SQL has long been the universal language for working with data. In fact it’s more relevant today than it was 40 years ago. Many data technologies were born without it and inevitably ended up adopting it later on. Apache Kafka is one of these data technologies. At Lenses.io, we were the first in the market to develop a SQL layer for Kafka (yes, before KSQL) and integrate it in a few different areas of our product for different workloads.
Have you ever found yourself copy-pasting the same bits of JavaScript code between different projects? Well, when this situation happens two or three times in a row, it’s usually a good indicator that you have a piece of code that is useful and reusable. So, if you are already reusing your code across several different projects, why not go the extra mile and convert it into a library that allows you to optimize this code-sharing?
“You cannot be the same, think the same and act the same if you hope to be successful in a world that does not remain the same.” This sentence by John C. Maxwell is so relevant to rapidly changing cloud hosting technology. Businesses understand the added value and are looking at cloud technologies to handle both operational and analytical workloads.
This blog post is a first of a series on how to leverage PyTorch’s ecosystem tools to easily jumpstart your ML / DL project. The first part of this blog describes common problems appearing when developing ML / DL solutions, and the second describes a simple image classification example demonstrating how to use Allegro Trains and PyTorch to address those problems.
Employees today are more mobile than ever. As we saw, due to COVID-19 the majority of organizations moved their employees to a work from home model overnight. This quick change of location forced businesses to implement solutions that would provide their workforces secure remote access to an increasingly complex corporate network.
If you write software for a living, you probably have a bias toward coded tests and against all things codeless. Most software engineers who become test engineers trust themselves to write well-designed structured code. Some people see record-and-playback as cheating, demeaning, or otherwise indicative of poor workmanship. Yet, research shows that test code maintenance costs correlate directly to the number of lines of written test code.
