Monitor Webhooks with Resend
Debug webhook issues in real-time
The problem
Resend webhooks provide critical delivery and engagement signals, but they are easy to lose in generic logs. Missing or delayed webhook handling can break lifecycle automations and skew funnel analysis.
When issues appear, teams need the exact payload plus processing context to understand what failed. Searching across providers and app logs slows incident response.
At scale, small webhook blind spots can compound into major communication reliability problems.
The solution
Quicklog captures Resend webhook events in real-time, including payload details and your handler outcomes. You can track delivery, bounce, open, and complaint flows with a clear, searchable timeline.
By attaching internal context like user ID, campaign, and workflow step, debugging becomes straightforward. Teams can quickly pinpoint where message processing diverged.
This improves email reliability and keeps lifecycle workflows dependable as event volume increases.
Why monitor this?
- See webhook payloads in real-time
- Debug integration issues faster
- Track processing success and failure
Quick setup
Handle Resend webhooks:
import { Quicklog } from '@quicklogio/node'
const quicklog = new Quicklog({ apiKey: process.env.QUICKLOG_API_KEY! })
// Handle Resend webhooks
app.post('/webhooks/resend', async (req, res) => {
const payload = req.body
// Log the webhook event
await quicklog.track({
channel: 'webhooks',
event: 'resend.' + (payload.type || 'event'),
description: 'Resend webhook received',
metadata: {
provider: 'resend',
eventType: payload.type,
payload
}
})
// Process the webhook...
await processWebhook(payload)
res.json({ received: true })
})Monitor Webhooks as an operational analytics workflow
This guide is built for teams that need actionable saas analytics, not just passive reports. By instrumenting monitor webhooks in Resend, you create a reliable signal that product, growth, and support can use in real time.
In Quicklog, these events become part of a shared timeline with user context, channel grouping, and trend visibility. That makes it easier to connect day-to-day operations with larger product analytics saas goals like activation quality, retention improvement, and faster troubleshooting.
If you are evaluating saas analytics tools, this use case is a strong baseline because it combines technical implementation with clear business outcomes. It also supports adjacent workflows such as analytical crm and webhook event monitoring without requiring a separate analytics stack.
Ready to monitor webhooks?
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