One of the most common use cases our customers are using Kong for is API rate limiting. There are a few common reasons for doing this:
For all those and more, we’re able to easily add this functionality with Kong's rate limit advanced plugin.
The plugin can be applied at different levels such as service, route, specific consumer, or even in a global scope. By having this flexibility, one can set a generic global limit but then still overrule the global limit to allow for a more specific rate limit at a lower level.
However, after working with many of Kong customers, one use case couldn’t be met with the specificity highlighted above. This use case is how can Kong help when customers want to have different rate limits based on an organization, partner, or tenant? The answer is Kong’s feature of “Consumer Groups,” which we’ll expand on below (and is documented here).
Released on 2.7, the Kong API gateway allows you to define limits per consumer groups. This means that one can still use the general RL functionality as mentioned above, but also add specific limits to certain groups. Let’s see how we can make it work.
Add a service
Add a route
Add 2 consumer groups — we will assign different users to different groups later on to test our functionality
As seen above, both John and Sarah have a limit of 1000 RPM as we wanted.
As we can see, it is very easy to configure Kong to rate limit your traffic with the relevant requirement for your use case — be it security, performance, or business use case.
In this blog post, we'll talk about the significant challenge of managing and governing a growing number of APIs across multiple teams in an organization — and how Control Plane Groups are a clear solution to avoid the chaos of inconsistent policies
Meet Emily. She’s an API product manager at ACME, Inc., an ecommerce company that runs on dozens of APIs. One morning, her team lead asks a simple question: “Who’s our top API consumer, and which of your APIs are causing the most issues right now?”
The healthcare industry is buzzing about FHIR (Fast Healthcare Interoperability Resources). Pronounced “fire,” this widely adopted data standard has been revolutionizing how healthcare information is exchanged. But building a truly modern, secure, a
Behind every smooth user experience is a maze of APIs quietly handling requests, responses, and data flows. This makes APIs critical connectors that enable applications to communicate and share data seamlessly. When these vital conduits fail, the
As enterprises increasingly embed AI and Large Language Models (LLMs) into their digital experiences, enforcing robust AI guardrails becomes paramount to safeguard users, protect data, manage operational costs, and comply with regulatory and ethical
Organizations are going all-in on large language models (LLMs), with research finding 72% anticipate increased LLM spending in the coming year (and about 40% are already investing more than $250,000 USD per year). As enterprises rapidly adopt LLMs
In the last two parts of this series, we discussed How to Strengthen a ReAct AI Agent with Kong AI Gateway and How to Build a Single-LLM AI Agent with Kong AI Gateway and LangGraph . In this third and final part, we're going to evolve the AI Agen