1 Answers
A:
Start with client-side throttling using a token bucket or leaky bucket algorithm to cap requests for example, no more than 50–100 requests per second per merchant account is a safe baseline, though Checkout.com’s exact limits depend on your plan and use case. Your integration should detect HTTP 429 Too Many Requests responses and respect the Retry-After header Checkout.com includes, pausing new requests until the cooldown period ends.
Next, add exponential backoff with jitter to your retry logic so multiple clients don’t hammer the API in sync. If you’re handling sensitive operations like refunds or capture calls, make retries idempotent by using Checkout.com’s idempotency_key header, this ensures you never double-charge a customer if a request is retried.
Implement per-tenant and per-endpoint quotas internally to prevent noisy scripts or background jobs from consuming all available bandwidth. For bulk or scheduled tasks (like batch settlements or transaction syncs), queue requests asynchronously and process them in small batches rather than firing them all at once.
Finally, monitor everything track average request rate, 429 frequency, latency, and retry success rates and set up alerts if throttling increases suddenly. If you’re scaling globally, deploy regional API clients to distribute load evenly across endpoints.
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