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.

Logs are the core of the human-machine interface for software developers and operators. Historically, they are very much like caveman paintings. They were our first attempt to express and understand how our software was working. For several decades, logs were an island of calm in a rapidly changing technological ecosystem. Logs remained the same even as software services became web-based and grew in scale.

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.

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.

Software testing has evolved from an inconvenient ad-hoc process to an integral part of the software development lifecycle. However, while many teams have caught on to the benefits of test automation frameworks, some organizations have yet to scale up and expand their test coverage with cloud-based devices for integration tests.

Flaky tests are one of the most common and frustrating issues in software testing. These are tests that pass or fail sporadically, even if the code being tested has not changed. This can cause confusion and wasted time for developers who are trying to fix issues that may not even exist.

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.

Despite its many advantages, Node.js comes with a set of potential pitfalls if you don't maintain your application properly, such as: In this post, we'll explore these pitfalls and how to avoid them. Let's dive straight in!

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.