Pegasystems PEGAPCSA84V1 Exam Prep
Pega Certified System Architect (PCSA) 87V1 (Page 6 )

1. Create a temporary Onboarding OU.
2. Move the new account into it.
3. Move the restrictive SCPs from the organization root to the Production OU.
4. Allow the account to update AWS Config.
5. Move the account into Production after onboarding.

• An SCP attached at the organization root applies to every account and OU beneath it.
• An SCP attached to the Production OU applies only to accounts in that OU.
• Therefore, moving the restrictive SCP from the root to Production temporarily exempts the onboarding account without weakening the policies for existing production accounts.
• Once onboarding is complete, moving the account into Production subjects it to the normal restrictions.

• Tokens: Individual units of text processed by a model, such as words, subwords, or characters.
• Models: Systems that learn patterns and generate predictions or outputs.
• Binaries: Data represented using the binary number system, not semantic representations.

• Data owners: Decide who should have access and approve the access rules.
• Business process owners: May help define business requirements, but normally do not enforce technical permissions.
• Security steering committee: Provides governance and direction; it does not manage individual access rights.
• Security administrators: Apply and enforce the approved access controls.

Box 1: No

• configure_azure_monitor() configures Azure Monitor and the OpenTelemetry pipeline.
• LangChain requires its own instrumentation or callback tracer, such as AzureAIOpenTelemetryTracer.
• You must pass the tracer to the LangChain execution configuration so chains, tools, prompts, and model calls become spans in Application Insights.

Box 2: Yes

text 
OTEL_SERVICE_NAME=customer-agent 
OTEL_SERVICE_NAME=invoice-agent

Manager role

DAX 
Country[Manager] = USERPRINCIPALNAME()

• Sales
• Human Resources

CFO role

• See sales for all countries
• See no Human Resources data

• Do not restrict the Country table or Sales table.
• Apply a filter to Human Resources that always returns false, such as:

DAX 
FALSE()

• Labels control access and protection, not blanket exclusion.
• If the user has permission to open a labeled file—especially if the label allows authenticated users to view it—Copilot can use that file in a summary.
• If the label applies encryption and the user lacks the required usage rights, Copilot should not use the file or reveal its contents.
• Copilot honors the user’s existing permissions, so it should not expose labeled content to an unauthorized user.

• Key-based authentication: Provides an endpoint secured with API keys.
• Real-time REST access: Supports online inference through an HTTP/REST endpoint.
• No VM vCPU quota consumption: Microsoft hosts and manages the underlying infrastructure, so your subscription’s VM quota isn’t used.

• Batch: Intended for asynchronous, large-volume processing rather than real-time requests.
• Self-hosted container: You manage the infrastructure and typically need compute resources and quota.
• Standard: This is not the clearest deployment type for the stated requirements; the specific Foundry option is serverless API.

• A. Remove rows where Sales[Status] is Canceled

• E. Remove Sales[Canceled Date]

• B: Removing Sales_Date would remove information users need—the date portion.
• C: Changing Delivery_Time to Integer could alter its meaning or precision and is not necessarily safe.
• D: Splitting the date/time column creates additional columns rather than simply removing unnecessary data.

• 50% memory utilization baseline: The environment can be provisioned with excess capacity, leaving room for growth and workload spikes.
• Storage scalability: Cloud storage can generally be expanded as needed without redesigning the physical platform.
• Single circuit failure resilience: A properly designed IaaS provider uses redundant power circuits and infrastructure, so failure of one circuit should not take the platform offline.

• A — Dual PDUs: Helps with power redundancy but does not provide storage scalability.
• C — Network load balancing: Provides network-path resilience, not memory or storage scalability, and does not address a power-circuit failure.
• D — Multiple NAS devices: May improve storage capacity, but does not inherently provide power resilience or the required compute-capacity baseline.

