also, it's important to know the concept of cloud -native testing and to develop skills in the direction of serverless architecture, microservices, and also contract testing. This, in fact, would ensure that SDETs could design, develop, and execute test cases that are optimized for those cloud environments.

And last but not least, still in the field of cloud technologies, is scalability and performance testing. I think these are concepts that should be known by SDETs and SDETs should be able to leverage cloud capabilities in order to conduct large-scale performance testing and in order to simulate to be able to simulate user load from different geographic regions.

This, in fact, allows to identify bottlenecks, potential bottlenecks, and to also ensure that the application performs well under various conditions. Last, but in this case, absolutely not least, so the last skill, technical skill that I think it's really important to develop is generative AI.

So, it seems really obvious to say that generative AI is revolutionizing various, if not all, the aspects of software development and testing. And for this reason, I really think that SDETs should embrace this technology in order to stay ahead. In particular, I wanted today to highlight two different aspects of generative AI in the context of testing.

And the first one is that I think SDETs should be able to leverage this technology, so generative AI, in order to be able to automate those phases of the testing life cycle that are still manual, time consuming, and also repetitive.

Examples are like the creation of automated test cases that could be done or that should, SDETs should learn to do it leveraging generative AI, thus in this way reducing the manual effort that is required and also at the same time improving the test coverage.

Another example that is analogous is the maintenance of those test cases, still using this technology to automate the update of the test cases whenever a code change is coming. This would reduce a lot the overhead of manual test maintenance and would speed up the readiness of the test cases after a change.

Last example maybe in this context is the possibility to use AI to automatically examine test results, thus to potentially predicting failures and also identifying areas of improvement. This would allow us to make a more data-driven decision. The other aspect that I wanted to highlight in the context of generative AI and testing is that of testing generative AI-based applications.

So I think it's quite obvious for every one of us that a lot of people have started and are developing GenAI based applications. However, I think we are still in the early stages now because most of them are just experimenting at the moment.

And for this reason, most of them are not really interested in testing and proving the outcomes of their applications. However, I am really sure that as soon as the times become more mature, the demand for testing Gen AI-based applications will rapidly ramp up.

For this reason, I would really recommend, as it is, that one wants to stay relevant in the future to develop skills in this direction and to start now doing it because the concept of testing GenAI-based applications is different from, let's say, what we can call standard testing.

It's important to start now that the technology is rising to develop those skills in order to have a strong foundation in this field. So, in summary, the top three skills that, in my opinion, and based, of course, on my experience as the T's should develop in order to stay relevant in the future are those of mastering CI/CD, being proficient in cloud technologies, and of course, embracing generative AI.

These skills, in fact, would not only enhance the effectiveness and efficiency of their testing techniques but would also position them to meet the demands of future software development environments.

Kavya (Director of Product Marketing, LambdaTest) - Thanks, Samuele. Those are some excellent skills to focus on, especially given how rapidly the testing landscape is changing. And interesting points on how you mentioned using generative AI to identify potential test failures.

For instance, LambdaTest HyperExecute has a feature called fail fast that lets you optimize your testing regime by automatically aborting jobs that can surpass the number of consecutive failures that are happening.

So, it basically gives you prompt feedback while ensuring that the entire testing process is also maintained. very interesting to know how aligned platforms such as LambdaTest are also with the skills that you just highlighted that need to work on.

Thank you so much for those excellent summaries as well that you had put together. Really appreciate it. And as we wrap up today's conversation, I would like to thank you, Samuele, for sharing your insights with us. I'm sure, you know, these have been some, there have been some valuable lessons for our audience.

And our audience, thank you for joining us today. Do reach out to Samuele in case you have questions about, you know, for starters or, say, for instance, you want to know about any other projects or upskilling initiatives that he's working on. I'm sure he would have a lot to share, but we'll also ensure that we are dropping, Samuele, your LinkedIn profile, on the chart so that our audience can get in touch with you.

Stay tuned for more episodes of the LambdaTest Experience Series, where we continue to bring you thought leaders and industry experts who share their knowledge and innovations. And do Subscribe to LambdaTest's YouTube Channel to get notifications for the next such interesting discussions. Thank you, everyone. Have a great day. Thank you, Samuele. Bye.

Samuele Moscatelli (Test Automation Team Lead, Accenture) - Bye-bye!