Systems | Development | Analytics | API | Testing

We're excited to announce the general availability of Konnect Debugger, formerly known as Active Tracing during its tech preview phase. This powerful debugging and observability solution in Kong Konnect has evolved from a focused tracing tool into a comprehensive debugging platform.

We’re excited to announce the beta support for Mesh Manager in the Konnect Terraform Provider — a new tool that brings the power of infrastructure-as-code to Kong’s Service Mesh management platform. This provider enables engineering teams to declaratively manage Konnect Mesh resources using HashiCorp Terraform.

We're happy to announce the 3.5 release of Kong Ingress Controller (KIC). This release includes the graduation of combined services to General Availability, support for connection draining, as well as the start of deprecating support for some Ingress types as we help move customers to the Kubernetes Gateway API. Let’s get into more details about these!

This is part one of a series exploring how Kong AI Gateway can be used in an AI Agent development with LangGraph. The series comprises three parts.

Today, I'm excited to announce one of our largest Kong AI Gateway releases (3.11), which ships with several new features critical in building modern and reliable AI agents in production. We strongly recommend updating to this version to get access to the latest and greatest that AI infrastructure has to offer.

We’re excited to bring you Kong Gateway Enterprise 3.11 with compelling new features to make your APIs and event streams even more powerful, including: We’ll also touch on what’s new with Konnect networking and Active Tracing. There’s a lot to unpack, so keep on reading for the full story!

RAG (Retrieval-Augmented Generation) is not a new concept in AI, and unsurprisingly, when talking to companies, everyone seems to have their own interpretation of how to implement it. So, let’s start with a refresher. RAG (short for Retrieval-Augmented Generation) is a technique that injects relevant data from an external knowledge source directly into a prompt before sending it to a Large Language Model (LLM). “But wait, my model is already fine-tuned on my domain-specific data.