Mocking APIs is a popular practice in software development. An increasing number of developers are reaping the benefits and no longer using their valuable time to spin up duplicate resources. Many mock services do not require account creation, making them easy to use and privacy-friendly. In the rest of this article, we explain what mock APIs are, when you should think about using them, and what solutions are available within the open-source and proprietary markets.

AI Adoption in SMBs: Key Trends, Benefits, and Challenges from 100+ Companies With larger competitors already using AI to streamline operations and gain a competitive edge, SMBs can’t afford to fall behind. But for many, adopting AI is easier said than done. Limited budgets, lack of in-house expertise, and the fear of wasting time and resources on the wrong tools often leave business owners stuck in decision paralysis.

Companies that stand still in today’s ever-evolving, fast-paced business landscape are at significant risk of losing competitive advantage. Increasingly, high-quality software is playing a vital role in ensuring that organizations are able to innovate, pivot, and adapt to suit the growing demands of their customer base. However, application testing challenges have significantly hindered the pace at which software can be delivered for too long.

According to recent research, scaling intelligent automation could save the Energy & Utilities industry between $237 billion and $813 billion in operational costs. Despite this immense potential, utility providers still grapple with intense competition, increasingly stringent regulations, and aging infrastructure and workforce challenges. The demand for more affordable and cleaner renewable energy only adds to these pressures.

When it comes to ensuring software quality, having a well-defined Test Plan and Test Strategy is crucial. As a software developer or QA professional, understanding the differences between these two concepts and how to write a Test Plan or execute a test strategy effectively can significantly improve your testing process.

From ancient Greek myths of talking statues to the modern-day Alexa and Siri, the concept of machines capable of understanding and responding to human language has captivated us for centuries. In recent years, this concept has evolved into AI chatbots, highly sophisticated tools that can read our queries and perform tasks ranging from customer service to automated alerts.

The Director of Product Management at AWS sat down with Fivetran to unpack how Iceberg and metadata are reshaping the future of data lakes, data warehouses and AI.

For the last couple of years, Retrieval-Augmented Generation (RAG) architectures have become a rising trend for AI-based applications. Generally speaking, RAG offers a solution to some of the limitations in traditional generative AI models, such as accuracy and hallucinations, allowing companies to create more contextually relevant AI applications.