HashiCorp Terraform Associate Exam Dumps & Practice Test Questions
Question No 1:
In Python, if you have a variable named num_servers that holds the number of servers, which of the following correctly assigns this value to the input named servers within a module or function?
A servers = num_servers
B servers = variable.num_servers
C servers = var(num_servers)
D servers = var.num_servers
Answer: A
Explanation:
In Python, the most straightforward and commonly used way to pass values between variables or to inputs within modules or functions is through direct assignment. This means taking the value stored in one variable and assigning it directly to another variable. In the context of the question, if you have a variable called num_servers that holds a numeric value (for example, the number of servers you want to configure), the correct way to assign this value to another variable called servers is simply writing servers = num_servers. This assigns the value of num_servers to servers, making servers now hold the same value.
To illustrate, if num_servers holds the value 10, then after servers = num_servers, the variable servers will also hold 10. This direct assignment is simple, efficient, and universally understood in Python programming.
Examining the other options, B assumes that there is an object or module named variable which has an attribute called num_servers. If no such object exists, using variable.num_servers will raise an AttributeError or NameError. Since the question does not mention any such object, this option is invalid in the general case.
Option C suggests using var(num_servers) as if var were a function that takes num_servers as an argument. Unless var is explicitly defined as a function in the code, this will result in a NameError, as Python will not recognize var.
Option D tries to access num_servers as an attribute of an object named var (var.num_servers). Similar to B, this will only work if var is a defined object with the attribute num_servers. Without this context, it will cause an error.
Therefore, because the question only refers to a simple variable num_servers and the intention is to assign its value to servers, the only valid and reliable option is A, which performs a direct and clear assignment.
Direct assignment is a foundational concept in Python and programming in general, enabling clean and readable code that efficiently transfers values between variables, parameters, or module inputs. It avoids unnecessary complexity and errors that could arise from assuming the presence of objects, functions, or attributes that may not exist in the current scope.
Question No 2:
Is it required for a Terraform provisioner to be declared within a resource block?
A True
B False
Answer: A
Explanation:
In Terraform, provisioners are specialized configuration blocks designed to execute scripts or commands on a resource after it has been created or updated. Their primary function is to facilitate additional configuration or setup tasks on the infrastructure components managed by Terraform, such as installing software, initializing services, or running custom configuration scripts on virtual machines, containers, or other resources.
It is essential that provisioners are declared inside the resource block to which they apply. A resource block in Terraform defines an individual infrastructure component—such as an AWS EC2 instance, an Azure VM, a Google Cloud database instance, or a networking device. Because provisioners run commands directly on the resource they are attached to, they require the context provided by the resource block to know where to execute those commands.
For instance, if you define an AWS EC2 instance resource and want to install Apache web server on it after creation, you would include a provisioner like remote-exec inside that specific aws_instance resource block. This linkage ensures that Terraform runs the provisioner commands on the exact EC2 instance you have declared. Without being nested inside the resource block, Terraform would not be able to identify which resource the provisioner pertains to, rendering the provisioner ineffective.
Placing a provisioner outside a resource block means it would lack this vital association and context, which Terraform requires to execute provisioning commands correctly. Terraform does not allow provisioners to exist independently in the configuration because their function is intrinsically tied to the lifecycle of a particular resource.
Additionally, the tight coupling between provisioners and resource blocks helps Terraform manage lifecycle operations, such as creating, updating, or destroying resources, while running provisioning commands at the appropriate stage. This ensures that any setup or configuration performed by the provisioner is directly related to the resource's state and lifecycle events.
In summary, defining provisioners inside resource blocks is a mandatory practice in Terraform. This guarantees proper context, successful execution of provisioning commands, and seamless integration of setup tasks within the infrastructure deployment process. Without this requirement, the entire provisioning mechanism would lose its meaning and functionality.
Question No 3:
Is it necessary to run Terraform on a Windows Server edition specifically for it to function correctly?
A True
B False
Answer: B
Explanation:
Terraform is a versatile Infrastructure as Code (IaC) tool developed by HashiCorp, designed to work seamlessly across multiple operating systems including Windows, macOS, and various Linux distributions. It is important to understand that Terraform does not require a specific Windows Server edition to function properly. Instead, it runs equally well on standard desktop editions of Windows such as Windows 10 or Windows 11.
The primary requirement to run Terraform on a Windows machine is simply to download the appropriate Windows-compatible binary from the official Terraform website. After downloading, users extract the binary and place it in a directory included in the system’s PATH environment variable, which allows Terraform to be executed from any command prompt or terminal window. This setup is straightforward and does not depend on whether the operating system is a server or desktop edition.
Many users mistakenly believe that Terraform must be run on a Windows Server edition due to the prevalence of servers in enterprise environments and the fact that many infrastructure management tools are traditionally deployed on server-class operating systems. However, Terraform itself is agnostic to the Windows edition and does not rely on any server-specific components or services. Its core functionality is platform-independent, and its ability to interact with cloud providers like AWS, Azure, Google Cloud, and others remains consistent regardless of whether it’s running on a Windows desktop or server operating system.
