Scaled Agile SAFe-RTE Exam Actual Questions
SAFe Release Train Engineer (Page 15 )

• Voice devices ? VLAN 10
• Data devices ? VLAN 20
• SVI for VLAN 10 ? 192.168.10.1
• SVI for VLAN 20 ? 192.168.20.1

• A: Describes a physical trunk interface, not an SVI.
• B: An SVI can provide management access, but that is not its primary definition here.
• D: SVI does not compensate for insufficient physical ports; it is a logical interface.

• IPsec: Protects traffic at the network layer, commonly for VPNs; it is not WPA2’s authentication protocol.
• SSL: Protects specific application sessions and has largely been replaced by TLS.
• SSH: Secures remote command-line administration.

• runParallel is defined as async, so it returns a Promise.
• To use the result, you attach a then handler (or use await inside another async function).

• A: “Async runParallel() .then(data);” is invalid. “async” is a keyword for function declarations, not something you put in front of a call, and you’d need a function as the then-argument.
• B: “runParallel().done(function(data){return data;});” .done is not standard in native Promises (it exists in some libraries). Without a compatible library, this won’t work.
• C: “runParallel().then(data);” is invalid because then expects a function as its argument; data is not a function.
• D: “runParallel().then(function(data){ return data; });” is valid (or equivalently, runParallel().then(data => data);).

• The robust, standard option is D.
• B could work only with a library that provides .done; otherwise it’s not reliable.

• The stage has a default file format defined (e.g., when you create the stage with FILE_FORMAT = (...)), and Snowflake will use that default.

• You use a named file format attached to the stage, or you specify an inline format in the COPY command, e.g., COPY INTO my_table FROM @my_stage FILE_FORMAT = (TYPE = 'CSV');

• Use a stage default: omit FILE_FORMAT in COPY.
• Or rely on a named/inline format: specify FILE_FORMAT in COPY or set a format on the stage.

• Correct answer: C: Amazon Comprehend.

• Why: The library wants to classify books based on their text content. This is an NLP (natural language processing) task. Amazon Comprehend is AWS’s managed NLP service that can perform content classification (including creating custom classifiers) and extract meaningful information from text. The other services are not focused on text classification:

• Quick note: In practice, you’d store the books in S3, extract text if needed (e.g., from PDFs with Textract), and then use Comprehend to classify the documents into topics or genres.

• Enable the owner dimension

• Assign a standard costing inventory model

• Batch dimension tracks batches or lots, such as expiration or production batches. It does not identify inventory ownership.
• Moving average is a costing method, but it is not the required choice for this consignment configuration.

• To get min/max per column, you need column profiling. That’s provided by enabling the column profile.
• To actually see those min/max values, you should show the column profile in the details pane, and you also need the details pane itself enabled so you can view it.

• Enable column profile (B)
• Show column profile in details pane (C)
• Enable details pane (E)

• Show column value distribution (D) shows distribution shape but isn’t required to get min/max.
• Show column quality details (D) deals with data quality metrics, not min/max.

• The 99.99% availability SLA for VMs is achieved when you run VMs across two or more Availability Zones.
• Two VMs in a single Availability Zone do not meet the 99.99% target (their SLA is lower, e.g., around 99.95% or less depending on configuration).

• Deploy at least two VMs across two different Availability Zones (one VM in each zone, or both in two zones with a load balancer).
• This provides the required zone redundancy and the 99.99% SLA.

• Answer: D: Making business cases for improvement action

• Continual Improvement focuses on identifying and planning improvements and ensuring they’re funded and prioritized. Creating a business case for an improvement action is part of justifying and obtaining support/resources to implement improvements.
• A (Identifying the cause of incidents) aligns with Problem Management.
• B (Authorizing changes) aligns with Change Enablement.
• C (Logging/managing incidents that result in improvement opportunities) aligns with Incident Management, not Continual Improvement.

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• Prompts and Suggestions: Retained for 28 days
• User Engagement Data: Kept for Two Years

• Two VMs
• Distributed across two separate availability zones

• Why: The data is unlabeled, so you can’t train a model with known input-output pairs. Unsupervised learning discovers structure in the data by grouping similar customers into clusters or tiers without labels.
• What it does: Clustering and segmentation (e.g., k-means, hierarchical clustering, DBSCAN, Gaussian mixtures) to form meaningful groups.
• Why the other options aren’t as suitable:

• The mapping and resolution of endpoint identities (EIDs) to their location (RLOCs) in an SD-Access fabric is handled by the control plane using the LISP protocol.
• Why not the others:

• B: Intégrez des résultats de due diligence tels que les évaluations de risque client.

