Systems | Development | Analytics | API | Testing

Have you ever released a feature only to see it break spectacularly in production? If you’re a developer or an SDET (Software Development Engineer in Test), you’ve likely been there. That’s where Alpha and Beta Testing come in – your last line of defense before your users turn into bug reporters! But what exactly are Alpha and Beta tests? How do they differ? And why should you, as a developer or SDET, care about them?

People are tired of talking about artificial intelligence (AI). They want action. Since the launch of ChatGPT, the financial services industry has been looking for ways to drive value with AI, but it's been a struggle to get real value out of AI experiments and pilot projects. The banking industry prefers to avoid potential risks, so how can financial sector leaders move from AI experimentation to AI value while being mindful of risk tolerance?

Supply chain disruption. Pandemics and medical crises. Climate change. Events that were once “black swans” are now near-everyday occurrences for citizens worldwide—and governments are facing growing pressure to provide effective public services in response. In the past, the ability to access, process, and apply data to make informed decisions about complex issues was crucial to creating effective public services.

You run your test suite, and a test fails. You re-run it—now it passes. No code changes, just random failures. Annoying, right? But here’s the scary part: flaky tests don’t just waste time—they slowly break trust in your entire testing process. Flaky tests show inconsistent results across runs. They create unreliable outcomes, hurting test accuracy. These tests may report false positives or negatives. False negatives flag non-existent defects, wasting time.

In today’s fast-paced software development landscape, ensuring quality while maintaining agility and cost control is a challenge. In 2022, poor software quality cost the US market over $2 trillion. To tackle this, businesses are increasingly turning to QA as a Service (QAaaS)—a model that offers expert testing solutions without the overhead of an in-house QA team. The software testing approach undergoes a revolutionary change through QAaaS solutions.

Just like aeroplanes have different indicators that help the pilots determine the performance of the flight, such as an airspeed indicator, attitude indicator, altimeter, turn coordinator, heading indicator, and vertical speed indicator, businesses also need indicators that help the FP&A determine the business’s performance. These indicators are known as Key Performance Indicators (KPIs). While we already know what KPIs are, let us refresh our memory.