Gubernator

Gubernator is a distributed, high performance, cloud native and stateless rate limiting service.

Features of Gubernator

• Gubernator evenly distributes rate limit requests across the entire cluster, which means you can scale the system by simply adding more nodes.
• Gubernator doesn’t rely on external caches like memcache or redis, as such there is no deployment synchronization with a dependant service. This makes dynamically growing or shrinking the cluster in an orchestration system like kubernetes or nomad trivial.
• Gubernator holds no state on disk, It’s configuration is passed to it by the client on a per-request basis.
• Gubernator provides both GRPC and HTTP access to it’s API.
• Can be run as a sidecar to services that need rate limiting or as a separate service.
• Can be used as a library to implement a domain specific rate limiting service.
• Supports optional eventually consistent rate limit distribution for extremely high throughput environments. (See GLOBAL behavior architecture.md)
• Gubernator is the english pronunciation of governor in Russian, also it sounds cool.

Stateless configuration

Gubernator is stateless in that it doesn’t require disk space to operate. No configuration or cache data is ever synced to disk. This is because every request to gubernator includes the config for the rate limit. At first you might think this an unnecessary overhead to each request. However, In reality a rate limit config is made up of only 4, 64bit integers.

An example rate limit request sent via GRPC might look like the following

yaml
rate_limits:
    # Scopes the request to a specific rate limit
  - name: requests_per_sec
    # A unique_key that identifies this instance of a rate limit request
    unique_key: account_id=123|source_ip=172.0.0.1
    # The number of hits we are requesting
    hits: 1
    # The total number of requests allowed for this rate limit
    limit: 100
    # The duration of the rate limit in milliseconds
    duration: 1000
    # The algorithm used to calculate the rate limit  
    # 0 = Token Bucket
    # 1 = Leaky Bucket
    algorithm: 0
    # The behavior of the rate limit in gubernator.
    # 0 = BATCHING (Enables batching of requests to peers)
    # 1 = NO_BATCHING (Disables batching)
    # 2 = GLOBAL (Enable global caching for this rate limit)
    behavior: 0

An example response would be

rate_limits:
    # The status of the rate limit.  OK = 0, OVER_LIMIT = 1
  - status: 0,
    # The current configured limit
    limit: 10,
    # The number of requests remaining
    remaining: 7,
    # A unix timestamp in milliseconds of when the bucket will reset, or if 
    # OVER_LIMIT is set it is the time at which the rate limit will no 
    # longer return OVER_LIMIT.
    reset_time: 1551309219226,
    # Additional metadata about the request the client might find useful
    metadata:
      # This is the name of the coordinator that rate limited this request
      "owner": "api-n03.staging.us-east-1.mailgun.org:9041"

Rate limit Algorithm

Gubernator currently supports 2 rate limit algorithms.

1. Token Bucket implementation starts with an empty bucket, then each

   Hit

   adds a token to the bucket until the bucket is full. Once the bucket is full, requests will return

   OVER_LIMIT

   until the

   reset_time

   is reached at which point the bucket is emptied and requests will return

   UNDER_LIMIT

   . This algorithm is useful for enforcing very bursty limits. (IE: Applications where a single request can add more than 1

   hit

   to the bucket; or non network based queuing systems.) The downside to this implementation is that once you have hit the limit no more requests are allowed until the configured rate limit duration resets the bucket to zero.

2. Leaky Bucket is implemented similarly to Token Bucket where

   OVER_LIMIT

   is returned when the bucket is full. However tokens leak from the bucket at a consistent rate which is calculated as

   duration / limit

   . This algorithm is useful for metering, as the bucket leaks allowing traffic to continue without the need to wait for the configured rate limit duration to reset the bucket to zero.

Performance

In our production environment, for every request to our API we send 2 rate limit requests to gubernator for rate limit evaluation, one to rate the HTTP request and the other is to rate the number of recipients a user can send an email too within the specific duration. Under this setup a single gubernator node fields over 2,000 requests a second with most batched responses returned in under 1 millisecond.

Peer requests forwarded to owning nodes typically respond in under 30 microseconds.

NOTE The above graphs only report the slowest request within the 1 second sample time. So you are seeing the slowest requests that gubernator fields to clients.

