Systems | Development | Analytics | API | Testing

GraphQL is a solid alternative to a traditional REST API, and offering one to your users may be easier than you think. Follow along as Kevin Cunningham builds a GraphQL endpoint with Node.js and MongoDB!

Git Sync lets you collaborate with your team on Design Documents that you create in Kong Insomnia. In the last release, we updated the way that Git Sync works for GitHub. We now leverage the OpenID Connect protocol and OAuth2 to make it easier for you to set up Git Sync. Today, we’re excited to announce that we’re bringing that same ease of setup to GitLab repositories as well!

Today, we are excited to announce the general availability of Kong Ingress Controller (KIC) 2.4! Earlier this year, we launched KIC 2.2 with initial support for Kubernetes Gateway API. In this release, we’re adding weighted load balancing and support for TCP and UDP routes, as well as some much needed quality-of-life features for our customers.

In our final year as undergraduates, we researched how to use human affect and behaviors to anticipate threats posed by other humans. We built a simple website that demonstrated the capabilities of the model we designed.

We’ve recently supported an organization who wanted to expose its Google Kubernetes Engine (GKE) backend behind Apigee X. A quite common architecture, which most of the users delivering modern web applications on Google Cloud tend to build upon. In this scenario, Google’s API gateway, Apigee, receives requests and performs L7 routing, redirecting you to the correct backend application, running as one or more pods on GKE.

Many API developers and companies struggle to find ways to easily set up systems to monetize their APIs. Some are simple but not customizable, some are complex and require massive engineering effort to actually get it all running. To make things easier, Moesif created a feature a few months ago called Billing Meters which gives massive customizability but with a minimal amount of code and engineering effort.

When you hear “Artificial Intelligence,” (AI) what do you think of? You might picture advanced humanoid robots or futuristic technology from sci-fi movies. But as it turns out, this “futuristic” technology is already integrated into our lives. It exists in our phones, televisions, and homes to make everyday tasks simpler. When it comes to software testing, AI can be implemented into your testing initiatives to increase efficiency.