• Label applied does not automatically exclude a file from Copilot.
• Encryption/usage rights determine whether Copilot can access the file’s content.
• If the user has no permission under Label2, File3 should be unavailable to Copilot for that user.
• File3’s label might be inherited by derived content only if File3 was actually processed and contributed by an authorized user; it should not be treated as contributing merely because it exists in the source set.

• Distinct values = 69

• Unique values = 4

• Insert is used when you are creating a new record. It saves the record to the table and then leaves the form.
• Update is used when editing an existing record. It saves the modifications and then leaves the form.

• A — Increased call deflection: o KCS disponibiliza conhecimento reutilizável para clientes e agentes, ajudando a resolver dúvidas sem abrir ou continuar chamadas.
• C — Reduced issue resolution time: os representantes reutilizam artigos e soluções já documentadas, acelerando o atendimento.
• E — Optimized use of resources: o conhecimento compartilhado reduz retrabalho e melhora o uso dos recursos da equipe.

• Periodic vulnerability assessments: Identify technical weaknesses but do not establish governance or ensure risks are managed.
• Established information security metrics: Help measure performance and report status, but measurement alone does not make governance effective.
• Advanced security technologies: Support security operations, but governance is primarily about direction, accountability, decision-making, and alignment with business objectives.

• 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.

• 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.

1. The original app version exists.
2. You create and publish a new version, so there are now two versions.
3. When you restore the previous version, Power Apps does not delete or overwrite the newer version. Instead, it creates another version based on the restored one.

• Original version
• Newly created and published version
• New version created by the restore operation

• netstat -tuln can show listening TCP ports.
• If the web service is not listening, or is bound only to 127.0.0.1, remote browsers cannot connect even though the server responds to ping.

• traceroute: Tests the path to the server, but ping already confirms basic reachability.
• tcpdump: Useful for detailed packet analysis, but it is more appropriate after checking whether a service is listening.
• arp: Helps troubleshoot local IP-to-MAC resolution, not an application-layer web connection.

• Report on the discount approval time for quotes

• Dashboard of opportunity stage duration

• Lead conversion trends measure lead-generation effectiveness, not opportunity closing time.
• Campaign ROI evaluates marketing performance, not delays in the sales process.

• A — Consumption-based pricing: AWS generally uses a pay-as-you-go model. You pay for the resources you consume rather than purchasing hardware upfront or paying for unused capacity.
• C — Economies of scale: AWS purchases and operates infrastructure at a very large scale, allowing it to reduce costs and pass some savings to customers through lower service prices.

• Perpetual licenses: These involve paying once for permanent software ownership and are not a primary AWS Cloud economic benefit.
• AWS Enterprise Support at no additional cost: Enterprise Support has an additional charge.
• Bring-your-own-hardware model: AWS provides and manages the underlying cloud infrastructure; customers do not normally bring their own physical servers.

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

• IaaS: You deploy and manage virtual machines, including the operating system and installed software. Azure manages the physical datacenter, hosts, and networking infrastructure.
• PaaS: Azure manages the infrastructure and operating system, while you deploy and manage your application code. Examples include Azure App Service and Azure Functions.

• \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.

• A — Improved management of storage space: Correct.

• B — Improved supplier relationships: Correct.

• C — Improved pricing decisions: Correct.

• D — Non-product-specific costs must be apportioned: Incorrect.

• E — Profitability of each customer group: Incorrect.

• Unfamiliar locations or IP addresses
• Anonymous or malicious IP addresses
• Leaked credentials
• Unusual sign-in behavior

• Architects design overall Splunk infrastructure and data strategy.
• Administrators manage configuration, access, and system operations.
• Knowledge Managers create and maintain knowledge objects such as data models, field extractions, and event types. They may support pivots, but they are not the primary users of them.

• Access List: controls whether a client is allowed or denied.
• Connect List: controls which wireless networks/APs a station may connect to.

• desktopwidth:i:1280
• desktopheight:i:1024

• Connection information: Controls connection-related settings, not the desktop resolution.
• Scaling plan: Controls when session hosts start, stop, or scale based on demand.
• Session behaviour: Controls behavior such as disconnect or logoff handling.
• Display settings: Specifically controls RDP display properties, making it the appropriate choice.

