Keebo | Costco Travel

Costco Travel Cuts Snowflake Costs in Half With Optimizations From Keebo

  • Increased processing and compute costs due to frequent data changes and fixes
  • More advanced reporting required due to growing workload and tightening SLAs
  • Limited data engineering resources due to small teamsize and ongoing industry-wide, pandemic recovery

Costco Travel offers its members exclusive savings on top-quality vacations, hotels, cruises and rental cars. Amidst ongoing, industry-wide pandemic recovery, Costco Travel faced tightening SLAs and minimal data engineering resources with which to meet them. By implementing Keebo, Costco Travel reduced Snowflake costs by 50%, freeing up engineers for more user-centric tasks.

  • Increased processing and compute costs due to frequent data changes and fixes
  • More advanced reporting required due to growing workload and tightening SLAs
  • Limited data engineering resources due to small teamsize and ongoing industry-wide, pandemic recovery

Costco Travel offers its members exclusive savings on top-quality vacations, hotels, cruises and rental cars. Amidst ongoing, industry-wide pandemic recovery, Costco Travel faced tightening SLAs and minimal data engineering resources with which to meet them. By implementing Keebo, Costco Travel reduced Snowflake costs by 50%, freeing up engineers for more user-centric tasks.

Initially, Costco Travel began implementing Snowflake’s boilerplate cost optimization advice: write better queries, monitor performance parameters—bytes scanned, execution time, query load percent, spillage, and queuing time— and adjust warehouse sizes manually.

The problem: Costco Travel’s data engineers had no reliable way to predict optimum warehouse sizes without constant monitoring. Not only was this a waste of precious data resources, but it detracted from more user-focused activities like data pipelines and reports.

To solve this problem, Costco Travel implemented Keebo’s artificial intelligence and machine learning optimization tool to dynamically adjust warehouse size and auto-suspend.

If Keebo determined a smaller warehouse could handle incoming requests with negligible impact on performance, it would scale down the warehouse until query and user volume ramped back up. Likewise, if Keebo determined a low likelihood of warehouse usage before the default auto-suspend period, it would preemptively suspend the warehouse, saving additional compute costs.

By implementing automated optimizations across Costco Travel’s Snowflake footprint, Keebo reduced costs, enabling Costco Travel to do more at higher quality. These optimizations added up to a 50% reduction in overall Snowflake costs.



Given the lean nature of their data team, these cost reductions enabled increased capabilities, not only in terms of data processing, but freeing up human resources for higher impact, user-centric activities.

Matt Browning, AVP of International & Business Services
Costco Travel

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