Systems | Development | Analytics | API | Testing

Scania is at the forefront of a more autonomous, connected, electric future for the transportation industry. Find out why its Head of Data and Information Management uses data mesh—and Snowflake—to make it a reality. Scania is a global truck, bus, and industrial engine manufacturer and offers an extensive range of related services so its customers can focus on their core business.

Instrumentation is an essential part of monitoring and operating an application, especially for apps heavily used in production. Even in today's everchanging technology landscape, visibility and observability still challenge developers and system administrators. Metrics and logging are essential for monitoring and operating an application. Metrics measure an application's performance and system health, while logging records system health and application state.

Testing in production carries a lot of risk, like possibly causing downtime for users. However, the advantages of using real user traffic are many, which has led to the popularity of traffic mirroring. Mirroring can be implemented as part of pre-deployment testing, as well as other parts of the developer experience like the development itself. But, how do you get started with it?

Analytics engineer is the latest role that combines the technical skills of a data engineer with the business knowledge of a data analyst. They are typically coding in SQL, building dbt data models, and automating data pipelines. You could say they own the steps between data ingestion and orchestration. Whether you are a seasoned analytics engineer or new to the field, it’s important to continually learn new things and improve the work you’ve already done.

If you’ve got an agile team interested in shipping fast without breaking things, this post is for you. In this piece, I’m going to explain how we at Rainforest QA approach automated testing in a continuous integration / continuous delivery (CI/CD) pipeline, with a focus on end-to-end (e2e) functional testing. The aim of our testing and other DevOps methodologies is to maintain a healthy balance between speed and product quality.

Data migration is something that all businesses will have to deal with at some point. Maybe a high level of growth has meant that you have too much data and need a larger server. Or maybe you want to move to a new cloud-based system. Regardless of the specifics, all modern businesses will know the power of unlocking data.

This Eckerson Group report gives you a good understanding of how the Unravel platform addresses multiple categories of data observability—application/pipeline performance, cluster/platform performance, data quality, and, most significant, FinOps cost governance—with automation and AI-driven recommendations.

Game engines are an essential part of the game development process. But which one should you use? Here, we cover what the most popular game engines are and how to use them. Follow along or jump to the section that interests you the most. ➡️ Essential Game Dev Software — Free.

Five things to know about how to get data from multiple sources: These days, organizations have more data at their fingertips than ever before and collect an incredible number of data sets from various sources. This creates a paradox for businesses such as e-commerce retailers struggling to deal with data complexity. With a deluge of information (and more arriving every day), how can you get data from multiple sources efficiently and unlock the hidden insights that it contains?