HashiCorp Terraform Associate 003 Exam Prep
HashiCorp Certified: Terraform Associate (Page 18 )

• State is stored remotely in Terraform Cloud/Enterprise, not as a local file.
• Terraform runs (plan/apply) can be executed on remote infrastructure, with results visible in the remote workspace UI.
• Supports workspace-based organization, state locking, and concurrency control.
• Useful for team collaboration, centralized governance, and auditable logs.

• In your configuration, you use a backend block like backend "remote" { ... }.
• You still run terraform init to configure/migrate to the remote backend.
• After setup, terraform plan/terraform apply may be executed remotely, and the outputs/logs appear in the Terraform Cloud/Enterprise UI rather than (only) in your local terminal.

• Other backends store state remotely but typically do not provide remote execution; with the remote backend you get remote runs and a collaborative UI, not just remote state storage.

• Answer: B (False)

• Explanation: The terraform.tfstate file is a snapshot Terraform uses to map your configuration to real resources. It does not always stay perfectly in sync with the live infrastructure. Drift can occur if resources are changed outside Terraform or manipulated directly. You can reconcile this with commands like terraform plan (to see what would change) and terraform refresh (to update the state). The state stored in a backend reflects the last known state, not a guaranteed real-time reflection of reality. See Terraform state documentation for details.

• Answer: False

• Why: The terraform.tfstate file is a snapshot of the resources as Terraform last applied or refreshed them. If someone or something changes infrastructure outside Terraform (drift), the state file may no longer match the real world until you refresh or re-apply. Terraform normally refreshes state during plan/apply, but it is not guaranteed to always be perfectly in sync without a refresh.

• A: Daily involvement is unnecessary and may not solve the availability problem.
• C: Clarifying all requirements at the start conflicts with agile’s iterative refinement.
• D: Simply reviewing based on availability leaves the problem unresolved and allows rework to continue.

• prompt: the input or instruction given to the model
• completion: the desired response

json 
{"prompt":"Summarize this customer complaint.","completion":"The customer reports a delayed shipment."}

• B: A .txt file containing CSV-style lines is not automatically a valid fine-tuning dataset. The required structure and format must match the selected Bedrock model.
• C: Provisioned Throughput provides dedicated inference capacity; it does not fine-tune a model.
• D: Journals and textbooks might support domain adaptation or pretraining, but they do not provide the prompt-to-answer examples typically required for supervised fine-tuning.

• The explanation states that Traffic Analytics can be enabled by a user with one of these subscription-level roles:

• Question 34 — Network Contributor: Yes
• Question 35 — Owner: Yes
• Question 36 — Reader: Yes, according to the stated explanation and documentation

python 
def add_integers(a, b): 
    return a + b

• Uses def to define a function.
• Accepts two parameters, a and b.
• Uses return to send their sum back to the caller.
• Uses indentation to define the function body.

python 
result = add_integers(3, 4) 
result is 7

• Inherent risk: Risk that exists before controls are implemented.
• Avoided risk: Risk eliminated by choosing not to perform the risky activity.
• Operational risk: Risk arising from failures in processes, people, systems, or daily operations.

• Azure Resource Manager (ARM) templates define Azure resources in a declarative JSON file.
• You can deploy the same template repeatedly for each business unit, ensuring that identical resources are created consistently.
• Templates reduce manual administrative effort and support repeatable, automated deployments.
• Parameters can customize values such as names, regions, and sizes while keeping the overall resource configuration the same.

• Honeypots: Decoy systems or services made to attract attackers. Legitimate users should not interact with them, so activity there is a strong indicator of malicious behavior.
• DNS sinkholes: Redirect requests for known malicious domains to a controlled internal system. This can reveal infected hosts attempting to contact command-and-control infrastructure.

• Tokenization: Replaces sensitive data with non-sensitive tokens.
• CI/CD: Automates software development, testing, and deployment.
• Threat modeling: Identifies and analyzes potential threats before or during system design.
• Data obfuscation: Makes data harder to understand or interpret.

1. Selling price per unit: $750
2. Required annual return:

1. Required profit per unit:

1. Target cost per unit:

• View/inspect configuration: Possible.
• Modify the installed application or its S-Controls: Typically restricted in a test-drive org.

• Failed login attempts
• The account being targeted
• The source user or system
• Time and frequency of attempts

• Two-factor authentication: Helps prevent unauthorized access, but does not primarily detect the employee’s attempts.
• Firewall: Controls network traffic; it generally does not monitor individual login attempts.
• Intrusion prevention system (IPS): Can detect certain network attacks, but this scenario is best addressed through authentication and audit logging.

