An enterprise is operating BigQuery on the Enterprise edition across several departments. The data engineering team manages a multi-tenant environment with the following workload requirements: ETL/ELT pipeline jobs: Require strictly guaranteed execution times and predictable slot allocation without interference or unexpected queue delays. Ad-hoc data analyst queries: Experience unpredictable traffic bursts during business hours, but can tolerate idle resource sharing to minimize costs. Which configuration strategy should the team implement across their reservations to satisfy these workload requirements while optimizing cost?

Create a dedicated reservation for ETL/ELT with baseline slots and set `ignore_idle_slots = true`; create a separate reservation for ad-hoc queries configured with autoscaling slots and set `ignore_idle_slots = false`.: ### What the Solution Is This strategy uses **BigQuery Editions reservation workload management** to isolate workloads by defining distinct reservations with customized capacity configurations and idle slot sharing behaviors. ### How it Meets the Requirements - **Guaranteed performance for ETL/ELT**: Allocating dedicated **baseline slots** guarantees that compute capacity is permanently provisioned and available immediately. Setting `ignore_idle_slots = true` ensures that queries in this reservation rely strictly on dedicated capacity, preventing external slot contention or unpredictable performance variations. - **Handling unpredictable ad-hoc queries**: Configuring **autoscaling slots** allows the ad-hoc reservation to dynamically scale capacity in increments of 50 slots up to a predefined maximum during demand spikes. - **Cost optimization**: Enabling `ignore_idle_slots = false` on the ad-hoc analytics reservation permits analyst queries to opportunistically consume unused baseline slots from other reservations in the same administration project, minimizing paid autoscaling events. ### Key Advantages - **Strict SLO compliance**: Critical data ingestion pipelines are isolated from unpredictable query surges. - **Dynamic scaling**: Workloads scale rapidly to meet bursts without requiring over-provisioning. - **Resource efficiency**: Baseline slots idle during lull periods are reclaimed by ad-hoc queries before triggering paid autoscaler expansions. - **Cost governance**: Maximum reservation limits prevent unconstrained scaling costs. ### Why This Is Optimal Separating the workloads into dedicated reservations allows fine-grained control over slot predictability and autoscaling elasticity. Combining baseline guarantees with isolated idle policies provides deterministic execution for ELT while delivering elasticity and cost efficiency for interactive analytics.

Bigquery Reservations Baseline Autoscaling Configuration | professional-cloud-data-engineer

Bigquery Reservations Baseline Autoscaling Configuration

Worked example. The correct answer is already marked and every option is explained below, so there is nothing to select here. To answer questions yourself, start the free trial.

An enterprise is operating BigQuery on the Enterprise edition across several departments. The data engineering team manages a multi-tenant environment with the following workload requirements:

ETL/ELT pipeline jobs: Require strictly guaranteed execution times and predictable slot allocation without interference or unexpected queue delays.
Ad-hoc data analyst queries: Experience unpredictable traffic bursts during business hours, but can tolerate idle resource sharing to minimize costs.

Which configuration strategy should the team implement across their reservations to satisfy these workload requirements while optimizing cost?

Create a single shared reservation with autoscaling slots only and set ignore_idle_slots = true for all projects across the organization.

Assign all ETL/ELT and ad-hoc query projects directly to the on-demand compute model without creating BigQuery reservations.

Create a dedicated reservation for ETL/ELT with baseline slots and set ignore_idle_slots = true; create a separate reservation for ad-hoc queries configured with autoscaling slots and set ignore_idle_slots = false.

Create a dedicated reservation for ETL/ELT with autoscaling slots and set ignore_idle_slots = false; create a separate reservation for ad-hoc queries with baseline slots only and set ignore_idle_slots = true.

Professional Cloud Data Engineer

Bigquery Reservations Baseline Autoscaling Configuration

Related questions