Google ACE Practice Question: Match each Google Cloud service to its primary…

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✓

  Compute Engine: Provides virtual machines for running workloads.

  Why this is correct

  Compute Engine is Google Cloud's Infrastructure-as-a-Service (IaaS) offering that provisions virtual machines on Google's hypervisor infrastructure. You select the machine family, vCPUs, memory, GPU accelerators, and boot disk images, then manage the guest OS, middleware, and runtime yourself. It is the correct match for the prompt because its primary purpose is precisely to run arbitrary workloads in VMs, not to provide managed database or analytics functionality.

• ✓

  Cloud Storage: Offers scalable object storage for unstructured data.

  Why this is correct

  Cloud Storage is a fully managed object storage service that stores unstructured data as objects in buckets, addressed by a unique key rather than a filesystem path. It offers high durability (11 nines), global edge caching, and lifecycle policies for data like images, videos, backups, and archives. While you can put structured exports in it, its primary purpose is object storage for arbitrary blobs, not to serve SQL queries or support data warehouse workloads.

• ✓

  Cloud SQL: Managed database service for MySQL, PostgreSQL, and SQL Server.

  Why this is correct

  Cloud SQL is a fully managed relational database-as-a-service (DBaaS) that supports MySQL, PostgreSQL, and SQL Server engines, handling automated backup, patch management, replication, and failover. It is intended for OLTP-style workloads that need transactional consistency and standard SQL, with vertical scaling and read replicas but not petabyte-scale analytics. The correct purpose here is specifically the managed relational database service, which distinguishes it from raw VMs on Compute Engine or serverless analytics in BigQuery.

• ✓

  BigQuery: Serverless data warehouse for analytics at petabyte scale.

  Why this is correct

  BigQuery is a fully managed, serverless data warehouse with a columnar storage engine and a distributed query engine that can run SQL over petabyte-scale datasets. It separates compute from storage, uses a slot-based architecture, and supports on-demand or reserved pricing, making it ideal for analytical and BI workloads. Its primary purpose is fast analysis of structured/semi-structured data using SQL, not general-purpose virtual machine hosting or transactional database operations.

• ✗

  Compute Engine: Managed relational database service.

  Why it's wrong here

  This pairing incorrectly assigns Compute Engine the role of a managed relational database service, which is the defining purpose of Cloud SQL. Compute Engine is IaaS: you can manually install and operate a database on a VM, but Google does not manage the database engine, patching, or replication for you. The wrongness here is a service-model error—confusing an unmanaged infrastructure compute option with a fully managed database platform.

• ✗

  Cloud Storage: Data warehousing for analytics.

  Why it's wrong here

  This pairing describes Cloud Storage as a data warehousing and analytics platform, which is actually the defining purpose of BigQuery. Cloud Storage's object store does not support SQL queries, table joins, or columnar scanning over your data; it simply stores and retrieves blobs. The wrongness is a functional mismatch—object storage cannot replace a serverless data warehouse engineered for petabyte-scale analytic processing.

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