Performance, reliability, and feature support in Terraform are consistent across all supported operating systems. The main differences users may encounter relate to OS-specific behaviors, such as how file paths are formatted or the available terminal capabilities, but these do not affect the underlying infrastructure provisioning capabilities of Terraform.
In summary, Terraform is highly flexible and cross-platform by design, and there is no technical or operational necessity to run it on a Windows Server edition. Desktop versions of Windows provide all the functionality needed to install, configure, and execute Terraform effectively, making it accessible to a broad range of users—from developers running it on personal machines to administrators managing large-scale infrastructure deployments.
Question No 4:
In Terraform, what is the primary role of the default "local" backend, and what specific type of file does it manage?
A. tfplan files
B. Terraform binary
C. Provider plugins
D. State file
Answer: D. State file
Explanation:
The default "local" backend in Terraform plays a vital role by handling the storage and management of the state file, which is essential for tracking the infrastructure that Terraform manages. This file, typically named terraform.tfstate, contains detailed records of all resources deployed through Terraform, mapping declared infrastructure in code to actual deployed resources.
When using the local backend, Terraform stores this file on the user’s local machine. Unlike remote backends such as AWS S3 or Azure Blob Storage, which are more suitable for team environments, the local backend is ideal for individual or smaller-scale use cases. It does not require cloud integration for state storage, making it straightforward and convenient for single-user setups.
The state file includes information such as current resource configurations, metadata like resource IDs, applied changes, and any outputs defined in the Terraform code. It is central to Terraform’s ability to plan, apply, and destroy resources accurately, ensuring changes align with the desired state.
The other options listed are unrelated to the backend’s core responsibility. tfplan files are generated temporarily during planning stages, the Terraform binary is the main executable used to run commands, and provider plugins enable communication with cloud services but are not part of backend storage. Therefore, the state file is the correct answer, as it is the primary data managed by the local backend.
Question No 5:
You and your development team are using Terraform for infrastructure as code and aim to maintain consistent formatting across all Terraform configuration files for clarity and maintenance.
What is the best method to ensure that your Terraform HCL files follow the standard formatting guidelines?
A. Run the terraform fmt command during the code linting phase of your CI/CD pipeline
B. Assign one team member to manually review and format everyone’s Terraform code
C. Manually apply two-space indentation and align equal signs in each .tf file
D. Create a shell script using tools like AWK, Python, and sed to format the files
Answer:
A. Run the terraform fmt command during the code linting phase of your CI/CD pipeline
Explanation:
Maintaining consistent formatting in Terraform files is essential for collaboration and readability. Terraform includes a built-in command, terraform fmt, which automatically formats HCL code according to official style guidelines. Running this command as part of your CI/CD pipeline ensures all code is checked and properly formatted before being merged or deployed.
This approach is efficient, scalable, and reduces the risk of manual formatting mistakes. It guarantees uniformity in indentation, spacing, and alignment across all Terraform files, regardless of who writes the code.
Option B relies on manual formatting, which is inefficient and not scalable for large teams.
Option C is prone to errors and cannot consistently enforce formatting rules.
Option D requires custom scripting that is unnecessary when Terraform already provides a dedicated formatting tool.
Automating the process with terraform fmt is the most reliable and professional approach.
Question No 6:
What is one of the primary advantages of using the private module registry available in Terraform Cloud or Terraform Enterprise when compared to the public Terraform Module Registry?
A. Modules in the private registry are automatically encrypted using third-party tools
B. The private registry does not support module versioning, encouraging real-time updates
C. The ability to restrict modules to members of Terraform Cloud or Enterprise organizations
D. Modules from the private registry are automatically converted into JSON for runtime use
Answer:
C. The ability to restrict modules to members of Terraform Cloud or Enterprise organizations
Explanation:
The private module registry in Terraform Cloud and Enterprise offers key benefits that go beyond what the public registry provides. One of the most valuable features is access control. Organizations can limit access to their internal modules so that only authorized users within their Terraform Cloud or Enterprise workspace can use them. This ensures sensitive infrastructure code remains secure and is not exposed publicly.
Other significant advantages include support for versioning and tagging, which helps teams track changes and safely manage deployments using specific module versions. The private registry also promotes centralized collaboration, making it easier to reuse, maintain, and govern shared modules across teams.
In contrast to the public registry, which is open to all Terraform users, the private registry offers a secure environment tailored to organizational needs.
Option A is incorrect because encryption is not managed by third-party tools automatically.
Option B is false; private registries do support module versioning.
Option D is inaccurate, as module conversion to JSON is not a feature of the registry.
Overall, the private module registry enhances security, governance, and collaboration, making it an ideal solution for enterprise-level infrastructure management.
Question No 7:
Which task is not performed by the terraform init command within the Terraform workflow?
