--- title: "Heartbeat Monitoring for Webhooks & ETL Pipelines | FourSight" description: "Track recurring webhook deliveries and ETL pipeline runs so silent data-flow failures never go unnoticed." lang: en json-ld: | [ { "@context": "https://schema.org", "@type": "Article", "headline": "Heartbeat Monitoring for Webhooks & ETL Pipelines", "description": "Track recurring webhook deliveries and ETL pipeline runs so silent data-flow failures never go unnoticed.", "author": { "@type": "Organization", "name": "FourSight" }, "publisher": { "@type": "Organization", "name": "FourSight" }, "url": "https://foursight.cloud/guides/heartbeat-monitoring-webhooks-etl", "mainEntityOfPage": "https://foursight.cloud/guides/heartbeat-monitoring-webhooks-etl", "datePublished": "2025-10-29", "dateModified": "2026-03-18", "wordCount": 1400 }, { "@context": "https://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": 1, "name": "Home", "item": "https://foursight.cloud" }, { "@type": "ListItem", "position": 2, "name": "Guides", "item": "https://foursight.cloud/guides" }, { "@type": "ListItem", "position": 3, "name": "Heartbeat Monitoring for Webhooks & ETL Pipelines", "item": "https://foursight.cloud/guides/heartbeat-monitoring-webhooks-etl" } ] } ] --- [FourSight ](/) [Features](/#features)[Pricing](/pricing)[Guides](/guides)[Glossary](/glossary)[FAQ](/faq) [Login](/auth)[Start free](/auth?signup=true) [Start free](/auth?signup=true) [All Guides](/guides) Reliability & Infrastructure # Heartbeat Monitoring for Webhooks & ETL Pipelines Track recurring webhook deliveries and ETL pipeline runs so silent data-flow failures never go unnoticed. 7 min read Guide Published Oct 29, 2025Updated Mar 18, 2026 ## When Data Stops Flowing Silently Webhooks from third-party services (Stripe, Shopify, GitHub) and ETL pipelines (Airbyte, dbt, custom scripts) are the arteries of modern SaaS applications. Unlike user-facing pages, these data flows fail silently. A [Stripe webhook](/glossary/stripe-webhook "Glossary: Stripe webhook") endpoint that returns 200 but stops being called, or a nightly ETL job that quietly crashes, can go undetected for days — causing stale dashboards, missed invoices, and broken analytics. ## Heartbeat Monitoring for Webhook Receivers If your application expects to receive webhooks at a predictable frequency, heartbeat monitoring can verify the flow continues. Add a ping to FourSight inside your webhook handler so that each successful processing cycle confirms the pipeline is alive. ### High-Frequency Webhooks For webhooks that fire many times per hour (e.g. order events), use a fixed interval like 5 or 10 minutes. Your handler pings FourSight on each successful batch or on a periodic timer within the handler process. ### Daily or Weekly Webhooks For less frequent events (e.g. a weekly subscription renewal batch from a payment provider), use cron-expression mode to match the expected schedule with a generous grace period. ``` // Inside your webhook handler (Node.js / Express) app.post("/webhooks/stripe", async (req, res) => { try { await processStripeEvent(req.body); // Confirm the pipeline is alive await fetch("https://ping.foursight.cloud/hb/"); res.sendStatus(200); } catch (err) { console.error("Webhook processing failed:", err); res.sendStatus(500); } }); ``` ### Monitoring a Commercial SaaS? FourSight's free plan includes 10 commercial-safe monitors with multi-region validation — free forever, no card. [Start Monitoring Free](/auth?signup=true) ## Monitoring ETL & Data Pipelines ETL jobs — whether built with dbt, Airflow, custom Python, or simple SQL scripts — should ping FourSight after a successful run. This catches not just crashes but also silent hangs where the process is stuck waiting on a locked table or an unresponsive API. ### dbt & Airflow Add a curl ping as the final task in your DAG or a post-hook in dbt. The ping only fires if all upstream tasks succeed. ### Database-to-Warehouse Sync After your nightly sync completes, ping FourSight. Pair this with a row-count validation step so you catch both 'didn't run' and 'ran but imported zero rows' failures. ``` # At the end of your ETL script import requests def run_etl(): extract() transform() load() # Signal success requests.get("https://ping.foursight.cloud/hb/", timeout=10) run_etl() ``` ## Designing Grace Periods for Data Pipelines Data pipelines often have variable execution times. A nightly warehouse refresh might take 12 minutes on Monday and 45 minutes on month-end. Set your grace period to cover the worst-case runtime, and use the miss threshold to require 2 consecutive misses before alerting — this prevents false alarms during occasional slow runs while still catching genuine failures promptly. ## Combining Heartbeats with HTTP Monitors For critical data flows, use both: an [HTTP monitor](/glossary/http-monitor "Glossary: HTTP monitor") on your webhook endpoint to verify it's reachable, and a [heartbeat monitor](/glossary/heartbeat-monitor "Glossary: heartbeat monitor") to verify it's actually being called and processing successfully. The HTTP check catches infrastructure failures; the heartbeat catches logical failures where the endpoint is up but no events are arriving. [Start Monitoring Your Pipelines →](/auth?signup=true) #### Related Guides [What Is Uptime Monitoring? 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