Systems | Development | Analytics | API | Testing

AI is no longer just a tool. It is now handling complex tasks with minimal human intervention and oversight. This transformative shift has given rise to agentic AI, where AI-powered systems make decisions, adapt to new information, and automate workflows across departments. From answering customer inquiries to managing financial data, these AI-driven agents are reshaping how businesses operate.

The industry of design and development faces numerous challenges. One of the biggest challenges is to move a project from a mere concept to successful execution. These projects involve many levels of stakeholders, like clients, designers, developers, and project heads, each having their own understanding and dreams with the concept at hand. Thus, to visually understand these differences and execute the concept successfully, communication becomes key.

Within the realms of microservices and distributed systems, gRPC has emerged as a cornerstone technology. Its adoption by tech giants like Google, Netflix, and Square underscores its capability to facilitate high-performance, scalable inter-service communication. Built as a modern take on the traditional Remote Procedure Call (RPC) paradigm, gRPC enables services, potentially written in different languages, to communicate efficiently and reliably across networks.

The Android emulator is an Android virtual device that is used to test and debug Android code. It looks and behaves the same as a physical Android device, and while it has some limitations (more of which later), it provides real time and cost savings for developers. Unlike the iPhone, which is limited to one manufacturer and a specific number of iOS versions, there are thousands of Android device types out there.

Saks, Canva, and Condé Nast centralize data with Fivetran to create elevated customer experiences, paving the way for personalized online retail and media.

Happy Earth Day 2025! This year's theme, "Our Power, Our Planet," resonates deeply with Qlik's ongoing commitment to environmental stewardship. We believe that creating a sustainable future requires a collective effort, and we're dedicated to prioritizing and embracing renewable energy sources. Our goal is ambitious: to triple the use of clean energy sources by 2030.

Across the globe, organizations are united by one shared priority: sustainability. While committing to environmental, social, and governance (ESG) initiatives is simply the right thing to do to preserve our planet for future generations, businesses face additional pressure to prioritize sustainability via regulations, expectations from investors, and consumer preferences. Since 2019, thousands of companies have committed to achieving net-zero emissions.

Enterprise organizations rarely operate with a single API gateway. As business units adopt technologies independently, it is common to find, for example, Kong in one domain, AWS API Gateway in another, and additional platforms elsewhere. This flexibility drives velocity—but it also fragments visibility. Without a unified view of API activity, enterprise teams face inconsistencies in reporting, gaps in customer insights, and difficulty enforcing governance policies.

Earth Day gives us all the opportunity to raise awareness, reflect and take action to support a sustainable future. The day, which offers so many ways to get involved, means many things to different people. Fortunately, in the data infrastructure business, there are many areas where we can make improvements to support resilience, efficiency and optimization. At Hitachi Vantara, we’re committed to the principles of sustainability and responsible business practices.

AI-powered development is moving faster than ever. Tools like Cursor, Windsurf, and GitHub Copilot, and models like ChatGPT-4, Claude, and Gemini transform how software is built. These tools can generate code, solve problems, and deliver full applications in a single day, far quicker than traditional methods. But with this rapid development comes a major challenge: testing. While code is generated in hours, traditional testing tools and methods lag.