Rate limiting reference
Arcjet rate limiting lets you define rules which limit the number of requests a client can make over a period of time.
Configuration
Section titled “Configuration”Each rate limit is configured on an exact path with a set of client characteristics and algorithm specific options.
Fixed window rate limit options
Section titled “Fixed window rate limit options”Tracks the number of requests made by a client over a fixed time window. Options are explained in the Configuration documentation. For more details about how the algorithm works, see the fixed window algorithm description.
// Options for fixed window rate limit// See https://docs.arcjet.com/rate-limiting/configurationtype FixedWindowRateLimitOptions = { // "LIVE" will block requests. "DRY_RUN" will log only mode?: "LIVE" | "DRY_RUN"; // How the client is identified. See https://docs.arcjet.com/fingerprints characteristics?: string[]; // Time window the rate limit applies to (e.g. "1h", "60s", or seconds as a number) window: string | number; // Maximum number of requests allowed in the time window max: number;};# Signature for arcjet.fixed_window# See https://docs.arcjet.com/rate-limiting/configurationdef fixed_window( *, # Required. Mode.LIVE blocks requests; Mode.DRY_RUN logs only. mode: Mode, # Time window in seconds the rate limit applies to (integer only — Python # does not accept the "1h"/"60s" duration strings that the JS SDK does). window: int, # Maximum number of requests allowed in the time window max: int, # How the client is identified. See https://docs.arcjet.com/fingerprints characteristics: Sequence[str] = (),) -> FixedWindow: ...Fixed window example
Section titled “Fixed window example”import os
from arcjet import Mode, arcjet_sync, fixed_window
aj = arcjet_sync( key=os.environ["ARCJET_KEY"], rules=[ fixed_window( mode=Mode.LIVE, # Blocks requests. Use Mode.DRY_RUN to log only # Tracked by IP address by default, but this can be customized # See https://docs.arcjet.com/fingerprints # characteristics=["ip.src"], window=60, # 60 second fixed window max=100, # allow a maximum of 100 requests ), ],)Sliding window rate limit options
Section titled “Sliding window rate limit options”Tracks the number of requests made by a client over a sliding window so that the window moves with time. Options are explained in the Configuration documentation. For more details about how the algorithm works, see the sliding window algorithm description.
// Options for sliding window rate limit// See https://docs.arcjet.com/rate-limiting/configurationtype SlidingWindowRateLimitOptions = { // "LIVE" will block requests. "DRY_RUN" will log only mode?: "LIVE" | "DRY_RUN"; // How the client is identified. See https://docs.arcjet.com/fingerprints characteristics?: string[]; // The time interval in seconds for the rate limit interval: number; // Maximum number of requests allowed over the time interval max: number;};# Signature for arcjet.sliding_window# See https://docs.arcjet.com/rate-limiting/configurationdef sliding_window( *, # Required. Mode.LIVE blocks requests; Mode.DRY_RUN logs only. mode: Mode, # The time interval in seconds for the rate limit interval: int, # Maximum number of requests allowed over the time interval max: int, # How the client is identified. See https://docs.arcjet.com/fingerprints characteristics: Sequence[str] = (),) -> SlidingWindow: ...Sliding window example
Section titled “Sliding window example”import os
from arcjet import Mode, arcjet_sync, sliding_window
aj = arcjet_sync( key=os.environ["ARCJET_KEY"], rules=[ sliding_window( mode=Mode.LIVE, # Blocks requests. Use Mode.DRY_RUN to log only # Tracked by IP address by default, but this can be customized # See https://docs.arcjet.com/fingerprints # characteristics=["ip.src"], interval=60, # 60 second sliding window max=100, # allow a maximum of 100 requests ), ],)Token bucket rate limit options
Section titled “Token bucket rate limit options”Based on a bucket filled with a specific number of tokens. Each request withdraws a token from the bucket and the bucket is refilled at a fixed rate. Once the bucket is empty, the client is blocked until the bucket refills. Options are explained in the Configuration documentation. For more details about how the algorithm works, see the token bucket algorithm description.
// Options for token bucket rate limit// See https://docs.arcjet.com/rate-limiting/configurationtype TokenBucketRateLimitOptions = { // "LIVE" will block requests. "DRY_RUN" will log only mode?: "LIVE" | "DRY_RUN"; // How the client is identified. See https://docs.arcjet.com/fingerprints characteristics?: string[]; // Number of tokens to add to the bucket at each interval refillRate: number; // The interval in seconds to add tokens to the bucket interval: number; // The maximum number of tokens the bucket can hold capacity: number;};# Signature for arcjet.token_bucket# See https://docs.arcjet.com/rate-limiting/configurationdef token_bucket( *, # Required. Mode.LIVE blocks requests; Mode.DRY_RUN logs only. mode: Mode, # Number of tokens to add to the bucket at each interval refill_rate: int, # The interval in seconds to add tokens to the bucket interval: int, # The maximum number of tokens the bucket can hold capacity: int, # How the client is identified. See https://docs.arcjet.com/fingerprints characteristics: Sequence[str] = (),) -> TokenBucket: ...When using a token bucket rate limit, each request must specify the number of
tokens it wishes to withdraw from the bucket. This is done by passing a
requested property to the protect function.
Token bucket example
Section titled “Token bucket example”For how to specify the number of tokens to request, see the token bucket request example.
import os
from arcjet import Mode, arcjet_sync, token_bucket
aj = arcjet_sync( key=os.environ["ARCJET_KEY"], rules=[ token_bucket( mode=Mode.LIVE, # Blocks requests. Use Mode.DRY_RUN to log only # Tracked by IP address by default, but this can be customized # See https://docs.arcjet.com/fingerprints # characteristics=["ip.src"], refill_rate=10, # refill 10 tokens per interval interval=60, # 60 second interval capacity=100, # bucket maximum capacity of 100 tokens ), ],)The amount of tokens to deduct from the bucket is specified in the requested
option as a positive integer when calling the Arcjet protect function.
// Deduct 50 tokens from the bucket// The value for `requested` must be a positive integerconst decision = await aj.protect(req, { requested: 50 });# Deduct 50 tokens from the bucket# The value for `requested` must be a positive integerdecision = await aj.protect(request, requested=50) # use aj.protect(request, ...) for arcjet_syncIdentify users
Section titled “Identify users”Rate limit rules use characteristics to identify the client and apply the
limit across requests. The default is to use the client’s IP address. However,
you can specify other
characteristics such as a user ID
or other metadata from your application.
In this example we define a rate limit rule that applies to a specific user ID.
The custom characteristic is userId with the value passed as a prop on the
protect function. You can use any string for the characteristic name and any
string, number or boolean for the value.
import os
from arcjet import Mode, arcjet_sync, fixed_windowfrom flask import Flask, jsonify, request
app = Flask(__name__)
aj = arcjet_sync( key=os.environ["ARCJET_KEY"], # Get your site key from https://console.arcjet.com rules=[ fixed_window( mode=Mode.LIVE, characteristics=["userId"], window=3600, # 1 hour in seconds max=60, ), ],)
@app.get("/")def index(): # Pass userId as a string to identify the user. This could also be a number # or boolean value decision = aj.protect(request, characteristics={"userId": "user123"}) print("Arcjet decision", decision)
if decision.is_denied(): return jsonify(error="Too Many Requests"), 429
return jsonify(message="Hello world")To identify users with different characteristics, such as IP address for anonymous
users and a user ID for logged in users, you can use withRule (JS) or
with_rule() (Python) to create augmented clients that use different
characteristics. See the
example in the custom characteristics section.
Decision
Section titled “Decision”Arcjet provides a single protect function that is used to execute your
protection rules. This requires a RequestEvent property which is the event
context as passed to the request handler.
This function returns a Promise that resolves to an
ArcjetDecision object. This contains the following properties:
id(string) – The unique ID for the request. This can be used to look up the request in the Arcjet dashboard. It is prefixed withreq_for decisions involving the Arcjet cloud API. For decisions taken locally, the prefix islreq_.conclusion(ArcjetConclusion) – The final conclusion based on evaluating each of the configured rules. If you wish to accept Arcjet’s recommended action based on the configured rules then you can use this property.reason(ArcjetReason) – An object containing more detailed information about the conclusion.results(ArcjetRuleResult[]) – An array ofArcjetRuleResultobjects containing the results of each rule that was executed.ip(ArcjetIpDetails) – An object containing Arcjet’s analysis of the client IP address. For more information, see the SDK reference.
To check whether a rate limit rule returned a deny conclusion, use
decision.isDenied() and decision.reason.isRateLimit() (JS) /
decision.is_denied() and decision.reason_v2.type == "RATE_LIMIT" (Python).
You can iterate through the results and check whether a rate limit was applied:
for (const result of decision.results) { console.log("Rule Result", result);}for result in decision.results: print("Rule Result", result)This example logs the full result as well as each rate limit rule:
import loggingimport os
from arcjet import Mode, arcjet_sync, detect_bot, fixed_windowfrom flask import Flask, jsonify, request
app = Flask(__name__)
logger = logging.getLogger(__name__)
aj = arcjet_sync( key=os.environ["ARCJET_KEY"], # Get your site key from https://console.arcjet.com rules=[ fixed_window(mode=Mode.LIVE, window=3600, max=60), detect_bot( mode=Mode.LIVE, allow=[], # "allow none" will block all detected bots ), ],)
@app.get("/")def index(): decision = aj.protect(request)
for result in decision.results: logger.info("Rule Result %s", result)
if result.reason_v2.type == "RATE_LIMIT": logger.info("Rate limit rule %s", result)
if result.reason_v2.type == "BOT": logger.info("Bot protection rule %s", result)
if decision.is_denied(): if decision.reason_v2.type == "RATE_LIMIT": return jsonify(error="Too Many Requests"), 429 return jsonify(error="Forbidden"), 403
return jsonify(message="Hello world")Token bucket request
Section titled “Token bucket request”When using a token bucket rule, pass an additional requested prop (a positive
integer) to the protect function. This is the number of tokens the client is
requesting to withdraw from the bucket.
