Systems | Development | Analytics | API | Testing

Let's dig deeper into emulator and UI test-related issues for Android! The last article of our Android testing series by Richard Bogdan, Senior Software Engineer.

A critical decision for organizations that are defining their automated testing strategy is choosing the right automated testing framework that will help their development and QA teams efficiently write and execute automated tests. The market offers a plethora of frameworks to choose from, and the decision isn’t always easy.

Knowing best practices for Amazon Web Services (AWS) data pipelines is essential for modern companies handling large datasets and requiring secure ETL (Extract, Transform, Load) processes. In this article, we discuss AWS data pipeline best practices to ensure top performance and streamlined processes — without complications that can impede the execution of data transfer.

Flutter is a user interface toolkit from Google which is primarily used to develop mobile applications but can also be deployed to create web and desktop apps. With Flutter, we can develop applications for both IOS and Android using the same source code. This dovetails neatly with Bugfender, our remote logging service that allows users to collect logs for everything in the application.

It's your time to set up your testing on Bitrise! In the third article of our Android testing series, we will give you some hints on how to effectively run a virtual device on your CI.

This is a step-by-step guide with hands-on tips for migrating your iOS apps from Jenkins and fastlane to Bitrise, quickly and easily.

We all know that what customers see in the market is, in fact, only a small percent of the shifts happening within our organizations. Recently, Time Magazine stated that “Every Company is a Tech Company… The Disruption is Just Beginning.” We’re seeing it in the way we wait in lines, find places to stay when traveling and work from anywhere. The disruption is distribution, and it impacts how we live and build applications.

If you’ve been following Apache Kafka over the past few years, you’ll know a very important milestone has now been reached. The company that was spun out of LinkedIn to propel this open source technology to the future is now going Public. Well done Confluent, congratulations on your IPO!

Across organizations large and small, ML teams are still faced with data silos that slow down or halt innovation. Read on to learn about how enterprises are tackling these challenges, by integrating with any data types to create a single end-to-end pipeline and rapidly run AI/ML with Azure Synapse Analytics with Iguazio.