• A. IDS attack signatures: An IDS primarily detects suspicious network activity; it is not the best control for scanning uploaded documents for malware.
• C. Load balancer: Distributes traffic among servers and improves availability, but does not inspect files for malware.
• D. WAF: Protects web applications against attacks such as SQL injection and command injection. It may help secure the upload function, but malware scanning is the key requirement here.

• Regression predicts continuous numeric outcomes, such as house price, temperature, or sales amount.
• Linear regression assumes the target can be estimated from a linear relationship between the input features and the target.
• In Azure Machine Learning, you use a labeled dataset containing:

• Classification predicts a category or class, such as “spam” or “not spam.”
• Clustering groups similar records without a known label; it is an unsupervised learning technique.

• Custom domain: miami.weyland.com requires a paid App Service tier; Free and Shared are unsuitable.
• Two instances: Standard supports scaling to multiple instances.
• SSL: Standard includes SSL support.
• 12 GB storage: Basic provides only about 10 GB, so it does not meet the requirement. Standard provides substantially more storage.
• Cost minimization: Standard is the lowest tier among the choices that satisfies all requirements.

• CPU: Number of virtual CPUs and, where applicable, CPU reservations.
• Memory: Amount of memory and memory reservations.

• Network interface: Usually configured through the VM or workload networking configuration.
• PCI devices: Specialized hardware and not a standard VM Class resource in this context.
• Storage: Typically selected through storage policies or the VM’s storage configuration.

• Active-active routers: Provide redundant Internet connections/devices. Both can operate, so traffic can fail over or be load-balanced.
• Active-active firewalls: Avoid a single firewall becoming a failure point while maintaining security inspection.
• Load balancers: Distribute requests across multiple web servers. If one server fails, traffic can go to the other.
• Redundant power supplies: A server with separate power supplies should connect to independent power sources or circuits.
• UPS A and UPS B: Provide backup power and redundancy. Ideally, each power supply is connected to a different UPS.
• SONET ring: A ring topology provides alternate paths if a fiber link or segment fails.

• Unsafe images: Requires image/content moderation before the image is processed.
• Hidden instructions embedded in images: These are indirect prompt injections contained in untrusted image content or extracted text, not necessarily in the user’s typed prompt.

• A. Adjust resolution: Incorrect because an incompatible resolution usually causes no display, distortion, or an unsupported-mode message—not intermittent flickering.
• B. Swap the HDMI cable: Correct. Replacing the common, easily tested component is the appropriate troubleshooting step.
• C. Replace the projector: Incorrect because the issue also occurs with a monitor.
• D. Configure refresh rate: A mismatched refresh rate can cause visual problems, but the repeated flicker across displays points more strongly to the cable.

• 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.

• Active remediation actions role in Microsoft Defender for Endpoint

• Security Reader role in Azure AD/Entra ID

• Security Administrator is broader than necessary because it grants extensive security-management permissions, violating least privilege.
• Compliance Data Administrator is intended for compliance data management, not Defender for Endpoint remediation approvals.

• Injection
• Broken access control
• Authentication failures
• Security misconfiguration
• Cross-site scripting

• STIX: A standardized language and format for exchanging threat intelligence.
• OVAL: Used to describe and assess system vulnerabilities and configuration issues.
• Threat intelligence feed: Provides current indicators and intelligence about threats, but not necessarily a structured overview of common application exploitation methods.
• CVE: A catalog of individually identified, publicly disclosed vulnerabilities.

• nmap - 10.11.1.130 — a network scanning command; mitigated with controls such as firewalls, monitoring, or access restrictions.
• “Click this link to get your free gift card.” — a phishing or social-engineering message; addressed through user awareness, email filtering, and authentication controls.
• “Your connection is not private.” — indicates a certificate or TLS validation problem; addressed by correcting the certificate or secure-connection configuration.

