When Webhook Infrastructure Slows Down, Ops Fail: One Pattern Reviewers Surfaced From webhooks.io

In most software layers, slowness is a performance problem. In webhook infrastructure, slowness can be something categorically different: a correctness problem. When a managed proxy layer between your provider and your application adds enough latency, providers begin treating the connection as failed. Their retry logic fires. Their narrow retry windows close. Events that should have been delivered cleanly arrive duplicated, arrive out of order, or do not arrive at all.

This is the pattern that makes webhook infrastructure performance worth evaluating before you commit to a managed tool, not after.

webhooks.io addresses a genuine engineering problem. Building a webhook proxy layer natively requires maintaining a stable public URL, capturing raw HTTP payloads, implementing retry logic, and providing some form of inspection and history. That is real infrastructure work. A managed service that absorbs it is a legitimate alternative to building it yourself. The question this post addresses is how to evaluate the performance dimension of any managed webhook tool, using webhooks.io as a specific case study. For the full evaluation framework, see the webhook vendor evaluation checklist. See also the G2 reviews for webhooks.io and webhooks.io documentation for current product details.

What webhooks.io offers

webhooks.io is a managed webhook proxy service. Instead of routing provider webhooks — from Stripe, Shopify, GitHub, Twilio, or other sources — directly to your application endpoint, you route them through webhooks.io. The service captures the inbound payload, handles the stable URL surface, and manages delivery with retry handling.

The Developer plan documentation lists 10 requests per second throughput and seven days of retention, with per-request overages above that limit. Higher tiers extend retention periods and throughput ceilings.

This is a real reduction in the "build a proxy" engineering cost. Teams that have spent time maintaining internal webhook relay infrastructure understand the ongoing cost of doing it natively: SSL certificate management, endpoint stability across deployments, retry logic tuning, payload inspection tooling. A managed layer that handles these concerns has a credible value proposition. That value is not in question here.

The performance-correlation signal

G2 currently shows two reviews for webhooks.io. One reviewer, writing on August 29, 2024, included the observation that "when it is slow, the operations failed." A webhook proxy layer that fails operations when it experiences latency couples the proxy's performance to your application's correctness — a fundamentally different problem than mere slowness.

This deserves careful handling. It is a single data point from a single reviewer in a two-review dataset. G2 itself displays a caution on the listing noting that there are not enough reviews to provide buying insight. That context matters. This observation cannot be taken as a statistical pattern or a general characterization of the product.

What it can be taken as is a question to ask before committing. The reviewer is describing a specific failure mode: not that operations were slowed, but that they failed. The distinction is operationally significant. A webhook proxy layer that returns 200 slowly is a latency problem. A webhook proxy layer where slowness correlates with operations failing is a different class of problem — one that connects the proxy's performance to your application's correctness.

Whether this reflects an architectural property of webhooks.io's delivery model, an isolated incident the reviewer experienced, a configuration problem on the reviewer's side, or something else entirely cannot be determined from a single data point. That uncertainty is precisely why it is a question to ask — not a verdict to accept.

Why performance-correlated failures are a specific risk pattern

Understanding why this failure mode matters requires understanding how provider retry behavior interacts with proxy layer latency.

When a provider sends a webhook, it expects a 2xx response within a defined timeout window. Stripe, for example, expects a response within 30 seconds; GitHub within 10 seconds. If the response does not arrive in time, the provider marks the delivery as failed and schedules a retry. The retry schedule varies by provider: Stripe uses exponential backoff across 72 hours; GitHub retries less aggressively.

If a webhook proxy layer introduces enough latency, the provider's timeout fires before the proxy has forwarded the request and returned the provider's desired acknowledgment. From the provider's perspective, the delivery failed. The provider retries. Your application may receive the event again later, or it may not receive it at all if the retry window expires. Meanwhile, the proxy may have actually received the payload — the failure is in the connection handshake and response path, not necessarily in payload capture.

