Leveraging Codezero can significantly benefit AI developers in building better, larger, and more sophisticated models through its suite of features designed to simplify and secure microservices development. By addressing common challenges in AI model development, such as environment consistency, collaboration, scalability, and security, Codezero provides a conducive environment for innovation and efficiency. Here’s how AI developers can harness Codezero for these advantages.

This article was origninally published here. In this article, we’re spilling the beans on why we switched from Azure to Codemagic and showing you exactly how to supercharge your CI/CD game. We’re covering the entire spectrum — from compiling and creating release notes to testing and deployment. Let’s rewind a bit to our iOS developers’ struggles. Our CI process (think builds, tests, and coverage) was taking a chunky 40–50 minutes.

In today's hyperconnected world, where negative reviews on social media can wreak havoc on a company’s reputation, delivering an exceptional customer experience isn't just a luxury—it's a business imperative. Companies are locked in a fierce battle for customers that is primarily based on their ability to deliver outstanding customer experiences (CX). According to research by The Conference Board, 65% of CEOs globally prioritize investing in strategies to improve CX.

Organizations are increasingly turning to business process management (BPM) to boost efficiency and meet aggressive business goals. BPM is a discipline and set of practices that enable organizations to optimize processes for greater efficiency, effectiveness, and business agility. Organizations buy commercial-off-the-shelf (COTS) BPM to facilitate this process. Data and software integration can be time- and resource-intensive with COTS BPM software.

Why did we choose MongoDB for our projects? Here’s a quick overview of the five big reasons that convinced us. From its perfect fit with JavaScript to its unmatched flexibility and growth.

Javascript Object Notation (JSON) is becoming the standard log format, with most modern applications and services taking advantage of its flexibility for their logging needs. However, the great flexibility for developers quickly turns into complexity for the DevOps and Data Engineers responsible for ingesting and processing the logs. That’s why we developed JSON FLEX: a scalable analytics solution for complex, nested JSON data.

Headline: The transition to Codemagic made our CI builds faster and more reliable and positively impacted the experience of contributors contributing to our open-source project, Tuist. Thanks to Codemagic’s support, we can bring new free goods to the Swift community and the ecosystem of app developers.

You can now unpack the Christmas present that was promised to you at the end of 2023! As you may have already read in the Flamegraph Feature Preview, this exciting new feature of the Profiler is now the focus of our first release in 2024. The Flamegraph complements the Timeline and Callgraph features and visualizes Aggregated Traces. The goal was to provide profiling information across many traces and thereby gaining new and deeper insights into performance.

In this blog series, I am exploring the “sliding doors”, or divergent paths, for creating value with data across different use cases, practices, and strategies. In this post, I want to discuss how to generate value with Data Products. As I reviewed in my last blog, grabbing the door to the better path for managing your data isn’t just about solving your particular use case: it’s ultimately about delivering value for your business.

Introducing new BigQuery SQL features for performing two of the most common time-series operations: windowing and gap filling.