Avaya 72301X Exam Actual Questions
Avaya Aura Communication Applications Support Certified Exam (Page 9 )

• Storage accounts: storage1, storage2, and storage3
• Log Analytics workspace: Analytics3

• Azure Backup reports can send the AzureBackupReports diagnostic log to eligible storage accounts. The storage account’s subscription and region do not have to match the Recovery Services vault, so all three listed storage accounts are valid.
• The Log Analytics workspace must be in the same region as the Recovery Services vault for this configuration. Vault1 and Analytics3 are both in West Europe, making Analytics3 the valid workspace.

• Side loading means installing software from sources outside official or trusted repositories.
• This process can bring in malicious payloads because the installed software hasn’t been vetted. A rootkit is a type of malware that hides its presence and maintains privileged access, making it a prime risk when using untrusted sources.
• Why not the other options:

• Only install apps from trusted sources; verify signatures.
• Use application whitelisting and security controls to block sideloading.
• Keep systems updated and use anti-malware tools capable of detecting rootkits.

• Why: A multi-modal embedding model maps both text and images into a shared vector space, enabling cross-modal similarity and retrieval (e.g., find images matching a text query or text matching an image).

• What it does: Enables efficient similarity search using a vector database or nearest-neighbor indexing.

• Why the other options aren’t suitable:

• Quick implementation note: you’d typically pair the embeddings with a vector store (e.g., ANN index) and possibly fine-tune on domain data for better alignment across modalities.

• 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.

• 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.

• ProductSearchModel.getProductSearchHits() — option C
• ProductSearchHit.getRepresentedProducts() — option B

• ProductMgr.queryAllSiteProducts() (A) queries every product in the site, which is heavy and not scalable for large catalogs.
• Category.getProducts() (D) retrieves all products in a category; this can be slow for large categories.
• Using the search model and hits (B and C) leverages the search index, supports paging, and avoids scanning the entire catalog, making it more scalable.

• A. Implement retries with exponential backoff

• C. Reduce the frequency and/or size of requests

• B. Use PutRecord instead of PutRecords — PutRecord sends one record per call and does not remove the underlying throughput limitation. It may increase request overhead.
• D. Use Amazon SNS instead — SNS is not a direct fix for Kinesis shard throttling and changes the required streaming architecture.
• E. Reduce KCL consumers — KCL consumers read from Kinesis; they do not solve producer-side PutRecords throttling.

• L2TP uses UDP port 1701 for the L2TP control channel.
• The destination port is 1701; the source port is a dynamically chosen ephemeral port on the client (not 1701).
• Therefore the statement that both source and destination ports are 1710 is incorrect (and 1710 is not the standard L2TP port).

• The destination port should be 1701, not 1710.
• The source port should be an ephemeral port chosen by the client, not 1701.

• Domeny tworza restrykcjony razem z typem. Wykorzystujesz je w kolumnach, aby miec spójna walidacje danych w wielu miejscach.
• To nie jest pelny niestandardowy typ z wlasnym input/output funkcjonowaniem. Aby stworzyc typ z wlasnym I/O i operacjami, uzylbys CREATE TYPE (lub rozszerzen w C). Domeny to uproszczona forma ograniczen na istniejacy typ.

• CREATE DOMAIN positive_int AS integer NOT NULL CHECK (VALUE > 0);
• CREATE TABLE orders (id serial, qty positive_int);

• latwo wymuszaja wspólne reguly dla wielu kolumn/naglówków,
• zmiana regul w jednym miejscu (domena) automatycznie wplywa na wszystkie kolumny ja uzywajace.

• The requirement: the support plan must allow opening new support requests (technical support incidents).
• Azure’s Basic plan does not include technical support incidents—only billing/subscription support and access to community support.
• Therefore, you must choose a paid plan to open new technical support requests: Developer, Standard, Professional Direct, or Premier.

• Answer: Data enhancement.

• Why: Augmenting gold-layer tables with an additional dataset is enriching or enhancing the existing data to support the ad-hoc analysis. The other options don’t capture the idea of adding external data to improve the dataset (ad-hoc improvements = tweaks, last-mile dashboarding = building dashboards, last-mile ETL = ETL steps at the end of the pipeline). In practice, this is often also called data enrichment.

• Correct answer: D) Microservices using API

• Why:

• Business
• People
• Governance
• Platform
• Security
• Operations

• Program and project management
• Risk management
• Cloud financial management
• Data governance
• Portfolio management

• Sustainability
• Performance efficiency
• Reliability

• 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.

• 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):

• Why: ADS is designed to collect information about on-premises environments to plan migrations. It inventories details like hostname, IP address, MAC address, OS, hardware, and installed software, plus dependency mappings. This data helps you understand your current environment before moving to AWS.

• How it differs from the other options:

• Practical use: Install the ADS agent on on-prem hosts to collect data, then view the inventory in Migration Hub to inform migration planning and sequencing.

• In Azure, the typical cost approach for pay-as-you-go VMs is an Operational Expenditure (OPEX) model. You’re billed for actual usage each month.
• The term “elastic expenditure model” isn’t a standard Azure cost category. Elasticity describes scaling capacity, not the billing category itself.
• So recommending the elastic expenditure model is not correct for this goal.

