AWS provider Collaborative Workflows — Timed 15 Questions

Question 1

You have a team-based collaboration project. Where should you store sensitive credentials like AWS secret keys so they are not hardcoded in your Terraform files?

Accepted Answer

In environment variables marked as 'sensitive'. Environment variables are the recommended way to supply sensitive credentials to Terraform because they are read at runtime by the AWS provider (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY) and never written into configuration or state. Marking them sensitive in the shell or CI system keeps them out of version control and out of plan output. This satisfies the requirement that secrets not be hardcoded in .tf files.

Answer

In a .tfvars file

Answer

In a version-controlled .env file

Answer

In the state file

Question 2

Which organization-level setting in HCP Terraform governs who can create new workspaces?

Accepted Answer

Team permissions. Team permissions in HCP Terraform are the organization-level mechanism that controls workspace creation rights. By default, only users with the 'Owner' or 'Admin' team permissions can create workspaces, but this can be delegated to other teams via custom permissions. This setting is managed at the organization level under 'Teams' and directly governs who can create new workspaces.

Answer

Global settings

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Agent pool settings

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Workspace settings

Question 3

You need to enforce that only specific VM sizes are used in your infrastructure. Which Sentinel feature provides this capability?

Accepted Answer

Policy enforcement. Policy enforcement in HCP Terraform (formerly Terraform Cloud) Sentinel is the feature that evaluates infrastructure plans against policy rules and blocks non-compliant changes. By writing a Sentinel policy that checks the instance_type attribute of AWS instances against an allow-list, you enforce that only approved VM sizes can be provisioned. This is the core purpose of Sentinel policy enforcement.

Answer

Run trigger

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Workspaces

Answer

Policy Set

Question 4

When implementing OPA policies, what is the 'soft-mandatory' enforcement level?

Accepted Answer

It allows the run if overridden. In OPA (Open Policy Agent) policy enforcement, 'soft-mandatory' is a level that allows a policy violation to be overridden by an authorized user, typically with a justification. This means the run is not blocked outright; instead, it proceeds if the override is applied. This is in contrast to 'hard-mandatory', which blocks the run completely, and 'advisory', which only logs the event. The correct answer is B because soft-mandatory enforcement permits the run when overridden.

Answer

It blocks the run completely

Answer

It is a deprecated feature

Answer

It only logs the event

Question 5

Which protocol does HCP Terraform use to communicate with Terraform CLI?

Accepted Answer

HCP Terraform API. Terraform uses the 'Terraform Cloud API' for all communication between the CLI and HCP Terraform.

Answer

gRPC

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FTP

Answer

SSH

Question 6

Which HCP Terraform feature allows you to manage infrastructure across multiple cloud accounts using a single organization?

Accepted Answer

Projects. HCP Terraform Projects allow you to organize workspaces and their associated infrastructure into logical groupings that can span multiple cloud accounts, all under a single organization. This feature provides a way to manage access control, policy enforcement, and cost allocation across different teams or environments without needing separate organizations. By using projects, you can delegate administration and apply consistent governance across disparate cloud accounts, which is exactly what the question describes.

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Shared modules

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Provider aliases

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Remote execution

Question 7

You have accidentally committed a secret to your VCS repository. After rotating the secret, what is the best practice to ensure it is not used in your workspace?

Accepted Answer

Use HCP Terraform sensitive variables. HCP Terraform sensitive variables are the recommended mechanism for injecting secrets into runs without storing them in VCS. After rotating a leaked secret, you mark the new value as sensitive in the workspace's variable set, so it is encrypted at rest, masked in logs, and never written to the repository. This ensures the workspace uses the rotated secret while the compromised value remains useless.

Answer

Delete the repository

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Disable VCS integration

Answer

Run terraform destroy

Question 8

Which THREE actions occur when you execute a Terraform run in HCP Terraform?

Accepted Answer

Policy evaluation. In an HCP Terraform (formerly Terraform Cloud) run, the workspace first performs plan generation (D), where Terraform creates an execution plan showing the proposed changes to reach the desired state defined in configuration. Policy evaluation (B) then occurs via Sentinel or OPA policy sets attached to the workspace, enforcing governance rules such as cost limits or required tags before any apply is permitted. Manual approval (C) is a standard stage in the run workflow when the workspace uses the default 'Manual apply' setting, requiring a user to confirm the apply after the plan and policies pass. The remaining options do not belong: immediate infrastructure destruction (A) is not an automatic run action—destruction only happens if the plan explicitly calls for it and is approved—and local environment cleanup (E) is not performed by HCP Terraform, since runs execute on remote runners rather than the user's local machine.

Answer

Immediate infrastructure destruction

Answer

Local environment cleanup

Question 9

You have a workspace configured for 'CLI-driven' workflow. What does this mean for how you apply changes?

Accepted Answer

The user triggers operations via the CLI. A CLI-driven workspace in HCP Terraform means the user runs `terraform plan` and `terraform apply` from their local terminal, with the run executing remotely in HCP Terraform's infrastructure. The CLI authenticates to the workspace and streams logs back, but the user remains the trigger for every operation. This is distinct from VCS-driven and API-driven workflows.

Answer

Operations are always automatic

Answer

It disables remote state

Answer

The plan happens locally, apply remotely

Question 10

Which TWO ways can you connect a workspace to your version control provider?

