Systems | Development | Analytics | API | Testing

Would you believe me if I say there is a development methodology that considers changing requirements and technical risks as part of the process instead of obstacles to be overcome? Sounds crazy, right? That’s exactly what I thought about the Spiral Model until I took a closer look. I’m not saying it’s perfect for every project or that we should all use it. But for certain types of projects, the messy, uncertain, high-stakes ones, it may be just what you need!

Not every failure is a bug and not every bug is what it seems. Sometimes, a test fails without warning. No code changes, no environment issues, just a red mark where there should be green. You rerun it, and it passes. These are flaky tests. And they do more than create noise. They drain team time, stall releases, and make it harder to trust automation at all. Left unchecked, they quietly become one of the most expensive problems in testing.

For Taohao, being a Senior Software Engineer means never standing still. Whether it’s picking up a new skill, diving deeper into a complex system, or exchanging ideas with teammates, he thrives in an environment where curiosity, innovation, and collaboration come together. Let’s find out what makes Confluent the place where engineers like Taohao aren’t just solving problems but are constantly learning, challenging each other, and building what’s next.

Build smart, innovative data products by pairing context-aware AI with automated data integration.

When developing iOS applications, creating an IPA file is a crucial step in distributing and testing your app. But managing this process—especially across development teams—can become tedious and error-prone if done manually. In this post, we’ll explain what an IPA is, why it matters in CI/CD pipelines, and how you can seamlessly generate, sign, and distribute IPA files using Bitrise automation.

With constant releases, testing on multiple devices, and users scattered across the globe, internal teams alone can fall short. To address these issues, companies are increasingly resorting to crowdsourced testing.

Let’s say you’re renovating a house. It’s a big project, and you’ll need a lot of planning, expertise, and equipment. Now imagine you live in a world where the hammers you bought at one store don’t match up with the nails you bought at another, and certain wrenches wouldn’t work on anything but the parts they came with. What a pain, right?

Amazon Web Services (AWS) had a well-documented failure of the S3 service in its US East region this week. The knock-on effects of the S3 outage took out many of Amazon’s other services and caused serious and long-lasting outages for many high-profile services including Quora, Trello, GitLab, and many others. Overall Amazon provides an outstanding set of services, and as anyone knows these things happen, the key is to architect your solution so that it can tolerate these kinds of failures.

I remember the time when Selenium was first set up. It felt empowering a reliable tool for browser automation. But over time, the shine wore off. I was spending more time fixing broken tests than validating real features. That’s when I thought of Migrating from Selenium to Playwright and honestly, I wish I had done it sooner. The speed, stability, and built-in smart features just work. What makes Playwright stand out from Selenium is its clarity.

Security breaches rarely begin with a hidden zero-day exploit or a complex web of escalated hacks. They often start in very simple ways – an internal team member is breached, a permission is misconfigured, an overly permissive API endpoint is overlooked, or a JWT simply doesn’t expire. An API, or application programming interface, is a set of protocols and tools that enable different software systems to communicate and exchange data, making them essential in modern software development.