Amazon MLS-C01 Exam Prep
AWS Certified Machine Learning - Specialty (MLS-C01) (Page 24 )

• Conserve public IPv4 addresses: IPv4 addresses are limited, so many internal devices share a smaller number of public addresses through NAT.
• Reduce direct exposure: Private addresses are not directly routable from the public Internet, which helps reduce unsolicited access to internal devices.

• Customer: Dual
• Date: Dual
• Sales: DirectQuery
• SalesAggregate: Import

• Sales – DirectQuery: Near-real-time data should not rely on an imported cache. DirectQuery sends queries to the source when visuals are loaded, allowing recent sales data to appear.
• SalesAggregate – Import: A weekly refresh is sufficient, and imported data generally gives faster visual performance because it is stored in Power BI’s in-memory cache.
• Customer and Date – Dual: These are dimension tables used with both the DirectQuery Sales table and the imported SalesAggregate table. Dual allows Power BI to use cached data when possible, while still behaving appropriately in queries involving DirectQuery data. This can improve performance and reduce unnecessary limited relationships.

• A vulnerability scanner automates discovery of known vulnerabilities and misconfigurations across systems. It can contribute to a supply-chain assessment.
• A penetration test actively attempts exploitation and is usually limited to an agreed scope.
• SCAP standardizes vulnerability and configuration assessment data; it is not the analysis itself.
• Illumination tool is not a commonly defined CompTIA Security+ term.

• Vulnerability scanner: Finds technical weaknesses in systems, applications, or devices. It does not usually analyze the entire supply chain.
• Penetration test: Simulates attacks against a defined target to identify exploitable weaknesses. Its scope is narrower.
• SCAP (Security Content Automation Protocol): Provides standardized formats and methods for automating security configuration and vulnerability checks, rather than mapping the full supply chain.

• A. IDS attack signatures: Primarily detects suspicious network activity, not necessarily malware embedded in uploaded files.
• C. Load balancer: Improves availability and distributes traffic; it does not inspect documents for malware.
• D. WAF: Protects web applications from attacks such as SQL injection and command injection, but its primary role is not scanning uploaded PDFs for malware.

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

• 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.

• The product is already in production.
• The organization is examining the product’s functions and cost drivers.
• The objective is to reduce cost without reducing perceived value or required quality.

• Kaizen costing focuses on continuous, usually incremental, cost reductions during the manufacturing stage. It is not specifically the systematic examination of a product’s functions.
• Standard costing compares actual costs with predetermined standards; it is a control technique, not a product redesign method.
• Process innovation concerns developing significantly improved production processes, rather than analysing the product’s functions and value.

• Create a CodeCommit repository in the secondary Region.
• Use CodeBuild to run a Git mirror operation from the primary repository to the secondary repository.
• Use EventBridge to detect relevant repository events, such as a pull request being merged.
• Invoke a Lambda function, which starts the CodeBuild project.

• B: Amazon S3 is object storage, not a Git repository that developers can use as a CodeCommit remote.
• C: CodeArtifact is intended for packages and artifacts, not source-code repository mirroring.
• D: An AWS Cloud9 environment is not an appropriate automated replication mechanism and would require manual or persistent infrastructure management.

• C — “when the query finishes”

• D — “when the query began”

• Azure Resource Manager (ARM) templates define the virtual machines and related Azure resources declaratively. You can deploy the same template repeatedly, ensuring consistent VM sizes, networking, storage, extensions, and other infrastructure settings.

• PowerShell DSC extension applies and maintains the required Windows configuration inside each VM. DSC is state-based: if a setting changes or becomes incorrect, DSC can bring it back to the desired configuration.

• Azure Pipelines deployment groups organize deployment targets, but they do not primarily enforce ongoing VM configuration.
• Custom Script Extension runs setup scripts, but it is generally less maintainable and does not continuously enforce configuration like DSC.
• Pipeline stage templates reuse pipeline workflow definitions; they do not configure the VMs themselves.

• Understating expenses and liabilities
• Overstating profit
• Misleading users of the financial information
• Potentially breaching integrity, objectivity, and professional competence and due care

• Employees can work from any location, including remote sites and offices worldwide.
• Login can be relatively seamless after the device is registered.
• It does not require distributing additional physical authentication equipment.

• Geotagging: Identifies location, but location alone is not a strong authentication method and may prevent legitimate remote access.
• Smart cards: Provide strong authentication but require card readers and physical cards, increasing equipment and management requirements.
• Time-based logins: Typically involve one-time codes that users must enter, making the experience less seamless and potentially requiring a token or authenticator app.

• R-squared: Typically used for regression, not classification.
• RMSE: Measures prediction error for continuous numerical values, so it is not the best fit here.
• Learning rate: A training hyperparameter that controls how quickly the model updates its weights; it is not an evaluation metric.

