lemonhall / gubernator

High Performance Rate Limiting MicroService and Library

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

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.

API

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

Health Check

Health check returns unhealthy in the event a peer is reported by etcd or kubernetes as up but the server instance is unable to contact that peer via it's advertised address.

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 then current state of the rate limit is retrieved but not incremented.

GRPC

rpc GetRateLimits (GetRateLimitsReq) returns (GetRateLimitsResp)

HTTP

POST /v1/GetRateLimits

Example Payload

{
    "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

# 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 flag which takes a file of key/values and places them into the local environment before startup.

See the example.conf for all available config options and their descriptions.

Architecture

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