We're evaluating Tenable Cloud Security for a ~50K cloud resource estate. The API rate limits are causing significant operational friction during bulk operations.
Key issues:
* The documented `X-RateLimit-Limit` header often doesn't match the actual enforced limit. We've observed throttling at 75% of the stated limit.
* The `Retry-After` header is inconsistent. We've seen it return a value in seconds, but the actual reset period was longer.
* Aggregating findings or exporting asset data for a full weekly snapshot takes 4x longer than it should due to constant 429s.
Our current workaround is suboptimal:
```scala
def callWithBackoff(op: => Response): Response = {
var backoff = 1.second
var attempts = 0
while (attempts 10K resources?
2. Has anyone gotten clarification from Tenable on whether the `X-RateLimit-Limit` is per-tenant, per-IP, or per-access-key? The docs are vague.
3. What's the actual upper bound for programmatic scanning triggers before hitting limits?
The lack of clear, predictable scaling semantics is a blocker for automation.
āgp
Data over opinions
The "per-tenant, per-IP, or per-access-key" question is a good one, because the answer is usually "all of the above, layered on top of a global pool you aren't told about." I've seen vendors throttle based on a rolling account-wide window, then apply a secondary, undocumented limit on the specific endpoint you're hammering. Your observation about the header not matching reality is classic - they'll publish a generous limit for the sales deck, then silently throttle you at a lower operational threshold to manage their own infrastructure costs.
You'll never get a straight answer on the upper bound for scanning triggers. Their official scaling semantics are always "contact sales," which translates to a costly custom contract add-on for "enterprise API capacity." Your 4x slowdown is probably the intended state for your current tier.
ā skeptical but fair
Oof, yes, this hits home. We saw something similar with their asset export API last quarter. The discrepancy between the advertised limit and actual enforcement felt like shifting goalposts.
That backoff strategy looks familiar. We ended up implementing a token bucket algorithm client-side based on the *observed* throttle rate, not the documented header. We also started batching requests by region in our orchestration layer, which helped a bit, but it's a workaround for what should be predictable behavior.
For your third question about scanning triggers, in our experience, the upper bound is tied to the underlying cloud provider's API limits on your scanning role, not just Tenable's own quota. It creates a double-layer of unpredictability. Have you tried escalating through your TAM? Sometimes a support ticket can get you the actual service quota metrics for your specific tenant.
cost first, then scale