- Overview
- Docker Image
- Supported Envoy APIs
- Building and Testing
- Configuration
- Request Fields
- GRPC Client
- Global ShadowMode
- Statistics
- HTTP Port
- Debug Port
- Local Cache
- Redis
- Memcache
- Custom headers
- Tracing
- TLS
- mTLS
- Contact
The rate limit service is a Go/gRPC service designed to enable generic rate limit scenarios from different types of applications. Applications request a rate limit decision based on a domain and a set of descriptors. The service reads the configuration from disk via runtime, composes a cache key, and talks to the Redis cache. A decision is then returned to the caller.
For every main commit, an image is pushed to Dockerhub. There is currently no versioning (post v1.4.0) and tags are based on commit sha.
v3 rls.proto is currently supported. Support for v2 rls proto is now deprecated.
v1.0.0
tagged on commit0ded92a2af8261d43096eba4132e45b99a3b8b14
. Ratelimit has been in production use at Lyft for over 2 years.v1.1.0
introduces the data-plane-api proto and initiates the deprecation of the legacy ratelimit.proto.e91321b
commit deleted support for the legacy ratelimit.proto. The current version of ratelimit protocol is changed to v3 rls.proto while v2 rls.proto is still supported as a legacy protocol.4bb32826
deleted support for legacy v2 rls.proto
-
Install Redis-server.
-
Make sure go is setup correctly and checkout rate limit service into your go path. More information about installing go here.
-
In order to run the integration tests using a local Redis server please run two Redis-server instances: one on port
6379
and another on port6380
redis-server --port 6379 & redis-server --port 6380 &
-
To setup for the first time (only done once):
make bootstrap
-
To compile:
make compile
Ensure you set the correct platform if running OSX host with a linux container e.g.
GOOS=linux make compile
-
To compile and run tests:
make tests
-
To run the server locally using some sensible default settings you can do this (this will setup the server to read the configuration files from the path you specify):
USE_STATSD=false LOG_LEVEL=debug REDIS_SOCKET_TYPE=tcp REDIS_URL=localhost:6379 RUNTIME_ROOT=/home/user/src/runtime/data RUNTIME_SUBDIRECTORY=ratelimit RUNTIME_APPDIRECTORY=config
The docker-compose setup has three containers: redis, ratelimit-build, and ratelimit. In order to run the docker-compose setup from the root of the repo, run
docker-compose up
The ratelimit-build container will build the ratelimit binary. Then via a shared volume the binary will be shared with the ratelimit container. This dual container setup is used in order to use a a minimal container to run the application, rather than the heftier container used to build it.
If you want to run with two redis instances, you will need to modify the docker-compose.yml file to run a second redis container, and change the environment variables as explained in the two redis instances section.
To run a fully configured environment to demo Envoy based rate limiting, run:
export CONFIG_TYPE=FILE
docker-compose -f docker-compose-example.yml up --build --remove-orphans
This will run ratelimit, redis, prom-statsd-exporter and two Envoy containers such that you can demo rate limiting by hitting the below endpoints.
curl localhost:8888/test
curl localhost:8888/header -H "foo: foo" # Header based
curl localhost:8888/twoheader -H "foo: foo" -H "bar: bar" # Two headers
curl localhost:8888/twoheader -H "foo: foo" -H "baz: baz" # This will be rate limited
curl localhost:8888/twoheader -H "foo: foo" -H "bar: banned" # Ban a particular header value
curl localhost:8888/twoheader -H "foo: foo" -H "baz: shady" # This will never be ratelimited since "baz" with value "shady" is in shadow_mode
curl localhost:8888/twoheader -H "foo: foo" -H "baz: not-so-shady" # This is subject to rate-limiting because the it's now in shadow_mode
Edit examples/ratelimit/config/example.yaml
to test different rate limit configs. Hot reloading is enabled.
The descriptors in example.yaml
and the actions in examples/envoy/proxy.yaml
should give you a good idea on how to configure rate limits.
To see the metrics in the example
# The metrics for the shadow_mode keys
curl http://localhost:9102/metrics | grep -i shadow
To run a fully configured environment to demo Envoy based rate limiting, run:
export CONFIG_TYPE=GRPC_XDS_SOTW
docker-compose -f docker-compose-example.yml --profile xds-config up --build --remove-orphans
This will run in xds-config
docker-compose profile which will run example xDS-Server, ratelimit, redis, prom-statsd-exporter and two Envoy containers such that you can demo rate limiting by hitting the below endpoints.
curl localhost:8888/test
curl localhost:8888/header -H "foo: foo" # Header based
curl localhost:8888/twoheader -H "foo: foo" -H "bar: bar" # Two headers
curl localhost:8888/twoheader -H "foo: foo" -H "baz: baz" # This will be rate limited
curl localhost:8888/twoheader -H "foo: foo" -H "bar: banned" # Ban a particular header value
curl localhost:8888/twoheader -H "foo: foo" -H "baz: shady" # This will never be ratelimited since "baz" with value "shady" is in shadow_mode
curl localhost:8888/twoheader -H "foo: foo" -H "baz: not-so-shady" # This is subject to rate-limiting because the it's now in shadow_mode
Editexamples/xds-sotw-config-server/resource.go
to test different rate limit configs.
