Systems | Development | Analytics | API | Testing

The latest Node.js release has arrived, and it's not just another incremental update. It delivers meaningful improvements that directly address real-world pain points and opens up new possibilities for JavaScript on the server. In this article, we'll cut through the changelog noise and focus on what's genuinely worth getting excited about in this release. Let's get started!

Balancing latency and throughput is critical for managing distributed rate limiting systems effectively.

You will need the following architectural decisions and migration process to make a data lake the center of your architecture.

Automation testing is designed to make your life easier by speeding up your releases, catching bugs before your users do, and providing you with some much-needed peace of mind. So why is it that so many teams pour time and energy into UI automation and still end up with slow, flaky runs and missed bugs in production? It might surprise you to know that most of these problems come down to a few common mistakes that are easily avoidable once you know what to look for.

Creating API documentation from scratch remains a complex and time-consuming challenge, especially as APIs become more central to digital transformation in 2025. Today’s best API documentation tools leverage automation, AI, and interactive features to simplify the process, ensuring documentation is clear, accessible, and up-to-date for both technical and non-technical users.

Business intelligence (BI) dashboards, also known as BI dashboards, are a powerful way to help people collect, share and analyze their business data to make informed decisions. Business dashboard software can help users monitor operations, optimize processes, and improve overall business performance by having data readily available, and can also help detect and prevent potential problems before they become issues with its use of real time data.

Data products in BigQuery help teams organize and share data effectively, by managing data as a product, cutting down time to insights.

Everyone is taking part in the AI scramble, some more successfully than others, as we all know. But many enterprise companies are still just getting their feet wet. Here at Qlik we saw an opportunity to try to capture what it is that these successful companies did to get value from AI for their organizations. So, we partnered with IDC to get those answers and discovered that preparation is a major difference maker for success with AI.

When evaluating automation testing companies, you’ll notice most promise the same benefits: faster release cycles, fewer bugs in production, and less testing work for your development team. But in our experience, many fall short. They bottleneck releases, miss bugs users immediately notice, and still rely on your developers to write and maintain tests.

Between the relentless pressure to ship new features and updates, and the increasing adoption rates of DevOps, AI’s influence in the future of the testing landscape is palpable, and the focus in the coming years will be applying that to QA teams everywhere.