Data scientists today have to choose between a massive toolbox where every item has its pros and cons. We love the simplicity of Python tools like pandas and Scikit-learn, the operation-readiness of Kubernetes, and the scalability of Spark and Hadoop, so we just use all of them. What happens? Data scientists explore data using pandas, then data engineers use Spark to recode the same logic to scale or with live streams or operational databases.
Flutter blurs the lines between designer and developer and endorses a new designer developer archetype. Part designer part engineer, part Picasso and part Pascal. With ambitious designs comes the responsibility to make those designs run on the screen without losing frames. While Flutter is performant by design, how much should we really pay attention to performance optimisation? In most cases … we don’t.
To follow up on my previous article, Guide to Testing Automation with Robot Framework, I will go into more detail about the overall process of writing automated Robot Framework test cases and how to track automation in Jira using Xray. Test automation may seem hard, but it gets easier with the right tools and an open and helpful community like the one surrounding Robot Framework. If your team is using Jira, you can easily integrate testing results coming from the CI/CD pipeline.
In today’s enterprise computing landscape, multi-cloud organizations are quickly becoming the norm rather than the exception. By leveraging an API-first strategy with a microservice-based architecture, companies can achieve significant speed to market across multiple clouds. In order to achieve this, container orchestration and a well-designed CI/CD strategy are essential components in this journey.
Development can successfully remove the bottlenecks created by waterfall methodology by improving development productivity through encouraging collaboration,continuous feedback loops, and automating processes. Collaboration. Feedback. Automation. These are the main building blocks of Development operations. However, not all Development implementations are successful. Why? Building blocks are not enough. You need to take these building blocks and design a Development pipeline that suits your needs.
One of the challenges when you’re starting out with Development is getting the lay of the land. There are a lot of tools out there. And when one of the goals of Development is continually improving your processes, it’s important for you to understand how those tools might fit in your infrastructure. At the same time, you want to be efficient. You don’t want to add tools that overlap with one another. Or tools that cost more than other effective alternatives.
