Automated Confluent Consumer Lag Alerts
Every hour, WebRun opens Confluent Cloud, checks consumer group lag on every critical topic against your alert threshold, logs any spike to Airtable, and keeps the incident notes updated in Notion until it recovers.
How do I catch Kafka consumer lag on Confluent before it causes an outage?
WebRun checks Confluent Cloud consumer group lag every hour against the threshold you set per topic. When a group falls behind, it logs the topic, consumer group, and lag size to Airtable and updates the incident notes in Notion, so a slow consumer gets caught and tracked before it turns into a customer-facing outage.
- Consumer lag gets caught within the hour, not after a downstream outage
- Every spike is logged and tracked instead of living in someone's memory
- Recovered consumer groups clear themselves from the incident notes automatically
Built for data engineering teams · platform engineers · streaming data teams · site reliability engineers
What does WebRun do on every run?
The exact actions WebRun takes, in order - in plain language, so you can adjust anything.
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WebRun signs in and gets to work
Opens
confluent.cloudin a real browser with your saved login - no setup, no API keys. -
1
Confluent - check consumer group lag
confluent.io
WebRun opens Confluent to check consumer group lag. - Open Confluent Cloud and list active consumer groups for each critical topic
- Compare current lag to your alert threshold
- Note the topic, consumer group, and lag size for any breach
Done when Every critical topic's consumer lag has been checked.
-
2
Airtable - log the spike
airtable.com
WebRun opens Airtable to log the spike. - Log a row for each lag spike with the topic, consumer group, and size
- Mark it open until lag drops back under threshold
Done when Every open lag spike is logged in the tracker.
-
3
Notion - keep incident notes current
notion.so
WebRun updates Notion to keep incident notes current. - Update the incident notes page with the new spike and likely cause
- Close out notes for any spike that has already recovered
Done when The incident notes reflect every currently open lag spike.
How is each run configured?
Secure by default
Connect once, stays signed in
WebRun signs in once and keeps each session in a persistent environment, so every run picks up right where it left off.
Every action is checked against this policy before it runs.
Questions, answered
Will it restart a consumer or scale partitions on its own?
No. WebRun only detects and logs the lag spike. Restarting a consumer, adding partitions, or scaling is left to a human.
How does it decide what counts as a spike?
It compares each consumer group's current lag against the alert threshold you set per topic, so routine fluctuation doesn't trigger noise.
What happens once lag recovers?
It reads live lag figures from Confluent Cloud every run, so a group that's back under threshold gets closed out in the incident notes automatically.
Related templates
Put this on autopilot.
Turn it on in minutes - or have our team set it up for you.