How an API automation expert and developer of large-scale frameworks helps companies in healthcare, fintech, and SaaS maintain stability and competitiveness
In 2025, the API testing market is experiencing rapid growth: according to SNS Insider, its value is expected to exceed $10.5 billion by 2032, with an average annual growth rate of nearly 21%. APIs have become the “nervous system” of digital business — the reliability and speed of these interfaces determine the performance of telemedicine platforms, banking transactions, and the scalability of SaaS services. As systems become more complex every month, the challenges faced by quality engineers grow alongside them.
Mykhailo Sheptun is one of the specialists shaping solutions to these challenges. At A Place for Mom, a major U.S. online platform for senior living referrals, he has built large-scale automation frameworks in TypeScript using Cypress and Playwright, covering thousands of tests. His implementation of K6 performance testing accelerated releases and increased API stability. At the same time, Mykhailo has trained hundreds of automation engineers, developed educational frameworks, and published the book REST API Automation, whose methodologies are now used by teams worldwide.
In this interview, Mykhailo shares why APIs are becoming a key factor in the competitiveness of companies in healthcare, fintech, and SaaS, how large-scale frameworks and AI-driven approaches are transforming the industry, and which practices allow businesses to maintain stability and user trust.
Mykhailo, you built large-scale frameworks with over 1,900 automated tests at A Place for Mom — one of the largest senior living referral platforms in the U.S. What key lessons about the role of APIs in business have you drawn from this experience, particularly in terms of minimizing errors and accelerating new feature releases?
— In modern business, time-to-market is often more critical than the product itself. When we built a framework with over 1,900 tests for A Place for Mom, I realized that a well-thought-out API test architecture allows us to identify errors even before new features reach production. This not only saves resources — which, for a platform of this scale, amounts to millions of dollars — but also preserves user trust. In practice, this means users can quickly and safely find suitable senior living options without unexpected failures or delays, while the development team can release new features faster without compromising quality.
You are the author of the book REST API Automation, used by engineers worldwide. What key principles of API testing allow businesses to remain competitive in critical areas such as healthcare?
— In healthcare, mistakes are unacceptable because people’s health and lives are at stake. For me, principle number one is test reproducibility and transparency of results. This means that each test must produce the same result when rerun and be understandable to any engineer on the team. The second principle is integrating testing into the business processes themselves, rather than treating it as a separate technical block. When testing becomes part of daily operations, it transforms into a strategic tool: the company can scale confidently, launch new services, and maintain competitiveness.
In your projects, you have integrated both REST APIs, the classic method of data exchange between services, and GraphQL APIs, a more flexible approach to queries, into CI/CD pipelines using dynamic data. What is the key value of these approaches for the stability of digital platforms?
— Today, users do not tolerate delays or errors. When we implemented dynamic data generation and automatic test execution in CI/CD, the platform was constantly stress-tested. In practice, this means the user experience remains predictable and stable: pages load quickly, functionality works as intended, and bugs are detected before they can impact customers. This approach allows companies to reduce risks and avoid spending resources fixing production issues, which is especially important for high-traffic services.
You implemented frameworks with automatic test data generation and Playwright decorators, tools for UI testing with TypeScript extensions, for ERP systems — complex enterprise systems. How does the use of such tools help companies scale their services without reducing quality?
— ERP systems are the heart of a business, where even a small error can halt production or financial calculations. Automatic data generation allows us to cover scenarios that engineers might miss manually and validate them on the fly. In one project, we were able to test complex business processes with hundreds of data combinations without increasing the number of engineers, allowing services to scale without risking quality. This gives the company confidence that new features will not disrupt critical systems.
Your implementation of performance testing with K6 reduced API response times by 42%. What advantages does this provide to the business in terms of user experience and operational efficiency?
