HookWatch 记录了 1,095 月访问量,月度环比增长为 +797.5%,定价为免费增值,免费试用,免费。Openlayer 记录了 48,415 月访问量,增长率为 -6.4%,定价为免费增值,定价请咨询。

HookWatch is a webhook debugging, monitoring, and replay service for developers. It sits in front of your endpoints, captures every delivery with its request, response, and attempt history, groups repeated failures into incidents, and lets you replay the exact captured payload once your handler is fixed.
| 维度 / 指标 | ![]() | |
|---|---|---|
| 官方域名 | hookwatch.dev | openlayer.com |
| 定价模式 | 免费增值,免费试用,免费 | 免费增值,定价请咨询 |
| 月访问量 | 1095 (1,095) | 4.84万 (48,415) |
| 月度环比流量变化 | +973 (+797.5%) | -3303 (-6.4%) |
| 主要市场与份额 | 🇫🇷 法国 (100%) | 🇺🇸 美国 (44.1%) |
| 直接访问 / 月 | 403 | 2.59万 |
| 用户评分 | 4.2 | 4.4 |
| 支持的平台 | 网站 | 网站 |

HookWatch is a webhook debugging, monitoring, and replay service for developers. It sits in front of your endpoints, captures every delivery with its request, response, and attempt history, groups repeated failures into incidents, and lets you replay the exact captured payload once your handler is fixed.
Each endpoint gets a HookWatch URL that receives and forwards webhooks, recording status, provider, response code, latency, and attempt count for every delivery.
Re-send an exact captured payload after a fix, with manual replay and retry policies instead of recreating the event by hand.
Failed deliveries are categorized by reason — signature mismatch, timeout, 5xx, rate limit — so you know what broke without grepping logs.
Recurring failures group into a single incident routed to Slack or a webhook, so a flaky endpoint shows up as one problem.
Openlayer is a platform that tests AI systems before release, monitors them in production, and enforces policy and compliance requirements across every model and agent your company runs.
Dozens of pre-built evaluations cover quality, safety, security, and performance, with LLM-as-a-judge scorers, session-level metrics, and support for writing your own custom tests against your own data.
Import a repository and run evaluation suites automatically on every change, benchmark each iteration, and block releases when a metric regresses beyond the threshold you define.
Trace every request through multi-step agent workflows, including tool calls and retriever steps, with token counts, latency, cost per request, alerting integrations, and subpopulation analysis.
Register each AI system with an owner, purpose, data sensitivity, and risk tier, score inherent risk across multiple dimensions, and move systems through staged approval gates before they reach production.

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