Amazon AWS DevOps Engineer Professional Exam Prep
AWS DevOps Engineer - Professional (DOP-C02) (Page 16 )

• RPO and RTO definitions:

• Why B and D meet these goals:

• How they complement each other:

• Quick tips:

• ??? AWS CloudFormation ?????? Lambda ???? ???? ??????????? API Gateway ???? ???? ??? ?????????? ???? ???? ????.
• ???????? ????? Lambda ??????? aimmutable ????, ???????? ???? ??? ???? ?????????? ???? ??????? (versions) ????? ????.
• Canary release strategy ?????? ???? ?????? ???????????????? ??????? ??????? ?????? new ??????????? ????? ????, ???????? ???? ???????? ???? ????.
• ??? ????????? ?????????????? ?????????? ???? Lambda ??? ??? API ???? ???? ???????? ???????? ???? ???? ????, ???????? ???? ??????????????? IaC ???????? ????? ????.
• ???????? ????? ??????????, canary ????? ????? ??????? ???????? 100% ?? ???? ???? (promote).

• A: Route 53 failover ?? ???? canary ???? ?????????, gradual traffic shifting ???? ????? ????; ?????? ?????? ???????? DR ????.
• C, D: Elastic Beanstalk ????? OpsWorks ?? serverless-????? ? ??? ??????? ???????????? ???? ?????.

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

1. Required profit per unit:

1. Target cost per unit:

• B. Users accessing Salesforce from public Wi-Fi

• C. Users choosing the same password as their Facebook password

• A: 2FA does not protect an already-authenticated, unlocked session if someone accesses an unattended laptop.
• D: Weak password-reset questions are an account-recovery weakness. 2FA primarily strengthens login authentication, not necessarily the security-question reset process.

• SAMLRequest: the SAML authentication request
• RelayState: the original destination or application state

• RedirectURL: not the standard SAML parameter for preserving the original request.
• DisplayState: not a standard SAML SSO parameter.
• StartURL: Salesforce-related terminology, but not the standard parameter used in this SAML exchange.

• Snapshot: Captures a point-in-time state for rollback. It is not an independent running VM and does not protect against failure of the underlying host or storage.
• Convert to dynamic disks: Changes disk allocation behavior; it does not provide redundancy or high availability.
• P2V: Converts a physical machine into a virtual machine. That is a migration process, not an availability solution.

• Import — Loads data into Power BI. It requires a refresh, so it may not reflect changes within two minutes unless refresh is configured appropriately.
• Live connection — Connects to an existing Power BI semantic model or Analysis Services model; it is not the normal choice for connecting directly to an Azure SQL database.

• Modelo de embeddings de texto: trabalha principalmente com texto, não sendo adequado para imagens.
• Modelo generativo multimodal: pode interpretar ou gerar conteúdo de vários tipos, mas não é a opção específica para busca por similaridade.
• Modelo de geração de imagens: cria imagens a partir de entradas, não realiza busca multimodal.

Why

cmd 
PowerShell.exe -ExecutionPolicy Bypass -File C:\Scripts\ConfigureVM.ps1

Why the other options are less suitable

• GPO logon script: Runs only when a user logs on and may not run during initial VM provisioning.
• GPO startup script: Can work, but requires the VM to be joined to the domain and the policy to be applied. It is also normally evaluated at each startup.
• Place scripts in a VHD: Merely placing scripts on a disk does not cause them to execute.

• Data lakes: scalable, low-cost storage for structured, semi-structured, and unstructured data.
• Data warehouses: reliable SQL analytics, governance, and performance features.

• Data lake: Primarily provides flexible, scalable storage but may lack warehouse-style reliability and governance.
• Data warehouse: Strong for structured analytics but less flexible for raw and unstructured data.
• All of these: The individual lake and warehouse do not, by themselves, unify the siloed architecture.

• Equipment and hardware
• Facilities
• Inventory
• Backup media
• Supplies stored at an alternate or remote location

• Personal belongings of staff: Usually not organizational assets.
• DR line-item revenues: Revenue is a financial impact, not a physical asset.
• Cloud-based applications: These are primarily logical or information-processing assets, even though they depend on physical infrastructure.

• Valor maior: mais aderência às instruções e aos detalhes descritos.
• Valor menor: mais liberdade criativa e resultados potencialmente mais variados.
• Valor excessivamente alto: pode causar artefatos ou imagens menos naturais.

