Cross-stack root cause analysis

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Reads from
Airflow dbt Snowflake S3 CloudWatch CloudTrail Databricks Azure
// how it works
01
Failure detected
A webhook fires the moment a task fails — from Airflow, dbt Cloud, or any tool in your stack. No polling. No manual trigger.
passive trigger
02
Signals collected in parallel
Six collectors fan out simultaneously — task logs, S3 paths, CloudWatch errors, CloudTrail API events, dbt run results, Snowflake query history. Every signal gathered before a human has context-switched.
parallel fan-out
03
Cross-stack reasoning
All signals are passed to an LLM with your error signature library and similar past incidents. The model reasons across the full picture — not just the failing task.
LLM-powered RCA
04
Structured diagnosis in Slack
Root cause, chain of failure, blast radius, next steps, confidence score. Delivered to your incident channel — with feedback buttons that make the next RCA sharper.
slack delivery
// signal sources
Airflow
Task logs, run state, upstream cascade
S3
Missing files, staleness, partition gaps
CloudWatch
Lambda errors, throttling, log anomalies
CloudTrail
Permission changes, deletes, role modifications
dbt
Model failures, test results, schema drift
Snowflake
Failed queries, warehouse state, DDL changes
Databricks
Job runs, cluster state, notebook errors
coming soon
Azure
Data Factory, Synapse, Monitor logs
coming soon
// see it in action

Early access

Kodient is in private beta. If you run a data platform team and want to stop debugging pipelines by hand, get in touch.