• Matching hashes suggest the file has not changed.
• Different hashes indicate that the file was modified, whether authorized or unauthorized.

• Backup: Helps recover the previous version but does not identify or stop unauthorized changes.
• File labels: Classify or mark files; they do not verify integrity.
• Security audit: May discover weaknesses or improper changes, but is periodic and not a direct technical integrity control.

Flat organisation

• Few levels of management
• A wide span of control—managers supervise many employees
• Shorter communication channels
• More employee autonomy and quicker decisions
• Fewer formal promotion levels

Tall organisation

• Many levels of management
• A narrow span of control—managers supervise relatively few employees
• A clear hierarchy and reporting structure
• More formal supervision and communication channels
• More obvious promotion and career stages

• Interactive development and exploration
• Small datasets
• Lightweight transformations or testing
• Avoiding the overhead and cost of multiple workers

• Automated reports: Jobs may benefit from job clusters or SQL warehouses.
• Working with SQL in Databricks SQL: Databricks SQL warehouses are the relevant compute option.
• Automatically scaling for larger data: A multi-node cluster with autoscaling is more suitable.
• Large amounts of data: Distributed worker nodes are generally needed.

• Create a record-triggered Flow on Opportunity.
• Run it when the record is created or updated.
• Add entry criteria such as Probability > 50%.
• Use Create Records to create the related Sales Demo Request, populating its Opportunity lookup.

• Apex Trigger: Possible, but unnecessary custom code for a straightforward automation requirement.
• Workflow Rule: Cannot create a related custom record.
• Process Builder: Could create a record, but Flow is Salesforce’s preferred and more capable declarative automation tool.

• Looking up accounts, contacts, and opportunities
• Logging calls and updating Salesforce records
• Accessing previously available customer information when temporarily offline

• Salesforce Touch App: Primarily an older tablet-focused experience, not the best general solution for the sales team.
• Custom hybrid app: Unnecessary development when Salesforce provides the required capabilities natively.
• SalesforceA: Intended mainly for Salesforce administrators, not sales representatives.

• The inference container image or built-in algorithm
• The location of model artifacts in Amazon S3
• IAM permissions through the execution role
• Optional environment variables and networking settings

1. Create AWS::SageMaker::Model
2. Create an AWS::SageMaker::EndpointConfig that references the model
3. Create AWS::SageMaker::Endpoint that references the endpoint configuration

• AWS::SageMaker::Endpoint hosts a model but does not define the model itself.
• AWS::SageMaker::NotebookInstance provides a development environment.
• AWS::SageMaker::Pipeline orchestrates ML workflow steps.

• Multi-factor authentication
• A secure password change for users whose credentials may be compromised

1. Get Data ? Folder in Power BI Desktop.
2. In Power Query Editor, expand the Attributes column to expose metadata such as hidden status and other file attributes.
3. Remove the Content column (and any other data columns you do not need).

• Name
• Extension
• Date accessed
• Date modified
• Folder Path
• Attributes
• Content

• Assign users or their team an appropriate security role.
• Ensure the role has the required table privileges, such as read, create, write, and append.
• Share the app with that security role in the app designer.

• Dynamics administration center: Used for environment and service administration, not routine app access configuration.
• Manage Roles: Not the specific Dataverse area used to define app and data permissions.
• Security Roles: Define what users can access and which operations they can perform.

• A: Person Accounts cannot be merged directly with standard Contact records.
• C: There is no Account Setup option that automatically merges Person Account duplicates.
• D: Matching rules and duplicate rules can help identify or prevent duplicates, but they do not automatically merge Person Accounts. Also, relationship considerations do not change the basic merge capability.

• C — Schema.describeSObjects(new String[]{myObject})[0].fields.getMap()

• D — Schema.getGlobalDescribe().get(myObject).getDescribe().fields.getMap()

• A: sObjectType is not used this way, and fieldSet() is not the appropriate method for retrieving all fields.
• B: mySObject.myObject is not valid dynamic Apex syntax.

1. The sender hashes the original message and sends the message plus its hash.
2. The receiver applies the same hashing algorithm to the received message.
3. The receiver compares the newly calculated hash with the sender’s hash.
4. Matching values indicate that the message was not altered in transit.

• A binary image is not the normal description of a hash result.
• Using a different algorithm produces a different type of digest, so the values cannot be directly compared.
• Hashing verifies integrity, but by itself does not prove who sent the message. Digital signatures or MACs address authentication and integrity together.

