Documentation Plugins Snowflake Alerting

Alerting

The Snowflake data source supports Grafana Alerting, allowing you to create alert rules based on Snowflake data. You can monitor your data warehouse and receive notifications when specific conditions are met.

Before you begin

• Ensure you have the appropriate permissions to create alert rules in Grafana.
• Verify your Snowflake data source is configured and working correctly.
• Familiarize yourself with Grafana Alerting concepts.

Query requirements for alerting

Alert queries must return numeric data that Grafana can evaluate against a threshold. Ensure your SQL query:

• Returns at least one numeric column for the alert condition
• Includes a time column if you want time-series evaluation
• Returns data within the evaluation time range

Create an alert rule

To create an alert rule using Snowflake data:

1. Go to Alerting > Alert rules.
2. Click New alert rule.
3. Enter a name for your alert rule.
4. In the Define query and alert condition section:
   • Select your Snowflake data source.
   • Write a SQL query that returns numeric data.
   • Add a Reduce expression if your query returns multiple series.
   • Add a Threshold expression to define the alert condition.
5. Configure the Set evaluation behavior:
   • Select or create a folder and evaluation group.
   • Set the evaluation interval (how often the alert is checked).
   • Set the pending period (how long the condition must be true before firing).
6. Add labels and annotations to provide context for notifications.
7. Click Save rule.

For detailed instructions, refer to Create a Grafana-managed alert rule.

Example: Warehouse credit usage alert

This example creates an alert that fires when warehouse credit usage exceeds a threshold:

1. Create a new alert rule.

2. Configure the query:

   SQL Copy

   SELECT
     end_time AS time,
     credits_used
   FROM snowflake.account_usage.warehouse_metering_history
   WHERE warehouse_name = 'COMPUTE_WH'
     AND $__timeFilter(end_time)
   ORDER BY end_time

3. Add expressions:

   • Reduce: Last value (to get the most recent data point)
   • Threshold: Is above 10 (or your desired credit limit)

4. Set evaluation to run every 5 minutes with a 10-minute pending period.

5. Save the rule.

Example: Query performance alert

This example alerts when queries take longer than expected:

1. Create a new alert rule.

2. Configure the query:

   SQL Copy

   SELECT
     end_time AS time,
     AVG(total_elapsed_time) / 1000 AS avg_query_time_seconds
   FROM snowflake.account_usage.query_history
   WHERE $__timeFilter(end_time)
     AND execution_status = 'SUCCESS'
   GROUP BY end_time
   ORDER BY end_time

3. Add expressions:

   • Reduce: Mean (average across all data points)
   • Threshold: Is above 30 (seconds)

4. Set evaluation to run every 5 minutes.

5. Save the rule.

Example: Data freshness alert

This example alerts when data hasn’t been updated within the expected timeframe:

1. Create a new alert rule.

2. Configure the query:

   SQL Copy

   SELECT
     CURRENT_TIMESTAMP() AS time,
     DATEDIFF('minute', MAX(updated_at), CURRENT_TIMESTAMP()) AS minutes_since_update
   FROM your_database.your_schema.your_table

3. Add expressions:

   • Reduce: Last value
   • Threshold: Is above 60 (minutes)

4. Set evaluation to run every 10 minutes.

5. Save the rule.

Example: Failed query count alert

This example alerts when the number of failed queries exceeds a threshold:

1. Create a new alert rule.

2. Configure the query:

   SQL Copy

   SELECT
     DATE_TRUNC('hour', end_time) AS time,
     COUNT(*) AS failed_query_count
   FROM snowflake.account_usage.query_history
   WHERE $__timeFilter(end_time)
     AND execution_status = 'FAIL'
   GROUP BY DATE_TRUNC('hour', end_time)
   ORDER BY time

3. Add expressions:

   • Reduce: Last value
   • Threshold: Is above 5

4. Set evaluation to run every 15 minutes.

5. Save the rule.

Best practices

Follow these recommendations to create reliable and efficient alerts with Snowflake data.

Use appropriate query intervals

• Set the alert evaluation interval based on how frequently your data updates.
• For queries against account_usage views, note that data may have a latency of up to 45 minutes.
• Avoid very short intervals (less than 1 minute) as they may cause evaluation timeouts.

Reduce multiple series

When your Snowflake query returns multiple time series (for example, metrics per warehouse), use the Reduce expression to aggregate them:

• Last: Use the most recent value
• Mean: Average across all series
• Max/Min: Use the highest or lowest value
• Sum: Total across all series

Handle no data conditions

Configure what happens when no data is returned:

1. In the alert rule, find Configure no data and error handling.
2. Choose an appropriate action:
   • No Data: Keep the alert in its current state
   • Alerting: Treat no data as an alert condition
   • OK: Treat no data as a healthy state

Test queries before alerting

Always verify your query returns expected data before creating an alert:

1. Go to Explore.
2. Select your Snowflake data source.
3. Run the query you plan to use for alerting.
4. Confirm the data format and values are correct.

Consider query costs

Alerting queries run at regular intervals. To minimize Snowflake compute costs:

• Use efficient queries that leverage clustering and partitioning.
• Consider using smaller warehouses for alerting queries.
• Use aggregate functions to reduce data scanned.
• Take advantage of Snowflake’s result caching where possible.

Troubleshooting

If your alerts are not working as expected:

• No data returned: Verify the query runs successfully in Explore and returns data for the evaluation time range.
• Query timeout: Increase the query timeout in data source settings or optimize your query.
• Unexpected values: Check that your query returns the correct data type (numeric for thresholds).

For additional troubleshooting, refer to Troubleshooting.

Additional resources

• Grafana Alerting documentation
• Create alert rules
• Configure notifications