To see the metrics in the example
# The metrics for the shadow_mode keys
curl http://localhost:9102/metrics | grep -i shadow
Integration tests are coded as bash-scripts in integration-test/scripts
.
The test suite will spin up a docker-compose environment from integration-test/docker-compose-integration-test.yml
If the test suite fails it will exit with code 1.
make integration_tests
The rate limit configuration file format is YAML (mainly so that comments are supported).
- Domain: A domain is a container for a set of rate limits. All domains known to the Ratelimit service must be globally unique. They serve as a way for different teams/projects to have rate limit configurations that don't conflict.
- Descriptor: A descriptor is a list of key/value pairs owned by a domain that the Ratelimit service uses to
select the correct rate limit to use when limiting. Descriptors are case-sensitive. Examples of descriptors are:
- ("database", "users")
- ("message_type", "marketing"),("to_number","2061234567")
- ("to_cluster", "service_a")
- ("to_cluster", "service_a"),("from_cluster", "service_b")
Each configuration contains a top level descriptor list and potentially multiple nested lists beneath that. The format is:
domain: <unique domain ID>
descriptors:
- key: <rule key: required>
value: <rule value: optional>
rate_limit: (optional block)
name: (optional)
replaces: (optional)
- name: (optional)
unit: <see below: required>
requests_per_unit: <see below: required>
shadow_mode: (optional)
detailed_metric: (optional)
descriptors: (optional block)
- ... (nested repetition of above)
Each descriptor in a descriptor list must have a key. It can also optionally have a value to enable a more specific match. The "rate_limit" block is optional and if present sets up an actual rate limit rule. See below for how the rule is defined. If the rate limit is not present and there are no nested descriptors, then the descriptor is effectively whitelisted. Otherwise, nested descriptors allow more complex matching and rate limiting scenarios.
rate_limit:
unit: <second, minute, hour, day>
requests_per_unit: <uint>
The rate limit block specifies the actual rate limit that will be used when there is a match. Currently the service supports per second, minute, hour, and day limits. More types of limits may be added in the future based on user demand.
The replaces key indicates that this descriptor will replace the configuration set by another descriptor.
If there is a rule being evaluated, and multiple descriptors can apply, the replaces descriptor will drop evaluation of the descriptor which it is replacing.
To enable this, any descriptor which should potentially be replaced by another should have a name keyword in the rate_limit section, and any descriptor which should potentially replace the original descriptor should have a name keyword in its respective replaces section. Whenever limits match to both rules, only the rule which replaces the original will take effect, and the limit of the original will not be changed after evaluation.
For example, let's say you have a bunch of endpoints and each is classified under read or write, with read having a certain limit and write having another. Each user has a certain limit for both endpoints. However, let's say that you want to increase a user's limit to a single read endpoint. The only option without using replaces would be to increase their limit for the read category. The replaces keyword allows increasing the limit of a single endpoint in this case.
A shadow_mode key in a rule indicates that whatever the outcome of the evaluation of the rule, the end-result will always be "OK".
When a block is in ShadowMode all functions of the rate limiting service are executed as normal, with cache-lookup and statistics
An additional statistic is added to keep track of how many times a key with "shadow_mode" has overridden result.
There is also a Global Shadow Mode
Setting the detailed_metric: true
for a descriptor will extend the metrics that are produced. Normally a descriptor that matches a value that is not explicitly listed in the configuration will from a metrics point-of-view be rolled-up into the base entry. This can be problematic if you want to have those details available for analysis.
NB! This should only be enabled in situations where the potentially large cardinality of metrics that this can lead to is acceptable.
Let's start with a simple example:
domain: mongo_cps
descriptors:
- key: database
value: users
rate_limit:
unit: second
requests_per_unit: 500
- key: database
value: default
rate_limit:
unit: second
requests_per_unit: 500
In the configuration above the domain is "mongo_cps" and we setup 2 different rate limits in the top level descriptor list. Each of the limits have the same key ("database"). They have a different value ("users", and "default"), and each of them setup a 500 request per second rate limit.
A slightly more complex example:
domain: messaging
descriptors:
# Only allow 5 marketing messages a day
- key: message_type
value: marketing
descriptors:
- key: to_number
rate_limit:
unit: day
requests_per_unit: 5
# Only allow 100 messages a day to any unique phone number
- key: to_number
rate_limit:
unit: day
requests_per_unit: 100
In the preceding example, the domain is "messaging" and we setup two different scenarios that illustrate more complex functionality. First, we want to limit on marketing messages to a specific number. To enable this, we make use of nested descriptor lists. The top level descriptor is ("message_type", "marketing"). However this descriptor does not have a limit assigned so it's just a placeholder. Contained within this entry we have another descriptor list that includes an entry with key "to_number". However, notice that no value is provided. This means that the service will match against any value supplied for "to_number" and generate a unique limit. Thus, ("message_type", "marketing"), ("to_number", "2061111111") and ("message_type", "marketing"),("to_number", "2062222222") will each get 5 requests per day.
The configuration also sets up another rule without a value. This one creates an overall limit for messages sent to any particular number during a 1 day period. Thus, ("to_number", "2061111111") and ("to_number", "2062222222") both get 100 requests per day.
