Systems | Development | Analytics | API | Testing

Scaling Kubernetes Deployments of Kong

In my previous post on scaling Kong deployments with and without a database, we covered the concepts of deploying Kong with and without a database, as well as using decK, distributed, and hybrid deployments. In this article, we take a tour of some of the possible Kubernetes deployments of Kong. Kubernetes (K8s) is the container orchestration war winner. While there are still deployments using other engines, we see K8s far more.

Exposing Services with the Kubernetes Gateway API

The Gateway API is the next generation of the Ingress API, one of the most widely used resources across Kubernetes. We will explore the rich set of features provided by this API and deep dive into a demo-oriented talk where we will learn how to expose applications outside the cluster boundaries. We will leverage the Kong Gateway Operator to deploy the controlplane (Kong Ingress Controller) and dataplane (Kong), then, with the help of the Gateway API, expose services outside the cluster boundaries and perform traffic splitting and load balancing based on different rules.

Docker Logging

As more organizations are moving to a cloud-native architecture, there is an ever-increasing need to monitor applications and services. Logging is a crucial part of this process, as it provides the insights and visibility to identify potential issues and track application performance. When it comes to managing and monitoring applications, Docker logging is an essential part of the process.

How to Create a Kubernetes Preview Environment

A Kubernetes preview environment is an isolated environment that allows developers to test their code at any time without worrying about how others may be affected. While implementations and use cases may vary, simulating a production environment as closely as possible is the main goal. Imagine you’re part of a team developing a complex API, and you’ve been tasked with adding a new endpoint that relies on features within the codebase currently being optimized by one of your team members.

Building a Mock Server from User Traffic in Kubernetes

A mock server can prove useful in many circumstances. Imagine you’re an engineer working on optimizing a feature inside of an existing API that relies on multiple other microservices to function properly. To fully test the optimizations, you’ll have to set up test versions of all the dependencies, which quickly proves to be quite a task in and of itself. This is where a mocks—a server that simulates the behavior of a real server—can be very beneficial.