Cisco 350-501 Exam Actual Questions
Implementing and Operating Cisco Service Provider Network Core Technologies (SPCOR) (Page 26 )

• A) configure matching hold and delay timers

• B) configure matching key-strings

• C) configure matching priority values

• D) configure unique virtual IP addresses

• Correct choices: A and D.

• Why not B, C, or E?

• B. Enable column profile — This turns on column profiling, which computes statistics like min and max for each column.
• C. Show column profile in details pane — This ensures the per-column profile is visible in the details pane.
• E. Enable details pane — This makes the details pane available so you can view the column profile there.

• A. Show column value distribution may help with distribution but isn’t specifically about min/max.
• D. Show column quality details shows data quality (valid/null counts), not min/max.

Why B works

• AWS KMS keys are Regional resources. A normal customer managed key in Region A cannot be used directly in Region B.
• A customer managed multi-Region KMS key (MRK) has related key replicas in both Regions. The replicas share key material and key ID, although each has a Regional ARN.
• With client-side encryption, the application encrypts the data before storing it in S3. Cross-Region replication then copies already-encrypted objects, so S3 does not need to decrypt and re-encrypt them with a different Regional key.

Why the other choices are weaker

• A and C: SSE-S3 uses Amazon-managed S3 keys, not the required customer managed KMS key.
• D: SSE-KMS can work only if the solution creates and configures the appropriate KMS key or multi-Region key replica in each Region. As written, it says to create a customer managed KMS key in each Region, which implies separate keys—not the same KMS key. Replication also requires additional KMS permissions and destination encryption configuration.

• Correct answer: A. System characterization

• Why the other options are not correct:

• Answer: No.

• Why:

• If you need such an assessment while controlling costs, you’d generally pursue a paid MCS engagement or another option outside of the basic Premier entitlement.

• Sustainability is not a CAF perspective (it's not one of the CAF perspectives).
• Performance efficiency and Reliability are pillars of the AWS Well-Architected Framework, not CAF.

• Quick context: In a three-tier network (Access, Distribution, Core), roles are:

• Why A is correct: The Distribution layer runs Layer 2 and Layer 3 technologies. It often handles VLAN access (L2) and can perform inter-VLAN routing or connect to the core (L3). So it makes sense for the distribution layer to support both L2 and L3.

• Why B is correct: The Core layer is designed to maintain continuous connectivity when devices fail. It is built for high availability and redundancy, providing multiple paths so the network remains reachable even if some components fail.

• Why the others are not correct:

• Key concept: ALE = SLE × ARO

• SLE = $15,000
• Occurrences: 2 in 3 years ? ARO = 2/3 per year ˜ 0.6667

• ALE = $15,000 × 0.6667 ˜ $10,000 per year

• ALE is the expected annual loss, so it averages the losses over each year.
• This helps prioritize risk treatments by comparing ALE to the cost of controls.

• Each statement is evaluated as True (Yes) or False (No) independently.
• Key Azure facts to recall:

• Correct answer: D (Special category data)

• Why:

• Quick notes:

• A separate scope using a /32 subnet: A /32 identifies one host, but it is not a practical DHCP scope for this purpose.
• A static IP within the DHCP range: This can cause an IP address conflict if DHCP assigns that address to another device.
• SLAAC: Used for automatic IPv6 address configuration, not for assigning a predictable IPv4 address through DHCP.

• Two VMs
• Distributed across two separate availability zones

• Correct answer: A) Hashing

• Why: Hashing produces a fixed-size digest of the software. If the final build is altered in any way, the hash will change, enabling you to detect tampering by comparing the stored digest with a freshly computed one.

• Why not the others:

• Correct answer: D. AWS CloudShell

• Why: AWS CloudShell is a browser-based shell that runs in the AWS Console and uses the current authenticated session. It provides a pre-authenticated, ready-to-use command-line environment directly from the Management Console, with AWS CLI and common tools installed.

• Why the other options aren’t correct:

• 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.

