Rate Limiting

Rate limit how many HTTP requests can be made in a given period of seconds, minutes, hours, days, months, or years. If the underlying Service/Route (or deprecated API entity) has no authentication layer, the Client IP address will be used, otherwise the Consumer will be used if an authentication plugin has been configured.

Configuration Reference

You can configure this plugin using the Kong Admin API or through declarative configuration, which involves directly editing the Kong configuration file.

This plugin is compatible with requests with the following protocols:

• http
• https

This plugin is partially compatible with DB-less mode.

In DB-less mode, Kong does not have an Admin API. If using this mode, configure the plugin using declarative configuration.

The plugin will run fine with the local policy (which doesn’t use the database) or the redis policy (which uses an independent Redis, so it is compatible with DB-less).

The plugin will not work with the cluster policy, which requires writes to the database.

Enabling the plugin on a Service

$ curl -X POST http://<admin-hostname>:8001/services/<service>/plugins \
    --data "name=rate-limiting"  \
    --data "config.second=5" \
    --data "config.hour=10000" \
    --data "config.policy=local"

apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: <rate-limiting-example>
config: 
  second: 5
  hour: 10000
  policy: local
plugin: rate-limiting

apiVersion: v1
kind: Service
metadata:
  name: <service>
  labels:
    app: <service>
  annotations:
    plugins.konghq.com: <rate-limiting-example>
spec:
  ports:
  - port: 80
    targetPort: 80
    protocol: TCP
    name: <service>
  selector:
    app: <service>

plugins:
- name: rate-limiting
  service: <service>
  config: 
    second: 5
    hour: 10000
    policy: local

<service> is the id or name of the Service that this plugin configuration will target.

Enabling the plugin on a Route

$ curl -X POST http://<admin-hostname>:8001/routes/<route>/plugins \
    --data "name=rate-limiting"  \
    --data "config.second=5" \
    --data "config.hour=10000" \
    --data "config.policy=local"

apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: <rate-limiting-example>
config: 
  second: 5
  hour: 10000
  policy: local
plugin: rate-limiting

apiVersion: networking/v1beta1
kind: Ingress
metadata:
  name: <route>
  annotations:
    plugins.konghq.com: <rate-limiting-example>
spec:
  rules:
  - host: examplehostname.com
    http:
      paths:
      - path: /bar
        backend:
          serviceName: echo
          servicePort: 80

plugins:
- name: rate-limiting
  route: <route>
  config: 
    second: 5
    hour: 10000
    policy: local

<route> is the id or name of the Route that this plugin configuration will target.

Enabling the plugin on a Consumer

$ curl -X POST http://<admin-hostname>:8001/consumers/<consumer>/plugins \
    --data "name=rate-limiting"  \
    --data "config.second=5" \
    --data "config.hour=10000" \
    --data "config.policy=local"

apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: <rate-limiting-example>
config: 
  second: 5
  hour: 10000
  policy: local
plugin: rate-limiting

apiVersion: configuration.konghq.com/v1
kind: KongConsumer
metadata:
  name: <consumer>
  annotations:
    plugins.konghq.com: <rate-limiting-example>

plugins:
- name: rate-limiting
  consumer: <consumer>
  config: 
    second: 5
    hour: 10000
    policy: local

<consumer> is the id or username of the Consumer that this plugin configuration will target.

Enabling the plugin globally

A plugin which is not associated to any Service, Route, or Consumer is considered global, and will be run on every request. Read the Plugin Reference and the Plugin Precedence sections for more information.

$ curl -X POST http://<admin-hostname>:8001/plugins/ \
    --data "name=rate-limiting"  \
    --data "config.second=5" \
    --data "config.hour=10000" \
    --data "config.policy=local"

apiVersion: configuration.konghq.com/v1
kind: KongClusterPlugin
metadata:
  name: <global-rate-limiting>
  labels:
    global: \"true\"
config: 
  second: 5
  hour: 10000
  policy: local
plugin: rate-limiting

plugins:
- name: rate-limiting
  config: 
    second: 5
    hour: 10000
    policy: local

Parameters

Here's a list of all the parameters which can be used in this plugin's configuration:

Headers sent to the client

When this plugin is enabled, Kong will send some additional headers back to the client telling what are the limits allowed, how many requests are available and how long it will take until the quota will be restored, for example:

RateLimit-Limit: 6
RateLimit-Remaining: 4
RateLimit-Reset: 47

The plugin will also send headers telling the limits in the time frame and the number of requests remaining:

X-RateLimit-Limit-Minute: 10
X-RateLimit-Remaining-Minute: 9

or it will return a combination of more time limits, if more than one is being set:

X-RateLimit-Limit-Second: 5
X-RateLimit-Remaining-Second: 4
X-RateLimit-Limit-Minute: 10
X-RateLimit-Remaining-Minute: 9

If any of the limits configured is being reached, the plugin will return a HTTP/1.1 429 status code to the client with the following JSON body:

{ "message": "API rate limit exceeded" }

NOTE:

Implementation considerations

The plugin supports 3 policies, which each have their specific pros and cons.

There are 2 use cases that are most common:

1. every transaction counts. These are for example transactions with financial consequences. Here the highest level of accuracy is required.
2. backend protection. This is where accuracy is not as relevant, but it is merely used to protect backend services from overload. Either by specific users, or to protect against an attack in general.

NOTE:

Every transaction counts

In this scenario, the local policy is not an option. So here the decision is between the extra performance of the redis policy against its extra support effort. Based on that balance, the choice should either be cluster or redis.

The recommendation is to start with the cluster policy, with the option to move over to redis if performance reduces drastically. Keep in mind existing usage metrics cannot be ported from the datastore to redis. Generally with shortlived metrics (per second or per minute) this is not an issue, but with longer lived ones (months) it might be, so you might want to plan your switch more carefully.

Backend protection

If accuracy is of lesser importance, the local policy can be used. It might require some experimenting to get the proper setting. For example, if the user is bound to 100 requests per second, and you have an equally balanced 5 node Kong cluster, setting the local limit to something like 30 requests per second should work. If you are worried about too many false-negatives, increase the value.

Keep in mind as the cluster scales to more nodes, the users will get more requests granted, and likewise when the cluster scales down the probability of false-negatives increases. So in general, update your limits when scaling.

The above-mentioned inaccuracy can be mitigated by using a consistent-hashing load balancer in front of Kong, which ensures the same user is always directed to the same Kong node. This will both reduce the inaccuracy and prevent the scaling issues.

Most likely the user will be granted more than was agreed when using the local policy, but it will effectively block any attacks while maintaining the best performance.