Snowflake’s innovative architecture separating compute from storage has revolutionized cloud data analytics. This flexible model, coupled with Snowflake’s consumption-based pricing billed by the second, allows unlimited scale and unmatched performance as you blend and analyze datasets. But behind this powerful separation lies a costly catch – the idle time drain.
As a Snowflake customer, your job is to make your contracted credits last until the next renewal period. But there’s a silent threat eating away at those credits – idle compute time.
Between queries, data loads, and other cloud data operations, chances are your warehouses are sitting idle for extended periods, racking up charges while performing no actual work. And those idle minutes rapidly add up.
Are You Blindly Burning Credits on Idle Resources?
Let’s look at some typical examples to see the shocking idle time impacts:
Data Ingestion via COPY INTO
- Warehouse: XS
- Process: Ingesting batches via COPY INTO every 5 mins, each taking 2 mins
- Over 30 Days: 17,280 minutes of queries, but 8,640 minutes (33%) wasted on idle periods between ingestion batches
BI Dashboard Monitoring
- Warehouse: Medium
- Process: Dashboards refreshing every 3 mins during non-peak hours (6pm-12pm)
- Over 30 Days: 16,200 minutes of dashboard queries, but 10,800 minutes (40%) wasted on idle time between refreshes
Across multiple workloads like these, idle time can quietly consume over a third of your Snowflake credits each month! That’s a massive chunk of your contracted capacity going to waste.
This “Idle Tax” is Trickier Than You Think
While Snowflake’s auto-suspend feature helps reduce idle time, the minimum suspension interval is 60 seconds. Attempting to set overly aggressive auto-suspend periods below 60 seconds is ineffective, as the background process that suspends warehouses runs approximately every 60 seconds.
One potential solution is consolidating multiple workloads onto shared warehouses to minimize idle periods between jobs. However, this approach requires careful sizing and load testing to avoid performance degradations from consolidated workloads competing for resources. When done intelligently, workload consolidation can reduce the idle time tax
Implementing complex scaling policies and schedules to proactively adjusting warehouse sizing is also possible, but can become an operational burden. The idle time issue highlights the need for intelligent rightsizing across your Snowflake deployment.
Get Full Visibility Into Your Idle Time Waste
The first step to attacking this issue is understanding your idle time exposure across all warehouses and workloads.
That’s why we created the Yuki Waste Calculator app, available for free on Snowflake’s marketplace.
By installing Yuki, you’ll get:
- Detailed active vs. idle time breakdowns per warehouse
- Totals of credits wasted on idle resources over time periods
- Identification of your biggest idle time offenders
If you wish to explore this topic even further, feel free to contact us at contact@yukidata.com
