⚡ API Rate Limits

HTTP/1.1 200 OK
X-RateLimit-Limit: 10000
X-RateLimit-Remaining: 9987
X-RateLimit-Reset: 1635724800
X-RateLimit-Burst: 500
X-RateLimit-Burst-Remaining: 495
X-RateLimit-Retry-After: 3600
Content-Type: application/json

Header Descriptions

Header	Description
`X-RateLimit-Limit`	Maximum requests allowed per hour
`X-RateLimit-Remaining`	Requests remaining in current window
`X-RateLimit-Reset`	Unix timestamp when rate limit resets
`X-RateLimit-Burst`	Maximum burst requests per minute
`X-RateLimit-Burst-Remaining`	Burst requests remaining
`X-RateLimit-Retry-After`	Seconds to wait before next request

⚠️ Rate Limit Exceeded Response

When rate limits are exceeded, you'll receive a 429 Too Many Requests response:

{
  "error": {
    "code": "RATE_LIMIT_EXCEEDED",
    "message": "Rate limit exceeded. Please wait before making more requests.",
    "details": {
      "limit": 10000,
      "remaining": 0,
      "reset_time": "2025-01-15T14:00:00Z",
      "retry_after": 3600,
      "current_usage": 10000
    },
    "request_id": "req_rate_limit_123"
  }
}

🎛️ Service-Specific Limits

Critical Operations

Some endpoints have stricter limits due to resource intensity:

Service Category	Specific Limits
Billing Operations	100 requests/hour
Service Provisioning	50 requests/hour
Large Data Exports	10 requests/hour
Account Management	200 requests/hour

Read vs Write Operations

Operation Type	Rate Multiplier
GET (Read)	1x standard rate
POST (Create)	2x rate consumption
PUT (Update)	2x rate consumption
DELETE	3x rate consumption

🚀 Rate Limit Optimization

Best Practices

1. Implement Exponential Backoff

import time
import random

def api_call_with_backoff(api_function, max_retries=5):
    for attempt in range(max_retries):
        try:
            response = api_function()
            if response.status_code == 429:
                # Get retry-after header
                retry_after = int(response.headers.get('X-RateLimit-Retry-After', 60))
                # Add jitter to prevent thundering herd
                jitter = random.uniform(0.5, 1.5)
                sleep_time = (2 ** attempt) * jitter
                time.sleep(min(sleep_time, retry_after))
                continue
            return response
        except Exception as e:
            if attempt == max_retries - 1:
                raise e

2. Monitor Rate Limit Headers

def check_rate_limits(response):
    remaining = int(response.headers.get('X-RateLimit-Remaining', 0))
    reset_time = int(response.headers.get('X-RateLimit-Reset', 0))
    
    if remaining < 100:  # Less than 100 requests remaining
        current_time = time.time()
        sleep_time = reset_time - current_time
        if sleep_time > 0:
            print(f"Rate limit low. Sleeping for {sleep_time} seconds.")
            time.sleep(sleep_time)

3. Batch Operations

# Instead of multiple single requests
for item in items:
    api.create_item(item)

# Use batch operations
api.create_items_batch(items)

4. Use Webhooks for Real-time Updates

Instead of polling for changes, use webhooks to receive notifications:

# Avoid frequent polling
while True:
    status = api.get_service_status()
    time.sleep(30)  # Wastes rate limits

# Use webhooks instead
@webhook_handler('/service-status-update')
def handle_status_update(data):
    # Process status update
    pass

Caching Strategies

1. Response Caching

from functools import lru_cache
import time

@lru_cache(maxsize=100)
def get_account_info(account_id, cache_timestamp):
    return api.get_account(account_id)

# Use with 5-minute cache
cache_key = int(time.time() // 300)  # 5-minute buckets
account = get_account_info("acc_123", cache_key)

2. ETag Support

def get_with_etag(endpoint, etag=None):
    headers = {}
    if etag:
        headers['If-None-Match'] = etag
    
    response = api.get(endpoint, headers=headers)
    
    if response.status_code == 304:  # Not Modified
        return cached_data  # Use cached version
    
    return response.json()

