Systems | Development | Analytics | API | Testing

In Java “an event that occurs during the execution of a program that disrupts the normal flow of instructions” is called an exception. This is generally an unexpected or unwanted event which can occur either at compile-time or run-time in application code. Java exceptions can be of several types and all exception types are organized in a fundamental hierarchy. Understanding this hierarchy is crucial for implementing robust error handling strategies in production.

Imagine spending months developing a C++ application, only to have users report that it crashes whenever they enter unexpected input or when network connections fail. This common scenario happens when programs lack proper error handling. The good news is that C++ provides a built-in mechanism called exceptions that helps your code anticipate and respond to problems rather than simply crashing.

APIs have become the backbone of our digital world, with surveys showing that over 70% of developers plan to increase API usage year-over-year. They power everything from mobile apps and SaaS integrations to IoT devices and partner platforms, enabling businesses to deliver seamless services and experiences to customers. As organizations grow, however, so does the complexity of their API ecosystem.

If you’re feeling intimidated about creating your first automated web test with Ghost Inspector, we’ve got you covered! In this article, we show you how easy it is to build and automate web tests with Ghost Inspector. We’ll break down creating your first Ghost Inspector test in just four simple steps. Once you’ve learned the basic steps for how to build a web test, you’ll be able to test complex processes easily, even with zero coding know-how. Ready? Let’s jump in.

Did you know that the average code coverage across industries falls between 74% to 76%?

Join Danielle Forier, Software Quality Assurance Analyst, as she shares the journey of how her QA team transformed their testing strategy by integrating functional and performance testing. Discover how reusable scripts and the right tools helped them achieve seamless workflows, greater efficiency, and the scalability needed to manage a growing and complex product portfolio.

Many organizations run Apache Kafka clusters in private Azure networks to meet stringent security, compliance, and operational requirements. However, securely replicating data across clusters without exposing traffic to the public internet has traditionally been complex, requiring self-managed mirroring solutions with significant operational overhead.

LLM Data Gateways are specialized tools that prepare and secure data for AI systems, ensuring better performance, compliance, and cost efficiency. They act as a bridge between raw data and large language models (LLMs), solving common challenges in AI like poor data quality and security risks.