• Required response and resolution times
• Availability or uptime targets
• Performance standards
• Support obligations
• Remedies or penalties for failing to meet the terms

• SOW (Statement of Work): Defines the project’s scope, tasks, deliverables, and schedule.
• MOA (Memorandum of Agreement): Describes agreed responsibilities between parties, often for a specific activity.
• MOU (Memorandum of Understanding): Records a mutual understanding or intention, usually less formal than a contract.

• 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.

• Data loss prevention (DLP): Helps detect or prevent sensitive data from being copied or transmitted, but it does not primarily protect a stolen laptop’s stored data.
• Operating system hardening: Reduces vulnerabilities and attack surface but does not encrypt files if the device is stolen.
• Boot security: Helps ensure that only trusted software starts, but it does not fully protect the drive if an attacker accesses it offline.

• The type of change: standard, normal, or emergency
• The risk, impact, and complexity
• The change model being used

• A standard change may be pre-authorized through its change model.
• A normal change may require assessment and approval by an appropriate change authority.
• An emergency change may be authorized by an emergency change authority, often using an expedited process.

• Change authorities are not only needed for emergency changes.
• They are not assigned only when a change is deployed.
• They are not only required for normal changes.

• 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.

• Owner, Contributor, and Network Contributor provide sufficient management permissions.
• Reader can view Traffic Analytics data but cannot enable or configure it.

• SQL injection (SQLi): Attacks databases by inserting malicious SQL commands.
• Cross-site scripting (XSS): Injects scripts into web pages viewed by other users.
• Sideloading: Installing an application from outside the official app store. It may install unauthorized apps, but it does not generally unlock the operating system or enable restricted system features.

• Password spraying: Tries a few common passwords against many accounts; no indication of repeated login attempts.
• Remote-access Trojan (RAT): Could install malware, but it does not explain how the attacker obtained the administrator’s credentials.
• Dictionary attack: Tries words or common passwords against an account; again, the scenario specifically highlights Telnet’s lack of encryption.

• 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.

• C: Develop the rule in the Rules Editor, define the events, match, and condition sections, then use the test rule feature. This directly validates the YARA-L rule without enabling it in production.
• A: UDM Search can help investigate data and refine filters, but it does not fully test YARA-L logic—especially complex event joins, match windows, and conditions.

• Two-part tariff pricing: $10 per unit
• Dual pricing: $20 per unit

Two-part tariff pricing

Dual pricing

• Division X, the seller, is credited with the market price: \(\$20\)
• Division Y, the buyer, is charged the marginal cost: \(\$10\)

• Server provisioning
• Operating systems and runtime infrastructure
• Scaling
• Much of the maintenance and patching

• Thin clients reduce endpoint hardware requirements but do not specifically streamline code deployment.
• Private cloud provides dedicated cloud infrastructure but usually requires more management and expense.
• Virtual machines improve resource utilization, but administrators still manage the VMs, operating systems, and deployments.

• Issuer: Identifies the party issuing a SAML message—usually the identity provider in the assertion. It is not the Salesforce-specific identifier the architect should provide for differentiating Salesforce.
• Identity Provider Login URL: The endpoint where users are sent to authenticate.
• SAML identity location: Determines where the user identity is found in the SAML assertion, such as the subject or an attribute.

• Accept: Acknowledge the risk and choose not to take additional action.
• Transfer: Shift the risk or its financial impact to another party, such as through insurance or outsourcing.
• Mitigate: Reduce the likelihood or impact of the risk, such as by implementing security controls.
• Avoid: Eliminate the activity or condition that creates the risk.

• Personally identifiable information (PII) detection

• Prompt Shields

• Self-harm content filtering addresses self-harm-related content.
• Violence content filtering addresses violent content.
• Neither protects customer PII or detects document-based prompt injection.

• Code signing: Verifies the software’s authenticity and integrity; it does not hide the source code or prevent reverse engineering.
• Tokenization: Replaces sensitive data with tokens, mainly for protecting data such as payment information—not software logic.
• Blockchain: Provides a tamper-resistant record of transactions or data; it does not protect compiled code from analysis.

CIMA P3 topics

• IT governance and systems strategy
• Systems development and implementation
• Change and project governance
• Strategic and business risk

• A — Plan for new systems: The committee should help identify and prioritise systems requirements and ensure planned systems support organisational needs.
• D — Consider competitive issues: New information systems may affect Y’s competitive position, service quality and efficiency. These strategic implications should be considered.
• E — Ensure the system meets company goals: This is a key governance responsibility. The committee should ensure the project remains aligned with Y’s objectives and delivers business value.

• B — Develop new systems: Detailed system development should be performed by IT specialists and project teams, not the steering committee.
• C — Manage the project: The project manager should handle day-to-day project management. The steering committee should provide oversight, challenge and key decisions, rather than manage daily activities.

• Continuous deployment: Automates software releases; it does not specifically test input handling.
• Static code analysis: Examines source or compiled code without executing it. It can find coding flaws but does not directly stress the application with malformed inputs.
• Manual peer review: Developers inspect code or design manually. Useful, but not the best practice specifically for testing how a live product handles invalid input.