Gubernator allows users to choose non-batching behavior which would further reduce latency for client rate limit requests. However because of throughput requirements our production environment uses Behaviour=BATCHING with the default 500 microsecond window. In production we have observed batch sizes of 1,000 during peak API usage. Other users who don’t have the same high traffic demands could disable batching and would see lower latencies but at the cost of throughput.

Gregorian Behavior

Users may choose a behavior called

DURATION_IS_GREGORIAN

Duration

Behavior

DURATION_IS_GREGORIAN

Duration

This is useful when you want to impose daily or monthly limits on a resource. Using this behavior you know when the end of the day or month is reached the limit on the resource is reset regardless of when the first rate limit request was received by Gubernator.

Given the following

Duration

Examples when using

Behavior = DURATION_IS_GREGORIAN

Duration = 2

Current = 0

Duration = 0

Current = 0

Duration = 4

Current = 0

Gubernator as a library

If you are using golang, you can use Gubernator as a library. This is useful if you wish to implement a rate limit service with your own company specific model on top. We do this internally here at mailgun with a service we creatively called

ratelimits

When you use the library, your service becomes a full member of the cluster participating in the same consistent hashing and caching as a stand alone Gubernator server would. All you need to do is provide the GRPC server instance and tell Gubernator where the peers in your cluster are located. The

cmd/gubernator/main.go

Optional Disk Persistence

While the Gubernator server currently doesn't directly support disk persistence, the Gubernator library does provide interfaces through which library users can implement persistence. The Gubernator library has two interfaces available for disk persistence. Depending on the use case an implementor can implement the Loader interface and only support persistence of rate limits at startup and shutdown, or users can implement the Store interface and Gubernator will continuously call

OnChange()

Get()

For those who choose to implement the

Store

OnChange()

OnChange()

API

All methods are accessed via GRPC but are also exposed via HTTP using the GRPC Gateway

Health Check

Health check returns

unhealthy

up

GRPC

rpc HealthCheck (HealthCheckReq) returns (HealthCheckResp)

HTTP

GET /v1/HealthCheck

Example response:

{
  "status": "healthy",
  "peer_count": 3
}

Get Rate Limit

Rate limits can be applied or retrieved using this interface. If the client makes a request to the server with

hits: 0

GRPC

rpc GetRateLimits (GetRateLimitsReq) returns (GetRateLimitsResp)

HTTP

POST /v1/GetRateLimits

Example Payload

json
{
    "requests":[
        {
            "name": "requests_per_sec",
            "unique_key": "account.id=1234",
            "hits": 1,
            "duration": 60000,
            "limit": 10
        }
    ]
}

Example response:

{
  "responses":[
    {
      "status": 0,
      "limit": "10",
      "remaining": "7",
      "reset_time": "1551309219226"
    }
  ]
}

Deployment

NOTE: Gubernator uses etcd or kubernetes to discover peers and establish a cluster. If you don't have either, the docker-compose method is the simplest way to try gubernator out.

Docker with existing etcd cluster

$ docker run -p 8081:81 -p 8080:80 -e GUBER_ETCD_ENDPOINTS=etcd1:2379,etcd2:2379 \
   thrawn01/gubernator:latest 

Hit the API at localhost:8080 (GRPC is at 8081)
$ curl http://localhost:8080/v1/HealthCheck

Docker compose

The docker compose file includes a local etcd server and 2 gubernator instances ```bash

Download the docker-compose file

$ curl -O https://raw.githubusercontent.com/mailgun/gubernator/master/docker-compose.yaml

Edit the compose file to change the environment config variables

$ vi docker-compose.yaml

Run the docker container

$ docker-compose up -d

Hit the API at localhost:8080 (GRPC is at 8081)

$ curl http://localhost:8080/v1/HealthCheck ```

Kubernetes

# Download the kubernetes deployment spec
$ curl -O https://raw.githubusercontent.com/mailgun/gubernator/master/k8s-deployment.yaml

Edit the deployment file to change the environment config variables
$ vi k8s-deployment.yaml
Create the deployment (includes headless service spec)
$ kubectl create -f k8s-deployment.yaml

Configuration

Gubernator is configured via environment variables with an optional

--config

See the

example.conf

Architecture

See architecture.md for a full description of the architecture and the inner workings of gubernator.