• Aumentar o número de passos de geração: pode melhorar qualidade e refinamento, mas não é o principal controle de especificidade do prompt.
• MASK_IMAGE_BLACK: relaciona-se ao uso de máscara em geração ou edição de imagens, não à especificidade textual.
• Prompt strength: é mais associado à força do prompt em processos como image-to-image; nesta questão, o parâmetro diretamente ligado à aderência textual é o CFG scale.

• Input feature distributions differ from training data ? Analyze dataset drift metrics

• Model accuracy drops without code changes ? Analyze dataset drift metrics

• Endpoint latency increases under load ? Investigate scaling and infrastructure metrics

• 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

• 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.

• The user authenticates with the external Identity Provider.
• Salesforce receives the SAML assertion.
• Salesforce uses attributes in that assertion—such as username, email, first name, last name, and profile/community information—to create the user during the first login.
• On later logins, Salesforce updates or uses the existing user record.

• On-the-fly provisioning is a general phrase; the Salesforce capability being tested is specifically JIT provisioning.
• Salesforce APIs would require a separate integration and provisioning process.
• Identity Connect is designed primarily to synchronize users from an identity directory, not to create users at the moment of their first SAML login.

• 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

• 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.

• A — conformant: Incorrect because one explicit requirement is violated.
• B — consistent: “Consistent” is not sufficient where the implementation contradicts a mandatory specification. The RPC mechanism is covered by the architecture, and the implementation differs from it.
• C — consistent: Incorrect reasoning: the RPC mechanism does have a defined architectural requirement, so conformance must be assessed.
• D — non-conformant: Correct because the implementation fails to follow the specified RPC/threading requirement.

• 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.

• An Anypoint VPC provides private network connectivity for CloudHub applications.
• An IPsec VPN tunnel or AWS Direct Connect connects that VPC to the customer’s on-premises network without exposing the database to the public internet.
• The VPC and on-premises firewalls must allow the required traffic, routes, and ports.

• Static IP addresses only identify the application’s outbound traffic; they do not create a private network path to the database.
• A Dedicated Load Balancer does not replace the required network connection to the on-premises environment. It is also unnecessary merely to reach individual databases.
• Moving sensitive databases to a DMZ is not the intended architecture and could reduce their protection.

• Creating and managing users and roles
• Granting and revoking roles and privileges
• Managing access-control responsibilities

• SYSADMIN: Manages warehouses, databases, schemas, and other objects—not primarily users and roles.
• PUBLIC: Automatically granted to every user; it is not an administrative role.
• ACCOUNTADMIN: Has the highest level of access, but should be reserved for account-level administration and emergencies rather than routine security tasks.

Correct choices

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

Why

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

• Reviewing security policies and standards checks whether controls are documented, not whether they work.
• Reviewing security logs may show that monitoring is occurring, but does not directly establish that preventive controls are effective.
• Analyzing technical security practices is broad and may assess implementation, but it is less objective than an actual controlled attack.

• Design/compliance effectiveness: policies, standards, and procedures
• Operational effectiveness: logs, records, and evidence that controls operate
• Technical security effectiveness: penetration testing or vulnerability testing

• Replaces the verbal message — this describes non-verbal communication being used instead of words.
• Substitutes for verbal communication — similar; it means communicating without speech.
• Confuses the verbal message — this occurs when non-verbal signals contradict or obscure the spoken message.

• 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.

• SQL injection
• Cross-site scripting (XSS)
• Malicious file uploads
• Common web-application exploits

• Layer 4 firewall: Filters primarily by IP addresses, ports, and transport protocols; it lacks detailed web-application inspection.
• NGFW: Provides advanced network filtering and may include application awareness, but a WAF is more specialized for protecting web applications.
• UTM: Combines several security functions in one device, but it is not specifically focused on web-application attacks.

• 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.

• 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.

• Modelo de embeddings multimodal: transforma texto e imagens em vetores no mesmo espaço semântico. Isso permite comparar uma consulta textual com imagens, ou uma imagem com textos relacionados.
• Modelo generativo multimodal: interpreta diferentes modalidades e gera conteúdo, mas não é a escolha específica para indexação e busca vetorial.
• Modelo de geração de imagens: cria imagens, portanto é inadequado.
• Modelo de embeddings de texto: não atende consultas com imagens.

• 6-phone boxes: 6x
• 8-phone boxes: 8x

• Users retain their existing usernames and passwords.
• Existing accounts can be used to access Azure-based resources.
• Administrators avoid manually recreating thousands of accounts.
• The transition is less disruptive before the on-premises data center is retired.