• Application management: Controls which apps can be installed or used; it does not remove existing data after theft.
• Full-disk encryption: Protects data when the device is powered off or locked, but it may not help if the attacker has already unlocked the device.
• Containerization: Separates corporate data from personal data, but the attacker may still access the corporate container using the stolen credentials.

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

Question 3: AWS Storage Gateway File Gateway

• A: S3 bucket per user — S3 is object storage, not a traditional shared file system; mounting it requires extra tools and is less efficient.
• B: File Gateway — Provides a local file share using standard file protocols while storing files in Amazon S3. This preserves convenient local access and extends storage capacity.
• C: WorkSpaces and WorkDocs — Designed for virtual desktops and document collaboration, not large shared file storage.
• D: EC2 with EBS — EBS is attached to one EC2 instance and is not designed for direct multi-user file sharing.

1. Write a structured log entry to CloudWatch Logs containing:

1. Create a CloudWatch Logs metric filter that:

text 
ApiRequests 
Operation=GetOrders 
ResponseCode=500 
Version=2.4.0

• B is incorrect: CloudWatch Logs Insights queries analyze logs but do not directly publish metrics in this manner.
• C is incorrect: ALB access logs do not contain arbitrary Lambda response metadata as custom fields.
• D is incorrect: X-Ray traces and insights are not the appropriate mechanism for creating these custom, dimensioned application metrics.

• The Subscribe to Reports user permission.
• At least Viewer access to the report’s folder.
• Access to the report itself.

• Subscribe to Reports: Run Reports is not the relevant Salesforce permission.
• Chatter Subscribe to Reports is not a Salesforce permission.
• Set Running User relates to configuring the user whose permissions determine report results—not subscribing to a report.

• A: Configure security groups — Customers define inbound and outbound rules for resources such as Amazon EC2 instances.
• B: Classify company assets — Customers decide how their data and assets should be classified and protected.

• C: Amazon S3 is a regional service; customers select a Region, not individual Availability Zones for buckets.
• D: AWS manages the infrastructure and patching for Amazon DynamoDB.
• E: AWS manages the infrastructure used by AWS Lambda; customers do not select EC2 instances for Lambda functions.

Correct choices

• DB1: Azure Data Box Heavy
• Virtual machines: Azure Migrate

Why

• Replication with minimal downtime
• A test migration
• Final cutover after validation

• Share of overall contribution: part of the organization’s total contribution is allocated to the supplying division.
• Dual pricing: the supplying division may record a higher transfer price while the receiving division records a lower price, with central accounts absorbing the difference.
• A centrally imposed price range: this may allow the transfer price to be set above variable cost, helping the supplying division recover fixed costs.

• VLAN 10 for data
• VLAN 20 for voice

• A: Describes physical trunking or logical switch ports, not an SVI.
• B: An SVI can provide management access, but that is only one use—not the best description here.
• D: SVI use is not related to running out of physical ports.

• 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.

• C series: CPU-optimized instances; not designed primarily for LLM training.
• G series: GPU instances generally optimized for graphics and some machine learning workloads, but not specifically large-scale model training efficiency.
• P series: Powerful GPU instances for ML training, but typically consume more energy than Trainium-based instances for suitable training workloads.

1. Define – establish the project’s objectives, scope, feasibility and requirements.
2. Design – plan how the project will be carried out, including resources, schedules and controls.
3. Deliver – execute the project and produce the required outputs.
4. Develop – close the project formally and capture learning for future projects.

• Filing documentation and records
• Closing project and accounting systems
• Settling costs
• Handing over the completed work and obtaining sign-off
• Reviewing performance and giving feedback

• Install unauthorized or unsupported software
• Access features blocked by the manufacturer or operating system
• Customize system behavior beyond normal settings

• Authentication — verifies who the user is.
• Authorization — determines what the authenticated user is allowed to access.
• Accounting — records session activity, such as login time and resource usage.

• CIA — confidentiality, integrity, and availability; core security objectives.
• ACL — access control list; rules that permit or deny traffic or access.
• PEM — Privacy Enhanced Mail, an older email security standard.

• Import: Copies data into the Power BI model. It requires scheduled or manual refresh, so it may not meet the two-minute requirement.
• Live connection: Connects to an existing Power BI semantic model or Analysis Services model; it is not the appropriate choice for connecting directly to the Azure SQL database in this scenario.

• Link-local — FE80::/10; valid only on the local link/subnet and not routed by routers.
• Multicast — FF00::/8; identifies a group of interfaces rather than a private address range.
• Global unicast — 2000::/3; publicly routable IPv6 addressing.

• The application failing to start or becoming unhealthy
• An incorrect probe path, port, or protocol
• The application needing more startup time
• Dependency or configuration failures
• A liveness probe being too aggressive

bash 
kubectl describe pod <pod-name> 
kubectl logs <pod-name> --previous

• Scale to more replicas: may hide the issue but does not diagnose it.
• Decrease initialDelaySeconds: makes probes run earlier and could worsen startup failures.
• Drain and reboot the node: node metrics are normal, so rebooting is not justified as the first step.