Systems | Development | Analytics | API | Testing

Have you ever wished you could just ask your CI platform a question instead of digging through logs or scrolling through builds? Well your wish has been granted: Bitrise MCP (Model Context Protocol) Server is here, a new, conversational way to interact with your CI.

Quality can no longer be an afterthought and traditional testing approaches often struggle to keep up with modern applications’ complexities. This is where data-driven testing comes in - bringing predictive insights to the forefront of QA. Data-driven testing enables a strategic approach to quality, where every test is backed by insights. As the world moves into a future driven by AI, automation, and continuous testing, embracing data-driven testing became essential.

Recent leaks have once again brought API and data security concerns into the spotlight. Specifically, the leaks pointed at the following as major areas to consider when thinking through your API and data security strategies: When considering the above, it’s critical to think about best practices across every stage of the API lifecycle, starting with the initial phases of API design and testing.

Software development has always evolved with new paradigms to meet the growing demands of modern systems. One of the most significant shifts has been the adoption of microservices. Emerging in the early 2010s, this architectural pattern moved away from monolithic applications in favor of smaller, independent services that interact with each other over a network.

APIs (application programming interfaces) have transformed how we build modern software systems. As our digital experiences become more modular and interconnected, APIs power mobile apps, partner integrations, and internal services. Most companies now expose APIs not just for technical access, but as part of a larger API business model. But simply deploying APIs through a gateway like Gravitee doesn’t suffice.

For today’s IT Director, the pressure has never been greater. Tasked with delivering business-critical technology in a landscape of shrinking budgets and expanding expectations, IT leaders find themselves at the intersection of business demands and technical realities. On one side, C-suite executives and department heads expect solutions that improve efficiency, drive innovation, and deliver competitive advantage.

In this episode, Derric Gilling chats with James Higginbotham, founder of LaunchAny, about designing successful API strategies that drive business value. James dives into his “Align-Define-Design-Refine” (ADDR) methodology, a framework that guides organizations from initial business alignment through iterative API design and deployment.

Google Cloud Platform, or GCP, is a cloud resources collection offered by Google for enterprise and standard users. GCP offers a wide range of cloud services, including compute, storage, networking, security, analytics, and even machine learning models. Google Cloud products are the backbone of many cloud applications. Google Cloud allows flexibility with the scalable and predictable cost management.

Data visualization is an elementary component of human learning and understanding. It's also a significant capability of business intelligence (BI) and analytics solutions today. So, how did data visualization first come to be? The humble origins and gradual evolution of data visualization tools has led to an interesting timeline.

As data-driven decision-making becomes more complex, businesses need tools that don’t just analyze data but actively guide smarter, faster decisions. At Databox, we are embracing the shift. In 2024, AI became one of our top strategic priorities. Now, we are taking an even more significant step: transitioning into an AI-first company.