Alerts with Fiddler Client

The Fiddler API client provides programmatic control for alert management alongside the Fiddler UI, enabling these key workflows:

• Create alert rules

• Remove alert rules

• Retrieve all configured alert rules

• Access triggered alert history

📘 Note: For UI-based alert configuration, refer to the alert setup guide.

Creating Alert Rules

The Fiddler client can be used to create a variety of alert rule types, including Data Drift, Performance, Data Integrity, Service Metrics, and Custom Metrics.

The Fiddler client supports multiple alert rule types, including:

• Data Drift

• Performance

• Data Integrity

• Service Metrics

• Custom Metrics

Understanding Alert Thresholds

When configuring thresholds:

• Absolute thresholds (CompareTo.RAW_VALUE): For percentage-based metrics like null_violation_percentage, express values as percentages (e.g., 10 for 10%).

• Relative thresholds (CompareTo.TIME_PERIOD): Express values as decimal fractions regardless of metric type (e.g., 0.1 for 10%)

Example Implementations

Example 1: Data Integrity Alert with Static Threshold

This example creates an alert that monitors for missing values in the age column. It triggers notifications when null values exceed 5% (warning) or 10% (critical) of daily values.

MODEL_ID = '299c7b40-b87c-4dad-bb94-251dbcd3cbdf'

alert_rule = AlertRule(
    name='Bank Churn Missing Values Static Percent',
    model_id=MODEL_ID,
    metric_id='null_violation_percentage',
    priority=Priority.HIGH,
    compare_to=CompareTo.RAW_VALUE,
    condition=AlertCondition.GREATER,
    bin_size=BinSize.DAY,
    critical_threshold=10,
    warning_threshold=5,
    columns=['age'],
).create()

notifications = alert_rule.set_notification_config(
    emails=['[email protected]', '[email protected]'],
)

Example 2: Data Integrity Alert with Historical Comparison

This example creates an alert that compares today's missing values against yesterday's values. It triggers when null values increase by 5% (warning) or 10% (critical) compared to the previous day.

MODEL_ID = '299c7b40-b87c-4dad-bb94-251dbcd3cbdf'

alert_rule = AlertRule(
    name='Bank Churn Missing Values Rolling Historical Percent',
    model_id=MODEL_ID,
    metric_id='null_violation_percentage',
    priority=Priority.HIGH,
    compare_to=CompareTo.TIME_PERIOD,
    compare_bin_delta=1,
    condition=AlertCondition.GREATER,
    bin_size=BinSize.DAY,
    critical_threshold=0.1,
    warning_threshold=0.05,
    columns=['age'],
).create()

notifications = alert_rule.set_notification_config(
    emails=['[email protected]', '[email protected]'],
)

Example 3: Performance Alert with Time-Based Comparison

This example creates a performance alert that monitors for precision changes. It compares today's precision with yesterday's values and triggers when precision decreases by 5% (warning) or 10% (critical).

MODEL_ID = '4531bfd9-2ca2-4a7b-bb5a-136c8da09ca2'

alert_rule = AlertRule(
    name='Bank Churn Precision Relative',
    model_id=MODEL_ID,
    metric_id='precision',
    priority=Priority.HIGH,
    compare_to=CompareTo.TIME_PERIOD,
    compare_bin_delta=1,
    condition=AlertCondition.LESSER,
    bin_size=BinSize.DAY,
    critical_threshold=0.1,
    warning_threshold=0.05,
).create()

notifications = alert_rule.set_notification_config(
    emails=['[email protected]', '[email protected]'],
)

🚧 Please note, the possible values for compare_bin_delta vs bin_size are:

Bin Size	Allowed Compare bin delta
BinSize.Hour	[1, 24, 24 * 7, 24 * 30, 24 * 90]
BinSize.Day	[1, 7, 30, 90]
BinSize.Week	[1]
BinSize.Month	[1]

Retrieving Alert Rules

The AlertRule.list() method retrieves alert rules that match your specified criteria. This method returns a Python iterator of matching rules.

MODEL_ID = '4531bfd9-2ca2-4a7b-bb5a-136c8da09ca2'

alert_rules = AlertRule.list(
    model_id=MODEL_ID,  # Optional parameter
    metric_id='jsd',  # Optional parameter
    columns=['age'],  # Optional parameter
    ordering=[
        'critical_threshold'
    ],  # Add **-** prefix for descending sort ['-critical_threshold']
)

Tip: All filter parameters are optional. Omit them to retrieve all alert rules.

Removing Alert Rules

To delete an alert rule, call the delete() method on an AlertRule object. You can retrieve the rule object using either:

• The list() method with filters

• The get() method with the rule's unique identifier

# Delete from a list of alerts
MODEL_ID = '4531bfd9-2ca2-4a7b-bb5a-136c8da09ca2'
alert_rules = AlertRule.list(model_id=MODEL_ID)

for alert_rule in alert_rules:
    if alert_rule.name == 'Bank Churn Precision Relative':
        alert_rule.delete()
        break

# Delete using the alert rule's unique identifier
ALERT_RULE_ID = '6da9c3c0-a9fa-4ab6-8b64-8d07b0736e77'
rule = AlertRule.get(id_=ALERT_RULE_ID)
rule.delete()

Tip: Find the alert rule ID in the Alert Rule tab of your Fiddler Alerts page.

Accessing Triggered Alerts

Use the AlertRecord.list() method to retrieve alerts triggered by a specific rule:

from datetime import datetime

triggered_alerts = AlertRecord.list(
    alert_rule_id=ALERT_RULE_ID,     # Required: ID of the alert rule
    start_time=datetime(2024, 9, 1), # Optional: Start of time range
    end_time=datetime(2024, 9, 24),  # Optional: End of time range
    ordering=['alert_time_bucket'],  # Optional: Sort order
                                     # Use '-alert_time_bucket' for descending
)

Configuring Notifications

After creating an alert rule, configure how notifications are sent when the rule triggers. Fiddler supports these notification channels:

• Email

• PagerDuty

• Slack webhooks

• Custom webhooks

You can specify multiple notification types, and each type can have multiple recipients.

ALERT_RULE_ID = '72e8835b-cde2-4dd2-a435-a35d4b51196b'
rule = AlertRule.get(id_=ALERT_RULE_ID)

rule.set_notification_config(
    emails=['[email protected]', '[email protected]'],
    webhooks=['8b403d99-530a-4c5a-a519-89688d65ddc1'],  # Webhook UUID
    pagerduty_services=[
        'pagerduty_service_1',
        'pagerduty_service_2',
    ],  # PagerDuty service names
    pagerduty_severity='critical',  # Only applies to PagerDuty
)

Important: PagerDuty, Slack webhooks, and custom webhooks must be pre-configured by your Fiddler administrator.