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02/09/2026 3:57 pm
TL;DR: A five-minute, 5,000-connection burst test showed a gateway held 0.83-second p99 response times and 14,331 sustained requests per second, according to Highflame, while interpreted gateways fell into multi-second latency and request loss. For practitioners, the finding is that peak concurrency, not average throughput, determines whether inline policy inspection stays usable on the hot path.
NHIMG editorial — based on content published by Highflame: AI gateway load testing shows concurrency, not average load, is decisive
Questions worth separating out
Q: How should security teams govern AI gateways in production environments?
A: Security teams should govern AI gateways like shared control planes, not convenience proxies.
Q: Why do AI gateways become bottlenecks during peak developer activity?
A: Because the workload is spiky, not smooth.
Q: What signs show that inline AI policy checks are too slow to keep?
A: Watch for rising p99 latency, retry behaviour, abandoned sessions, and sudden drops in completed requests when concurrency increases.
Practitioner guidance
- Benchmark peak concurrency, not average throughput Run sustained tests that hold thousands of concurrent requests open while measuring p99 latency, error rate, and queue growth on the gateway itself.
- Validate inline policy overhead on the hot path Measure the added cost of request inspection for LLM and MCP calls, then confirm that the control remains fast enough that developers will not bypass it.
- Size for synchronized workflow bursts Model morning logins, CI fan-out, and agent workflows as a single burst pattern, then test the gateway against that combined load rather than against isolated averages.
What's in the full article
Highflame's full analysis covers the operational detail this post intentionally leaves for the source:
- Per-gateway benchmark tables with sustained throughput, p99 drift, memory use, and failed-request counts across the four tested systems
- The two-host AWS test setup and how the load generator, backend mock, and five-minute steady-state runs were arranged
- The difference between burst ceiling behaviour and held-open connection response times under the morning-rush scenario
- Highflame's own explanation of why compiled concurrency models behave differently from interpreted gateway runtimes
👉 Read Highflame's benchmark of AI gateway performance under burst concurrency →
AI gateway concurrency under burst load: are your controls keeping up?
Explore further
02/09/2026 3:58 pm
AI gateway performance is now an identity governance issue, not just an infrastructure benchmark. When gateways sit in front of LLM and MCP traffic, they become part of the authorization path for human users, service accounts, and AI agents. A slow gateway invites bypasses, shadow pathways, and reduced inspection coverage. That means gateway design must be evaluated as part of IAM and NHI governance, not as a separate performance concern.
A question worth separating out:
Q: Should organisations prioritise gateway performance or deeper inspection first?
A: They should design both together, because a control that is too slow will not stay enabled. A fast gateway with weak inspection is also insufficient, but performance is the prerequisite that keeps governance embedded in the workflow. The right order is usable policy enforcement first, then deeper inspection depth.
👉 Read our full editorial: AI gateway load testing shows concurrency, not average load, is decisive