When calling the rate limit service, the client can specify multiple descriptors to limit on in a single call. This limits round trips and allows limiting on aggregate rule definitions. For example, using the preceding configuration, the client could send this complete request (in pseudo IDL):
RateLimitRequest:
domain: messaging
descriptor: ("message_type", "marketing"),("to_number", "2061111111")
descriptor: ("to_number", "2061111111")
And the service will rate limit against all matching rules and return an aggregate result; a logical OR of all the individual rate limit decisions.
An example to illustrate matching order.
domain: edge_proxy_per_ip
descriptors:
- key: remote_address
rate_limit:
unit: second
requests_per_unit: 10
# Black list IP
- key: remote_address
value: 50.0.0.5
rate_limit:
unit: second
requests_per_unit: 0
In the preceding example, we setup a generic rate limit for individual IP addresses. The architecture's edge proxy can
be configured to make a rate limit service call with the descriptor ("remote_address", "50.0.0.1")
for example. This IP would
get 10 requests per second as
would any other IP. However, the configuration also contains a second configuration that explicitly defines a
value along with the same key.
If the descriptor ("remote_address", "50.0.0.5")
is received, the service
will attempt the most specific match possible. This means
the most specific descriptor at the same level as your request. Thus, key/value is always attempted as a match before just key.
The Ratelimit service matches requests to configuration entries with the same level, i.e same number of tuples in the request's descriptor as nested levels of descriptors in the configuration file. For instance, the following request:
RateLimitRequest:
domain: example4
descriptor: ("key", "value"),("subkey", "subvalue")
Would not match the following configuration. Even though the first descriptor in the request matches the 1st level descriptor in the configuration, the request has two tuples in the descriptor.
domain: example4
descriptors:
- key: key
value: value
rate_limit:
requests_per_unit: 300
unit: second
However, it would match the following configuration:
domain: example4
descriptors:
- key: key
value: value
descriptors:
- key: subkey
rate_limit:
requests_per_unit: 300
unit: second
We can also define unlimited rate limit descriptors:
domain: internal
descriptors:
- key: ldap
rate_limit:
unlimited: true
- key: azure
rate_limit:
unit: minute
requests_per_unit: 100
For an unlimited descriptor, the request will not be sent to the underlying cache (Redis/Memcached), but will be quickly returned locally by the ratelimit instance. This can be useful for collecting statistics, or if one wants to define a descriptor that has no limit but the client wants to distinguish between such descriptor and one that does not exist.
The return value for unlimited descriptors will be an OK status code with the LimitRemaining field set to MaxUint32 value.
A rule using shadow_mode is useful for soft-launching rate limiting. In this example
RateLimitRequest:
domain: example6
descriptor: ("service", "auth-service"),("user", "user-a")
user-a
of the auth-service
would not get rate-limited regardless of the rate of requests, there would however be statistics related to the breach of the configured limit of 10 req / sec.
user-b
would be limited to 20 req / sec however.
domain: example6
descriptors:
- key: service
descriptors:
- key: user
value: user-a
rate_limit:
requests_per_unit: 10
unit: second
shadow_mode: true
- key: user
value: user-b
rate_limit:
requests_per_unit: 20
unit: second
When the replaces keyword is used, that limit will replace any limit which has the name being replaced as its name, and the original descriptor's limit will not be affected.
In the example below, the following limits will apply:
(key_1, value_1), (user, bkthomps): 5 / sec
(key_2, value_2), (user, bkthomps): 10 / sec
(key_1, value_1), (key_2, value_2), (user, bkthomps): 10 / sec since the (key_1, value_1), (user, bkthomps) rule was replaced and this will not affect the 5 / sec limit that would take effect with (key_2, value_2), (user, bkthomps)
domain: example7
descriptors:
- key: key_1
value: value_1
descriptors:
- key: user
value: bkthomps
rate_limit:
name: specific_limit
requests_per_unit: 5
unit: second
- key: key_2
value: value_2
descriptors:
- key: user
value: bkthomps
rate_limit:
replaces:
- name: specific_limit
requests_per_unit: 10
unit: second
In this example we demonstrate how a descriptor without a specified value is configured to override the default behavior and include the matched-value in the metrics.
Rate limiting configuration and tracking works as normally
(key_1, unspecified_value): 10 / sec
(key_1, unspecified_value2): 10 / sec
(key_1, value_1): 20 / sec
domain: example8
descriptors:
- key: key1
detailed_metric: true
rate_limit:
unit: minute
requests_per_unit: 10
- key: key1
value: value1
rate_limit:
unit: minute
requests_per_unit: 20
The metrics keys will be the following:
"key1_unspecified_value" "key1_unspecified_value2" "key1_value1"
rather than the normal "key1" "key1_value1"
Value supports wildcard matching to apply rate-limit for nested endpoints:
(key_1, value_1): 20 / sec
(key_1, value_2): 20 / sec
domain: example9
descriptors:
- key: key1
value: value*
rate_limit:
unit: minute
requests_per_unit: 20
Rate limit service supports following configuration loading methods. You can define which methods to use by configuring environment variable CONFIG_TYPE
.
Config Loading Method | Value for Environment Variable CONFIG_TYPE |
---|---|
File Based Configuration Loading | FILE (Default) |
xDS Server Based Configuration Loading | GRPC_XDS_SOTW |
When the environment variable FORCE_START_WITHOUT_INITIAL_CONFIG
set to false
, the Rate limit service will wait for initial rate limit configuration before
starting the server (gRPC, Rest server endpoints). When set to true
the server will start even without initial configuration.
