Thanks to PHP being an interpreted language and it that it has a garbage collector, PHP developers don't often have to think about memory management. Unlike developers in compiled languages, such as C/C++, we don't have to give that much thought to memory allocation and deallocation. However, it's helpful to have a broad understanding of how garbage collection works in PHP, along with how you can interact with it so that you can create high performing applications.

Learn how becoming an API-driven enterprise will help your business unlock new revenue streams, boost productivity, and encourage innovation.

Handling secrets has always been a challenging and critical task within organizations.

My first car had a manual choke. It would change the ratio of air and fuel to allow the engine to start - you would pull it when starting the engine cold, wait a bit and then set it back. The car had many other peculiarities - a manual transmission (of course), no power steering, and the engine had a tendency to overheat in the summer - or, if going uphill, year-round.

This month we have released one of our biggest UX updates since Bugfender 2, the new viewer. We are quite excited because we have been working on it over several months, we hope you like it!

Data enablement doesn’t stop by delivering data in a data lake or data warehouse. Data must reach easily its point of consumption. Whether it is accessed as a self-service by a business user or integrated into an application, making trusted data available to all when it’s needed is of utmost importance.

We’re pleased to announce that our first release in the 1.4 series is out! Our engineering team and awesome community members added numerous new features, improvements and fixes in this release. Read below on the most relevant changes in Kong Gateway 1.4 and how you can make the most of these additions. Please refer to the Changelog for complete details and the Upgrade Path for instructions on how to upgrade from previous Kong versions.

To maximize the benefits of cloud, data & machine learning and make it available to innovative digital teams and customers, the data lake is the definite reference model. How can we accelerate its implementation and scope without losing control or jeopardizing its sustainability?