• C: Utilisez des correspondants en aval pour enquêter et signaler les activités suspectes.

• Topic: Conditional Access (CA) policy and MFA for Azure management.
• Policy name: Policy1, created with the template “Require multifactor authentication for Azure management.”
• What the template does: It enforces MFA when signing in to manage Azure resources (Azure management) for the users included in the policy.
• Who is included: The question lists Admin1, Admin2, Admin3, and Admin4 as the admins in the tenant. The template’s default scope for this scenario is to apply to those admin accounts (i.e., all four admins unless you explicitly limit the scope).

• CA policy for “Azure management” targets admin sign-ins.
• If the policy includes Admin1–Admin4, all of them must use MFA on their next sign-in (choice D).

• A — IDS attack signatures: An IDS generally detects suspicious network activity but does not necessarily scan uploaded PDF files or prevent them from being accepted.
• C — Load balancer: Distributes traffic among servers; it does not inspect files for malware.
• D — WAF command-injection blocking: A WAF can help block web attacks such as command injection, SQL injection, and cross-site scripting, but this option does not specifically address malicious PDF uploads.

• The correct answer is “Think and work holistically” (Option B).

• Focus on value: ensures outcomes matter to stakeholders, but isn’t specifically about end-to-end delivery.
• Optimize and automate: about efficiency and performance, not the holistic view.
• Collaborate and promote visibility: about teamwork and sharing information, not the end-to-end scope.

• 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

• Permanent table (E): Correct. A dropped permanent table can be restored with UNDROP TABLE during its Time Travel retention period. Permanent tables also have Fail-safe protection.
• Transient table: It can also generally be restored during its shorter Time Travel period, although it has no Fail-safe. Therefore, excluding it makes the question questionable.
• Temporary table: Usually cannot be recovered after it is dropped; its lifecycle is limited to the session.
• Materialized view (D): The answer key treats it as recoverable, but recovery behavior depends on the specific Snowflake object/version capabilities. It should not be confused with an ordinary view.

• Co to znaczy: transakcje zachowuja sie tak, jakby byly wykonywane jeden po drugim. Dzieki temu nie ma brudnych odczytów, niepowtarzalnych odczytów ani phantom reads.

• Implementacja: PostgreSQL uzywa SSI (Serializable Snapshot Isolation). W praktyce oznacza to, ze jesli wykryje konflikt miedzy transakcjami, jedna z nich zostanie zakonczona bledem “serialization failure” i trzeba ja ponowic.

• Zalózmy tabele orders(customer_id int, amount int).

• Transakcja T1:

• Transakcja T2, równoczesnie:

• T1 ponownie wykonuje to zapytanie:

• A) configure matching hold and delay timers

• B) configure matching key-strings

• C) configure matching priority values

• D) configure unique virtual IP addresses

• Active vs passive: Active assessment involves actively scanning targets by sending probes/packets to identify hosts, services, and vulnerabilities. Passive assessment observes traffic without probing.
• External vs internal: External assessment is about testing from outside the network perimeter; the scenario doesn’t specify external vantage, only that tools are identifying hosts/services across the enterprise network.

• Basic: billing/subscription support only; no technical support requests can be opened.
• Developer, Standard, Professional Direct, and Premier: include technical support and allow opening new support requests.

• If option A corresponds to “Developer, Standard, Professional Direct, Premier,” that is the correct choice.
• If the option text is really “Premier only,” that would be incorrect per current Azure docs.

• A. IDS attack signatures: An IDS primarily detects suspicious network activity and usually alerts rather than directly scanning and blocking uploaded files.
• C. Load balancer: Distributes traffic among servers but does not inspect files for malware.
• D. WAF: Protects web applications from attacks such as SQL injection, cross-site scripting, and some malicious requests. It is not primarily a PDF-malware scanning solution.

• Assignment
• Decision
• Get Records
• Loop

• Screen flow: Would include a Screen element.
• Inactive version: Inactive status does not restrict the available elements.
• Activated version: Activation status also does not determine the toolbox contents.

python 
import azure.cognitiveservices.speech as speechsdk 


speech_config = speechsdk.SpeechConfig( 
    subscription="YOUR_KEY", 
    region="YOUR_REGION" 
)

Important Azure Speech SDK classes

• SpeechConfig

• AudioConfig

python 
  audio_config = speechsdk.audio.AudioConfig( 
      use_default_microphone=True 
  )

• SpeechRecognizer

python 
  recognizer = speechsdk.SpeechRecognizer( 
      speech_config=speech_config, 
      audio_config=audio_config 
  )

• SpeechSynthesizer

• AudioOutputConfig

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