Systems | Development | Analytics | API | Testing

TL;DR – No flaky builds because of “data‑center air” at Bitrise! We built our own chassis that can talk to the Bitrise scheduler, can pre‑cool itself, and squeezes 32 Mac minis into a 6 rack unit oversized pizza box—while looking downright gorgeous doing it. We call it the mini Orchard.

Every new protocol introduces complexities—onboarding new tools and SDKs, adapting to new processes, evaluating security and performance implications, ensuring compatibility with existing systems, and overcoming the learning curve. So when a new protocol shows up, the first question to ask is: is it really necessary? Let’s ask that about MCP—what problem is it trying to solve?

Automation has long been a key driver of efficiency. Traditional RPA and IDP technology promised to relieve carriers from rekeying, extracting data from forms, and other repetitive tasks. At Appian, we saw early that automation in isolation doesn't achieve transformative outcomes. Why? Because AI has too often been deployed at the edges of workflows: copilots, chatbots, or analytics dashboards that assist us when prompted.

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.

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?

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.

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

Speed isn’t everything in software development, but getting high quality apps out fast is still crucial. That’s where DevOps comes in: its core purpose is to streamline the delivery of apps as quickly and reliably as possible, without sacrificing quality at any stage of the process. ‍ At the heart of DevOps automation are three essential concepts: CI, CD, and CT. ‍ CI and CD are often used interchangeably, but each of the three concepts serves a distinct purpose.

A joint post from the teams at NeuBird and Confluent For organizations leveraging Confluent, ensuring smooth operations is mission-critical. While Confluent Cloud eliminates the operational burden of managing Apache Kafka, application teams still need to monitor and troubleshoot client applications connecting to Kafka clusters.