Systems | Development | Analytics | API | Testing

In today's rapidly evolving digital landscape, businesses are inundated with vast amounts of data. Transforming this data into actionable insights is crucial for maintaining a competitive edge. Microsoft Azure stands at the forefront of this transformation, offering a comprehensive suite of analytics tools designed to harness the power of data effectively.

Artificial intelligence (AI) is no longer a futuristic concept—it’s here, and it’s transforming the way enterprises operate, innovate, and compete. From automating workflows to delivering data-driven insights, AI is reshaping industries and creating new opportunities. But as AI becomes more integrated into our lives and businesses, a critical question arises: Who owns and controls the AI agents that are increasingly making decisions on our behalf?

In the rapidly evolving world of embedded analytics and business intelligence, one important question has emerged at the forefront: How can you leverage artificial intelligence (AI) to enhance your data analysis? According to insightsoftware and Hanover Research’s recent Embedded Analytics Report, developers see AI as the most important trend of the next five years.

Even in light of recent return-to-work mandates, it’s clear that the way we work has changed. Remote and hybrid teams are now the norm, and while this shift has brought flexibility, it’s also introduced unique challenges for AI and ML teams. One of the most pressing issues is ensuring seamless access to the compute resources needed to run machine learning workloads.

In 2025, over 80% of enterprises have adopted DevOps practices to speed up software delivery, improve system reliability, and enhance cloud-native transformation. With AI-driven automation, cloud-native applications, and the need for rapid deployment cycles, enterprises are investing more than ever in DevOps consulting services. Choosing the right DevOps implementation partner can make the difference between a stalled transformation and a high-velocity delivery pipeline.

The Java Native Interface (JNI) stands as a pivotal link between the realms of Java and native programming languages like C and C++. It plays a crucial role in Java programming, particularly when integrating native libraries — .so files in Linux or.dll files in Windows. JNI allows Java applications to access and leverage the performance and capabilities inherent in native code.

There is a well-worn adage attributed to famous early American statesman and inventor Benjamin Franklin, who purportedly said, only two things in life are guaranteed: death and taxes. So it’s not without some sense of irony – Tuesday having been “Tax Day” in the U.S. (April 15, the day annual income taxes are due) – that we can proudly proclaim there are now officially THREE things in life that are guaranteed! What’s the third one, you (and Mr. Franklin) might ask?

Application Performance Monitoring (APM) tools are software platforms that help developers, DevOps engineers, and technical managers track the performance and health of their apps and infrastructure in real time. They collect telemetry data like response times, error rates, resource usage, and user behavior, visualize this data, and make it easier to detect performance issues, pinpoint root causes, and ensure a smooth user experience. In short, they help teams be proactive rather than reactive.

The workplace is on the brink of a transformation unlike anything we’ve seen before. With the rise of AI agents—autonomous software entities capable of executing tasks, making decisions, and even optimizing workflows—the way we define work itself is evolving. While automation and AI-assisted processes have been gradually reshaping industries, the concept of the agentic enterprise takes this a step further, shifting from AI as a tool to AI as an active participant in business operations.

AI agents are all the rage these days. Poised as the next big thing after Gen AI…is there substance underneath all the hype? The answer is a resounding yes. For instance, the 2024 State of AI Agents report revealed that 51% of AI professionals are already using AI agents, while 78% of enterprises and mid-sized companies have active plans to put AI agents into production. However, doing this successfully requires paying attention to certain key factors.