API Limits
Traffic Profile
Utilization Summary
Your team can safely issue 48,000 requests per minute before hitting the buffer.
At a Glance
- Queue headroom: No headroom — expect queue growth
- Queue growth: Stable — inbound rate stays within safe budget
- Burst backlog: Burst stays within safe capacity
- Burst recovery: 0 seconds to recover
Token Bucket Blueprint
These parameters work well for implementing a token bucket or leaky bucket throttle in code.
- Capacity: 60,000 tokens (matches provider window)
- Refill rate: 800 tokens / second
- Worker allowance: 66.67 tokens / second per client
- Sleep interval: 15 ms
Scaling Guidance
Understand when to scale horizontally versus dialing back concurrency.
- Add workers when: utilization exceeds 85% and backlog forms faster than it drains.
- Throttle per worker: target 4,000 requests per minute or slower.
- Queue sizing: allow for at least 0 pending requests to absorb spikes.
- Backoff policy: exponential backoff starting at 15 ms keeps retries within limits.
Operational Checklist
- ✅ Log 429 responses with correlation IDs to tune buffers.
- ✅ Surface queue depth in dashboards; alert at 70% capacity.
- ✅ Stagger worker start-up to avoid synchronized bursts.
- ✅ Recalculate when API providers change limits or pricing tiers.
Need higher throughput? Ask the provider for regional limits or evaluate multi-account sharding.
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Understanding Rate Limiting and Throttling
What is Rate Limiting?
Rate limiting is a critical mechanism for controlling access to APIs and services. It prevents abuse, ensures fair usage among multiple clients, protects backend infrastructure from being overwhelmed, and helps maintain quality of service. Rate limits are typically expressed as a maximum number of requests allowed within a specific time window.
Common Rate Limiting Strategies
Fixed Window limits count requests within fixed time intervals (e.g., 0-60 seconds, 60-120 seconds). Sliding Window provides a more accurate count by tracking requests over the last N seconds at any point in time. Token Bucket algorithms add tokens at a steady rate and consume one token per request, allowing brief bursts above the average rate. Leaky Bucket processes requests at a constant rate, smoothing out bursts.
Calculating Safe Rates
Never operate at exactly 100% of the stated rate limit. Network latency, clock drift, processing delays, and system jitter can cause requests to arrive slightly faster or slower than expected. A safety buffer (typically 15-25%) ensures you stay comfortably below the limit. The buffer also provides headroom for traffic spikes and accommodates multiple concurrent clients that may not be perfectly synchronized.
Distributing Load Across Workers
When a single client cannot achieve the required throughput within rate limits, distribute requests across multiple workers or clients. Each worker should respect its proportional share of the rate limit. The total rate across all workers should not exceed the safe limit. Use coordination mechanisms (like a shared token bucket or centralized rate limiter) to prevent workers from collectively exceeding limits.
Handling Bursts and Queue Management
Traffic bursts are normal in many applications. Your system should be able to absorb short-term spikes without hitting rate limits. Calculate burst capacity by determining how many extra requests can be sent during the burst window while staying within limits. If bursts create a backlog, ensure you have enough headroom to drain the queue afterward. Monitor queue depth and adjust worker counts or request rates accordingly.
Best Practices for API Consumption
Always respect rate limits to maintain good standing with API providers. Implement exponential backoff when receiving 429 (Too Many Requests) errors. Log rate limit metrics and set up alerting for high utilization. Use client-side rate limiters to prevent sending excessive requests. Consider the cost implications of different rate limit tiers. Optimize your API usage by batching requests where possible and caching responses to reduce unnecessary calls.
Frequently Asked Questions
Common questions about the Rate Limit Calculator
Rate limiting is a technique used to control the frequency of requests made to an API or service. It prevents abuse, ensures fair resource allocation, and protects backend systems from being overwhelmed. Rate limits are typically expressed as a number of requests allowed within a time window (e.g., 1000 requests per minute).
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