• The solution does not meet the goal. Answer: No (B).

• Pay-as-you-go aligns with OPEX because costs vary with usage.
• Elasticity is about scaling resources, which affects performance and capacity, not the fundamental cost model.

• Multiple AWS accounts: Create a separate account for each department or workload. This provides clear isolation and makes it easier to track each department’s usage and costs for chargeback.
• Consolidated billing: AWS Organizations can combine billing for multiple accounts into one central payer account. The company can still view costs by account while managing payment centrally.

• Placement groups: Control how EC2 instances are physically placed for networking or performance; they do not provide departmental billing separation.
• Edge locations: Infrastructure used by services such as Amazon CloudFront; unrelated to chargeback.
• AWS Config: Records and evaluates resource configurations and compliance; it is not a billing-separation mechanism.

• Disabling GPS: Affects location services, not email connectivity.
• Configuring 4G usage only: Does not enable international data access and could prevent connectivity if 4G is unavailable.
• Connecting using a hotspot: Could provide data, but it is not the most direct solution and depends on another network or device.

• 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).

• Phishing can map to two MITRE ATT&CK tactics depending on the attacker’s objective.

• Therefore, phishing isn’t confined to a single tactic; it can serve both Reconnaissance and Initial Access, which is why option D (Reconnaissance, Initial Access) is correct.

• The correct AAA mapping (per Cisco objectives) is:

• Why the given options aren’t fully correct:

• Quick takeaway: when you configure AAA, you should conceptually map them as:

• Example commands (to reinforce concepts):

• Used for communication on the local link or LAN segment
• Automatically generated on IPv6-enabled interfaces
• Not routed by routers to other networks
• Commonly used by devices to communicate with their local IPv6 router
• Begins with FE80 through FEBF

• FC00::/7 — unique local unicast
• FE80::/10 — link-local unicast
• FF00::/8 — multicast
• 2000::/3 — global unicast

• 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.

• 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.

• Authenticating websites with TLS/HTTPS
• Enabling certificate-based VPN authentication
• Signing or encrypting email
• Supporting device or user authentication

• VLAN tagging: Uses network-frame tags, such as 802.1Q; it does not rely on X.509 certificates.
• LDAP: May integrate with PKI in some environments, but X.509 certificates are not most commonly associated with LDAP itself.
• MFA: Certificates can be one authentication factor, but X.509 is fundamentally a PKI technology.

• Automation handles repetitive tasks, and orchestration coordinates responses across tools (SIEM, SOAR, EDR, etc.).
• This allows the security team to process more events with the same number of people, improving throughput and response times.
• Analysts can focus on more complex tasks like investigation and threat hunting instead of manual triage.

• It increases complexity: automation can reduce complexity when well-implemented; complexity is not the main intended benefit.
• It removes technical debt: automation/OR focuses on current incident response efficiency, not primarily on architectural debt.
• It adds additional guard rails: governance is important but not the core value of automation/orchestration within a SIEM.

• Cross-account access is typically implemented with an IAM role. You create a role in the target account (where the resources live) and configure a trust policy that allows principals from the source account to assume that role.
• Users in the source account then assume the role (via Switch Role in the console or STS:AssumeRole) and receive temporary credentials with the role’s permissions to access the resources.

• IAM group: Groups exist inside a single account; they don’t grant cross-account access.
• IAM tag: Tags are metadata and do not grant access.
• IAM Access Analyzer: It analyzes and identifies public or cross-account access but does not grant access itself.

• The Balanced Scorecard translates an organization’s vision and strategy into a set of concrete objectives and metrics across four perspectives (financial, customer, internal processes, learning & growth). This framework explicitly links IT goals to business goals and provides a way to measure and monitor alignment over time.

• Enterprise architecture (EA): Great for governance, standards, and roadmaps to ensure IT assets support business needs, but it’s more about structure and alignment at design time rather than directly measuring ongoing alignment of goals.
• KPIs: Useful metrics, but they don’t by themselves provide a full framework to ensure IT goals are aligned with organizational strategy.
• Enterprise dashboard: A visualization tool for metrics; it helps report status but doesn’t inherently establish or assess alignment.

• 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.

• S3 Versioning stores all versions of an object. If an object is overwritten or deleted, you can recover the previous version using its version ID.
• This protects against accidental deletion or overwriting because the original data remains accessible as an older version.
• How to enable:

• Practical notes:

• S3 Lifecycle rules: automate moving/expiring data, not specifically protection against deletion.
• S3 bucket policies: control access but don’t inherently preserve previous data.
• S3 server-side encryption: protects data at rest, not against deletion/overwrite.

• B — Increase provisioned concurrency for Lambda

• D — Refactor the Lambda functions

• E — Use Amazon RDS Proxy

• A. Configure prompt modifications to enforce tone, disclaimers, and refusal behavior at the system level.

• D. Configure Power Platform DLP policies to restrict unauthorized data connectors.

• B: Manual topic-by-topic disclaimer edits are specifically discouraged.
• C: Channel settings do not replace agent-level Responsible AI controls.
• E: Publishing before enabling safety filters violates the stated deployment sequence. Responsible AI filters should be enabled before publication, not afterward.

