Snowflake Cost Monitoring
Last updated
Last updated
The Snowflake Cost Monitoring dashboard, part of Paradime's Radar suite, offers comprehensive insights into your Snowflake warehouse usage and costs. This tool enables teams to effectively monitor warehouse spend, analyze usage patterns, and make data-driven decisions to optimize costs without compromising performance.
Completed the Cost Management setup in Radar's Get Started guide.
1. Daily Warehouse Spend
Value: Track daily spend across various Snowflake warehouses to identify high-cost areas and opportunities for optimization.
How to Use:
Use this chart to identify which warehouses contribute the most to your overall Snowflake costs.
Focus on high-spending warehouses and look for opportunities to reduce unnecessary costs by adjusting workloads or query patterns.
2. Query Spend by Segment
Value: Analyze query spending by user and role to identify which segments of your organization are driving the most costs.
Charts to Add:
How to Use:
Use this insight to focus on high-cost users or roles that may require query optimization or cost management.
Investigate users or roles with unexpectedly high query costs to understand the cause.
Implement strategies to help optimize query performance for users or roles that are driving up costs.
3. Snowflake Timeout Queries
Value: Identify queries that timed out, along with their associated costs, to investigate inefficiencies.
How to Use:
Look for recurring timeout queries that may indicate inefficiencies or potential areas for optimization.
Use the search function to locate specific queries that are frequently timing out and investigate the root cause.
Implement performance improvements to reduce or eliminate timeout queries and minimize wasted resources.
4. dbt™ Project Costs
Value: Understand the cost implications of dbt™ operations, including individual query costs and overall production run costs.
How to Use:
Focus on high-cost dbt™ queries to identify areas where optimization could lead to significant cost savings.
Review production runs to find patterns in cost spikes and investigate whether certain jobs can be optimized or run less frequently.
Use the detailed query cost analysis to pinpoint inefficient queries and prioritize optimizations for those that will have the greatest impact on cost savings.
Use the "Select date range" and "Select warehouse" dropdowns at the top of the dashboard to filter your analysis:
Date Range: Select a specific time period to focus your analysis on relevant data.
Warehouse: Focus on a specific warehouse to see its detailed cost breakdown and usage patterns.
The dashboard will automatically update based on your filter selections, enabling focused analysis on Snowflake cost trends.
Best Practices
Monitor Regularly: Keep a close eye on daily warehouse spend and query costs to identify anomalies early.
Focus on High-Cost Users and Roles: Use the Query Spend by User and Query Spend by Role charts to identify high-cost segments.
Review dbt™ Costs: Regularly check the dbt™ Project Costs section to identify high-cost dbt™ models and queries and optimize for better cost efficiency.
