Systems | Development | Analytics | API | Testing

Just a few years ago, AI’s effect on software development was debatable — would it be as transformative as everyone predicted? But its impact is undeniable. In a 2024 survey, a majority of developers reported using AI in development, a sharp increase from the year before. In a short period of time, developers adapted, integrating agentic AI into their daily operations to boost productivity. Quality assurance teams are not far behind.

Most modern enterprises are generating more data than they can use, let alone integrate, analyze, and extract value from. Some figure out the secret to data value extraction is monetization—identifying data so valuable that other companies will pay for it. And now, the shift to real time data monetization is no longer a strategic option but a fundamental requirement for modern enterprises.

WSO2 Integrator, which unites the BI, MI, SI, and ICP components, continues to evolve to help enterprises build and manage integrations that are faster, smarter, and easier to operate. With the November 2025 release, the product becomes more cohesive, intelligent, and developer-friendly than ever before. Included in this release: Together, these updates empower teams to innovate faster, govern integrations effectively, and operate reliably across the enterprise.

When you treat data as a product, your architecture delivers reliable, reusable data assets for every team.

In a previous blog post, we introduced one of the most significant advancements in Qlik Predict to date — multivariate time series (MVTS) forecasting, bringing enterprise-scale accuracy and context to complex prediction problems. But MVTS is only part of the story. Over the past few months, we’ve continued to enhance Qlik Predict with several powerful updates designed to make predictive AI more trustworthy, fair, and connected for our customers.

Software teams today are routinely under pressure to release features more quickly, while keeping quality in check, in today’s fast-paced digital ecosystem. Automation testing enables teams to develop this balance; however, most teams find that writing and maintaining test scripts becomes a heavy burden with technical complexity, and takes time away from building features. This is where a Test Recorder is of great assistance.

Is your artificial intelligence (AI) underperforming? You're not alone. Stale, fragmented data is a leading obstacle to optimal AI performance. Outdated information cripples your decision-making, fuels operational inefficiencies, and leads to missed opportunities—from slow fraud detection to irrelevant chatbot responses. AI’s rapid evolution makes real-time data even more critical: That’s why real-time data streaming isn’t merely an option.

The Kubernetes networking landscape is evolving, and recent announcements confirm a significant community shift. The Kubernetes community recently announced the upcoming retirement of one of its most widely used components: Ingress NGINX "To prioritize the safety and security of the ecosystem, Kubernetes SIG Network and the Security Response Committee are announcing the upcoming retirement of Ingress NGINX. Best-effort maintenance will continue until March 2026.

BigQuery managed AI functions let you use generative AI for common analytical tasks within SQL queries, without complex prompt tuning or new tools.

The new MATCH_RECOGNIZE feature in BigQuery allows you to perform complex pattern matching on your data directly within your SQL queries.