Messaging Throughput and Rate Limit Headroom Calculator
Most messaging integrations are sized by guesswork until a shift-change alert or a month-end notice floods the queue. This calculator turns daily volume, peak behavior and processing time into a peak rate, headroom under your rate limit and a worker count. Adjust the inputs to match your own numbers.
Your numbers
Outbound plus inbound events you must process.
How much busier the busiest minute is than the average.
Use your account's current documented or observed limit.
Includes ERP lookup and send call.
For example a shift-change alert to all staff.
Your results
Rate limits differ by platform, account tier and time, and are subject to change. Enter the limit from your own account documentation.
Peak rate vs peak-to-average ratio
Sweeps Peak to average ratio from 1 to 20, holding your other inputs fixed.
Capacity review for ERP messaging flows
Share your volumes and limits and receive a short sizing and queueing recommendation.
Optional. The tool and every export work without this. No spam.
How to use the calculator
Enter your daily message count and the hours in which messages are actually sent. The peak ratio captures burstiness: a flat system is near 1, while alerts tied to shift starts can exceed 10. Enter the rate limit that applies to your account, the average processing time per message including ERP lookups, and how many calls one worker handles at once. Retry overhead adds extra traffic for transient failures. The burst size models a one-off blast.
The method
Average rate is daily volume divided by active seconds. Peak rate multiplies that by the peak ratio and the retry factor. Headroom is the gap between the limit and the peak, as a percentage of the limit. A worker handles concurrency divided by processing time messages per second, and the number of workers is the peak rate divided by that, rounded up. Burst drain time divides the burst by the lesser of the limit and total worker capacity.
- Average = daily / (hours x 3600)
- Peak = average x ratio x (1 + retry)
- Headroom = (limit - peak) / limit
- Workers = ceil(peak / per-worker rate)
Reading the result
Under about 30 percent headroom, a modest change in volume can push you past the limit, so add queueing with rate-aware sending and backoff. If workers exceed what your ERP API tolerates, the bottleneck is the ERP, not the channel, and you should cache lookups or batch them. Check the burst drain time against your tolerance: a three thousand message alert that takes ten minutes to drain may be unacceptable for a safety notice. Consider sending critical alerts first.
Frequently Asked Questions
What peak ratio should I use?
Measure it from logs if you can: busiest minute divided by the average minute. If unknown, 3 to 5 is a cautious starting point for business hours traffic, higher for shift-based alerts.
Where do I find my rate limit?
In your platform's documentation and your account or tenant settings. Limits vary by tier and can change, so confirm them before sizing and monitor for throttling responses.
How is burst drain time calculated?
The burst size is divided by the lower of your rate limit and your total worker capacity, then converted to minutes. It ignores retries and assumes workers start empty.
Does it model per-user limits?
No. It assumes a single aggregate limit. Some platforms also limit per recipient or per conversation, which you should test separately.
If your ERP API is the bottleneck for messaging or agent workloads, Netray can help design caching, queueing and prioritization on your own infrastructure.
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