📈 Rate Limit Monitoring

Real-time Monitoring Dashboard

Access your rate limit usage at: https://dashboard.solveforce.com/api/rate-limits

Monitoring Metrics

Current Usage: Real-time request consumption
Usage Trends: Historical usage patterns
Peak Times: Identify high-usage periods
Limit Approaches: Alerts when approaching limits

API Monitoring Endpoint

GET /api/v1/monitoring/rate-limits

Response:

{
  "current_usage": {
    "requests_this_hour": 2450,
    "hourly_limit": 10000,
    "burst_used": 12,
    "burst_limit": 500
  },
  "usage_history": [
    {
      "hour": "2025-01-15T13:00:00Z",
      "requests": 2450,
      "percentage": 24.5
    }
  ],
  "projected_usage": {
    "end_of_hour": 3200,
    "risk_level": "low"
  }
}

🎛️ Dynamic Rate Limiting

Intelligent Scaling

SolveForce implements dynamic rate limiting that:

Adapts to Usage Patterns: Higher limits during your peak hours
Rewards Good Behavior: Increased limits for well-behaved applications
Prevents Abuse: Automatic detection and mitigation of abuse patterns
Seasonal Adjustments: Rate limits adjust for business cycles

Request Priority System

Different request types have different priorities:

Priority Level	Description	Queue Position
Critical	Service outages, security issues	Front of queue
High	Billing, account management	High priority
Normal	Standard API operations	Standard queue
Low	Bulk operations, reports	Background processing

🛠️ Tools and SDKs

Official SDKs with Rate Limit Handling

Python SDK

from solveforce import SolveForceAPI

client = SolveForceAPI(
    api_key="your_key",
    auto_retry=True,
    max_retries=3,
    respect_rate_limits=True
)

# Automatic rate limit handling
response = client.accounts.list()

JavaScript SDK

const SolveForce = require('@solveforce/api');

const client = new SolveForce({
  apiKey: 'your_key',
  autoRetry: true,
  respectRateLimits: true,
  retryDelay: 'exponential'
});

Rate Limit Testing Tools

CLI Tool

# Install rate limit tester
npm install -g @solveforce/rate-limit-tester

# Test your rate limits
sf-rate-test --endpoint "/api/v1/accounts" --concurrency 10

🚨 Rate Limit Violations

Violation Types

Violation	Description	Consequence
Soft Limit	Exceeded hourly rate	Temporary throttling
Hard Limit	Excessive burst requests	5-minute suspension
Abuse Pattern	Consistent violations	Account review

Appeal Process

If you believe your account was incorrectly limited:

Contact Support: api-support@solveforce.com
Provide Details: Request IDs, timestamps, usage patterns
Review Timeline: 24-48 hours for resolution
Account Restoration: Automatic once resolved

💡 Rate Limit Increase Requests

Temporary Increases

For special events or launches:

Request Window: 72 hours advance notice
Duration: Up to 30 days
Approval: Automatic for existing customers
Cost: No additional charges for reasonable increases

Permanent Increases

For growing applications:

Upgrade Plans: Automatic with plan upgrades
Custom Limits: Available for enterprise customers
Volume Discounts: Reduced per-request costs at scale
SLA Guarantees: Enhanced SLAs with higher tiers

📞 Support and Resources

Getting Help

Documentation: Complete rate limit guide at docs.solveforce.com
Support Email: api-support@solveforce.com
Phone Support: (888) 765-8301 ext. API
Community Forum: community.solveforce.com
Status Page: status.solveforce.com

Additional Resources

Rate Limit Calculator: Calculate optimal limits for your use case
Best Practices Guide: Comprehensive optimization strategies
SDK Documentation: Language-specific implementation guides
Monitoring Tools: Real-time rate limit monitoring solutions

Need higher rate limits or custom rate limiting solutions? Contact our API team at (888) 765-8301 to discuss your requirements.

Optimize your API usage with SolveForce's intelligent rate limiting system.

SOLVEFORCE.COM Documentation