Avixa AVIXA-CTS Exam Prep
Certified Technology Specialist (Page 20 )

• Each driver: Z = 8 O.
• If drivers are in series, impedances add: Z_series = Z1 + Z2 + ... = 8 × (number in series).
• If drivers are in parallel, impedances combine as: 1/Z_parallel = 1/Z1 + 1/Z2 + ...; for identical drivers: Z_parallel = 8 O ÷ (number in parallel).
• For mixed arrangements, reduce step by step (combine small groups first, then combine those results).

• Four pairs in parallel, with the four pairs in series: each pair = 8||8 = 4 O; four in series ? 4 × 4 O = 16 O.
• Two banks of four in parallel, connected in series: each bank = 8||8||8||8 = 2 O; in series ? 2 O + 2 O = 4 O.

• Compare each server’s drive specifications and performance data.
• Identify the drive that is faulty, slow, or mismatched.
• Replace it with a drive that matches the required interface, capacity, and performance characteristics.
• Avoid selecting a slower drive, because storage performance can bottleneck the entire server.
• In a redundant array, use a compatible replacement so rebuilding does not create unnecessary performance degradation.

sql 
CREATE PROCEDURE dbo.usp_CreateOrder 
AS 
BEGIN 
    SET NOCOUNT ON; 
    SET XACT_ABORT ON; 


    BEGIN TRY 
        BEGIN TRANSACTION; 


        INSERT INTO dbo.Orders (/ columns /) 
        VALUES (/ values /); 


        SET @OrderID = SCOPE_IDENTITY(); 


        COMMIT TRANSACTION; 
    END TRY 
    BEGIN CATCH 
        IF @@TRANCOUNT > 0 
            ROLLBACK TRANSACTION; 


        THROW; 
    END CATCH; 
END;

• BEGIN TRY contains the transactional work.
• SCOPE_IDENTITY() retrieves the identity generated by the INSERT; it belongs after the insert, not as the error-handling logic.
• COMMIT runs only if all statements succeed.
• BEGIN CATCH handles failures.
• IF @@TRANCOUNT > 0 prevents attempting a rollback when no transaction is active.
• ROLLBACK undoes partial changes.
• THROW re-raises the original error with consistent details for the application.
• SET XACT_ABORT ON ensures many run-time errors automatically terminate and roll back the transaction.

• Amazon EC2 instances — ???????? ?? ?? ??????? CPU, memory ??? instance size ???????? ???????
• AWS Lambda functions — memory configuration ?????????? ???????
• Amazon EBS volumes — volume type ?? size optimize ???? ???????
• ??????? ECS workloads — resource configuration ? cost optimization-?? ???????

• Memory ? compute usage ?????????? ???? custom code ????? ???? development ? maintenance ??????
• Cost allocation tags ???? ????? ??? ?????? ???? ??????? ???; inefficient resource ??????? ?? recommendation ???? ???
• CloudTrail resource ???? ?? API activity ??????, resource utilization ????

• Honeypots: Deliberately vulnerable or attractive systems designed to lure attackers. Legitimate users should not access them, so activity on a honeypot is a strong indicator of compromise.
• DNS sinkholes: Redirect requests for known malicious domains to a controlled internal system instead of allowing the connection. This can identify infected hosts attempting to contact command-and-control infrastructure.

• Tokenization: Replaces sensitive data with non-sensitive tokens; it protects data but does not primarily detect attackers.
• CI/CD: Automates software development and deployment processes.
• Threat modeling: Identifies potential threats and weaknesses before or during system design.
• Data obfuscation: Makes data harder to understand, but it is not an attacker-detection method.

• Endpoint Manager: manages hosts and sensor-related settings.
• Falcon Investigator: supports investigation and analysis, but does not necessarily grant RTR access.
• Remediation Manager: handles remediation-related actions rather than interactive host access.

• Microservices: An application design approach that divides software into small services; it does not specifically reduce the number of operating systems.
• Containerization: Uses isolated containers that share the host OS kernel—best match.
• Virtualization: Creates separate virtual machines, and each typically requires its own guest OS, so it does not minimize OS instances as effectively.
• Infrastructure as code: Automates deployment and management of infrastructure; it does not describe the architecture being used.

