Systems | Development | Analytics | API | Testing

Next.js (a React framework) and Vercel (the platform created by the Next.js team) are renowned for providing a smooth and efficient development workflow. This allows developers to quickly build, test, and iterate on interfaces for AI features, which is crucial in the rapidly evolving AI space. Features like Fast Refresh, easy setup, and integrated tooling speed things up considerably.

WSO2 APK (WSO2 API Platform for Kubernetes) provides a robust, Kubernetes-native platform for managing APIs. It’s purpose-built for cloud-native teams requiring fine-grained control over APIs in modern, distributed environments. With support for microservices architecture, secure ingress, and service discovery, APK solves the infrastructure side of the API equation.

As developers, we know how essential APIs have become in building modern software systems, from internal services to public-facing products at scale. We spend countless hours crafting elegant code, meticulously designing interfaces, and ensuring everything should work flawlessly. And, we must ship these services fast to stay competitive. But what happens after deployment? In reality, even the most beautifully crafted API can fall flat without deep insight into its real-world usage.

In this episode, Derric Gilling, CEO of Moesif, sits down with Mike Amundsen, a leader in the API ecosystem, to explore the evolving role of observability in API design and customer experience. They break down the differences between machine vs. customer observability, best practices for tracking key metrics, and the importance of designing observability into APIs from the start.

A report by Bloomberg Intelligence projects the AI industry will reach $1.3 trillion by 2032, with proprietary data fueling much of this growth. As businesses increasingly adopt generative AI (genAI) to enhance efficiency, data is rapidly becoming one of the most valuable assets in the digital economy. Foundational AI models require vast amounts of data for training, and many AI products are now leveraging proprietary datasets alongside these models to power innovative applications and AI agents.