The Ratelimit service uses a library written by Lyft called goruntime to do configuration loading. Goruntime monitors a designated path, and watches for symlink swaps to files in the directory tree to reload configuration files.
The path to watch can be configured via the settings package with the following environment variables:
RUNTIME_ROOT default:"/srv/runtime_data/current"
RUNTIME_SUBDIRECTORY
RUNTIME_APPDIRECTORY default:"config"
RUNTIME_IGNOREDOTFILES default:"false"
Configuration files are loaded from RUNTIME_ROOT/RUNTIME_SUBDIRECTORY/RUNTIME_APPDIRECTORY/*.yaml
There are two methods for triggering a configuration reload:
- Symlink RUNTIME_ROOT to a different directory.
- Update the contents inside
RUNTIME_ROOT/RUNTIME_SUBDIRECTORY/RUNTIME_APPDIRECTORY/
directly.
The former is the default behavior. To use the latter method, set the RUNTIME_WATCH_ROOT
environment variable to false
.
The following filesystem operations on configuration files inside RUNTIME_ROOT/RUNTIME_SUBDIRECTORY/RUNTIME_APPDIRECTORY/
will force a reload of all config files:
- Write
- Create
- Chmod
- Remove
For more information on how runtime works you can read its README.
By default it is not possible to define multiple configuration files within RUNTIME_SUBDIRECTORY
referencing the same domain.
To enable this behavior set MERGE_DOMAIN_CONFIG
to true
.
xDS Management Server is a gRPC server which implements the Aggregated Discovery Service (ADS).
The xDS Management server serves Discovery Response with Ratelimit Configuration Resources
and with Type URL "type.googleapis.com/ratelimit.config.ratelimit.v3.RateLimitConfig"
.
The xDS client in the Rate limit service configure Rate limit service with the provided configuration. In case of connection failures, the xDS Client retries the connection to the xDS server with exponential backoff and the backoff parameters are configurable.
XDS_CLIENT_BACKOFF_JITTER
: set to"true"
to add jitter to the exponential backoff.XDS_CLIENT_BACKOFF_INITIAL_INTERVAL
: The base amount of time the xDS client waits before retyring the connection after failure. Default: "10s"XDS_CLIENT_BACKOFF_MAX_INTERVAL
: The max backoff interval is the upper limit on the amount of time the xDS client will wait between retries. After reaching the max backoff interval, the next retries will continue using the max interval. Default: "60s"XDS_CLIENT_BACKOFF_RANDOM_FACTOR
: This is a factor by which the initial interval is multiplied to calculate the next backoff interval. Default: "0.5"
For more information on xDS protocol please refer to the envoy proxy documentation.
You can refer to the sample xDS configuration management server.
The xDS server for listening for configuration can be set via settings package with the following environment variables:
CONFIG_GRPC_XDS_NODE_ID default:"default"
CONFIG_GRPC_XDS_SERVER_URL default:"localhost:18000"
CONFIG_GRPC_XDS_SERVER_CONNECT_RETRY_INTERVAL default:"3s"
As well Ratelimit supports TLS connections, these can be configured using the following environment variables:
CONFIG_GRPC_XDS_SERVER_USE_TLS
: set to"true"
to enable a TLS connection with the xDS configuration management server.CONFIG_GRPC_XDS_CLIENT_TLS_CERT
,CONFIG_GRPC_XDS_CLIENT_TLS_KEY
, andCONFIG_GRPC_XDS_SERVER_TLS_CACERT
to provides files to specify a TLS connection configuration to the xDS configuration management server.CONFIG_GRPC_XDS_SERVER_TLS_SAN
: (Optional) Override the SAN value to validate from the server certificate.
When using xDS you can configure extra headers that will be added to GRPC requests to the xDS Management server. Extra headers can be useful for providing additional authorization information. This can be configured using the following environment variable:
CONFIG_GRPC_XDS_CLIENT_ADDITIONAL_HEADERS
- set to "<k1:v1>,<k2:v2>"
to add multiple headers to GRPC requests.