• Port 515: LPD/LPR line-printer service
• Port 631: IPP — Internet Printing Protocol
• Port 9100: JetDirect/RAW printing, commonly used by network printers

• Linux machine: Linux could run these services, but the three printer-specific ports strongly indicate a printer.
• Router: Routers may use Telnet and HTTP, but normally would not expose ports 515, 631, and 9100 together.
• Windows machine: Windows can share printers, but this particular service combination is more characteristic of a network printer’s embedded operating system.

• 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.

1. Define Power Platform DLP policies

1. Add custom prompt modifications

1. Conduct adversarial testing

1. Start with the 48-bit MAC address.
2. Split it into two 24-bit halves.
3. Insert FF:FE between the halves, creating a 64-bit value.
4. Invert the U/L bit—the seventh bit from the left in the first MAC byte.

text 
MAC:       00:1A:2B:3C:4D:5E 
EUI-64:    02:1A:2B:FF:FE:3C:4D:5E

• FE80 is the prefix commonly used for an IPv6 link-local address, not part of the EUI-64 interface ID.
• The interface ID is not random.
• The MAC address is modified by inserting FF:FE and changing the U/L bit.

sql 
GRANT ALTER ON SCHEMA::schemaA TO User1;

• TRUNCATE TABLE is a DDL operation, not a normal DELETE.
• Having DELETE permission on a table is not sufficient to truncate it.
• The minimum relevant permission is ALTER on the table.
• Granting ALTER on SCHEMA::schemaA allows the user to truncate tables within schemaA.
• It does not grant equivalent permissions on schemaB or schemaC, satisfying least privilege.

• 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 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.

• Actual filename: Document.xml.txt
• Explorer displays: Document.xml
• File type: Text Document (.txt)

text 
Document.txt ? Document.xml

• SageMaker endpoint: Not required because the model is being used through Amazon Bedrock.
• SageMaker Model Registry: Used for managing SageMaker models, not for making a Bedrock custom model available.
• Grant access in Amazon Bedrock: IAM permissions may still be needed, but granting access alone does not provide the required inference capacity.

• Disaster recovery backups
• Long-term backup retention
• Data archiving that still needs occasional access

• Multi-Regional Storage: Intended for frequently accessed data needing broad geographic availability; it costs more.
• Regional Storage: Suitable for frequently accessed data within one region.
• Nearline Storage: Intended for data accessed roughly once per month, such as monthly backups.
• Coldline Storage: Better fit for backups accessed only during a disaster or occasional recovery event.

• 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.

• Drops packets when traffic exceeds a certain bitrate: This describes traffic policing, not shaping.
• Fragments large packets and queues them: Shaping does not fragment packets as its primary congestion-control action.
• Drops packets randomly from lower-priority queues: Packet dropping may occur if a shaping queue becomes full, but it is not the defining behavior.

• Shaping: buffers and delays excess traffic.
• Policing: drops or marks traffic that exceeds the configured rate.

• A. IDS attack signatures: An IDS primarily detects suspicious network activity and usually does not provide dedicated file-upload malware scanning. It is generally detective rather than preventive.
• C. Load balancer: Distributes traffic among servers and improves availability; it does not inspect documents for malware.
• D. WAF: Helps block web-application attacks such as SQL injection, command injection, and XSS. Although a WAF may inspect upload requests, malware detection in PDF files is more directly addressed by antivirus or content-scanning functionality.

• A — Add a Path for Stage: A Path lets users update the Opportunity’s Stage directly from the record page, without opening the full edit form. It can also display guidance and key fields.
• B — Use a Kanban list view: Users can move Opportunities between stages by dragging records between columns, which is ideal when Stage is the only field they normally change.

• A. Number ? Decimal — Correct. Salesforce Number fields are represented in Apex as Decimal.
• D. Date/Time ? Datetime — This is correct conceptually, but “Dateline” is not an Apex type. If the option literally says “Dateline,” it is incorrect.
• E. Checkbox ? Boolean — Correct. A checkbox contains true or false.

• Number ? Integer — A Number field maps to Decimal, even when its scale is zero.
• Text Area ? List<String> — A text area maps to a single String, not a list.

• SAML: Enables federated authentication and single sign-on between the IdP and SaaS providers.
• OAuth tokens: Allow delegated application access; OAuth is not primarily the first step for employee SSO.
• Password vaulting: Stores or autofills multiple passwords but does not eliminate the separate credentials or provide true federation.

• A. Extranet
• B. VLAN
• C. Intranet
• D. VPN

• 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.