In the dynamic world of software development, quality is paramount. Every line of code, every feature, every functionality needs to be meticulously evaluated to ensure a flawless user experience. This is where test cases come in – the unsung heroes of the development process.

Today’s data-driven world requires an agile approach. Modern data teams are constantly under pressure to deliver innovative solutions faster than ever before. Fragmented tooling across data engineering, application development and AI/ML development creates a significant bottleneck, hindering the speed of value delivery required to stay competitive. Disparate tools create a complex landscape for developers and data teams, hindering efficient pipeline development and deployment.

The medical device industry has recently seen a troubling increase in recalls, often due to software failures or software-to-hardware miscommunication. The number of medical devices with software is also increasing, considering the rise in IoMT (Internet of Medical Things). These issues highlight the urgent need for thorough and robust testing methodologies to ensure the reliability and safety of medical devices.

Having a dedicated branching strategy is key for teams wanting to speed up their workflows, meet tasks on a deadline, and reduce code errors. But with all the different branching strategies – including release branching, trunk-based branching, feature branching, and more – it can be difficult to determine which one best fits your team’s needs.

Discovering and surfacing telemetry traditionally can be a tedious and challenging process, especially when it comes to pinpointing specific issues for debugging. However, as applications and pipelines grow in complexity, understanding what’s happening beneath the surface becomes increasingly crucial. A lack of visibility hinders the development and maintenance of high-quality applications and pipelines, ultimately impacting customer experience.

As a developer, you usually work with JSON data, and may need to compare JSON files. This might involve checking a list of products from the database against a previous version or comparing an updated user profile returned by your REST API with the original data sent to the server. In this article, we’ll explore several methods and tools developers can use to compare two JSON files effectively.

How to use Gemini generative AI models through BigQuery to boost productivity in Google productivity tools like Sheets.