Viharika, a leader in Big Data QA, shares insights on automation, performance testing, and career growth, inspiring future engineers with her expertise and journey.
Having served for more than a decade in the technology world, Viharika stood out as one influential force in the dimension of Big Data QA Engineering and Testing. Her rise from Junior Developer to Senior QA Engineer is filled with remarkable achievements across various platforms and industries. In this interview, we look at the highlights of her career, the lessons she has learned, and the advice she has for future engineers.
1. What urged or inspired you to join Big Data Quality Assurance and Software Analyst as your career?
Understanding how things work and how they can be improved through the dissection of things has always been of interest to me while I was growing up. This naturally brought me into the world of Big Data Software Testing, where a challenge was at hand-not only in making something work but also in finding its limitations and making it handle real-world usage of huge data sets in different formats. What drew me into QA, though, was the problem-solving aspect, the intricate details, and satisfaction in finding and fixing potential issues that could affect millions of users. I felt that this was a major contribution to the improvement of quality in products and the creation of a seamless user experience.
2. What's a Big project or moment that really defined your career?
One of the most important moments in my career took place during the Dynamic Ad insertion project. It pushed me to leverage my skills in Big data, performance testing, and automation because of the project's complexity: real-time in nature, a lot of involved and integral interplay of different systems. Working on such a transformative project, where the success of ad insertions directly impacted the business' revenue, had its challenges, but ultimately it was rewarding to boot. It really sealed for me how important testing for performance and scalability really is in real-world applications.
3. What are some of the challenges that you faced along the way, and how did you overcome them?
One of the recurring challenges I have faced is to reach an equilibrium between manual and Big Data automated testing in fast-paced environments. And with continuous integration, rapid deployment schedules are a thing that makes it tough to keep the quality of output high without cutting corners anywhere. The key to overcoming those was staying ahead with automation practices by adopting the right toolset, such as Selenium, Cypress, and JMeter and lately PyCharm, Python, Boto3 and VS Code. Equally important, it has been clear communication with the stakeholders that sets pragmatic expectations and makes sure we never settle or compromise on the end-user experience.
4. You have great exposure to working with media and telecommunication domains. How do you foresee the future of testing in these industries?
Media and the telecommunications industries are also some of the fastest-growing ones, considering the rise in streaming platforms and On-demand services. Testing in these fields will be even more dynamic, with a deeper focus on real-time performance and scalability as the demand for 4K content increases, including live streaming services. Automation will also play an even larger role, with further dependence on AI-based testing tools to help sort through vast complexities that are created by users across multi-devices. It is simultaneously both a challenging and exciting time to be in the field, and only those who can keep up will flourish.
5. Could you also tell me something about using automation in your work and how it transformed the testing process?
Automation has been a real game-changer, not just for me but for the teams I have worked with. In fact, while working with projects that involved huge data sets in the media and entertainment industry, it would have been impossible to do testing manually. With the help of tools such as Selenium, JMeter, VS Code, PyCharm, there is so much more we can automate besides functional testing: performance and load testing is also critical for applications that must scale. Automation not only streamlined our processes but also reduced human errors, thus freeing us to put more concentration on high-level test strategies and problem-solving.
6. How would you approach performance and scalability testing, particularly for high-demand applications with millions of users for things like video streaming?
Performance and scalability testing requires deep knowledge about both application architecture and expected user behavior. This particularly means the simulation of a great number of concurrent users, variable network conditions for streaming services, in order to make sure the system copes with extreme loads. JMeter and BlazeMeter are good open-source tools for running load, stress, and endurance tests. However, Splunk and Grafana are indispensable tools regarding real-time performance metrics analysis. In fact, it is very important to test the application and the infrastructure it runs or will run on to ensure scaling at both levels.
7. What would you suggest to a person who is looking forward to a career in quality assurance and testing?
The most important message could be: always be inquisitive and never stop learning. QA is a constantly changing area; new tools, technologies, methodologies-the list goes on-are emerging all the time. Focus on mastering automation early in your career, as this is becoming a fundamental part of testing. Develop good communication skills. As the world is shifting towards AI, explore how to incorporate AI Automation as a Quality Assurance Engineer. After all, as a QA, you are often the bridge to development teams, stakeholders, and customers. Lastly, never underestimate the power of paying attention to detail. It is these little things that often make so much difference in delivering a quality product.
8. You've been involved in migrating projects to the cloud and working with big data. How has this impacted your approach to testing?
The Cloud environments, especially platforms like AWS, brought new challenges and opportunities to provide testing. On premise cloud migration usually adds additional test complexity into the area of data integrity and security during the move. Big data deals with the testing of real-time data pipelines to ensure that this big data is handled correctly and efficiently. This renders performance testing even more important since, with cloud-based systems, we pay for resources utilized, and inefficiencies will thus turn out costly. Automating and having robust monitoring are the ways in which these challenges can be handled.
9. How about the role of certification and ongoing education in your professional development?
Certifications have played a pivotal role in my professional journey. My SAFe Agile certification has been instrumental in understanding and implementing best practices, but I've also recognized the growing importance of AI in our field. That's why I pursued and obtained the Microsoft Azure AI Engineer Associate certification and AWS Fundamentals of ML and AI certification. These AI-focused credentials have helped me leverage cutting-edge tools like GitHub Copilot in my testing workflows, significantly improving efficiency and innovation in my work. That said, continuing education goes beyond certifications. The technology world is always evolving; new tools and methodologies emerge constantly. I also engage in frequent online courses, attend workshops, and participate in community forums to stay current with the latest developments. At the same time, mentoring others has been a great learning experience. Teaching helps me reinforce my knowledge and keeps me sharp, especially when introducing newer team members to AI-powered testing tools and methodologies.
10. How do you handle high-pressure working environments, especially when working on mission-critical projects?
High-pressure environments are undoubtedly challenging, but I've learned to thrive under these conditions through strong organization and effective prioritization. I break down large projects into manageable tasks, establish clear timelines, and maintain open lines of communication with all team members to ensure everyone is aligned. Keeping calm is essential even when setbacks occur, it's our response that defines success. By fostering a collaborative and supportive team culture, we consistently deliver quality results on time without compromising on standards.
About Viharika
Viharika's Tech journey has been one of pursuit of excellence and adaptation towards changing landscapes. From pioneering automation frameworks, ensuring performance and scalability for streaming platforms, she continued to push boundaries in the field of quality assurance. Her story serves as an inspiration to aspiring engineers-a story that tells that in technology, possibilities are endless with curiosity, perseverance, and the right mindset.