Dagster Alerting and Automation
Describes how to route Dagster quality failures into alerts, hooks, and automated remediation while keeping SLA semantics stable.
What this file does
Describes how to route Dagster quality failures into alerts, hooks, and automated remediation while keeping SLA semantics stable.
When to use it
- You need SLA-aware quality operations in Dagster
- Failures should trigger notifications or follow-up jobs
- You want to standardize response to warning vs failure severity
- You are moving from manual reruns to automation-driven response
Assumes this stack
title: Dagster Alerting and Automation
Dagster Alerting and Automation
Dagster can surface quality information through hooks, schedules, automation policies, and external operators. Truthound's Dagster package focuses on keeping the payload and SLA semantics stable while letting Dagster own the automation layer.
Who This Is For
- platform teams routing quality failures into operational alerting
- operators deciding how much automation should happen in Dagster itself
- teams moving from manual reruns to automation-driven response
When To Use It
Use this page when:
- you need SLA-aware quality operations in Dagster
- failures should trigger notifications or follow-up jobs
- you want to standardize response to warning vs failure severity
Prerequisites
SLAResourceor another quality result evaluation path- a Dagster deployment with jobs, schedules, or automation rules
- a defined notification or escalation policy
Minimal Quickstart
Use the SLA surface as the policy boundary:
from truthound_dagster import SLAConfig, SLAResource
sla = SLAResource(
default_config=SLAConfig(max_failure_rate=0.05).to_dict()
)
For richer environments, pair the SLA resource with metrics or logging hooks:
from truthound_dagster import CompositeSLAHook, LoggingSLAHook, MetricsSLAHook
hooks = CompositeSLAHook(hooks=[LoggingSLAHook(), MetricsSLAHook()])
Production Pattern
Recommended automation split:
| Concern | Owner |
|---|---|
| validation execution | Truthound resource/op/asset helper |
| run orchestration | Dagster job or asset automation |
| alert routing | SLA hooks plus operator tooling |
Checklist:
- define whether warnings should notify or only log
- route high-noise checks to metrics before paging
- keep remediation jobs separate from primary validation jobs
Failure Modes and Troubleshooting
| Symptom | Likely Cause | What To Do |
|---|---|---|
| too many alerts | low-value checks are treated as incidents | downgrade to warn or metrics-only |
| no operator context in alerts | automation reads only check pass/fail | include dataset and partition metadata |
| remediation loops | automated rerun policy restarts unstable quality jobs | cap retries and preserve manual review gates |
Related Pages
What's inside
4 sections, 1 code snippet, 1 table, 1 troubleshooting table, 4 related page links
Change this for your project
- Replace
truthound_dagsterwith your own package name in all imports - Replace
SLAResource,SLAConfig, and hook classes with your own implementations
Where it goes
Keep it in your repository where the agent or team that needs it will read it.
Worth borrowing
- Separate validation execution, run orchestration, and alert routing into distinct owners
- Route high-noise checks to metrics before paging to reduce alert fatigue
- Cap retries and preserve manual review gates to prevent remediation loops
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