• Response and resolution time frames
• Availability or uptime requirements
• Performance targets
• Support obligations
• Penalties for failing to meet requirements

• SOW (Statement of Work): Defines the project’s scope, tasks, and deliverables.
• MOA (Memorandum of Agreement): Describes cooperation and responsibilities between parties.
• MOU (Memorandum of Understanding): Records a general mutual understanding, usually without detailed enforceable service targets.

• B: Não é preciso implantar o modelo em um endpoint do Amazon SageMaker, pois o Bedrock já oferece a infraestrutura de inferência.
• C: O SageMaker Model Registry é usado para gerenciar modelos no SageMaker, não é requisito para modelos customizados no Bedrock.
• D: Não existe uma etapa geral de “conceder acesso” ao modelo customizado como requisito principal de uso. O ponto essencial é adquirir o Provisioned Throughput.

• 10 minutes have elapsed, or
• 20 MB of accounting data has accumulated

• Feedback form: Captures opinions, not necessarily actual behavior; users may not respond.
• Questionnaire: Relies on memory and subjective judgments about usefulness.
• Interviews: Can provide valuable qualitative insights, but a sample of users may not represent overall usage accurately.

• Error correction (ECC): Improves data reliability but does not maximize bandwidth.
• RAM voltage: Increasing voltage may affect stability or speed, but it is not the primary method for increasing module bandwidth.
• Physical module size: Refers to the capacity or form factor of the RAM, not its data-transfer bandwidth.

• Economy: Obtaining inputs at the lowest appropriate cost.
• Efficiency: Making the best use of resources, such as staff, money, and equipment.
• Effectiveness: Achieving the intended objectives or outcomes.

1. Discovery tries the SSH probe first.
2. SSH fails.
3. Discovery tries SNMP, which succeeds.
4. Discovery records SNMP as the preferred service for that IP.
5. Future discoveries try SNMP first.

• Classification identifies the type of device, such as a server, router, or printer.
• Credential affinity remembers which credentials work for a device.
• MID Server affinity associates a device or network with a particular MID Server.
• IP service affinity specifically controls the preferred discovery protocol or service.

• Customer information must not be revealed ? PII Detection
• Malicious instructions embedded in images/documents must be blocked ? Prompt Shields

• If the question allows multiple selections, choose PII Detection and Prompt Shields.
• If it requires one selection specifically for the image-based threat, choose Prompt Shields.

• Create and manage approved IT services as products
• Control which users can deploy those products
• Apply governance, permissions, and constraints
• Use and manage infrastructure-as-code templates, such as AWS CloudFormation templates

• AWS Resource Explorer: Helps find and browse AWS resources; it does not govern IaC deployments.
• AWS Organizations: Manages accounts, consolidated billing, and organization-wide policies.
• AWS Systems Manager: Provides operational management, such as patching, automation, and parameter storage, but it is not primarily used to catalog and govern IaC-based service deployments.

• Deterministic approve/reject results
• Strict adherence to predefined rules
• Consistent, reproducible outcomes
• Auditability and regulatory compliance

• Atomicity: a write fully succeeds or does not appear.
• Consistency: table state remains valid.
• Isolation: concurrent operations do not corrupt one another.
• Durability: committed changes persist.

• Flexible schemas: common data lakes often support flexible or schema-on-read data.
• Open-source formats: common data lakes commonly use open formats such as Parquet.
• Scalable storage: cloud data lakes already provide scalable storage.

• s3:GetObject for the relevant objects
• s3:ListBucket if listing is required
• Appropriate bucket and object resource permissions

• B: Making the bucket public is insecure and unnecessary.
• C: Prompt engineering cannot override AWS IAM or encryption permissions.
• D: Data sensitivity does not determine whether the role can access it.

• STP elects the switch with the lowest Bridge ID as the root bridge.
• The Bridge ID consists mainly of bridge priority + MAC address.
• If multiple switches have the same priority, the switch with the lower MAC address is preferred.
• STP bridge priority values are configured in increments of 4096, such as 0, 4096, 8192, and so on. 32768 is the standard default value.

• The CSV contains the external users’ email addresses.
• The bulk invitation feature supports inviting many guest users in one operation.
• Each invited user becomes a guest account in contoso.com.

• Sets a high initial price for a new product.
• Targets customers willing to pay more, often called early adopters.
• Gradually reduces the price to attract more price-sensitive customers as the product becomes less novel and competition increases.