A centralized log collection system works better with logs in json format. JSON format avoids the need for custom parsing rules. The Ratelimit service produces logs in a text format by default. For Example:
time="2020-09-10T17:22:35Z" level=debug msg="loading domain: messaging"
time="2020-09-10T17:22:35Z" level=debug msg="loading descriptor: key=messaging.message_type_marketing"
time="2020-09-10T17:22:35Z" level=debug msg="loading descriptor: key=messaging.message_type_marketing.to_number ratelimit={requests_per_unit=5, unit=DAY}"
time="2020-09-10T17:22:35Z" level=debug msg="loading descriptor: key=messaging.to_number ratelimit={requests_per_unit=100, unit=DAY}"
time="2020-09-10T17:21:55Z" level=warning msg="Listening for debug on ':6070'"
time="2020-09-10T17:21:55Z" level=warning msg="Listening for HTTP on ':8080'"
time="2020-09-10T17:21:55Z" level=debug msg="waiting for runtime update"
time="2020-09-10T17:21:55Z" level=warning msg="Listening for gRPC on ':8081'"
JSON Log format can be configured using the following environment variables:
LOG_FORMAT=json
Output example:
{"@message":"loading domain: messaging","@timestamp":"2020-09-10T17:22:44.926010192Z","level":"debug"}
{"@message":"loading descriptor: key=messaging.message_type_marketing","@timestamp":"2020-09-10T17:22:44.926019315Z","level":"debug"}
{"@message":"loading descriptor: key=messaging.message_type_marketing.to_number ratelimit={requests_per_unit=5, unit=DAY}","@timestamp":"2020-09-10T17:22:44.926037174Z","level":"debug"}
{"@message":"loading descriptor: key=messaging.to_number ratelimit={requests_per_unit=100, unit=DAY}","@timestamp":"2020-09-10T17:22:44.926048993Z","level":"debug"}
{"@message":"Listening for debug on ':6070'","@timestamp":"2020-09-10T17:22:44.926113905Z","level":"warning"}
{"@message":"Listening for gRPC on ':8081'","@timestamp":"2020-09-10T17:22:44.926182006Z","level":"warning"}
{"@message":"Listening for HTTP on ':8080'","@timestamp":"2020-09-10T17:22:44.926227031Z","level":"warning"}
{"@message":"waiting for runtime update","@timestamp":"2020-09-10T17:22:44.926267808Z","level":"debug"}
Client-side GRPC DNS re-resolution in scenarios with auto scaling enabled might not work as expected and the current workaround is to configure connection keepalive on server-side. The behavior can be fixed by configuring the following env variables for the ratelimit server:
GRPC_MAX_CONNECTION_AGE
: a duration for the maximum amount of time a connection may exist before it will be closed by sending a GoAway. A random jitter of +/-10% will be added to MaxConnectionAge to spread out connection storms.GRPC_MAX_CONNECTION_AGE_GRACE
: an additive period after MaxConnectionAge after which the connection will be forcibly closed.
Health check status is determined internally by individual components. Currently, we have three components that determine the overall health status of the rate limit service. Each of the individual component's health needs to be healthy for the overall to report healthy. Some components may be turned OFF via configurations so overall health is not effected by that component's health status.
- Redis health (Turned ON. Defaults to healthy)
- Configuration status (Turned OFF unless configured to be ON via
HEALTHY_WITH_AT_LEAST_ONE_CONFIG_LOADED
see below section. Defaults to unhealthy)- If the environment variable is enabled then, it will start in an unhealthy state and become healthy when at least one config is loaded. If we later fail to load any configs, it will go unhealthy again.
- Sigterm (Turned ON. Defaults to healthy)
- Turns unhealthy if receives sigterm signal All components needs to be healthy for overall health to be healthy.
Health check can be configured to check if rate-limit configurations are loaded using the following environment variable.
HEALTHY_WITH_AT_LEAST_ONE_CONFIG_LOADED default:"false"`
If HEALTHY_WITH_AT_LEAST_ONE_CONFIG_LOADED
is enabled then health check will start as unhealthy and becomes healthy if
it detects at least one domain is loaded with the config. If it detects no config again then it will change to unhealthy.
By default the ratelimit gRPC server binds to 0.0.0.0:8081
. To change this set
GRPC_HOST
and/or GRPC_PORT
. If you want to run the server on a unix domain
socket then set GRPC_UDS
, e.g. GRPC_UDS=/<dir>/ratelimit.sock
and leave
GRPC_HOST
and GRPC_PORT
unmodified.
For information on the fields of a Ratelimit gRPC request please read the information on the RateLimitRequest message type in the Ratelimit proto file.
The gRPC client will interact with ratelimit server and tell you if the requests are over limit.
-dial_string
: used to specify the address of ratelimit server. It defaults tolocalhost:8081
.-domain
: used to specify the domain.-descriptors
: used to specify one descriptor. You can pass multiple descriptors like following:
go run main.go -domain test \
-descriptors name=foo,age=14 -descriptors name=bar,age=18
There is a global shadow-mode which can make it easier to introduce rate limiting into an existing service landscape. It will override whatever result is returned by the regular rate limiting process.
The global shadow mode is configured with an environment variable
Setting environment variable SHADOW_MODE
to true
will enable the feature.
There is an additional service-level statistics generated that will increment whenever the global shadow mode has overridden a rate limiting result.
The rate limit service generates various statistics for each configured rate limit rule that will be useful for end users both for visibility and for setting alarms. Ratelimit uses gostats as its statistics library. Please refer to gostats' documentation for more information on the library.
Statistics default to using StatsD and configured via the env vars from gostats.
To output statistics to stdout instead, set env var USE_STATSD
to false
Configure statistics output frequency with STATS_FLUSH_INTERVAL
, where the type is time.Duration
, e.g. 10s
is the default value.
To disable statistics entirely, set env var DISABLE_STATS
to true
Rate Limit Statistic Path:
ratelimit.service.rate_limit.DOMAIN.KEY_VALUE.STAT
DOMAIN:
- As specified in the domain value in the YAML runtime file
KEY_VALUE:
- A combination of the key value
- Nested descriptors would be suffixed in the stats path
The default mode is that the value-part is omitted if the rule that matches is a descriptor without a value. Specifying the detailed_metric
configuration parameter changes this behavior and creates a unique metric even in this situation.
