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Google ACE Practice Question: A DevOps team uses Terraform to manage GCP…

A DevOps team uses Terraform to manage GCP infrastructure and wants to store Terraform state in a shared location that all team members can access securely, with state locking to prevent concurrent modifications. Which backend configuration achieves this?

⚠ Common exam trap

A common mix-up: candidates confuse the `gcp` provider (which manages GCP resources) with a backend name, or assume that any shared filesystem (like Cloud Filestore) can provide locking, ignoring that Terraform requires atomic, server-side locking which only object storage backends like `gcs` or `s3` provide natively.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

gcs backend storing state in a Cloud Storage bucket

The `gcs` backend is the correct choice because it stores Terraform state in a Google Cloud Storage bucket, which provides secure, shared access via IAM policies and supports state locking natively through object versioning and write-preconditions. This ensures that only one team member can modify the state at a time, preventing conflicts and corruption.

Answer analysis

Option-by-option breakdown

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

  • gcs backend storing state in a Cloud Storage bucket

    Why this is correct

    The `gcs` backend is the official Google Cloud Terraform backend: it stores the state file in a Cloud Storage bucket and supports state locking through the coordinated creation of a lock object using GCS object generation and precondition checks. This lock is released after the operation, preventing concurrent runs from corrupting state. It also supports bucket versioning to retain history and can use customer-managed encryption keys (CMEK) for at-rest protection, making it the correct choice for team collaboration.

  • gcp backend storing state in a BigQuery table

    Why it's wrong here

    Terraform has no native `gcp` backend, nor does it support BigQuery as a state storage location; BigQuery is a petabyte-scale data warehouse, not a file system with atomic read-modify-write semantics. A backend named `gcp` would be invalid and Terraform would reject it at initialization. BigQuery lacks the locking and consistency guarantees required for safe state manipulation, so this option is incorrect.

  • remote backend connected to a Cloud SQL database

    Why it's wrong here

    The `remote` backend in Terraform is exclusively used to connect to Terraform Cloud or Terraform Enterprise via their API; it is not a generic SQL client. Cloud SQL is a fully managed relational database, but Terraform provides no backend that writes state to Cloud SQL or any other SQL database. Even if a database could hold the state, backend state handling requires HTTP-based or object-store primitives, not SQL connections, so this option is wrong.

  • local backend with a path shared over Cloud Filestore

    Why it's wrong here

    A `local` backend writes the state file to a path on the local filesystem; even if that path is shared via Cloud Filestore, it is still the local backend. Terraform's local backend does not implement state locking, and NFS-based file locks over Filestore are unreliable across concurrent processes. Multiple team members running Terraform simultaneously would cause lost writes or state corruption, making this configuration unsafe despite the shared storage.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This ACE practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the ACE exam.