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Documentation Index

Fetch the complete documentation index at: https://docs.anomalyarmor.ai/llms.txt

Use this file to discover all available pages before exploring further.

As a data engineer, you build and maintain the pipelines that keep data flowing. AnomalyArmor helps you catch breaking changes before they impact downstream systems.
Data Engineer Journey: Connect (~5 min) → Discover (~3 min) → Monitor (~5 min) → Alert (~5 min)

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Your Key Workflows

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Detect Breaking Schema Changes

Schema drift is your biggest enemy. A column rename or type change can silently break pipelines that ran fine yesterday.
1

Connect Your Database

Start with your most critical production database. Connect now
2

Run Discovery

AnomalyArmor catalogs all tables, views, and columns. Run discovery
3

Configure Schema Alerts

Get notified of column additions, removals, type changes, and renames. Set up alerts

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Integrate with Your CI/CD

Gate deployments on data quality using the CLI: 
# Install
pip install anomalyarmor-cli

# Check freshness before running dbt
armor freshness check snowflake.prod.warehouse.orders

# Exit code 1 if stale, blocking the pipeline
Full CLI reference

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Automate with Webhooks

Trigger actions when schema changes are detected: 
from anomalyarmor import Client

client = Client()

# Get schema changes from last 24 hours
changes = client.schema.changes(
    since="24h",
    change_types=["column_removed", "type_changed"]
)

for change in changes:
    print(f"Breaking change: {change.asset_name} - {change.description}")
Python SDK guide
FeatureWhy You Need It
Schema Drift DetectionCatch column changes before they break pipelines
Freshness MonitoringKnow when upstream data is stale
Webhook AlertsIntegrate with your existing monitoring
CLIAutomate checks in CI/CD

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Common Tasks

Set Up dbt Integration

Run AnomalyArmor checks as part of dbt runs

Airflow Pre-flight Checks

Gate DAG tasks on data freshness

GitHub Actions Integration

Add data quality checks to your CI pipeline

CLI Reference

Full command documentation

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Common Questions

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How do I gate a dbt run or Airflow DAG on data freshness?

Use the armor freshness check <asset> CLI command in your pipeline. It exits non-zero when data is stale, which blocks the next step in most orchestrators. See CLI overview and Airflow integration.

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Can AnomalyArmor catch a breaking schema change before my pipeline runs?

Yes, if you schedule discovery to run before your pipelines. Point discovery at production every hour and schedule it 30-60 minutes before your main ETL windows. Breaking changes (column removed, type changed) fire alerts on the next discovery.

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How do I send schema change alerts to a webhook for automation?

Create a webhook destination, then build an alert rule scoped to the change types you care about (e.g. column_removed, type_changed). Incoming payloads include asset name, change type, and diff for your automation to act on. See Webhook destinations.

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Can I pull schema change history programmatically?

Yes, via the Python SDK: client.schema.changes(since="24h", change_types=[...]). See Python SDK guide.

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How does AnomalyArmor handle column renames?

Today a rename surfaces as a column removed plus a column added. You can correlate the pair in your webhook handler or alert rule. Automatic rename detection is on the roadmap.