How API Rate Limits Work for B2B SaaS Integrations

The text discusses the challenges and intricacies of managing rate limits in B2B SaaS integrations, particularly when scaling. It highlights a case where a Salesforce API integration faced issues due to rate limiting, which went unnoticed because the code ignored 429 (Too Many Requests) errors. The text explains that rate limits are crucial for protecting infrastructure and ensuring fair usage, yet they are often overlooked during initial integration design since sandbox environments typically have more lenient limits. As integrations scale, encountering rate limits becomes inevitable, often leading to customer complaints when data is delayed or missing. The text elaborates on different types of rate limit patterns, such as fixed window, sliding window, token bucket, leaky bucket, concurrent request limits, and per-endpoint limits, each requiring specific handling strategies. It emphasizes the importance of implementing reactive patterns like exponential backoff with jitter and circuit breakers to manage rate limits effectively. The reactive strategies help mitigate the impact of rate limits, but the text also points out that proactive approaches will be necessary for larger-scale operations, which will be covered in a subsequent discussion.