STAT:
- near_limit: Number of rule hits over the NearLimit ratio threshold (currently 80%) but under the threshold rate.
- over_limit: Number of rule hits exceeding the threshold rate
- total_hits: Number of rule hits in total
- shadow_mode: Number of rule hits where shadow_mode would trigger and override the over_limit result
To use a custom near_limit ratio threshold, you can specify with NEAR_LIMIT_RATIO
environment variable. It defaults to 0.8
(0-1 scale). These are examples of generated stats for some configured rate limit rules from the above examples:
ratelimit.service.rate_limit.mongo_cps.database_default.over_limit: 0
ratelimit.service.rate_limit.mongo_cps.database_default.total_hits: 2846
ratelimit.service.rate_limit.mongo_cps.database_users.over_limit: 0
ratelimit.service.rate_limit.mongo_cps.database_users.total_hits: 2939
ratelimit.service.rate_limit.messaging.message_type_marketing.to_number.over_limit: 0
ratelimit.service.rate_limit.messaging.message_type_marketing.to_number.total_hits: 0
ratelimit.service.rate_limit.messaging.auth-service.over_limit.total_hits: 1
ratelimit.service.rate_limit.messaging.auth-service.over_limit.over_limit: 1
ratelimit.service.rate_limit.messaging.auth-service.over_limit.shadow_mode: 1
EXTRA_TAGS
: set to"<k1:v1>,<k2:v2>"
to tag all emitted stats with the provided tags. You might want to tag build commit or release version, for example.
To enable dogstatsd integration set:
USE_DOG_STATSD
:true
to use DogStatsD
dogstatsd also enables so called mogrifiers
which can
convert from traditional stats tags into a combination of stat name and tags.
To enable mogrifiers, set a comma-separated list of them in DOG_STATSD_MOGRIFIERS
.
e.g. USE_DOG_STATSD_MOGRIFIERS
: FOO,BAR
For each mogrifier, define variables that declare the mogrification
DOG_STATSD_MOGRIFIERS_%s_PATTERN
: The regex pattern to match onDOG_STATSD_MOGRIFIERS_%s_NAME
: The name of the metric to emit. Can contain variables.DOG_STATSD_MOGRIFIERS_%s_TAGS
: Comma-separated list of tags to emit. Can contain variables.
Variables within mogrifiers are strings such as $1
, $2
, $3
which can be used to reference
a match group from the regex pattern.
In the example below we will set mogrifier DOMAIN to adjust
some.original.metric.TAG
to some.original.metric
with tag domain:TAG
First enable a single mogrifier:
USE_DOG_STATSD_MOGRIFIERS
:DOMAIN
Then, declare the rules for the DOMAIN
modifier:
DOG_STATSD_MOGRIFIER_DOMAIN_PATTERN
:^some\.original\.metric\.(.*)$
DOG_STATSD_MOGRIFIER_DOMAIN_NAME
:some.original.metric
DOG_STATSD_MOGRIFIER_DOMAIN_TAGS
:domain:$1
Let's also set another mogrifier which outputs the hits metrics with a domain and descriptor tag
First, enable an extra mogrifier:
USE_DOG_STATSD_MOGRIFIERS
:DOMAIN,HITS
Then, declare additional rules for the DESCRIPTOR
mogrifier
DOG_STATSD_MOGRIFIER_HITS_PATTERN
:^ratelimit\.service\.rate_limit\.([^.]+)\.(.*)\.([^.]+)$
DOG_STATSD_MOGRIFIER_HITS_NAME
:ratelimit.service.rate_limit.$3
DOG_STATSD_MOGRIFIER_HITS_TAGS
:domain:$1,descriptor:$2
The ratelimit service listens to HTTP 1.1 (by default on port 8080) with two endpoints:
- /healthcheck → return a 200 if this service is healthy
- /json → HTTP 1.1 endpoint for interacting with ratelimit service
Takes an HTTP POST with a JSON body of the form e.g.
{
"domain": "dummy",
"descriptors": [
{ "entries": [{ "key": "one_per_day", "value": "something" }] }
]
}
The service will return an http 200 if this request is allowed (if no ratelimits exceeded) or 429 if one or more ratelimits were exceeded.
The response is a RateLimitResponse encoded with proto3-to-json mapping:
{
"overallCode": "OVER_LIMIT",
"statuses": [
{
"code": "OVER_LIMIT",
"currentLimit": {
"requestsPerUnit": 1,
"unit": "MINUTE"
}
},
{
"code": "OK",
"currentLimit": {
"requestsPerUnit": 2,
"unit": "MINUTE"
},
"limitRemaining": 1
}
]
}
The debug port can be used to interact with the running process.
$ curl 0:6070/
/debug/pprof/: root of various pprof endpoints. hit for help.
/rlconfig: print out the currently loaded configuration for debugging
/stats: print out stats
You can specify the debug server address with the DEBUG_HOST
and DEBUG_PORT
environment variables. They currently default to 0.0.0.0
and 6070
respectively.
Ratelimit optionally uses freecache as its local caching layer, which stores the over-the-limit cache keys, and thus avoids reading the
redis cache again for the already over-the-limit keys. The local cache size can be configured via LocalCacheSizeInBytes
in the settings.
If LocalCacheSizeInBytes
is 0, local cache is disabled.
