The latest news and announcements about Kong, our products, and our ecosystem, as well as voices from across our community.
Kong Insomnia 13 delivers native Kong Konnect Gateway integration that lets developers query live gateway configuration directly from their terminal, so what they test is always what's deployed, with no manual spec imports and no stale collections. To get started for free, click here . You invested…
AI moves fast: new models, new pricing, new capabilities, sometimes all at once. Prepaid credits let customers buy value upfront and spend it across whatever you're offering today or launch next, without needing to reprice, remigrate, or renegotiate every time something changes. Prepaid credits are…
A new version of KAi, the Kong Konnect agentic platform assistant, is live. This is the release that turns KAi from a knowledgeable guide into something that can actually build inside your org — of course, within guardrails that you control. Until now, KAi could tell you how to set up a service,…
As API ecosystems grow, developers and platform teams often work in separate environments. Platform teams manage APIs, gateways, and governance centrally, while developers recreate those configurations locally for testing and debugging. Over time, this can lead to configuration drift, inconsistent…
TL;DR: To get started for free, click here . Before you dig in, you may… Have you ever…. If you answered yes to any of these above…. We have great news: Friend, the Insomnia x Kong Konnect integration might just be for you. Kong Konnect is where your API truth lives. Every service, spec,…
AI agents move fast. Securing them shouldn't slow you down. Kong and Noma are partnering to change that. Noma is the newest member of Kong's Technology Partner Program . This program delivers high-quality, reliable integrations providing real business value for customers. Together, Kong and Noma…
Today we're announcing kongctl 1.0, Kong's new command-line (CLI) tool for managing Kong Konnect programmatically. This release brings kongctl to the Generally Available (GA) level of support and capabilities, giving developers, platform engineers, and AI coding agents a streamlined tool for…
Legacy API management platforms were built for a different era. They weren't designed for microservices, multi-cloud deployments, or AI workloads. They're expensive, rigid, and hold engineering teams back. The problem is that migration has always felt hard. APIs are load-bearing infrastructure.…
Customers today face significant challenges as their Kubernetes environments scale. The proliferation of microservices, external integrations, and new AI workloads increases traffic volume and connectivity complexity, creating material risks to performance and availability. The core issue is a lack…
Your AI infrastructure is producing financial signals your CFO has never seen. Token consumption is a direct cost line item. Cache hit rate is a margin improvement. Model routing decisions are cost arbitrage events. These things are happening right now, in the gateway layer, with no route to the…
Digital agreements are at the heart of many critical business processes. As companies modernize their technology stacks and adopt API-driven architectures, integrating agreement workflows directly into applications has become increasingly important. By combining the capabilities of Kong Konnect…
When enterprises started experimenting with LLMs, the governance challenge — while still difficult — was relatively contained once you had an AI Gateway for LLM traffic. You had a request going to a model, a response coming back, and a gateway in between to enforce policy. With the right solutions,…
Every enterprise moving AI into production is about to face a familiar problem in an unfamiliar form: the cost explosion, but for LLMs. This is very similar to what happened with cloud. In the early days of cloud, teams spun up infrastructure with no visibility into who was consuming what. Finance…
As enterprises race to deploy multicloud architectures and Agentic AI, they face a common bottleneck: "state." To govern AI token usage, manage agent-to-agent communication, or optimize performance via caching, API and AI gateways require a persistence layer to synchronize data. We’re excited to…
A persistent challenge arises as businesses adopt multicloud architectures and agentic AI: the need for state synchronization. API and AI gateways require a robust persistence layer to synchronize data, whether it's for governing AI token usage, facilitating agent-to-agent communication, or…
As enterprises start deploying AI agents into real systems, a new architectural challenge is emerging. Agents need a reliable way to discover tools, services, and capabilities dynamically, instead of relying on hardcoded integrations. This is where the Model Context Protocol (MCP) ecosystem is…