Upon close inspection of the growing adoption of artificial intelligence across different industries, it becomes apparent that a lot it rests on the shoulders of API-powered systems. A survey by McKinsey found that 56% of respondents reported AI adoption in at least one function within their organizations, with significant increase in the use of AI APIs for tasks like natural language processing and computer vision.

API governance sets the rules and practices to manage APIs efficiently, ensuring they remain discoverable, consistent, and secure. It’s crucial for businesses aiming to control API sprawl and enhance collaboration. This guide explores API governance, its role in effective API management, its benefits, and best practices for successful implementation.

An API model acts as a blueprint for building scalable and maintainable software interfaces. In this article, you’ll discover how to design, implement, and validate a robust API model, including the use of AI models. We’ll cover key concepts like API modeling, essential components, user identification, and best practices.

The open-source philosophy and principles have always been about the democratization of knowledge—giving everyone the opportunity to access, learn, modify, and share software freely. As we see AI technologies seemingly taking over our day-to-day lives, we need those benefits in AI as well. Open-source AI inherits the open-source principles. It fosters transparency and collaboration, allowing us to build robust and secure AI systems.

Product analytics helps you understand how users interact with your product, offering insights that drive growth and improve user experience. In this guide, you’ll learn about essential metrics, strategies, and tools for effective product analytics. By leveraging these insights, businesses can make informed decisions, optimize product features, and enhance overall user satisfaction.

Not long ago, the thought of Artificial intelligence (AI) products becoming mainstream seemed far off. Fast forward to the widespread adoption of ChatGPT, Gemini, and other large-scale apps, and it’s easy to see that the world has changed drastically. AI isn’t just the future anymore – it’s the present, and every business is hopping on the bandwagon. From chatbots streamlining customer service to algorithms predicting market trends, AI is reshaping how businesses operate.

Building and consuming Application Programming Interfaces (APIs) has become an essential skill for developers. APIs are the glue that enables seamless integration and interaction between different software systems, including those that leverage AI. As the demand for artificial intelligence (AI) grows, the monetization of AI APIs has emerged as a critical concern for businesses looking to capitalize on their technological investments. Almost all AI functionality that companies build is exposed as an API.

API versioning is key to updating your API without breaking clients’ integrations. It ensures smooth transitions and maintains compatibility. This guide explains the best strategies and practices for effective API versioning. API versioning is not just about the technicalities of managing different versions; it also involves a strategic approach to communication, documentation, and support.

An API endpoint, often referred to as an endpoint URL, is a specific URL that allows access to a particular resource on a server, facilitating communication between different systems. It’s crucial for developers as it enables them to integrate and utilize functionalities from other systems, like payment gateways or social media platforms, streamlining their development process.

If you’re looking to integrate web services using Python, mastering REST APIs is crucial. This article delivers a clear, step-by-step guide to leveraging Python with REST API’s straightforward syntax and libraries to build and connect with RESTful services. From environment setup to security and beyond, expect practical advice that will elevate your Python with REST API projects seamlessly within the world of REST APIs.

What does ‘API’ stand for, and why is it essential in the tech world? API, short for Application Programming Interface or the API acronym, is a crucial component that enables different software programs to communicate with each other. This article is your guide to understanding APIs: from their basic definition to their architectures, and their role in shaping modern digital experiences.

Testing REST APIs is crucial for reliable software. This article zeroes in on harnessing REST API for test, focusing on the practicalities of verifying API performance and security. Learn the steps and techniques for testing REST API, including the tools and methods used, the challenges faced, and the significance of REST API testing in web applications. Skip the guesswork and discover surefire tools and techniques that fortify your testing protocol.

API observability is essential for enhancing performance, speeding up issue resolution, and tightening security. An API observability tool is crucial for understanding and managing the complex web of API interactions within modern enterprise applications. With the benefits of API observability, you can dive deep into API behavior, ensuring reliability and better user experiences.

In the previous article, we set up the AI API with AWS Lambda and Gateway, integrated it with Moesif, and then connected Stripe with Moesif. We now have the infrastructure to begin billing for API usage. In this article, we move on to configuring Moesif with the following steps in the API monetization journey: First, let’s set the prices we want to charge for API usage in Moesif.

Building APIs is a fact of life for most modern developers. When we aren’t building them, we integrate them within our applications. Regardless of how you look at it, modern businesses are built on top of the foundation that APIs have built. They’re the bridges that allow different software systems to talk, share data, and work together seamlessly. But with great power comes great responsibility.