snowflake-observability

# Snowflake Observability ## Overview Set up comprehensive observability for Snowflake using built-in ACCOUNT_USAGE views, Snowflake Alerts, and integration with external monitoring systems. ## Prerequisites - Role with access to `SNOWFLAKE.ACCOUNT_USAGE` (ACCOUNTADMIN or granted) - Notification integration configured for alerts - Optional: Prometheus/Grafana or Datadog for external dashboards ## Instructions ### Step 1: Key Monitoring Queries ```sql -- === QUERY PERFORMANCE === -- Average query time by warehouse (last 7 days) SELECT warehouse_name, COUNT(*) AS query_count, ROUND(AVG(total_elapsed_time) / 1000, 1) AS avg_seconds, ROUND(PERCENTILE_CONT(0.95) WITHIN GROUP (ORDER BY total_elapsed_time) / 1000, 1) AS p95_seconds, ROUND(PERCENTILE_CONT(0.99) WITHIN GROUP (ORDER BY total_elapsed_time) / 1000, 1) AS p99_seconds FROM SNOWFLAKE.ACCOUNT_USAGE.QUERY_HISTORY WHERE start_time >= DATEADD(days, -7, CURRENT_TIMESTAMP()) AND execution_status = 'SUCCESS' AND query_type = 'SELECT' GROUP BY warehouse_name ORDER BY avg_seconds DESC; -- === ERROR RATE === -- Error rate by hour SELECT DATE_TRUNC('hour', start_time) AS hour, COUNT_IF(execution_status = 'SUCCESS') AS success, COUNT_IF(execution_status = 'FAIL') AS failures, ROUND(COUNT_IF(execution_status = 'FAIL') * 100.0 / NULLIF(COUNT(*), 0), 2) AS error_rate_pct FROM SNOWFLAKE.ACCOUNT_USAGE.QUERY_HISTORY WHERE start_time >= DATEADD(hours, -24, CURRENT_TIMES...