If you asked anyone at your organization, there’s no question they could name at least one business process that needs streamlining—probably they could name several. That’s the hard truth for leaders looking to gain digital transformation speed in pursuit of critical business goals, like faster customer onboarding and faster time to market.

As Java has evolved over the years, multiple attempts have been made to simplify development for various use cases. From official standards like Java Enterprise Edition, to community-driven frameworks, Java is continuing to prove itself to be adaptable and viable. Our top list is based on usage from Hotframework.com's Java ranking and several other sources including blog posts and GitHub download numbers.

How many times have you heard the sentence that starts with “This software is compatible with Windows 8 and above” or “Only compatible with Android version 6.0 and above”? I am sure this would ring a bell for all gamers as games are highly sensitive to the platform they are run on. But for non-gamers too this would be the first thing they need to check if they know they are operating on an older version of the operating system.

S3 Lake Formation with Apache Iceberg enables ACID compliance, the key to data lake governance and regulatory compliance.

Imagine you’re planning a road trip across the country. You’ve got your car, a map, and plenty of snacks for the journey. But there’s one crucial thing missing – a functional engine that will get you from point A to point B without any issues. That’s exactly why API functional testing is so important. APIs are the engines that power our software applications. They allow different systems to communicate with each other and transfer data seamlessly.

Today, all applications run on API. It connects one microservice to another, clients with servers, and runs the most basic yet essential application services. Clearly, a well-oiled API is imperative to ensure the smooth functioning of every system. If API breaks down, the complete user experience and application are put at risk. And only proper API testing can secure the system from such downtime possibilities.

In today’s data-driven world, businesses must deal with complex challenges related to managing, integrating, and properly using massive amounts of data housed in multiple locations. Organizations that unlock the right data architectural approach empower themselves with much better decision-making and strategic insights. Two popular approaches — data mesh and data fabric — have surfaced as prominent and innovative solutions for handling data at scale.

There are many ways to load code and access file-related constants in Ruby. We can create a clear architecture by separating and handling concerns into classes and pulling in only the classes we depend on. Many full-stack frameworks like Rails and Hanami offer a built-in method to access the classes we want, as long as we stick with a certain convention. How does this work? In this post, we will explore three different options for loading code: using load, require, and autoload.

Welcome to the third blog post in our series highlighting Snowflake’s data ingestion capabilities, covering the latest on Snowpipe Streaming (currently in public preview) and how streaming ingestion can accelerate data engineering on Snowflake.

Following the improvements to Bitrise’s Breakdown Chart, here is a quick walkthrough of how to leverage those Breakdown Chart improvements, including filtering options, exporting data, and more.