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.

Logging is a crucial practice that helps developers monitor, debug, and maintain their applications. Python, a versatile and widely used programming language, provides a comprehensive logging module that makes it easy to integrate logging into your applications. This post introduces Python logging, covering the basics, various logging levels, practical implementations, and more.

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.

With practically everything moving online now and consumers making snap decisions about what to buy and what not- can you really afford to not have an ecommerce website for your business? Well, we don’t think so! According to Tech Jury, 90% of online experiences begin with a search engine. Yes, that’s true! This basically means that if your business doesn’t have a website, you’re losing out on a lot of potential consumers.

At Ably, we provide a realtime messaging service that aims to deliver messages between globally-distributed participants with the lowest latency possible. When powering apps that enable realtime collaboration, or require time-critical updates, low and consistent latency is essential.

Manufacturing has been one of the most prominent industries worldwide since the Industrial Revolution. Since then, from producing textiles to computer chips, manufacturers have always looked for ways to innovate. In the age of AI and APIs (or application programming interfaces), tech companies are looking for technological breakthroughs to gain an edge over the competition.

Internal app sharing is a crucial step in ensuring the quality and functionality of applications before their public release. With the upcoming discontinuation of Microsoft's App Center, developers are looking for robust alternatives that streamline the distribution process and address common challenges faced during internal testing phases. This post explores the intricacies of internal app sharing, highlighting common obstacles and reviewing platforms designed to simplify the process.

At the heart of BPA is automation, which drives efficiency and reduces manual effort. Key elements to look for include: Effective data management is crucial for informed decision-making and operational efficiency. The right platform will offer a strong data fabric architecture to make this possible. A data fabric combines data management, integration, automation, and low-code development tools to build impactful and data-rich digital solutions.

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.