• Correct answer: C — The model is deployed at UK border checkpoints.

• The EU AI Act applies to AI systems used within the EU or by entities established in the EU. So:

• Amazon DynamoDB — Managed NoSQL database, not PostgreSQL.
• Amazon Athena — Serverless service for querying data in S3; intended for analytics, not OLTP.
• Amazon EMR — Managed cluster platform for big-data frameworks such as Hadoop and Spark.

• A? ??? Aurora Replicas? ?? ??? ???? ?? ???, ?? ???? Network Load Balancer(NLB)? ??????. NLB? ?? 4 ?? ???? HTTP ??? ?? ???(Sticky sessions)? ????? ???? ????.
• ??? ?? ??????? ?? ?? ???? ??? ???? ?? ????? ????? ?? ?? ???(?? ?/??? ??)? ?????. ? ??? ALB?? ?? ????, NLB?? ???? ?????.
• ??? ??? ??? ??? ???? ?? ???? ???? HTTP ???? ??? ALB? ???? ???. A? ? ??? ??????.

• 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.

• Answer:

• Why:

• Why the other centers aren’t the right fit here:

• Answer: D

• The strongest security comes from enforcing access at the storage layer. An IAM policy scoped to the Cognito identity prefix restricts each user to their own S3 prefix (folder), so users can only access their own files regardless of client or server code.
• This per-user isolation reduces risk of cross-user data access and is more robust than UI validation or Lambda/API validation alone.
• Implementation note: attach a policy to the Cognito identity role that allows actions on arn:aws:s3:::your-bucket/${cognito-identity.amazonaws.com:sub}/* (per-user prefix). Ensure TLS in transit and enable at-rest encryption (SSE-S3 or SSE-KMS). Use multipart upload for large files up to 300 MB.

• Answer: D) Out-of-band management

• Why this is correct:

• Why the other options aren’t suitable here:

• The two correct options are:

• The two incorrect options:

• Goal: Identify the host that originated the infection, then label each remaining host as infected or clean based on log evidence.

• Logs to review (across hosts and firewall):

• How to identify the origin:

• How to classify other hosts:

• Quick tip: use the Reset All option if you want to re-run the scenario and practice again.

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.

• Correct answer: All four statements are true (A, B, C, and D). The given key (A,B) is likely incorrect.

• A) Customers can change the size of the Warehouse after creation — Yes. You can resize a virtual warehouse after it’s created using ALTER WAREHOUSE ... SET WAREHOUSE_SIZE.
• B) A Warehouse can be resized while running — Yes. Snowflake supports online resizing; you can change the size without stopping queries.
• C) A Warehouse can be configured to suspend after a period of inactivity — Yes. You can enable auto-suspend with a delay (AUTO_SUSPEND).
• D) A Warehouse can be configured to auto-resume when new queries are submitted — Yes. You can enable auto-resume (AUTO_RESUME) so a suspended warehouse automatically resumes on new queries.

• Example commands:

• Even if a warehouse is resizing or auto-suspending, queries will be queued and then executed once the warehouse has the appropriate capacity.

• State is stored remotely in Terraform Cloud/Enterprise, not as a local file.
• Terraform runs (plan/apply) can be executed on remote infrastructure, with results visible in the remote workspace UI.
• Supports workspace-based organization, state locking, and concurrency control.
• Useful for team collaboration, centralized governance, and auditable logs.

• In your configuration, you use a backend block like backend "remote" { ... }.
• You still run terraform init to configure/migrate to the remote backend.
• After setup, terraform plan/terraform apply may be executed remotely, and the outputs/logs appear in the Terraform Cloud/Enterprise UI rather than (only) in your local terminal.

• Other backends store state remotely but typically do not provide remote execution; with the remote backend you get remote runs and a collaborative UI, not just remote state storage.

• What the scenario asks: You have a Power BI semantic model that pulls from multiple sources (Azure SQL Database and SharePoint Online), must support a single dataset for three reports, keep data current (daily refresh by 7 AM PT), and apply RLS to limit sales data by region. You need to choose a storage mode for the tables.

• Correct choice: Dual storage mode.

• Why Dual fits:

• Key concepts:

• Correct answer: D — use the same hashing algorithm as the sender's to create a numerical representation of the file.

• Integrity is verified by recomputing the hash on the received data and comparing it to the sender’s hash. This must use the same hash function; if you use a different algorithm, the digests won’t match even if the data is intact.
• The hash output is a fixed-length digest (a numerical representation). Whether you call it a “binary image” or a “numerical representation,” the key is that you generate the same type of digest with the same algorithm and compare them.

• A: same algorithm but the result is described as a binary image instead of a digest; you still compare the digest, but the phrasing is less precise.
• B/C: using a different algorithm would produce a different digest, causing false mismatch or failure to verify integrity.

• Progress iteratively with feedback focuses on making improvements in manageable steps and learning from feedback.
• Optimize and automate focuses on maximizing value from resources and automating suitable activities.
• Start where you are focuses on assessing the current situation and reusing what already exists.

• 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.