— For users, this is very tangible: pages load faster, the system responds instantly, and they do not feel frustration or a desire to switch to competitors. For the business, this translates into lower server load and fewer incidents, meaning less downtime and higher infrastructure ROI. In the case of A Place for Mom, it allowed the platform to handle millions of requests without failures, which is critical for a service where users are searching for care for their relatives.
You have served as a mentor and trained over 800 students. How important is it for modern businesses that specialists understand the nuances of API testing and can implement best practices?
— API testing today is not a narrow technical specialty; it is a key skill for any engineer in the digital economy. Companies that invest in training their employees gain not just specialists, but teams capable of creating sustainable competitive advantages. I have seen graduates of my courses immediately implement modern practices in real projects, accelerating releases and reducing the risk of errors.
You integrated AWS CloudWatch, a system monitoring service, and Sentry, an error tracking tool, directly into QA frameworks. How do such solutions help businesses quickly detect and prevent API failures before they impact customers?
— These tools allow real-time monitoring of system health and prediction of potential failures. Previously, we only reacted to user complaints, but now we can resolve issues before they reach the customer. This is a fundamentally different level of service quality: companies can be proactive rather than reactive, which is critical for platforms with millions of users.
Your frameworks are used both in startups and large enterprises. What differences do you see in approaches to API testing, and how do they affect the competitiveness of these companies?
— Startups usually start with a minimal set of tests because speed-to-market is their top priority. Large companies invest in scalable frameworks with thousands of scenarios. But in both cases, API testing determines whether the business can survive in a competitive environment. Companies that build professional frameworks react faster to changes and minimize risks for users.
You implemented regression tests for ERP systems with more than 900 automated tests. How does regular API testing help prevent costly errors in complex business processes?
— Regression testing acts like an insurance policy for a business. When an ERP system processes financial or production data, a mistake can cost millions of dollars. Automated tests allow every release to be checked with consistent precision and without human error, reducing the risk of catastrophic failures.
You combine practice and publications, becoming a recognized expert in API automation. Which current trends in API testing could radically change company strategies in the coming years?
— The most significant trends are AI integration into API testing, where algorithms predict potential vulnerabilities, and shift-left, where testing moves to the early stages of development. I am convinced that automated tests should predict problems rather than fix them retroactively. Companies that adopt these approaches first can foresee — or rather, forecast — potential challenges, roll out new features faster, and set the market tone rather than chasing competitors.
You served as a judge at the QA Innovation Awards, evaluating 87 projects. Which innovations in API testing do you see as most promising for improving company competitiveness?
— I am especially impressed by projects where API testing is integrated with business analytics. This allows not just verification of system functionality but also forecasting how changes will impact key company metrics, such as request processing speed or user satisfaction.
Your experience includes integrating REST and GraphQL API tests into enterprise pipelines. What mistakes do companies most often make when implementing API testing, and how can they be avoided?
— The main mistake is treating testing as the final stage of development. APIs need to be checked at all stages; otherwise, errors emerge too late and become costly. The second mistake is cutting corners on infrastructure. Good testing requires investment, but in the long run, it pays off many times over.
You helped implement AI and dynamic data generation in Playwright. How do these methods enable businesses to respond faster to changing requirements and scale services without losing quality?
— AI allows tests to adapt to changes in interfaces and business logic. Previously, rewriting hundreds of tests would take days; now the system adjusts automatically. This not only saves time but also reduces the risk of human error.
You developed frameworks for platforms serving millions of users. What strategic advantages does a company gain if its API testing is professional and scalable?
— First and foremost, it ensures resilience. The company can scale, launch new services, and confidently implement innovations knowing that its API foundation is reliable. For healthcare and fintech, this becomes a key competitive advantage.
You actively publish articles and run educational projects. How important is it for tech companies to develop an internal culture of API quality and share knowledge among engineers?
— A culture of quality is what separates mature companies from those that live “release to release.” When experts share knowledge within the team, new employees get up to speed faster, and the company reduces errors and implements new solutions more quickly. This is how a sustainable technology business is created.
