Systems | Development | Analytics | API | Testing

Imagine pushing a new release, only to have a crucial API endpoint break in production — leading to a service outage and angry customers. According to one recent survey, API failures account for more than 35% of production incidents in microservices environments. Reliable API testing is not optional anymore.

When writing automated tests with Selenium WebDriver and Python, one common task is dealing with input fields that already contain text. Whether you're working with a login form, a search bar, or a multi-step checkout flow, starting with a clean field helps ensure consistency every time your test runs. The clear() method in Selenium offers a direct way to remove any existing text inside a form field before you input new data.

Every second your software slows down, you lose customers. Studies show that a delay of just 100 milliseconds can decrease conversion rates by 7%. That’s how fragile performance can be — and why software performance engineering has become a core discipline for every business serious about growth and reliability.

In my work helping teams adopt canaries, I’ve seen several recurring mistakes. Here’s a “pro tip” list to avoid them: Pro Tip: Don’t skip staging testing. Canary isn’t your only safety net—use staging to catch basic issues first. Is Your Infrastructure Ready for Global Traffic Spikes? Unexpected load surges can disrupt your services.

Traditional test scripts are too brittle for today’s fast-moving, complex systems. AI-powered agents enable a shift to scenario-based testing - high-level, reusable flows that describe user intent and behavior. Agents can help extract, generate, and evolve these scenarios, while humans guide relevance, risk, and validation. This approach improves stability, cross-platform coverage, and business alignment.

When you think about test automation, what image comes to mind? For many QA leaders, automation still means running the same scripts every night, chasing down false-positives, and fighting maintenance debt. That model served us well for a while, but it was always limited: automation only runs what humans script. The next era is about AI-powered testing. AI-powered testing doesn’t just execute predefined tasks; it generates coverage dynamically, adapting as your application evolves.

APIs are most commonly and widely used in modern applications. To build the complete application frontend, backend, and databases are required, and to make proper communication, the APIs are required. But what happens when the backend isn’t ready or third-party APIs are unstable?. This is the point at which the use of API mocking comes in. By using the API mocking, developers can build, test, and debug their applications or products faster without waiting for real APIs to be live.

Deterministic masking is essential for any businesses that need to secure application data across multiple non-production environments — since it ensures data is masked consistently everywhere it appears. As CTO of Perforce Delphix, I’ve worked with many companies who need to protect sensitive data while providing realistic data for testing and development. This is especially important in industries like insurance, healthcare, and financial services.

AI doesn’t just learn from data, it learns from us, and we are far from perfect. When it scrapes the internet for knowledge, it also absorbs our biases, blind spots, and noise, shaping how it interprets the world..

If you have ever searched for a crowdsourced testing partner, you have probably seen the same promise repeated: “thousands of devices, hundreds of geographies.” While impressive at first glance, these vanity metrics rarely reflect the true quality of a QA partnership.