• Azure Resource Manager templates: Use ARM templates to define the VM infrastructure and baseline configuration as code. This ensures all Windows Server 2016 VMs are created with a uniform setup, minimizing manual configuration.

• PowerShell Desired State Configuration (DSC) extension for Windows: DSC enforces a defined state across all servers and can automatically remediate drift. This keeps the VMs in the desired configuration with minimal ongoing admin effort.

• I can’t view the images, so I can’t tell which table is labeled as A in your screenshot. But here’s how to decide:

• How to identify the fact table:

• How to identify the surrogate key in the Patient table:

• Relationship:

• Multi-pass wipe: Overwrites the drive’s existing data multiple times, making recovery much more difficult while preserving the drive’s functionality.
• Single-pass wipe: May be sufficient in some modern sanitization standards, but is presented here as less secure than multiple overwrites.
• Degaussing: Uses a strong magnetic field to disrupt data. It can render the drive unusable or unreliable, reducing its resale value.
• Pinning: Is not an appropriate data-sanitization method.

• 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:

• Wiping securely overwrites the drive so the original data cannot reasonably be recovered. It is generally less expensive than physically destroying the device.
• Recycling could expose the data if the drive is not securely erased first.
• Shredding physically destroys the drive and is effective, but usually more costly and prevents reuse.
• Deletion only removes file references; it is not a secure sanitization method.

• Startup scripts run at computer startup, before any user logs on, making them ideal for machine-wide configuration on each new VM.
• They execute under the Local System account, which is appropriate for initial setup tasks.
• Linking a GPO to the OU ensures every new VM in that domain automatically receives the configuration—great for scalability.

• A) SetupComplete.cmd runs only once, right after Windows Setup, not on every boot, so it isn’t ideal for provisioning multiple VMs consistently.
• B) Logon scripts run per user, not per machine, so they aren’t reliable for initial VM configuration before a user signs in.
• D) Placing scripts in a VHD doesn’t automatically execute them.

• The two correct options are:

• The two incorrect options:

• Mapping:

• Why:

• Quick note: If you were to host a website on a VM, it would be IaaS; if you used a platform service instead of a VM, it would be PaaS. CaaS (containers) isn’t shown here.

• Goal: Guests should not use cameras, but company users can.
• Correct configuration: Guest access settings in the Org-wide settings.

• External access: Controls external-domain communication, not guest capabilities inside Teams.
• Teams settings in Org-wide settings: Too generic; doesn’t specifically target guest capabilities.
• Audio & Video in the default Meeting Policy: Would affect everyone assigned to that policy. To meet the requirement without impacting internal users, you’d need separate policies or guest-specific settings; the exam focuses on the guest-access policy.

• prompt: the input or instruction given to the model
• completion: the desired response

json 
{"prompt":"Summarize this customer complaint.","completion":"The customer reports a delayed shipment."}

• B: A .txt file containing CSV-style lines is not automatically a valid fine-tuning dataset. The required structure and format must match the selected Bedrock model.
• C: Provisioned Throughput provides dedicated inference capacity; it does not fine-tune a model.
• D: Journals and textbooks might support domain adaptation or pretraining, but they do not provide the prompt-to-answer examples typically required for supervised fine-tuning.

• A assigned without var becomes a global variable (in non-strict mode). So after myFunction(), a = 5 is accessible.
• b is declared with var inside the function, so it’s local to that function (function-scoped). It’s not defined in the outer (global) scope.

• console.log(a) prints 5.
• console.log(b) throws a ReferenceError: b is not defined.

• Why this is correct: In Azure Virtual Desktop, user access to a host pool is controlled through App Groups. The default app group for a host pool publishes the full desktop, so adding members to that app group grants them sign-in and access to the desktop (and any RemoteApps in that group). This is the standard way to give users access to AVD resources.