This creates a specific failure mode: events that the provider believes were not delivered that actually were captured, and events that were genuinely missed because provider retries were exhausted. That ambiguity is operationally expensive. Untangling it requires cross-referencing provider delivery logs against captured payload history, which assumes the proxy captured something to inspect.

For payment events, inventory updates, or any event where exactly-once semantics matter, the replay and forensic burden of this failure mode is significant.

How to stress-test any webhook tool before committing

Any managed webhook tool handling your production event traffic should be evaluated under load before a commitment, not after. Any provider with a 10-second timeout starts becoming a risk when proxy overhead reaches 2-3 seconds. See the webhook retry storms post for what happens when latency-induced failures accumulate into a retry cascade.

Latency under burst. Send a burst of requests above your expected peak volume and measure the p50, p95, and p99 latency of the proxy's response path — not the end-to-end roundtrip to your handler, but the latency introduced by the proxy itself. Any provider with a 10-second timeout starts becoming a risk when proxy overhead reaches 2-3 seconds.

Behavior under saturation. What happens when you exceed the plan's throughput ceiling? Does the proxy queue the excess? Return errors? Silently drop requests? The answer to this question under load is more useful than the answer in documentation.

Visibility into failures. When a delivery attempt fails — because your downstream handler returned a 5xx or timed out — what does the proxy surface? Can you see the failure reason, the response code, the timing? The quality of that failure visibility determines how quickly you can diagnose problems in production.

Support responsiveness. File a direct support inquiry asking how the proxy behaves when it experiences internal latency or resource contention. The quality and speed of the response gives you information about what support looks like during a production incident.

These are questions any webhook tool should be able to answer concretely. Vague or unavailable answers are a signal about operational transparency.

HookTunnel's capture-first design

HookTunnel's architecture separates the capture step from the forwarding step at the design level. Capture-first means the payload is in storage before forwarding begins — slow forwarding cannot result in lost evidence. The webhook-driven architecture post covers this as Principle 1. See HookTunnel pricing for the flat $19/month Pro plan with 30-day history. When a webhook arrives at a HookTunnel hook URL, the raw HTTP request — method, headers, body, timestamp — is captured and stored before any forwarding attempt is made. Capture is synchronous at the ingress point. Forwarding is a downstream operation.

This design means that slow downstream handling does not translate to lost events at the capture layer. If forwarding to your handler is slow, or fails, the original payload is already in HookTunnel's storage. It is available for inspection immediately and replayable to any target you specify — your production endpoint, a staging server, a local tunnel during development.

HookTunnel's Terms of Service do not include uptime or delivery guarantees. We are not in a position to tell you that your webhooks will always be captured or that forwarding will always succeed. For systems where provider-to-application delivery needs contractual SLA backing, a different category of tooling is appropriate.

What the capture-first model does provide is a decoupling of "did we record what the provider sent" from "did we successfully deliver it to your handler." When something goes wrong in the forwarding path, the original payload is available for forensics and replay. That decoupling is the architectural property that matters most when evaluating how a webhook tool behaves when things are not running smoothly.

On Pro at $19 per month, HookTunnel retains thirty days of request history. Free accounts retain twenty-four hours. Replay is available on Pro and sends the exact captured payload — headers and body unchanged — to any endpoint you specify at replay time.

Performance signals are research prompts

The August 2024 reviewer's observation about webhooks.io — that slowness correlated with operation failures — is a single data point from a two-review dataset. It is not a verdict. It is a question to ask.

The right response to a performance-correlation signal in any vendor review is to understand the mechanism behind it. Does the tool's architecture couple proxy latency to delivery success? What happens to captured payloads when forwarding slows? Can you inspect exactly what the proxy captured versus what your handler confirmed? How does the tool behave when its own infrastructure is under resource pressure?

Any webhook tool worth using in production has direct, specific answers to those questions. Performance signals from reviews are early warning signs, not verdicts. Test the tool under your actual load profile before forming a conclusion.