Your finance team runs an hourly BigQuery dashboard that must finish within five minutes. During month-end, spikes of analysts' interactive queries-billed on on-demand pricing-consume most available slots, so the dashboard now takes 12 minutes. You must guarantee enough compute for the dashboard while allowing analysts to use any surplus capacity without adding fixed cost for them. What should you do?
Replicate the dataset to a different region and schedule the dashboard there to avoid competition for slots in the primary region.
Change the dashboard query priority to batch; it will wait for free capacity and complete within the SLA once resources free up.
Buy two equal slot reservations-one for finance and one for analysts-and disable idle-slot sharing between them to avoid contention.
Purchase a BigQuery reservation sized for the dashboard, assign only the dashboard's service account to it, and leave the analysts on on-demand so they can use any idle slots.
Creating a dedicated BigQuery capacity reservation for the critical dashboard guarantees that its queries always have the required baseline number of slots. By assigning only the dashboard's service account (or project) to that reservation, the capacity is reserved for the job whenever it runs. When the dashboard is idle, any unused slots automatically flow back to the on-demand pool, where analysts' interactive queries can borrow them at on-demand rates. Changing the dashboard to batch priority would not guarantee a five-minute SLA, and buying a separate reservation for analysts or disabling idle-slot sharing would raise costs and strand capacity. Running the dashboard in another region avoids contention locally but adds data-transfer cost and still provides no slot guarantee.
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