• Why the other options are not correct:

• Practical steps (high level):

• Version control provides a single source of truth for metadata changes and tracks every modification.
• It supports branching and merging, so each feature can be developed in isolation and later merged without overwriting others.
• It allows diffs and conflict resolution, making it easier to manage dependencies across features and ensure a stable release.

• Setup Audit Trail: only logs who/change when something happened; it doesn’t prevent overwriting or manage cross-feature dependencies.
• Change Sets: used to deploy changes between orgs, not to coordinate parallel development or prevent conflicts across ongoing sprints.

• A) MTU mismatch: OSPF neighbors must exchange Hello packets with a compatible MTU. If MTUs differ, the neighbor conversation fails and the adjacency cannot become Full.

• B) Incorrect subnet mask: Routers must be in the same IP subnet on the connected link to form a neighbor relationship. A subnet mismatch prevents Hello packets from being considered valid on the same network.

• D) Area ID not the same: Neighbors must share the same Area ID. A mismatch stops adjacency from forming beyond the 2-Way state.

• E) Different metric set on each end of the link: Cost differences do not prevent OSPF adjacency; they affect routing decisions, not neighbor formation.
• F) Router ID not defined: OSPF can auto-choose a router ID; an undefined ID is not a prerequisite for adjacency to reach Full.

• Correct answer: Day 3 (Option B)

• Why: In Engagement Studio, when the program is paused, the prospects’ wait times are also paused and do not count down. They resume from the same point when the program restarts. Here, the prospect was at day 3 of a 5-day wait when paused, so they resume on day 3 after the 1-day pause.

• Why: Table.Profile returns a per-column profile that includes statistics such as count, null count, distinct count, and standard deviation. It also provides min/max and average where applicable, which matches the requested metrics (Count, Average, Null count, Distinct count, Standard deviation).
• Syntax: Table.Profile(table as table, optional additionalAggregates as nullable list) as table
• How it helps: After running Table.Profile on your table, you can extract the per-column stats you need and display them in your semantic model or report.

• 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.

• Ablauf: Er wird in der gleichen Transaktion ausgeführt, bei der z. B. ein Datensatz erstellt oder aktualisiert wird. Der Benutzer wartet, bis der Workflow abgeschlossen ist.
• Stufen: Kann vor dem Vorgang (pre-operation) oder nach dem Vorgang (post-operation) laufen.
• Zweck: Sofortige Validierung oder Anpassung von Daten, ggf. auch das Verhindern eines Vorgangs, wenn Bedingungen nicht erfüllt sind.

• Automatisierte Flows (Power Automate, automatisierte/ Background Flows) laufen asynchron im Hintergrund, nachdem der Trigger erkannt wurde, und blockieren den Benutzer nicht.

• An IDS monitors network traffic for signs of attacks and raises alerts. It can be deployed out-of-band (via a SPAN/mirror port or a tap) so it analyzes traffic without being inline, meaning it doesn’t measurably affect latency.
• An IPS (intrusion prevention system) is inline and can block threats, but that processing can introduce some latency and potential throughput impact.
• A firewall also inspects traffic and can add latency, though usually modest with proper hardware, but its primary purpose isn’t continuous passive analysis.
• A load balancer distributes traffic and isn’t used for intrusion analysis.

• Answer: A. Use Amazon SageMaker Serverless Inference to deploy the model.

• Why: SageMaker Serverless Inference hosts the model and serves real-time predictions without you provisioning or managing servers. It scales automatically and handles deployment details.

• Why the others aren’t suitable:

• Quick example flow: web app ? SageMaker Serverless Inference endpoint ? model ? response.

• Review the risk register.
• Use the previously defined risk response plan, such as assigning a backup resource, reprioritizing work, or using another qualified engineer.
• Implement the response promptly because the task is on the critical path.

• B: Revising the schedule without first applying the planned response may be premature.
• C: Excluding a required task could compromise the project’s objectives and requirements.
• D: Updating the risk and lessons learned records is appropriate, but it should happen after managing the immediate issue, not as the next primary action.

