Huawei H35-911 Exam Prep
HCS Microwave Hardware Installation (Written) (Page 2 )

• 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.

• 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.

• Scheduling overlapping working hours for critical collaboration
• Assigning independent tasks that can proceed asynchronously
• Adding clear handoffs between offices
• Documenting decisions, questions, and required inputs
• Building appropriate time into the schedule for responses

• Internal hostnames and subdomains
• Network structure and naming conventions
• Servers and services
• Relationships between systems

• Determining ISP-assigned address space: Usually involves external registration and DNS information, not internal host discovery.
• Bypassing DNS sinkholing: Would require evidence that malicious DNS requests avoided redirection.
• Initial access: DNS queries alone do not show that the attacker gained access.
• Exfiltrating data: DNS tunneling can do this, but the snippet would typically show encoded or unusually long DNS queries.

• 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.

• 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.

• Domínios personalizados.
• Armazenamento suficiente.
• Instâncias dedicadas.
• Balanceamento de carga.
• Menor custo entre os planos que atendem a tudo.

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

• Menerjemahkan soal ke bahasa Indonesia.
• Menyebutkan jawaban yang benar.
• Menjelaskan alasan jawaban tersebut.
• Memberi tahu jika kunci jawaban yang tersedia tampaknya keliru.
• Menjelaskan istilah teknis penting dalam soal.

• Escape to host: A virtualization attack where code escapes a guest VM and accesses the host system. Nothing in the scenario mentions virtualization.
• Browser extension: Can redirect or manipulate web-browser traffic, but not normally database-server traffic.
• Valid accounts: Describes using stolen or compromised credentials, not redirecting network traffic.
• Process injection: Injecting malicious code into a legitimate database or networking process could allow an attacker to alter how that process handles outgoing traffic.

1. You try to access a cloud application, such as accounting software.
2. The application redirects you to the company’s IdP.
3. You authenticate with the IdP.
4. The IdP sends a digitally signed SAML assertion to the application.
5. The application validates the assertion and grants access.

• The user’s identity
• Whether authentication succeeded
• Roles or group membership
• Access-related attributes

• 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.

• 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.

• The requirement is an assessment of the Azure environment’s design, which requires a support plan offering proactive architectural guidance.
• Premier support would provide this capability, but it is a high-cost option.
• Since the requirement says to minimize expenses, Premier is not the best recommendation.
• A lower-cost plan with the required advisory/design-review capability—historically Professional Direct in Azure’s support-plan model—would be more appropriate.

• A. IDS attack signatures: An IDS primarily detects suspicious network activity; it is not the best tool for scanning uploaded files.
• C. Load balancer: Improves availability and distributes traffic but does not inspect files for malware.
• D. WAF: Protects web applications against attacks such as SQL injection and command injection. It may inspect HTTP requests, but malware scanning of uploaded PDFs is the key requirement here.

• AWS AppSync is designed for serverless applications that need to retrieve and combine data from multiple sources.
• A pipeline resolver can invoke multiple functions or data-source resolvers, including resolvers connected to different DynamoDB tables.
• The application can receive the combined result through one GraphQL request, without requiring custom aggregation logic in the application.
• This is operationally efficient because AppSync manages the API layer and resolver execution.

• Athena Federated Query is intended primarily for analytics and ad hoc querying, not low-latency application data retrieval.
• Querying DynamoDB through Athena can consume DynamoDB read capacity and may affect table performance.
• It also introduces analytical-query overhead and is not the normal choice for a microservice web application.

• NIDS: Monitors network traffic for suspicious activity and network-based attacks targeting the application or its supporting services.
• HIPS: Protects an individual host by monitoring processes, files, and system activity. It can help secure the web server, but it is not focused specifically on the application’s network attack surface.
• SIEM: Aggregates and correlates logs; it does not directly prevent attacks.
• Honeypot: A decoy system, not the primary protection for a production web application.
• Certificate revocation list: Deals with certificate trust, not application exploitation.

• Suspended an operator who refused to use unsafe equipment.
• Paid another operator a bonus for using it.
• Prioritised short-term productivity over employee safety.

• A — Management is not particularly concerned with managing risks.

• B — Employees will perceive that management does not care about health and safety risks.

• C — The factory’s safety record is likely to be poor.

