Kubernetes shouldn’t be reserved for production. Using local Kubernetes in development means you can build and test your service using the same technologies as your live deployments. Some organizations provide a shared Kubernetes cluster for development activities. Others offer on-demand virtual clusters that serve staging environments for significant changes.
In your machine learning projects, have you ever wondered “why is model Y is performing better than Z, which dataset was model Y trained on, what are the training parameters I used for model Y, and what are the model performance metrics I used to select model Y?” Does this sound familiar to you? Have you wondered if there is a simple way to answer the questions above? Data science experiments can get complex, which is why you need a system to simplify tracking.
It’s that time of year again. Conference season is upon us! And, for the first time in what feels like a lifetime, the data ecosystem is getting back together in person. It couldn’t come at a more important time. The decade of data is upon us, as we unveiled at our own customer conference Beyond 2022. The opportunity is greater than ever before. So, too, is the need to change.
Test automation has undergone a steady evolution since its inception. While the process of writing test cases to test the software remains the same, the “how” part keeps changing. Sometimes, we like to perform simple and plain test script development as we did in the 90s using a spreadsheet. Sometimes, we record our test cases and run them through programming languages as we did in the 2010s using Selenium.
Over the past several years, supply chain shocks have battered organizations across industry sectors—from life sciences to retail to oil and gas. Telecommunications companies have felt the pain as well. Between semiconductor shortages, shifts in demand, and labor and equipment shortfalls, telecommunications companies face their share of supply chain challenges.