• Penetration pricing: starts with a low price to gain market share quickly.
• Premium pricing: maintains a high price to communicate superior quality or status; it does not necessarily involve later price reductions.
• Loss leader pricing: sells one product at a very low price, sometimes below cost, to attract customers who may buy other products.

• Virus signatures: Primarily associated with antivirus or antimalware tools.
• Security agent deployment: Usually handled by endpoint-management or endpoint-security platforms.
• Vulnerability scanning: Performed by vulnerability-assessment tools, although a SIEM may ingest their results.

• Online payment fraud
• Account takeover
• Fake account creation
• Suspicious transactions

• Cloud architecture
• Data architecture
• Platform engineering
• Data engineering
• Provisioning and modernization

• Data protection is associated mainly with security and risk management.
• Data governance belongs to the governance perspective.
• Data science is not an AWS CAF capability.

• Ease of exploitation
• Required privileges
• User interaction
• Impact on confidentiality, integrity, and availability

• CVE: Identifies and names a specific publicly known vulnerability; it does not measure severity.
• OSINT: Refers to intelligence gathered from publicly available sources.
• SOAR: Automates and coordinates security operations, such as alert response and playbooks.

• Azure Machine Learning is the overall Azure service.
• Machine Learning designer is the visual, drag-and-drop interface within Azure Machine Learning.
• Microsoft may refer to the broader product as Azure Machine Learning studio, while “Designer” remains the specific visual workflow tool.

• Azure Logic Apps: Workflow and integration automation.
• Azure Batch: Large-scale parallel or batch compute.
• Azure Cosmos DB: Globally distributed NoSQL database.

yaml 
clusterIP: None

• CronJob: Runs Jobs on a schedule and normally does not need stable networking.
• Deployment: Manages interchangeable, stateless replicas and usually uses a regular Service.
• DaemonSet: Runs a Pod on selected nodes but does not inherently require stable Pod identities.

• Input validation: Prevents malicious or malformed input within an application; it does not authenticate a software package.
• Secure cookies: Protect web-session cookies; they do not protect downloadable software.
• Fuzzing: Tests software by supplying unexpected input to find vulnerabilities; it does not verify software integrity.

• Base table — the table containing common inherited fields
• Parent table — the table directly extended by the child
• Other tables in the hierarchy

• Managerial: policies, standards, risk management, governance
• Operational: procedures carried out by people, such as training, incident response, and backups
• Technical: firewalls, encryption, access-control systems
• Physical: locks, guards, cameras

• Third-party attestation: Provides independent validation, but is typically periodic and performed by an external party.
• Penetration testing: Simulates attacks to identify exploitable vulnerabilities; it does not primarily track compliance.
• Vulnerability scans: Identify technical weaknesses, but do not provide a detailed review of procedures or compliance activities.

• 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.

• Asynchronous inference is designed for applications that submit individual inference requests, place them in a queue, and retrieve results later. It is useful when requests may take a long time or when traffic is intermittent.
• Batch transform is designed specifically to run inference over an entire large dataset stored in Amazon S3 and produce an output dataset.

• Large dataset/offline processing ? Batch transform
• Large or slow individual requests processed later ? Asynchronous inference

• Transport and handling
• Storage and warehousing
• Refrigeration
• Shelf-stacking or replenishment
• Other costs directly attributable to product P

• Accept: Acknowledging the risk without taking additional action.
• Transfer: Shifting the risk’s impact to a third party, such as through insurance or outsourcing.
• Mitigate: Reducing the likelihood or impact of the risk through security controls.
• Avoid: Eliminating the activity or process that creates the risk.

• The requirement is to obtain an assessment of the Azure environment’s design.
• The proposed solution is the Premier support plan.
• Premier can provide this type of guidance, but it is a higher-tier, more expensive option.
• The question specifically says to keep costs to a minimum. A lower tier—typically Professional Direct in the support-plan model used by this question—provides architectural/design guidance.

• A — Securing information assets: This is the responsibility of management and operational/security teams.
• B — Validating protection: Correct. The auditor checks whether controls—such as access restrictions, encryption, retention, and handling procedures—match the asset’s classification.
• C — Ensuring alignment with regulations: Management and legal/compliance functions typically establish classification requirements; the auditor may assess compliance but does not primarily define alignment.
• D — Defining classification levels: This is a management responsibility based on business needs, risk, and regulatory obligations.

• A — If there is no demand, there should be no production.

• B — Not all sales equal profit.

