Systems | Development | Analytics | API | Testing

Gartner published a report last week that I think marks a genuine inflection point for how enterprise technology leaders should think about AI strategy. The headline finding: we have crossed a threshold where competitive advantage in the AI era is no longer about access to data — it's about the semantic intelligence wrapped around it. Gartner calls this the "context economy," and they believe it will reshape how software is built, sold, and monetized over the next several years. I agree.

A Response to Gartner’s Latest Research Last week, Gartner published a report titled MCP Servers Will Fuel the Next AI Revenue Surge — Context as a Service (1) that should be required reading for every enterprise technology leader. Then, Kong CEO Augusto Marietti (Aghi for short) wrote out his thoughts on the subject and why context is king. I’d like to continue that conversation.

Your Kafka Doesn't Have to Live Behind a Wall There's a problem that almost every platform team running Kafka at scale eventually hits, and it usually starts with a reasonable ask: "Can you give our partners access to this event stream?" What follows is rarely simple. You start scoping VPC peering. Then someone asks about firewall rules. Then you realize each new external consumer is going to need its own network arrangement.

Kong Operator 2.1 is a significant update for our customers, opening up integration into the Kong ecosystem for our Kubernetes customers. With Kong Ingress Controller, when your Control Plane was hosted in Kong Konnect, and you were using Kubernetes Gateway API, your dataplane, routes, and services were in read-only mode.

The promise of agentic AI is clear: autonomous systems that can reason, plan, and act on your behalf. But there's a fundamental problem standing between that vision and enterprise reality: agents need context to make decisions, and that context lives scattered across your organization. Context is any data — or any abstraction that enables access to data — that an agent needs to do its job. Customer records in your CRM. Inventory levels behind your fulfillment APIs.

APIs and integrations are the foundation of the modern enterprise. Every organization needs to securely connect systems, move data, and automate workflows, all while maintaining control, visibility, and flexibility. Increasingly, those same APIs are also being consumed by AI-powered applications and agents that must interact safely with underlying business systems.

In today's digital landscape, APIs are the backbone of modern applications, and AI is the engine of innovation. As organizations increasingly rely on microservices and AI-powered features, the API gateway has become the critical control point for managing traffic. But as LLM/GenAI and MCP requests flow through these gateways, they bring a new wave of security challenges.

An enterprise API strategy is no longer an optional IT exercise but a mandate for modern business survival. In the digital economy, your organization's internal connectivity, or lack thereof, determines your speed, agility, and capacity for innovation. This cookbook provides the eight essential ingredients for translating technology investment into clear business outcomes, focusing the C-Suite on value, not code.

For too long, the Model Context Protocol (MCP) has operated on a principle of open access: connect an AI agent to an MCP server, and it gets access to every single tool that server offers. While this approach is simple for initial experimentation, it quickly becomes a liability in production.

In the rapidly evolving landscape of AI-driven development, the Model Context Protocol (MCP) has emerged as the critical standard for connecting AI applications to the data and tools they need. We are excited to announce the Technical Preview (TP) of Kong MCP Registry, a major milestone in our mission to provide the most comprehensive platform for modern API and AI management.