• vSmart controls the overlay control plane. It uses OMP to exchange routing information, distribute policies, and determine how WAN Edge devices reach one another.
• vManage is the centralized management and configuration platform.
• vBond is the orchestrator. It helps devices authenticate, discover controllers, and traverse NAT during onboarding.
• APIC-EM is not the SD-WAN control-plane component described here.

• Workspace: Stores notebooks, libraries, jobs, and other project resources.
• Notebooks: Interactive documents containing code, queries, visualizations, and explanations. Common languages include Python, SQL, Scala, and R.
• Clusters: Groups of virtual machines that run Spark workloads. Clusters can be started, stopped, and automatically scaled.
• Data access: Databricks can read from services such as Azure Data Lake Storage, Azure Blob Storage, and Azure SQL.
• Jobs: Automate notebooks or data-processing workflows on a schedule or in response to events.

• How quickly the vendor must respond to an incident or request
• Target resolution times
• Availability or uptime requirements
• Performance metrics and penalties for not meeting them

• SOW (Statement of Work): Describes the project’s scope, tasks, deliverables, and timeline.
• MOA (Memorandum of Agreement): Documents a formal agreement to cooperate or perform specific activities.
• MOU (Memorandum of Understanding): Records a mutual understanding or intent, often less binding than a contract.

• B. Data loss prevention (DLP): Helps prevent sensitive data from being copied, emailed, or exfiltrated. It is not the primary control for protecting a stolen laptop’s stored data.
• C. Operating system hardening: Reduces vulnerabilities by disabling unnecessary services and applying secure settings, but it does not necessarily protect the files if the disk is accessed directly.
• D. Boot security: Helps ensure the device starts only through trusted software or approved processes. It supports platform integrity but does not itself encrypt stored files.

• Create Power Query parameters for the Azure SQL server/database—or at least the database name.
• Use the parameter in the PBIX connection.
• Publish the same PBIX separately to the relevant development, test, and production workspaces.
• Set each dataset’s parameter value in the Power BI service so it points to the corresponding Azure SQL database.

• Development dataset ? DevelopmentDB
• Test dataset ? TestDB
• Production dataset ? ProductionDB

• The same PBIX is used for every lifecycle stage.
• Each stage consumes data from its matching database.
• Deployment pipelines are not required.
• Azure SQL is a cloud source, so gateway administration is generally avoided.
• Only the parameter value differs between published datasets, reducing maintenance.

• The listener has a virtual IP address on the load balancer.
• The active SQL Server replica must respond using the listener’s IP address, not its own VM IP.
• Floating IP allows the listener IP to be preserved and returned by the active replica.
• This is required for the SQL Always On listener configuration.

• A health probe for the SQL listener/cluster role
• The SQL Server listener port, commonly 1433
• Appropriate backend pool membership

• tag=Priv searches the tag field for values beginning with Priv. The wildcard can match the remaining characters, so it matches Privileged.
• tag=Priv would search for the exact tag Priv, not Privileged.
• tag=priv* uses lowercase priv; tag matching is treated as case-sensitive here, so it may not match the tag Privileged.
• tag=privileged uses the wrong capitalization for the exact tag.

• 800 devices ? a scalable, centralized solution is needed.
• Four hardware/vendor classes ? the tool must handle different drivers and images.
• Two user groups ? it should allow different configurations for each group.
• “Distribute custom images” ? an imaging/deployment tool is required, not just a file-copy utility.

• Compensating control: The server is end-of-life, so it may no longer receive security patches or support. Placing it on a restricted VLAN provides an alternative layer of protection by reducing who can access it and limiting its exposure.
• Technical control: VLAN segmentation and access control lists (ACLs) are technology-based mechanisms that enforce network access restrictions automatically.

• Managerial: Policies, procedures, and governance—not network configuration.
• Physical: Locks, guards, or barriers.
• Corrective: Restores systems after an incident.
• Detective: Identifies suspicious activity rather than restricting access.
• Deterrent: Discourages behavior but does not enforce access rules.

• Secure: uses encryption, such as HTTPS or SFTP.
• Cross-platform: supported by many languages and operating systems.
• Internet-friendly: designed to communicate across networks, usually using standard Internet protocols.

• JSON/REST over HTTPS — widely supported, secure, and Internet-friendly.
• SOAP over HTTPS — also secure and highly cross-platform, though more heavyweight.
• XML over SFTP — secure file-based exchange, but it is not an API-style interface.

