Making a decision to start automation is easy but choosing an appropriate tool for automation is not. There are teams that are spending a lot on hiring new manual testing resources but find it hard to invest in automation. The reasons could be many.
Ruby has always been known for the productivity it brings to its developers. Alongside features such as elegant syntax, rich meta-programming support, etc. that make you productive when writing code, it also has another secret weapon called TracePoint that can help you “debug” faster. In this post, I’ll use a simple example to show you 2 interesting facts I found out about debugging.
Go has built-in features to make it easier for programmers to implement logging. Third parties have also built additional tools to make logging easier. What's the difference between them? Which should you choose? In this article Ayooluwa Isaiah describes both of these and discusses when you'd prefer one over the other.
Tired of waiting for sluggish HTTP requests to complete before your backend code can proceed with other things? Sanic is an asynchronous web framework in Python, that is built to be fast. In a world where Flask and Django are the most preferred web development options in Python, Sanic is the new kid on the block. It’s a promising alternative that is not only faster but also delivers efficiency, simplicity, and scalability.
We’re announcing a key capability to help organizations govern their data in Google Cloud. Our new BigQuery column-level security controls are an important step toward placing policies on data that differentiate between classes. This allows for compliance with regulations that mandate such distinction, such as GDPR or CCPA.
SOLID is one of the most popular sets of design principles in object-oriented software development. All of them are broadly used and worth knowing. But in this first post of my series about the SOLID principles, I will focus on the first one: the Single Responsibility Principle.
Data is the new oil and a critical differentiator in generating retrospective, interactive, and predictive ML insights. There has been an exponential growth in the amount of data in the form of structured, semi-structured, and unstructured data collected within the enterprise. Harnessing this data today is difficult — typically data in the lakes is not consistent, interpretable, accurate, timely, standardized, or sufficient. Scully et. al.
The advantages of remote work have been praised for a while now. Team members gravitate towards the flexible work schedule and enjoy an increase in personal freedom, while companies benefit from a talent pool unencumbered by geographical borders. From remote-first tech giants like Automattic (which powers a third of the internet), to newbies such as NASA, companies are steadily progressing towards telecommuting. But working from home comes with its own unique set of challenges.