• C — Stocking up on inventory is bad for business.

• D — All costs, except materials, are considered fixed.

• E — Departments should operate at full capacity regardless of bottlenecks.

• Access controls — ensuring only authorized users can access it.
• Encryption — protecting the data if it is intercepted or exposed.

• Disable default accounts: Default or unused accounts may have known usernames or predictable settings, making them targets. They should be disabled, removed, or securely configured.
• Remove unnecessary services: Every running service creates potential vulnerabilities. Removing services the server does not need reduces exploitable entry points.

• Add the server to the asset inventory: Important for asset management, but not a hardening step.
• Document default passwords: Default passwords should be changed or eliminated—not documented for continued use.
• Send server logs to the SIEM: Valuable for monitoring and detection, but generally performed as part of logging/monitoring configuration.
• Join the server to the corporate domain: May be necessary operationally, but does not itself harden the server.

• \Pipeline1
• \Folder1\Lakehouse1

• Pipeline1 remains at the workspace root in Workspace1, so it is deployed to the root of Workspace2.
• Lakehouse1 was moved into Folder1, so its full path is preserved as \Folder1\Lakehouse1.
• Fabric deployment pipelines preserve folder paths because an item’s full path is treated as part of its name.

Correct reasoning

• Create storage5 as a General-purpose v2 (StorageV2) account.
• Configure Blob object replication from storage5 to an existing compatible storage account.
• The destination must support object replication—typically another StorageV2 or premium block blob account.
• Blob versioning must be enabled on both accounts.
• Blob change feed must be enabled on the source account.
• The accounts must meet Azure’s object-replication requirements, including being in supported regions and having compatible configuration.

• Reduce the training data: Usually makes overfitting worse.
• Add hyperparameters: Hyperparameters already control training; simply adding them does not solve the problem. Proper tuning could help, but that is not what the option states.
• Increase training time: More training can worsen overfitting if the model is already memorizing the training data.

• A static IP gives the surveillance system a predictable local address, so users can reliably reach it on the LAN.
• However, a static IP does not block internet-based login attempts. If the router exposes the device through port forwarding, attackers could still reach it.
• Port mapping normally exposes an internal service externally, so A is a poor choice as written.
• Subnetting alone also does not block traffic; it would require routing/firewall rules.

• Microsoft Foundry is an enterprise platform for developers, data scientists, and IT teams.
• It supports the full AI application lifecycle: selecting models, connecting enterprise data, developing, evaluating, deploying, monitoring, and scaling solutions.
• It can include visual tools and low-code experiences, but it is not primarily designed to enable business users to build complete generative AI solutions independently.

• B: You still need to select and configure an appropriate model.
• C: Business users may participate through visual tools, but they are not the primary target audience.
• D: Foundry includes low-code tools, but it is not fundamentally a low-code-only platform.

• transform() — modifies every element in an array
• filter() — keeps elements matching a condition
• exists() — checks whether any element matches
• aggregate() — reduces array elements to one result

sql 
SELECT transform(scores, x -> x * 2) 
FROM student_scores;

• A is incorrect because higher-order functions are mainly useful for nested or complex data.
• B is incorrect because they do not convert logic into Python.
• D is incorrect because their purpose is not to fix slow built-in functions, but to process arrays or maps with custom logic.

• The servers are powered on.
• The network is functioning.
• Devices can still reach the server network.

• ARP poisoning: Redirects or intercepts local network traffic; it usually affects communication paths rather than overwhelming a service.
• Jamming: Disrupts wireless or radio signals. It would not fit a system that remains accessible from devices on the server network.
• Kerberoasting: Attempts to crack service-account credentials from Kerberos tickets; it does not normally cause an immediate outage.

• If the hashes match, the software has likely not changed.
• If they differ, the software was modified or corrupted.

• Encryption: Protects confidentiality by making data unreadable; it does not primarily verify that software was unchanged.
• Baselines: Establish expected configurations or states, but hashing is the specific method for checking file integrity.
• Tokenization: Replaces sensitive data with non-sensitive tokens and is unrelated to software integrity.

• Matching hashes: The software likely has not changed.
• Different hashes: The software was modified or corrupted.

• Encryption: Protects confidentiality by making data unreadable; it does not primarily detect changes.
• Baselines: Define an approved system or configuration state, but they are not the specific integrity mechanism here.
• Tokenization: Replaces sensitive data with substitute values.