• B — Prompts and suggestions retained for 28 days
• C — User engagement data kept for two years

• The key distinction is between content data—your prompts, code context, and generated suggestions—and engagement data, such as usage activity.
• Do not confuse retention with training: enterprise Copilot data is generally not used to train GitHub’s models without appropriate authorization.
• For a current exam, verify the policy version cited by the exam provider. The key’s C is likely correct, but B should be treated cautiously and may no longer reflect the current policy.

• A. Microsoft 365 group with Assigned membership
• C. Microsoft 365 group with Dynamic User membership

Why?

• Assigned membership: You explicitly add User1, User2, and User3.
• Dynamic User membership: Membership is automatically determined by a rule based on user attributes.

Why the other options are incorrect

• B and D: Security groups do not support the Microsoft 365 group expiration policy.
• E: Dynamic Device groups are intended for devices, not these users, and are also security groups.

kusto 
Event 
| summarize make_set(EventID) by Computer

• summarize groups records.
• by Computer creates one result row per virtual machine.
• make_set(EventID) returns an array containing unique event IDs for that computer.

kusto 
| summarize make_list(EventID) by Computer

• A — Custom Button: A button can launch a flow, typically by passing the flow’s URL and record context.
• D — From a Process: A Process can invoke a flow using an Apex action configured for flow invocation. However, this is automation-triggered, not directly accessed by a user.
• B — Quick Action: In current Salesforce functionality, a Flow Quick Action can launch a screen flow directly from a record page. This makes B a valid modern method.
• C — Visual Workflow Launcher: This is not generally listed as a standard access method in current Salesforce terminology; Salesforce commonly uses the Flow component on Lightning pages instead.

• A — IDS attack signatures: An IDS generally detects suspicious network activity but does not necessarily scan uploaded PDF files or prevent them from being accepted.
• C — Load balancer: Distributes traffic among servers; it does not inspect files for malware.
• D — WAF command-injection blocking: A WAF can help block web attacks such as command injection, SQL injection, and cross-site scripting, but this option does not specifically address malicious PDF uploads.

• Dynamics 365 Remote Assist — used for remote collaboration and mixed-reality scenarios.
• Dynamics 365 Finance — supports financial and operational management.
• Dynamics 365 Business Central — designed primarily for small and medium-sized businesses’ finance and operations.
• Dynamics 365 for Phones — provides mobile access to Dynamics 365 apps, including Sales, through the mobile Unified Interface.

• Employees can use approved devices from remote locations or worldwide offices.
• Users do not need to carry or insert extra hardware.
• It helps prevent account takeovers from unknown devices.

• Geotagging: Restricts access based on location, which could interfere with remote work and travel.
• Smart cards: Require additional physical equipment and card readers.
• Time-based logins: Limit access according to time but do not strongly bind access to an authorized user device.

• Vertical scaling (scale up) means increasing the size of an existing VM—for example, adding CPU or RAM.
• Vertical scaling down means reducing the VM’s size when less capacity is needed.
• Horizontal scaling (scale out) means adding more VM instances rather than making one VM larger.
• Elasticity is the broader ability to automatically adjust resources based on demand; it does not specifically mean adding CPU or memory to one VM.
• Agility refers to the ability to provision or change resources quickly.

• Azure Cosmos DB is a globally distributed NoSQL database service. It stores and retrieves application data, but it does not provide the tools needed to build, test, and deploy predictive analytics models.
• Azure Machine Learning—including the historical Azure Machine Learning Studio—is designed for the machine-learning lifecycle:

• Restarting the device: may fix software problems, but not a directional connection issue.
• Swollen battery: is a safety concern, but would not typically cause recognition only in one orientation.
• Failing cable: possible in general, but less likely because it works on other similar devices.
• Dirty or damaged port: best matches the symptoms. Inspect and carefully clean the port, or have it serviced if damaged.

python 
import azure.cognitiveservices.speech as speechsdk 


speech_config = speechsdk.SpeechConfig( 
    subscription="YOUR_KEY", 
    region="YOUR_REGION" 
)

Important Azure Speech SDK classes

• SpeechConfig

• AudioConfig

python 
  audio_config = speechsdk.audio.AudioConfig( 
      use_default_microphone=True 
  )

• SpeechRecognizer

python 
  recognizer = speechsdk.SpeechRecognizer( 
      speech_config=speech_config, 
      audio_config=audio_config 
  )

• SpeechSynthesizer

• AudioOutputConfig

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