• 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

• Confirm the required columns and data types
• Identify the target/label column
• Handle missing or duplicate records if present
• Transform data into a suitable format
• Split it into training and validation/test datasets

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

• Reporting relationships
• Organizational structures
• Leadership styles
• Team maturity
• Individual and group behavior
• Communication and motivation

• Acquire Project Team: Focuses on obtaining the people needed for the project.
• Develop Project Team: Focuses on improving team skills, relationships, and performance.
• Manage Project Team: Focuses on tracking performance, resolving issues, and managing changes within the team.

• 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.

• 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.

• MFA adds an additional authentication factor, such as a phone notification or verification code.
• It helps prevent unauthorized sign-ins, even if a password is compromised.
• It does not encrypt, store, or protect credentials used by deployment processes.

• SQL injection
• Cross-site scripting (XSS)
• Malicious or malformed web requests
• Some application-layer abuse

• Layer 4 firewall: Filters based mainly on IP addresses, ports, and connections; it lacks detailed web-request inspection.
• NGFW: Provides broader network security, but a WAF is more specialized for protecting web applications.
• UTM: Combines multiple security functions, but it is not necessarily optimized for web-application protection.

• A valid input returns the expected result
• An invalid input raises an error
• Boundary values are handled correctly

• B: Copilot may help generate tests, but it does not automatically write all necessary tests.
• C: Writing the implementation does not verify that it works correctly.
• D: Copilot can suggest test commands or test code, but the developer or development environment must execute and validate the tests.

• Espionage: Stealing information for intelligence or competitive purposes.
• Data exfiltration: Unauthorized removal or transfer of data.
• Nation-state attack: An attack sponsored or conducted by a government.
• Shadow IT: Technology or access methods used outside approved IT processes.

• 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.

1. Find the subnet-mask increment in the octet where the prefix ends.
2. Identify the network address by finding the subnet boundary at or below the given IP.
3. The first usable address is network address + 1.
4. The broadcast address is one address before the next subnet.
5. The last usable address is broadcast - 1.

• 172.28.228.144/18

• 172.28.228.144/23

• Additional running costs: $800
• Less depreciation: $300

• The $100 reduction in fixed production overhead absorbed is only an accounting reallocation. It does not represent an actual saving in total fixed overhead.

• 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.

• A — Capacity: The system must handle all current records and anticipated future records. A system that cannot cope with volume will quickly become ineffective.
• C — Accuracy: Academic records are critical, so the new system must be at least as accurate as the existing system and comparable systems. Poor accuracy could cause serious administrative and reputational problems.
• D — Integration: Linking with the university’s financial systems supports consistency and avoids duplicate data entry, especially for registration, deregistration and fee-related transactions.

• B — Parallel running: This is a useful implementation and risk-control technique, but it is not an essential feature of the system itself. It may also be expensive and time-consuming.
• E — Internet access for all information: This creates significant confidentiality and security risks. External access might be needed for selected services, but unrestricted access to all information is not essential and would be inappropriate for student records.

1. insert con; ? 1
2. Database.setSavepoint(); ? 2
3. update con; ? 3
4. Database.rollback(sp_admin); ? 4

• Install unauthorized or unapproved applications
• Access system areas normally restricted
• Add features unavailable in the default software
• Modify the device’s operating system

• SQL injection (SQLi): Attacks databases by inserting malicious SQL commands.
• Cross-site scripting (XSS): Injects malicious scripts into web pages viewed by users.
• Sideloading: Installs an application from outside the official app store, but it does not necessarily remove the phone’s operating-system restrictions.

• 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.

• IaaS: você gerencia a VM e o sistema operacional.
• PaaS: o Azure gerencia a infraestrutura; você se concentra no aplicativo.

• Each Case must follow defined support steps.
• Each step must be completed within a specified time limit.

• Case Escalation Rules: Escalate Cases based mainly on age or criteria; they do not model a complete sequence of service steps.
• Process Builder with Scheduled Actions: Can automate time-based actions but is not the standard framework for Case service-level commitments.
• Omni-Channel Routing: Routes work to agents based on capacity and priority; it does not track Case lifecycle deadlines.

spl 
error AND host=WWW3 
status=404 OR status=500 
NOT source=access.log

• Quotation marks are used for exact phrases or values containing spaces.
• Parentheses group parts of a Boolean expression, but they are not required for every Boolean search.

• 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.

