Systems | Development | Analytics | API | Testing

In addition to its existing text embedding models, you can now use both Google’s Gemini and open-source (OSS) models directly within BigQuery.

Your AI-powered data science partner just got a major upgrade. The Data Science Agent now automates ML workflows with Spark, BigQuery ML, & BigQuery DataFrames.

Enterprises often host their backend services within private internal networks, whether in on-premises data centers or restricted cloud environments. This setup is essential for protecting sensitive data, meeting compliance requirements, and reducing exposure to external threats. But it also introduces a major hurdle: how do you let external consumers and partners access the right APIs without opening unnecessary doors into your private infrastructure?

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.