Accepted Answer

Direct VCS integration. Option A (Direct VCS integration) is correct because connecting a workspace directly to a supported version control provider (such as GitHub, GitLab, Bitbucket, or Azure DevOps) via OAuth or a VCS connection lets Terraform automatically ingest the repository and trigger runs on commits, which is a first-class supported method. Option B (CLI-driven workflow) is also correct because you can run Terraform CLI commands from your local machine or CI/CD pipeline against a workspace, using the remote backend or API-driven runs to associate and push configuration from your version control provider without a direct VCS link. Option C (Manual UI file upload) is not a supported way to connect a workspace to a VCS provider, since the UI does not provide a mechanism to upload files as a version control connection. Option D (FTP upload) is incorrect because FTP is not a supported protocol for connecting workspaces to version control. Option E (Emailing code to Terraform support) is incorrect because support cannot ingest code via email to establish a VCS connection.

Answer

Manual UI file upload

Answer

FTP upload

Answer

Emailing code to Terraform support

Question 11

Which TWO features help maintain consistency across multiple workspaces?

Accepted Answer

Shared modules. Shared modules (D) are correct because they let multiple workspaces consume the same versioned, reusable Terraform module, so identical infrastructure definitions are applied everywhere instead of drifting apart. Variable sets (E) are correct because they supply the same centrally managed variable values to many workspaces at once, ensuring consistent inputs without duplicating configuration. Together these features enforce uniformity across workspaces. Unique state files per module (A) actually fragment state and do not promote consistency. Local execution only (B) removes centralized runs and shared state, increasing drift. Manual copy-pasting of code (C) is error-prone and creates divergent copies rather than consistent shared definitions.

Answer

Unique state files for every module

Answer

Using local execution only

Answer

Manual copy-pasting of code

Question 12

You are configuring a policy set in HCP Terraform using Sentinel. You want to enforce that all AWS EC2 instances have a specific tag, but you also want to allow an override for emergency changes with a documented approval. Which TWO Sentinel features should you use to achieve this? (Choose two.)

Accepted Answer

Implement a policy that checks for the tag and returns a boolean result.. To enforce tagging while permitting emergency overrides, the policy must evaluate the tag and return a failing result when absent. Setting the enforcement level to soft-mandatory allows authorized users to override the failure, enabling emergency changes with approval. This combination balances governance with operational flexibility.

Answer

Use the 'advisory' enforcement level on the policy.

Answer

Use the 'hard-mandatory' enforcement level on the policy.

Answer

Configure the policy set to use the 'sentinel' CLI locally before applying.

Question 13

Your team uses HCP Terraform with remote state and run triggers. A run in workspace 'networking' completes successfully and triggers a run in 'application'. The application run plans and applies correctly, but the networking team later discovers that the application run used an outdated state of networking outputs because the run trigger fired before the state was fully persisted. What is the most likely cause?

Accepted Answer

The run trigger fired before the networking state was fully written to the remote backend, causing the application run to read an older state version.. Run triggers in HCP Terraform initiate a run in a dependent workspace after an upstream run finishes. However, the downstream run may start before the upstream state is fully persisted, especially under heavy load or network latency. This race condition can cause the downstream run to read an older state version, leading to outdated outputs. To mitigate, ensure that the downstream workspace uses explicit dependencies or retries, or consider using a longer delay via a custom solution.

Answer

The run trigger was configured with a delay of zero seconds, which is not supported and causes a race condition.

Answer

The application workspace is not configured to use the networking workspace's state as a data source, so it relies on stale outputs.

Answer

The networking workspace uses local state instead of remote state, so the run trigger cannot access the latest outputs.

Question 14

You are setting up a collaborative workflow in HCP Terraform where multiple teams will manage infrastructure across several AWS accounts. You need to ensure that team members can run plans but cannot apply changes without approval. Which TWO configurations should you implement? (Choose two.)

Accepted Answer

Assign the 'Apply' permission only to a specific team and enable 'Manual Apply'.. To prevent applies without approval, you must both restrict who can apply and require manual confirmation. Enabling Manual Apply forces an explicit approval after a successful plan, and limiting the Apply permission to a specific team ensures only authorized users can perform that action. Other options either do not enforce approval or are unrelated to access control.

Answer

Use Sentinel policies with 'hard-mandatory' enforcement.

Answer

Set the workspace's execution mode to 'Remote'.

Answer

Assign the 'Plan' permission to the team for the workspace.

Question 15

You are using HCP Terraform with a VCS-driven workflow. A developer pushes a commit to the main branch, triggering a run. The run's plan succeeds, but the apply fails due to a transient AWS API error. What should you do to retry the apply without re-running the plan?

Accepted Answer

Use the 'Confirm & Apply' button again on the same run to retry the apply.. HCP Terraform allows retrying a failed apply without re-planning by using the 'Confirm & Apply' button on the run page. This reuses the existing plan, which is particularly useful for transient errors. It ensures that the exact same changes are applied, maintaining consistency and saving time.

Answer

Trigger a new run by pushing an empty commit to the VCS repository.

Answer

Use the 'Retry' button on the run page in HCP Terraform to re-execute the apply.

Answer

Run terraform apply locally using the saved plan file from the failed run.