Systems | Development | Analytics | API | Testing

With the globe becoming more and more digitally linked, mobile applications are becoming an essential part of our everyday life. We use smartphone applications for a wide range of purposes, from healthcare and education to banking and shopping. It's important to understand, though, that not everyone uses these applications in the same manner.

What if a single software glitch could cost your company millions? In today’s digital world, that’s not just a possibility – it’s reality. As businesses double down on digital-first strategies, software powers everything from critical infrastructure to day-to-day consumer experiences. Even minor bugs can cause massive disruptions, halt business operations, and compromise customer trust. The margin for error has never been smaller.

Before we dive in, we want to remind our readers that the Konnect engineering team actively uses Kong products like Kong Gateway, Kong Mesh, and Insomnia. In this post, we'll showcase the power of Kong Gateway and two plugins — the JQ and Request Transformer Advanced Plugins — to govern and configure APIs, and explain how it played, and continues to play, a crucial role in the release of a new v2 Konnect API specification. The key takeaway here is: don’t do more work than is necessary.

Heuristics is the key to turn you into the Turkish Olympic guy. It is something that comes with experience. At a certain point, experts all develop that “sense” in their field of work. Repeated exposure to hundreds of problems helps them recognize patterns that beginners don’t easily see. Heuristics is not always foolproof, but it's good for immediate problem-solving.

Over the past year, we’ve been dedicated to making Databox faster and more powerful for you and your team. We’ve introduced new features, visualizations, and integrations to help you leverage your data to make better decisions. In case you missed any of these updates, we’ve put together a roundup of the top highlights from 2024.

In today’s fast-paced, data-driven business landscape, having a comprehensive view of your operations is essential for success. Dashboards provide a centralized, real-time visual representation of key metrics, tasks, and performance indicators, enabling teams to stay organized and make informed decisions. ClickUp’s customizable dashboards elevate this by allowing users to build and personalize their own layouts tailored to specific needs.

Data pipeline automation plays a central role in integrating and delivering data across systems. The architecture is excellent at handling repetitive, structured tasks, such as extracting, transforming, and loading data in a steady, predictable environment, because the pipelines are built around fixed rules and predefined processes. So, they will continue to work if you maintain the status quo, i.e., as long as your data follows a consistent structure.

One of the benefits of Ruby's developer-friendly syntax is that it's straightforward to quickly build scripts to automate tasks. Web scraping with Ruby is fun, useful, and straightforward. In this article, we'll explore using HTTParty to pull a web page and check it for a given string. To be specific, we'll build a cron job in Ruby to check if a product is in stock on a website!

Data transformation is a critical step in the data pipeline process, enabling organizations to prepare and process their data for creating dashboards, reporting, and analytics. The right tools can make this process efficient, secure, and scalable. In this blog, we will explore how data transformation tools handle the most common tasks, such as filtering, aggregating, joining, and cleansing data to move to a data lake or a cloud platform of your choice, and what to consider when evaluating these tools.

In today's data-driven landscape, the ability to gather, process, and analyze data has become essential for businesses of all sizes. While extracting, transforming, and loading (ETL) data into a centralized warehouse like Snowflake has long been a standard practice, the concept of data activation is gaining traction as the next step in deriving value from data. But what exactly is data activation, and how does it relate to ETL?