In the space of APIs for consuming up-to-date data (say, events or state available within an hour of occurring) many API paradigms exist. There are file- or object-based paradigms, e.g., S3 access. There’s database access, e.g., direct Snowflake access. Last, we have decoupled client-server APIs, e.g., REST APIs, gRPC, webhooks, and streaming APIs.

In the modern era of AI-based innovations and cloud transitions, businesses face the challenge of managing complex processes across multiple systems — and the rate of change is only accelerating. At the same time, businesses need to ensure that the introduction of new innovations driven by accelerated business transformation doesn’t break existing processes and systems.

Snowflake’s mission is to mobilize the entire world’s data, and there are millions of data scientists and developers who don’t have access to full-stack engineering teams. It’s been our endeavor to bring the power of the AI Data Cloud to every individual developer, data scientist and machine learning engineer, so that they can build and share world-class data apps — all by themselves. Streamlit is an open source library that turns Python scripts into shareable web apps.

In the dynamic world of technology, managing and optimizing workforce productivity is a challenge for many organizations. Insightful, a leading workforce analytics and productivity software, is designed to address this challenge by providing actionable data insights. This review will delve into the features, pricing, pros, and cons of Insightful, a tool that is transforming the way organizations manage their teams.

Testing early and often may sound like a simple idea, but implemented effectively requires a cultural shift and the right set of practical tools.

Handwriting code for database APIs can be a time consuming and expensive process that often exposes organizations to a variety of risks relating to quality, consistency, and developer effort. DreamFactory specialises in REST API generation for a range of databases that gives you the ability to generate a secure, fully documented API in minutes.

When we initially started building our test recorder, we needed a way to validate the id attributes being used on the page. We would sometimes capture an id attribute in a recording, only to find that it failed when we used it in a test, because it didn’t meet specification. For instance, sometimes websites would use an id with a number in front, like this: That is technically invalid, at least in the HTML4 specification.

Welcome to the ultimate resource for mastering load testing! Whether you’re a non-technical business owner, a software engineer, a student, a product owner, a member of a web agency, or a DevOps professional, this article will show you how to approach load testing challenges head on. We’ll progress from the fundamentals to more in-depth strategies, all in a relaxed and easy-to-understand manner. Are you ready to ensure that your website runs smoothly even during peak traffic periods?

At a time when artificial intelligence (AI) and tools like generative AI (GenAI) and large language models (LLMs) have exploded in popularity, getting the most out of organizational data is critical to driving business value and carving out a competitive market advantage. To reach that goal, more businesses are turning toward hybrid cloud infrastructure – with data on-premises, in the cloud, or both – as a means to tap into valuable data.

Using BigQuery DataFrames with CARTO visualization tools can help Python users access cloud-native analytics and generative AI services.