Welcome back to another one of our Community Roundups, folks. We’ve got plenty of mentions, from articles to unofficial clients — and, of course, some good old tweets. Let’s get started!

Writing tests is an underappreciated part of software development. It usually distracts us from our primary goal and makes us feel we aren’t being productive. However, these tests are a great way to ensure our code works as expected, and they can save us plenty of headaches when we don’t have full control of certain parts of a project (for example, when we are working on the client app and another colleague is working on the server).

Back in April last year, we made the business decision to make Keboola Connection available on Azure too (no, we're not quitting AWS). The story behind the decision is quite simple — our customers want it.

What is embedded analytics? Embedded analytics is the integration of analytical capabilities and data visualizations - real-time reports and dashboards - into another software application. This allows the end user to analyze the data held within the software application into which the analytics platform is embedded. With this analysis, the end user can identify and mitigate issues and spot opportunities to maximize.

Nowadays, in the era of instant gratification, when everyone want everything in a matter of moments, understanding the performance of your website, web application, web service is more important than has ever been. Using web performance tools to understand how your application behaves is easy and a best practice that you should follow on a daily basis.

Katalon is establishing a new partnership with CircleCI — the leading platform for continuous integration and continuous delivery pipeline. This collaboration marks the official support of integrating Katalon Studio automation capability with the CircleCI infrastructure. Katalon provides a robust cross-platform test automation solution that supports web, application programming interface (API), mobile, and desktop testing for teams with minimum requirements for programming skills.

Apache Hadoop Ozone was designed to address the scale limitation of HDFS with respect to small files and the total number of file system objects. On current data center hardware, HDFS has a limit of about 350 million files and 700 million file system objects. Ozone’s architecture addresses these limitations[4]. This article compares the performance of Ozone with HDFS, the de-facto big data file system.

Solving a problem programatically often involves grouping data items together so they can be conveniently operated on or copied as a single unit – the items are collected in a data structure. Many different data structures have been designed over the past decades, some store individual items like phone numbers, others store more complex objects like name/phone number pairs. Each has strengths and weaknesses and is more or less suitable for a specific use case.