Systems | Development | Analytics | API | Testing

The promise of agentic AI is huge. But how is it impacting the enterprise and the developers and IT professionals most likely to be working with it right now? To find out, Kong evaluated labor market data and surveyed 550 tech leaders, developers, IT decision-makers, and Kong users.

It's Monday morning, and your team is about to walk into a nightmare: over the weekend, your web app broke in three different browsers. Checkout flows are getting stuck, animations are glitching, and support tickets are already stacking up. Traditional forms of testing would take forever to find the root cause of this catastrophe, and until then, your team cannot release it. But today, no team or developer has days to spare.

These days, in the quickly evolving world of software, just executing automated testing is not sufficient. Real quality only results from what follows results analysis, pattern tracking, and insights from failure.Test reporting and analytics come into their own here. By converting raw test data into valuable insights, teams can catch flaky tests, pinpoint common problems, and make better decisions more quickly.

Building real-time applications in the cloud means making the right infrastructure choices early. And for many engineering teams leveraging Amazon Web Services (AWS), Apache Kafka is a key component of their streaming architectures. While open source Kafka provides a powerful foundation, operating it at scale in production often means navigating challenges when provisioning, scaling, securing, and integrating across environments. That’s where Confluent Cloud comes in.

Every action you automate in Selenium starts with one thing: finding the right web element. That’s where locators come in. They guide Selenium to the exact button, input field, or text box it needs to interact with. Locators in Selenium are essential. Without them, you can't click a button, fill out a form, or verify if a message appears on the screen. They're the foundation of every test case you write. In this article, we’ll walk you through: Let’s get started!

Testing is hitting its limits in speed, scale, and insight. AI-augmented and agentic systems can help but only if we adopt them intentionally. This blog series lays out a Crawl–Walk–Run maturity path for adopting agentic testing capabilities safely and strategically. We’ll show you how to move from assistive agents to coordinated systems without losing control or trust.

Vietnam is one of Asia's most significant high-growth markets for open banking adoption. With a young, tech-savvy population, rapid digital adoption, and a vibrant fintech ecosystem, the country is uniquely positioned to leapfrog traditional banking models. Vietnam's financial sector is ripe for mobile-first innovation. The country has roughly 49 financial institutions and an internet penetration rate approaching 80% supported by a youthful, digitally proficient population.

Modern enterprises are embracing multi-cloud strategies to avoid vendor lock-in, optimize costs, and ensure resilience. Yet managing API infrastructure (which also happens to be AI infrastructure) across multiple cloud providers while maintaining performance and simplicity remains a significant challenge.

IT Professionals Day is our opportunity to celebrate the people who keep the digital world running - the ones who make sure data is secure, reliable, and ready to power innovation. At Qlik, we know IT professionals aren’t just solving problems, they’re enabling possibilities.

A few months ago, at Qlik Connect, we announced the launch of Qlik Open Lakehouse, a new, fully managed capability that brings together the best of the Upsolver platform together with Qlik Talend Cloud. And today, we are excited to announce the general availability of Qlik Open Lakehouse within Qlik Talend Cloud that makes it easy and cost-effective for organizations to ingest, optimize, and manage massive amounts of data directly in Apache Iceberg–based lakehouses.