Ratelimit uses Redis as its caching layer. Ratelimit supports two operation modes:
- One Redis server for all limits.
- Two Redis instances: one for per second limits and another one for all other limits.
As well Ratelimit supports TLS connections and authentication. These can be configured using the following environment variables:
REDIS_TLS
&REDIS_PERSECOND_TLS
: set to"true"
to enable a TLS connection for the specific connection type.REDIS_TLS_CLIENT_CERT
,REDIS_TLS_CLIENT_KEY
, andREDIS_TLS_CACERT
to provides files to specify a TLS connection configuration to Redis server that requires client certificate verification. (This is effective whenREDIS_TLS
orREDIS_PERSECOND_TLS
is set to to"true"
).REDIS_TLS_SKIP_HOSTNAME_VERIFICATION
set to"true"
will skip hostname verification in environments where the certificate has an invalid hostname, such as GCP Memorystore.REDIS_AUTH
&REDIS_PERSECOND_AUTH
: set to"password"
to enable password-only authentication to the redis host.REDIS_AUTH
&REDIS_PERSECOND_AUTH
: set to"username:password"
to enable username-password authentication to the redis host.CACHE_KEY_PREFIX
: a string to prepend to all cache keys
For controlling the behavior of cache key incrementation when any of them is already over the limit, you can use the following configuration:
STOP_CACHE_KEY_INCREMENT_WHEN_OVERLIMIT
: Set this configuration totrue
to disallow key incrementation when one of the keys is already over the limit.
STOP_CACHE_KEY_INCREMENT_WHEN_OVERLIMIT
is useful when multiple descriptors are included in a single request. Setting this to true
can prevent the incrementation of other descriptors' counters if any of the descriptors is already over the limit.
Ratelimit supports different types of redis deployments:
- Single instance (default): Talk to a single instance of redis, or a redis proxy (e.g. https://www.envoyproxy.io/docs/envoy/latest/intro/arch_overview/other_protocols/redis)
- Sentinel: Talk to a redis deployment with sentinel instances (see https://redis.io/topics/sentinel)
- Cluster: Talk to a redis in cluster mode (see https://redis.io/topics/cluster-spec)
The deployment type can be specified with the REDIS_TYPE
/ REDIS_PERSECOND_TYPE
environment variables. Depending on the type defined, the REDIS_URL
and REDIS_PERSECOND_URL
are expected to have the following formats:
- "single": Depending on the socket type defined, either a single hostname:port pair or a unix domain socket reference.
- "sentinel": A comma separated list with the first string as the master name of the sentinel cluster followed by hostname:port pairs. The list size should be >= 2. The first item is the name of the master and the rest are the sentinels.
- "cluster": A comma separated list of hostname:port pairs with all the nodes in the cluster.
By default, for each request, ratelimit will pick up a connection from pool, write multiple redis commands in a single write then reads their responses in a single read. This reduces network delay.
For high throughput scenarios, ratelimit also support implicit pipelining . It can be configured using the following environment variables:
REDIS_PIPELINE_WINDOW
&REDIS_PERSECOND_PIPELINE_WINDOW
: sets the duration after which internal pipelines will be flushed. If window is zero then implicit pipelining will be disabled.REDIS_PIPELINE_LIMIT
&REDIS_PERSECOND_PIPELINE_LIMIT
: sets maximum number of commands that can be pipelined before flushing. If limit is zero then no limit will be used and pipelines will only be limited by the specified time window.
implicit pipelining
is disabled by default. To enable it, you can use default values used by radix and tune for the optimal value.
To configure one Redis instance use the following environment variables:
REDIS_SOCKET_TYPE
REDIS_URL
REDIS_POOL_SIZE
REDIS_TYPE
(optional)
This setup will use the same Redis server for all limits.
To configure two Redis instances use the following environment variables:
REDIS_SOCKET_TYPE
REDIS_URL
REDIS_POOL_SIZE
REDIS_PERSECOND
: set this to"true"
.REDIS_PERSECOND_SOCKET_TYPE
REDIS_PERSECOND_URL
REDIS_PERSECOND_POOL_SIZE
REDIS_PERSECOND_TYPE
(optional)
This setup will use the Redis server configured with the _PERSECOND_
vars for
per second limits, and the other Redis server for all other limits.
To configure whether to return health check failure if there is no active redis connection
REDIS_HEALTH_CHECK_ACTIVE_CONNECTION
: (default is "false")
Experimental Memcache support has been added as an alternative to Redis in v1.5.
To configure a Memcache instance use the following environment variables instead of the Redis variables:
MEMCACHE_HOST_PORT=
: a comma separated list of hostname:port pairs for memcache nodes (mutually exclusive withMEMCACHE_SRV
)MEMCACHE_SRV=
: an SRV record to lookup hosts from (mutually exclusive withMEMCACHE_HOST_PORT
)MEMCACHE_SRV_REFRESH=0
: refresh the list of hosts every n seconds, if 0 no refreshing will happen, supports duration suffixes: "ns", "us" (or "µs"), "ms", "s", "m", "h".BACKEND_TYPE=memcache
CACHE_KEY_PREFIX
: a string to prepend to all cache keysMEMCACHE_MAX_IDLE_CONNS=2
: the maximum number of idle TCP connections per memcache node,2
is the default of the underlying libraryMEMCACHE_TLS
: set to"true"
to connect to the server with TLS.MEMCACHE_TLS_CLIENT_CERT
,MEMCACHE_TLS_CLIENT_KEY
, andMEMCACHE_TLS_CACERT
to provide files that parameterize the memcache client TLS connection configuration.MEMCACHE_TLS_SKIP_HOSTNAME_VERIFICATION
set to"true"
will skip hostname verification in environments where the certificate has an invalid hostname.