A) Sources all providers specified in the configuration and ensures they are downloaded and available locally
B) Connects to the backend
C) Sources any modules and copies the configuration locally
D) Validates all required variables are present
Answer: D) Validates all required variables are present
Explanation:
The terraform init command is essential for setting up a working directory containing Terraform configuration files. It prepares the environment by initializing providers, modules, and backends declared in the configuration files. However, terraform init does not handle all aspects of configuration validation.
Option A is a task performed by terraform init—it downloads and makes available all providers required by the configuration.
Option B is also handled by terraform init when a backend is configured; it establishes a connection to that backend to manage state storage.
Option C is correct as well because terraform init fetches and copies any referenced modules, whether remote or local.
Option D, however, is not a function of terraform init. The validation of required variables happens later during commands like terraform plan or terraform apply, which check for missing or incorrectly set variables and produce errors accordingly.
In summary, terraform init focuses on initializing providers, modules, and backends but does not validate the presence of required variables—that step is deferred to later Terraform commands.
Question No 8:
Given a variable named var.list that is a list of objects, each containing an attribute id, which of the following options will correctly return a list of id values? (Select two.)
A) { for o in var.list : o => o.id }
B) var.list[].id
C) [ var.list[].id ]
D) [ for o in var.list : o.id ]
Answer:
B) var.list[*].id
D) [ for o in var.list : o.id ]
Explanation:
When working with a list of objects like var.list, where each object has an id attribute, the goal is to extract all id values into a new list.
Option A is incorrect because its syntax is invalid; the use of the => operator is inappropriate in this context, so it will not return the desired list.
Option B uses the [*] syntax to extract the id attribute from each object within var.list. This is valid in languages like HashiCorp Configuration Language (HCL) and returns the list of ids directly.
Option C is incorrect since it places the result of var.list[*].id inside square brackets again, which would create a nested list or cause an error depending on the environment.
Option D uses list comprehension to iterate through each object in var.list and extracts the id attribute properly. This is also a correct and common way to generate a list of ids.
Therefore, options B and D both provide valid and effective ways to retrieve a list of id values from the list of objects.
Question No 9:
What is the primary function of Terraform in managing infrastructure?
A To automate software testing and deployment
B To configure and provision infrastructure through code
C To monitor system performance and logs
D To secure cloud environments from unauthorized access
Answer: B
Explanation:
Terraform is a widely used tool designed to manage infrastructure as code (IaC). Its main purpose is to allow users to define, provision, and manage cloud and on-premises resources using configuration files written in HashiCorp Configuration Language (HCL) or JSON. This method brings automation, repeatability, and version control to infrastructure management, enabling teams to provision servers, networks, databases, and other components efficiently.
Option A refers more to CI/CD pipelines and automated testing tools rather than infrastructure provisioning. Terraform does not handle software testing or application deployment directly.
Option B correctly describes Terraform’s core function: infrastructure configuration and provisioning. It supports multiple cloud providers such as AWS, Azure, Google Cloud, and many others through a plugin system called providers.
Option C relates to monitoring and logging tools like Prometheus or CloudWatch, which are outside Terraform’s scope.
Option D concerns security and access control solutions, which Terraform can assist in configuring but is not its primary purpose.
By using Terraform, organizations gain declarative management where the desired state of infrastructure is described, and Terraform makes the necessary changes to reach that state. This approach contrasts with imperative scripting, reducing human error and enhancing infrastructure scalability and consistency.
Question No 10:
Which Terraform command is used to start the process of downloading the necessary provider plugins and modules?
A terraform apply
B terraform init
C terraform plan
D terraform validate
Answer: B
Explanation:
The command terraform init is the fundamental step that prepares your Terraform working environment by downloading all the required provider plugins and modules referenced in your configuration files. When you begin a new Terraform project, or if you add new providers or modules to an existing configuration, running terraform init ensures that these external dependencies are retrieved and installed locally. Without this initialization, Terraform cannot interact with the infrastructure providers or properly execute other commands.
Option A, terraform apply, is used to actually implement changes in your infrastructure based on the configuration and the plan created earlier. It is not responsible for downloading or setting up plugins but applies the defined infrastructure changes.
Option C, terraform plan, generates an execution plan showing what changes Terraform will make, allowing you to preview those changes before applying them. However, it assumes the necessary plugins are already available and does not perform any downloads itself.
Option D, terraform validate, checks your configuration files for syntactical correctness and internal consistency but does not involve downloading or initializing providers or modules.
The significance of terraform init extends beyond simply downloading plugins; it also configures the backend where Terraform state files will be stored and prepares the working directory. This command creates the hidden .terraform directory where all these components reside. Running terraform init ensures your environment is fully prepared for subsequent commands like terraform plan and terraform apply. Without initialization, Terraform will throw errors because it won't be able to locate the required providers or modules.
In summary, terraform init is the essential starting point that guarantees Terraform can communicate with the necessary cloud or infrastructure services by setting up all required dependencies before any actual planning or applying takes place. This makes it an indispensable first step in every Terraform workflow.