• Unrestricted data mining: Data mining is not automatically a privacy violation. It becomes an issue when personal data is collected or used improperly.
• Identity theft: This is a possible consequence of inadequate privacy protection, but it is not the central focus of privacy regulations.
• Human rights protection: Privacy can be considered a human right, but this option is broader than the specific regulatory focus.
• Identifiable personal data: Regulations such as HIPAA focus directly on controlling the collection, use, disclosure, and protection of personal information.

• How quickly the vendor must respond to incidents or requests
• Availability or uptime requirements
• Resolution time targets
• Performance expectations and penalties for failing to meet them

• SOW (Statement of Work): Describes the work, deliverables, scope, and schedule.
• MOA (Memorandum of Agreement): Documents an agreement in which parties commit to specific responsibilities.
• MOU (Memorandum of Understanding): Records a general intention to cooperate; it may not be legally binding.

DAX 
Sales % of Total = 
DIVIDE( 
    [Total Sales], 
    CALCULATE( 
        [Total Sales], 
        ALLSELECTED(Products) 
    ) 
)

DAX 
Total Sales = 
SUM(Sales[SalesAmount])

Why ALLSELECTED is required

• The numerator, [Total Sales], is evaluated for the current product.
• ALLSELECTED(Products) removes the current product’s visual filter when calculating the denominator.
• It preserves filters applied at the report, page, or slicer level.

Why not ALL(Products)?

DAX 
CALCULATE([Total Sales], ALL(Products))

• PC A: 192.168.1.10/24
• PC B: 192.168.2.10/24

• Both PCs have a correct default gateway
• A router or Layer 3 switch connects the subnets
• Routing and firewall rules allow the traffic

• CSIRT: A team that responds to and manages security incidents.
• CVSS: A scoring system for rating the severity of vulnerabilities.
• SOAR: A technology platform for automating and coordinating security operations and incident response.

• Power BI dataset — Reuses the existing tables, relationships, and measures. You mainly create new visualizations.
• SharePoint folder — Connects to the source files, but you would need to rebuild the model and measures.
• Power BI dataflows — Primarily provide reusable data preparation; they do not automatically provide the existing report’s measures and model.
• Excel workbook — Requires reconnecting to and modeling the source data again.

• Bronze: Raw ingested data
• Silver: Cleaned, validated, and transformed data
• Gold: Business-level data for analytics, dashboards, and reporting

• Confirming the data has the required columns and data types
• Handling missing or duplicate records
• Converting data into a suitable format
• Selecting or engineering useful features
• Splitting it into training, validation, and test sets

1. Prepare the training data
2. Select an algorithm or configure AutoML
3. Train the model
4. Evaluate its performance
5. Tune hyperparameters if needed
6. Deploy the model

• Fine-tuning requires a properly formatted training dataset.
• For classification or instruction-style fine-tuning, examples are supplied in JSONL format.
• Each line represents one training example, typically containing the input prompt and the desired completion or label.
• The file must then be uploaded or made available to the Microsoft Foundry fine-tuning workflow.

• A: Prompt Flow is useful for prompt experimentation, but it is not required to start fine-tuning.
• B: You do not need to deploy the base model to an online endpoint before fine-tuning.
• C: Tracing supports observability and evaluation, but it does not prepare the fine-tuning job or dataset.

• Static IP address: Not needed if the workstation already has network connectivity.
• Subnet mask: Incorrect subnetting would usually prevent local communication, including pinging the server.
• Default gateway: Primarily affects communication outside the local network; it does not normally prevent finding an internal domain controller.

• Warehouse size: Larger warehouses use more credits per unit of time than smaller ones.
• Number of clusters: A multi-cluster warehouse can run multiple clusters, and each active cluster consumes credits. Therefore, increasing the maximum or active cluster count can increase consumption.

• Number of users: More users may cause more workload, but users themselves do not consume credits.
• Amount of data processed: Snowflake warehouses are not charged directly by the amount of data scanned. However, processing more data may cause the warehouse to run longer, indirectly increasing credits.