Modules and mixins are, without doubt, great resources that make Ruby so attractive. They give the application the ability to share the code that can be used with ease in other places. It also helps us organize our code by grouping functionalities and concerns, which improves the readability and maintainability of our code. In this article, we will go through the concepts behind modules and mixins.

For quick, scalable, highly-available web services, few options compare to AWS Lambda. Just provide your code, add a little configuration, and you're done! In this article, Milap Neupane will introduce us to Lambda, show us how to get it working with Ruby and the Serverless Framework, and discuss reasons to use — or to not use! — Lambda in production.

Even the systems that run smoothly day and night, can flounder when short of memory. Efficient memory usage has become of utmost importance for software applications. Nowadays, with growing audiences and faster speed and data retrieval expectations, memory issues pose a huge threat to performance and can lead to huge losses in terms of customers and money. Therefore, it is very important to build memory-efficient applications that ensure overall performance and a smooth customer experience.

Welcome to the Bugfender winter newsletter! We hope you had a great Christmas and new year. This quarter we’re bringing you a lot of insightful information on our blog. Take a good cup of coffee and find our latest recommended articles below. But first, let’s kick-off with the latest updates as we do on every quarterly newsletter: We hope you find all these updates useful!

At the heart of Kafka is real-time data. With data at the center of any Kafka environment, it should be the area that gets the most attention, but typically it gets the least. This happens because we see most organizations split their Kafka efforts into three areas: infrastructure, monitoring, and data operations.

As an engineering leader on Testlio’s platform team and former product leader at Skype and Microsoft, I’ve evaluated many new tools and concepts to elevate engineering practices and processes. To ensure better efficiency and team empowerment, I ask myself these three questions.

A developer's primary job is to work seamlessly, rapidly, and accurately to create software, apps, or websites that match business requirements. Unfortunately, there is a huge margin for error if you have to write lines and lines of complex code. Additionally, many basic tasks in the use of data-related software and other solutions, require extensive coding knowledge that many employees simply don't have. One solution to this is low-code software and development.

Every time someone uses an app, information travels from a database to the user via an API. Single instances may not seem very important. As long as they perform the required task, people don’t think too much about how applications work. From a business perspective, though, the big data flowing through APIs could unlock important knowledge that helps tap into emerging trends and target customers better. To get the best results, though, companies need the best big data API management.

No code tools and development platforms are becoming increasingly popular. With the no code development platform market expected to rise to $21.2 billion by 2022, these platforms are here to stay. Whether you’re a developer wanting to streamline development and reduce build times, or you’re a manager looking for a faster, easier way for development, a no code software solution could be just what you need.

In this installment, we’ll discuss how to do Get/Scan Operations and utilize PySpark SQL. Afterward, we’ll talk about Bulk Operations and then some troubleshooting errors you may come across while trying this yourself. Read the first blog here. Get/Scan Operations In this example, let’s load the table ‘tblEmployee’ that we made in the “Put Operations” in Part 1. I used the same exact catalog in order to load the table. Executing table.show() will give you: