APIs (Application Programming Interfaces) have become an integral part of software development and enable different applications to communicate with each other. However, APIs also need to be protected from abuse and overuse. That’s why API providers often enforce request rate limits.
What is an API request rate limit?
An API request rate limit sets the maximum number of API requests a client can make in a defined period. It is typically defined as requests per second, minute, hour, day, or month. Rate limits prevent clients from overwhelming the API server with too many requests.
Some common API rate limits are:
- 10 requests per second
- 1000 requests per hour
- 5000 requests per day
- 50,000 requests per month
These numbers will vary greatly depending on the API provider, the type of API, expected usage levels, infrastructure capacity and other factors.
Why are API rate limits needed?
There are several important reasons API providers enforce rate limits:
- Prevent abuse: Rate limits prevent malicious actors from launching attacks like DDoS by limiting how often they can send requests.
- Ensure fair usage: Rate limits ensure APIs are accessible to all users and no single user hogs resources.
- Control costs: Rate limits manage infrastructure costs by capping maximum usage levels.
- Maintain performance: Rate limits ensure APIs perform well under load and prevent outages.
- Comply with regulations: Some rate limits are imposed to meet regulatory requirements around data access.
Overall, rate limits protect the stability and security of APIs while providing fair access.
How are API rate limits implemented?
There are several technical methods used to enforce API rate limiting:
- IP rate limiting: Limits based on the requester’s IP address.
- User rate limiting: Limits based on user accounts.
- Application rate limiting: Limits based on the consuming application.
- Request throttling: Rejecting requests over the limit with an error.
- Load shedding: Gracefully degrading performance under high loads.
- Queueing: Delaying excess requests by putting them in a queue.
The actual rate limit logic can be implemented in the API gateway, at the application layer, or in surrounding infrastructure like load balancers. Popular rate limiting libraries include rate-limiter-flexible and ratelimit.js.
How are API rate limits enforced?
When a client application hits the API request limit, the API provider needs to enforce the limit. There are two main approaches:
- Hard limits: The request is rejected once the limit is reached, typically returning an error like 403 Forbidden or 429 Too Many Requests.
- Soft limits: Requests over the limit are throttled, but not rejected completely. This introduces latency but doesn’t fail the request.
Hard limits definitively enforce the rate limit, but may be a poor user experience. Soft limits are more flexible but complex to implement. Most APIs use a hybrid of soft and hard limits.
How can you determine your API’s rate limits?
If you are building an API, you’ll need to carefully determine appropriate request rate limits. Here are some tips:
- Profile expected usage patterns and set initial conservative limits based on your capacity.
- Gradually increase limits as you gather data on real world usage.
- Set different limits for bursting vs sustained requests.
- Scale limits relative to usage plans – free vs paid tiers, for example.
- Allow some headroom for spikes and make limits configurable.
Setting the right limits takes experimentation over time. The goal is to settle on optimal values that don’t undermine performance.
How can you manage exceeding API rate limits?
Even with well planned limits, it’s possible for client applications to exceed rate limits in production. Here are some ways to handle it:
- Have clear error handling logic for the rate limit exceeded response.
- Build in graceful degradation – reduce request frequency when nearing limits.
- Implement queuing and retries to space out requests.
- Consider using multiple API keys to provide higher combined limits.
- For hard failures, implement exponential backoff retries.
- Upgrade to a higher usage tier with higher limits if needed.
With robust client-side logic, short-term traffic bursts over the limit can be handled smoothly.
Best practices for setting API rate limits
Here are some API rate limiting best practices:
- Document your limits clearly for developers.
- Set reasonable default limits that you can increase later.
- Enforce limits through an API management platform if possible.
- Use both soft and hard limits for flexibility.
- Implement permissions to allow lifting limits for some users.
- Provide multiple API keys to allow higher combined limits.
- Monitor usage carefully and adjust limits accordingly.
Example API rate limit policies
Here are some example API rate limiting policies from major providers:
API | Rate Limit |
---|---|
15 requests per 15 minutes for public endpoints | |
Stripe | 100 requests per second |
Twilio | 1500 requests per 15 minutes |
Google Maps | 50 requests per second |
GitHub | 60 requests per hour for anonymous users |
As you can see, limits vary greatly depending on the API. Review documentation carefully before integrating with any third-party API.
Conclusion
API rate limits are essential for managing capacity, controlling costs, and preventing abuse. Carefully determining the optimal rates for limits requires a balance of capacity planning, usage monitoring, and trial-and-error. Implementing flexible client-side logic along with soft and hard limits on the API serves to enforce limits while providing a good developer experience. Rate limits require constant revisiting and optimization as usage evolves.