A media company runs a mission-critical BigQuery dashboard that must complete within 15 seconds at the top of every hour. Analysts in several other projects run unpredictable ad-hoc queries during business hours. On-demand pricing frequently exhausts the 2,000 shared concurrent slot pool, causing the dashboard to slow down. You need to guarantee enough compute for the dashboard without significantly increasing costs for the analysts. Which approach best meets the requirement?
Purchase a 1-year commitment for the minimum number of Enterprise Edition slots the dashboard needs and place them in a reservation that is assigned only to the dashboard's project, leaving other projects on on-demand pricing.
Rely on Flex Slots by requesting the required number of slots five minutes before each hour and releasing them when the dashboard finishes.
Create a single organization-wide reservation with enough slots for all workloads and assign every project to it, trusting BigQuery's scheduler to share capacity fairly.
Upgrade to Enterprise Plus Edition but do not buy any committed slots; let both the dashboard and analyst queries continue using on-demand capacity, which can burst automatically.
Creating a dedicated reservation guarantees that the dashboard receives its own fixed pool of slots, eliminating contention. Assigning only the dashboard project (or its service account) to the reservation isolates those slots, while all other projects continue to run on-demand and use any idle reserved capacity through idle-slot pooling. Flex slots do not guarantee availability because they are allocated on a best-effort basis and can be unavailable during peak times. Simply upgrading to Enterprise Plus without purchasing slots gives no dedicated capacity, and sharing a single reservation across all projects reintroduces contention, defeating the purpose of isolating critical workloads.
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