• The Scrum Guide specifies four required events: Sprint Planning, Daily Scrum, Sprint Review, and Sprint Retrospective. These events enable transparency, inspection, and adaptation.
• The other items listed are not mandatory under Scrum:

• 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.

• Multi-factor authentication
• A secure password change for users whose credentials may be compromised

• '15' is a string. With + and a string, JavaScript does string concatenation: '15' + 10 -> '1510'.
• The result '1510' is then used in a multiplication: '1510' 2. The operator triggers numeric conversion, so '1510' becomes the number 1510.
• 1510 * 2 = 3020.

• If the code were let x = (15 + 10) * 2, the result would be 50 since 15 + 10 is numeric addition.

• Event | search "error"
• Event | where EventType == "error"
• search in (Event) "error"

• Answer: No (B)

• SaaS (Software as a Service) delivers applications over the internet; you don’t manage the underlying infrastructure or OS.
• Deploying Azure virtual machines requires provisioning and managing virtual machines, OS, updates, and networking—this is classic IaaS (Infrastructure as a Service).
• PaaS is for managed runtime environments (apps hosted on a platform), not for VM deployment.

• Improve QA testing efficiency: A prototype may help discover defects early, but that is not its greatest benefit.
• Decrease time allocated for user testing and review: Prototyping usually requires additional user involvement and review, not less.
• Minimize scope changes: Prototypes can actually reveal new requirements or cause scope changes. However, discovering those changes early is beneficial.

• Answer: No.

• Why it doesn’t meet the goal:

• How to implement correctly (brief guidance):

• The Well-Architected Framework has five pillars: Operational Excellence, Security, Reliability, Performance Efficiency, and Cost Optimization.
• Operational Excellence: how you run and improve your systems—monitoring, incident response, and evolving processes.
• Reliability: the ability of a workload to recover from failures, maintain uptime, and scale as demand changes.

• Availability (A) is not a pillar name; it’s an outcome that relates to Reliability.
• Scalability (C) isn’t a pillar name; scalability touches on Performance Efficiency.
• Responsive design (D) is not a pillar in the Well-Architected Framework.

• Box 1: Azure Lighthouse — ??? ??????? ? ?????????? ????????? ? ?????????? Entra tenants. ??? ??????????? ??? ??? ????? ????? ? VM ? ?????? ?????????/????????.
• Box 2: Azure Monitor Agent ? ?????????????? Data Collection Rules (DCR) — AMA ???????? ??????? Windows (????????, Security Logs) ? DCR ??????????, ????? ??????? ???????? ? ???? ?????????? (? ?????? Log Analytics workspace).

• Context: You’ve enabled auditing in Dataverse and need to trim audit data to free storage. The question asks which deletion options you can use.

• What the options typically mean:

• About the provided answer (A, C, D): The list includes “by column,” which isn’t a typical or supported way to purge audit data. The more plausible trio is A (by record), B (date range), and C (by table older than date). If the exam expects A, C, D, that seems incorrect or mis-stated in the source.

• Practical takeaway: To reduce audit storage, use per-record deletions, per-table purge by date, and/or date-range deletions as supported by the environment’s audit management UI or admin docs.

• Correct answer: B) Context window.

• Why: The context window is the number of tokens the foundation model can process in a single inference. It sets the maximum length of the combined input (prompt) and the model’s output. A larger context window allows more content to be included in one prompt.

• How to use: Check the FM’s context window value and ensure your prompt length plus the desired completion stays within that limit. If needed, summarize or split input across multiple prompts.

• Why the other options aren’t correct:

• Quick tip: Verify the specific FM’s context window for Bedrock, since different models have different token limits.

• The diagnostic output shows that the protocol is TCP (proto=6) and the session state is 2.
• In FortiGate’s session output, state=2 maps to SYN_SENT. This means the TCP SYN has been sent but the handshake hasn’t completed yet.
• Therefore, the session is not ESTABLISHED, FIN/ACK-related states, or other states; it’s in SYN_SENT.