• Future costs — Only costs occurring in the future can be affected by the investment decision. Past costs are sunk and irrelevant.
• Incremental costs — These are additional costs caused by choosing the investment. They are relevant because they differ between alternatives.
• Cash flows — Capital investment decisions are based on future cash inflows and outflows, usually discounted to present value.

• Committed costs have already been agreed or incurred and generally cannot be changed by the decision.
• Unavoidable costs will arise regardless of which option is selected, so they do not affect the choice.

• Encryption to preserve confidentiality
• Integrity protection to detect alteration
• Authentication of the server through certificates

• SHA-256: A hashing algorithm; it does not encrypt data for transmission.
• SSL 3.0: Obsolete and insecure. It should not be used.
• AES-256: A strong encryption algorithm, but by itself it does not provide the complete secure communication protocol needed for data in transit.

Statement 1 — Correct

Statement 2 — Correct

• BCP (Business Continuity Plan): è più ampio e mira a mantenere le funzioni essenziali dell’organizzazione durante un’interruzione. Il DRP è una componente più specifica del BCP.
• Communication plan: stabilisce come comunicare con dipendenti, cittadini e altre parti interessate, ma non ripristina i sistemi.
• IRP (Incident Response Plan): gestisce la risposta iniziale a un incidente di sicurezza, come un attacco informatico, non principalmente il recupero da un disastro fisico.

• SharePoint search: Finds documents based on search terms, but it does not reliably identify every 32-character account number for DLP enforcement.
• A hunting query in Microsoft 365 Defender: Used for security investigations, not for defining sensitive content in a DLP policy.
• Azure Information Protection: Uses classification and labeling; it does not automatically identify this specific account-number pattern unless configured with a matching sensitive information type.
• RegEx pattern matching: Best suited for structured identifiers with a known format, such as account numbers, employee IDs, or policy numbers.

• The JSON files contain one billion items, so this is a big-data workload.
• PySpark uses Apache Spark’s distributed, parallel processing, allowing the data to be processed across multiple compute nodes.
• It can read and transform data directly from OneLake, helping minimize unnecessary data movement or duplication.
• A Fabric notebook can also support exploration and visualization, as well as Spark-based analytics and anomaly-detection workflows.

• Pandas is primarily in-memory and generally suited to smaller datasets. One billion records would be impractical on a typical single machine.
• A Power BI report with core visuals is appropriate for visualization and sharing, but it is not the best tool for large-scale transformation, parallel processing, or anomaly detection. It would normally consume prepared data rather than perform the entire workload.

• The vulnerability scan identifies a vulnerability.
• The administrator verifies that the vulnerability is not present.
• Therefore, the scan produced a false positive.

• True positive: A vulnerability is reported and genuinely exists.
• False negative: A vulnerability exists, but the scan fails to detect it.
• True negative: No vulnerability exists, and the scan correctly reports no issue.

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.

• The S3 bucket as an origin for static content
• The Application Load Balancer (ALB) as an origin for dynamic content
• An Amazon Route 53 alias record pointing the application domain to CloudFront

Why this works

• Static data: CloudFront caches objects from S3 at edge locations, reducing latency for users worldwide.
• Dynamic data: CloudFront forwards requests that require application processing to the ALB. It can also maintain persistent connections and use the AWS global edge network to improve delivery performance.
• One domain: CloudFront behaviors can route different path patterns to different origins—for example, /static/* to S3 and other paths to the ALB.

Why the other options are incorrect

• Global Accelerator is designed primarily for accelerating traffic to applications with endpoints such as ALBs, not for caching S3 content.
• Using separate domains or splitting static and dynamic traffic adds unnecessary complexity.
• CloudFront already provides the required global edge distribution and caching, so combining it with Global Accelerator is unnecessary here.

• Microservices: An application-design approach that divides an application into smaller services. It does not inherently reduce the number of operating systems.
• Virtualization: Creates virtual machines, but each VM generally requires its own complete operating system. This improves isolation but does not minimize OS instances as effectively.
• Infrastructure as code: Uses code to automate infrastructure deployment and configuration. It improves consistency but does not determine how many operating systems are used.

• A: Concerns task scheduling and avoiding missed runs, not directly sizing the warehouse.
• B: The amount of data in a stream alone does not reliably determine compute needs; the SQL processing is what matters.
• D: A multi-cluster warehouse addresses concurrency, not the compute size needed for one task execution.