import os
from arcjet import Mode, arcjet_sync, token_bucketfrom flask import Flask, jsonify, request
app = Flask(__name__)
aj = arcjet_sync( key=os.environ["ARCJET_KEY"], # Get your site key from https://console.arcjet.com rules=[ token_bucket( mode=Mode.LIVE, # Tracked by IP address by default, but this can be customized # See https://docs.arcjet.com/fingerprints # characteristics=["ip.src"], refill_rate=40_000, interval=86_400, # 1 day in seconds capacity=40_000, ), ],)
@app.get("/")def index(): decision = aj.protect(request, requested=50) print("Arcjet decision", decision)
if decision.is_denied(): return jsonify(error="Too Many Requests"), 429
return jsonify(message="Hello world")Rate limit headers
Section titled “Rate limit headers”With a rate limit rule enabled, you can access additional metadata in every Arcjet decision result:
max(number): The configured maximum number of requests applied to this request.remaining(number): The number of requests remaining beforemaxis reached within the window.window(number): The total amount of seconds in which requests are counted.reset(number): The remaining amount of seconds in the window.
These can be used to return RateLimit HTTP headers (draft
RFC) to
offer the client more detail.
In JavaScript, use setRateLimitHeaders
from @arcjet/decorate. In Python, use set_rate_limit_headers from the
arcjet package. Both write RateLimit and RateLimit-Policy headers from the
decision.
When several rate limit results are present, the tightest remaining budget is
advertised. If two policies share the same max, no headers are written.
import os
from arcjet import Mode, arcjet_sync, fixed_window, set_rate_limit_headersfrom flask import Flask, jsonify, request
app = Flask(__name__)
aj = arcjet_sync( key=os.environ["ARCJET_KEY"], # Get your site key from https://console.arcjet.com rules=[ fixed_window( mode=Mode.LIVE, window=3600, max=60, ), ],)
@app.get("/")def index(): decision = aj.protect(request) print("Arcjet decision", decision)
if decision.is_denied(): response = jsonify( error="Too Many Requests", reason=str(decision.reason_v2), ) response.status_code = 429 set_rate_limit_headers(response, decision) return response
response = jsonify(message="Hello world") set_rate_limit_headers(response, decision) return responseThis would result in draft RFC response headers similar to the following:
...< RateLimit: limit=10, remaining=5, reset=9< RateLimit-Policy: 10;w=10...Error handling
Section titled “Error handling”Arcjet is designed to fail open so that a service issue or misconfiguration does not block all requests. The SDK also times out and fails open after 2000 ms by default. However, in most cases, the response time is less than 20 ms to 30 ms.
If there is an error condition when processing the rule, Arcjet returns an
ERROR result for that rule and you can check the message property on the
rule’s error result for more information.
If all other rules that were run returned an ALLOW result, then the final
Arcjet conclusion is ERROR.
import loggingimport os
from arcjet import Mode, arcjet_sync, token_bucketfrom flask import Flask, jsonify, request
app = Flask(__name__)
logger = logging.getLogger(__name__)
aj = arcjet_sync( key=os.environ["ARCJET_KEY"], # Get your site key from https://console.arcjet.com rules=[ # Create a token bucket rate limit. Other algorithms are supported. token_bucket( mode=Mode.LIVE, # Blocks requests. Use Mode.DRY_RUN to log only characteristics=["userId"], # track requests by a custom user ID refill_rate=5, # refill 5 tokens per interval interval=10, # refill every 10 seconds capacity=10, # bucket maximum capacity of 10 tokens ), ],)
@app.get("/")def index(): user_id = "user123" # Replace with your authenticated user ID decision = aj.protect(request, characteristics={"userId": user_id}, requested=5) print("Arcjet decision", decision)
for result in decision.results: if result.reason_v2.type == "ERROR": # Fail open by logging the error and continuing logger.warning("Arcjet error: %s", result.reason_v2.message) # You could also fail closed here for very sensitive routes: # return jsonify(error="Service unavailable"), 503
if decision.is_denied(): return jsonify(error="Too Many Requests"), 429
return jsonify(message="Hello world")Testing
Section titled “Testing”Arcjet runs the same in any environment, including locally and in CI. You can
use the mode set to DRY_RUN to log the results of rule execution without
blocking any requests.
We have an example test framework you can use to automatically test your rules. Arcjet can also be triggered based using a sample of your traffic.
For details, see the Testing section of the docs.