Pipeline Performance Alerts

ELEMENTARY CLOUD

Elementary Cloud automatically monitors the execution duration of your dbt models, seeds, and snapshots — detecting unexpected slowdowns before they affect your data consumers.

The pipeline_task_performance monitor runs after each dbt job execution and compares the observed duration against a learned baseline or a fixed SLA threshold.

Monitoring modes

Anomaly detection (default)

The default mode uses a z-score seasonal model to learn normal execution duration for each dbt node. No configuration is required — Elementary automatically builds a baseline from your pipeline history.

The model accounts for time-of-day and day-of-week seasonality. For example, a model that normally runs longer on Monday morning will not be flagged during that window.

Static SLA

Static SLA mode lets you define a fixed duration threshold. The monitor fails whenever the observed execution time exceeds that threshold, regardless of historical behavior.

Use static SLA when you have a contractual or operational hard limit (e.g., “this model must complete within 10 minutes”).

Creating a monitor

Add Test wizard

The Add Test wizard supports models only. To add a pipeline_task_performance monitor for seeds or snapshots, use the API.

1. Open the model in Elementary Cloud.
2. Click Add Test → select Pipeline Task Performance.
3. Choose the mode: Anomaly detection or Static SLA.
4. Configure parameters (see Config reference below).
5. Save.

API

POST /{env_id}/tests

{
  "node_id": "<dbt_node_id>",
  "test_type": "pipeline_task_performance",
  "params": {
    "mode": "anomaly",
    "sensitivity": "medium"
  }
}

For static SLA:

{
  "node_id": "<dbt_node_id>",
  "test_type": "pipeline_task_performance",
  "params": {
    "mode": "static",
    "fixed_threshold": 600
  }
}

Config reference

Anomaly detection mode

Parameter	Description	Default
mode	"anomaly"	"anomaly"
sensitivity	Detection sensitivity: "low", "medium", "high"	"medium"
training_period	Number of days used to build the baseline	14
anomaly_direction	"spike" (duration longer than expected), "drop", or "both"	"spike"
excluded_time_ranges	List of time ranges to exclude from training and detection	[]

Static SLA mode

Parameter	Description	Default
mode	"static"	—
fixed_threshold	Maximum allowed execution duration in seconds	Required

Alerts and incidents

Failures from pipeline_task_performance raise alerts in the pipeline_performance alert category.

Alerts are routed through alert rules and delivered to all configured integrations:

• Slack
• Microsoft Teams
• PagerDuty
• OpsGenie
• Email

Incidents are created and managed through the standard incidents workflow.

Activating alerts

By default, pipeline_task_performance alerts are not active. To enable them:

1. Go to Setup → Alert Rules.
2. Edit the default rule (or create a new one) and add Pipeline performance to the alert categories.

Related

• Pipeline task performance monitor — full monitor reference under Automated Monitors
• Performance monitoring dashboard — view execution trends in the UI
• Manual performance monitoring (dbt-package) — manual dbt-test alternative using model_run_results