With memcache mode increments will happen asynchronously, so it's technically possible for a client to exceed quota briefly if multiple requests happen at exactly the same time.
Note that Memcache has a max key length of 250 characters, so operations referencing very long descriptors will fail. Descriptors sent to Memcache should not contain whitespaces or control characters.
When using multiple memcache nodes in MEMCACHE_HOST_PORT=
, one should provide the identical list of memcache nodes
to all ratelimiter instances to ensure that a particular cache key is always hashed to the same memcache node.
Ratelimit service can be configured to return custom headers with the ratelimit information. It will populate the response_headers_to_add as part of the RateLimitResponse.
The following environment variables control the custom response feature:
LIMIT_RESPONSE_HEADERS_ENABLED
- Enables the custom response headersLIMIT_LIMIT_HEADER
- The default value is "RateLimit-Limit", setting the environment variable will specify an alternative header nameLIMIT_REMAINING_HEADER
- The default value is "RateLimit-Remaining", setting the environment variable will specify an alternative header nameLIMIT_RESET_HEADER
- The default value is "RateLimit-Reset", setting the environment variable will specify an alternative header name
Ratelimit service supports exporting spans in OLTP format. See OpenTelemetry for more information.
The following environment variables control the tracing feature:
TRACING_ENABLED
- Enables the tracing feature. Only "true" and "false"(default) are allowed in this field.TRACING_EXPORTER_PROTOCOL
- Controls the protocol of exporter in tracing feature. Only "http"(default) and "grpc" are allowed in this field.TRACING_SERVICE_NAME
- Controls the service name appears in tracing span. The default value is "RateLimit".TRACING_SERVICE_NAMESPACE
- Controls the service namespace appears in tracing span. The default value is empty.TRACING_SERVICE_INSTANCE_ID
- Controls the service instance id appears in tracing span. It is recommended to put the pod name or container name in this field. The default value is a randomly generated version 4 uuid if unspecified.- Other fields in OTLP Exporter Documentation. These section needs to be correctly configured in order to enable the exporter to export span to the correct destination.
TRACING_SAMPLING_RATE
- Controls the sampling rate, defaults to 1 which means always sample. Valid range: 0.0-1.0. For high volume services, adjusting the sampling rate is recommended.
You may use the following commands to quickly setup a openTelemetry collector together with a Jaeger all-in-one binary for quickstart:
docker run --name otlp -d -p 4318 -p 4317 -v examples/otlp-collector:/tmp/otlp-collector otel/opentelemetry-collector:0.48.0 -- --config /tmp/otlp-collector/config.yaml
otelcol-contrib --config examples/otlp-collector/config.yaml
docker run -d --name jaeger -p 16686:16686 -p 14250:14250 jaegertracing/all-in-one:1.33
Ratelimit supports TLS for it's gRPC endpoint.
The following environment variables control the TLS feature:
GRPC_SERVER_USE_TLS
- Enables gRPC connections to server over TLSGRPC_SERVER_TLS_CERT
- Path to the file containing the server cert chainGRPC_SERVER_TLS_KEY
- Path to the file containing the server private key
Ratelimit uses goruntime to watch the TLS certificate and key and will hot reload them on changes.
Ratelimit supports mTLS when Envoy sends requests to the service.
TLS must be enabled on the gRPC endpoint in order for mTLS to work see TLS.
The following variables can be set to enable mTLS on the Ratelimit service.
GRPC_CLIENT_TLS_CACERT
- Path to the file containing the client CA certificate.GRPC_CLIENT_TLS_SAN
- (Optional) DNS Name to validate from the client cert during mTLS auth
In the envoy config use, add the transport_socket
section to the ratelimit service cluster config
"name": "ratelimit"
"transport_socket":
"name": "envoy.transport_sockets.tls"
"typed_config":
"@type": "type.googleapis.com/envoy.extensions.transport_sockets.tls.v3.UpstreamTlsContext"
"common_tls_context":
"tls_certificates":
- "certificate_chain":
"filename": "/opt/envoy/tls/ratelimit-client-cert.pem"
"private_key":
"filename": "/opt/envoy/tls/ratelimit-client-key.pem"
"validation_context":
"match_subject_alt_names":
- "exact": "ratelimit.server.dnsname"
"trusted_ca":
"filename": "/opt/envoy/tls/ratelimit-server-ca.pem"
- envoy-announce: Low frequency mailing list where we will email announcements only.
- envoy-users: General user discussion.
Please add
[ratelimit]
to the email subject. - envoy-dev: Envoy developer discussion (APIs,
feature design, etc.). Please add
[ratelimit]
to the email subject. - Slack: Slack, to get invited go here.
We have the IRC/XMPP gateways enabled if you prefer either of those. Once an account is created,
connection instructions for IRC/XMPP can be found here.
The
#ratelimit-users
channel is used for discussions about the ratelimit service.