2.2 Explain the Process of Onboarding and Configuring Data and AI Sources (e.g., Office 365, Databricks, Azure Foundry) CLOUD-SECURITY-ENGINEER Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   Which of the following is a common requirement when onboarding Databricks as a data source into a security platform?

   • AProviding the Databricks workspace URL and an access token
   • BCreating a new Databricks workspace specifically for the security platform
   • CInstalling a physical gateway appliance in the Databricks cluster
   • DExporting all Databricks data to a local file before ingestion
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2. 2application · medium

   An organization has onboarded an AI source that generates security alerts. The security team wants to ensure that the alerts are properly correlated with existing data sources and that the AI source does not overwhelm the platform with false positives. What should they configure?

   • AIngest all alerts without any filtering and rely on manual review.
   • BSet up alert thresholds and tune the AI model's sensitivity parameters.
   • CDisable the AI source and use only traditional data sources.
   • DIncrease the ingestion frequency to capture more alerts.
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4. 3application · medium

   A company is onboarding Azure Foundry as an AI source into their security platform. The AI source will be used for threat detection models. The security team needs to ensure that the connection is authenticated securely and that the platform can access the AI models without exposing credentials. Which configuration should they use?

   • AUse a shared access signature (SAS) token with full access to the Azure Foundry workspace.
   • BUse the Azure Foundry API key directly in the platform configuration.
   • CUse a service principal with a client secret stored in the platform's secure credential vault.
   • DUse a personal Microsoft account to authenticate to Azure Foundry.
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5. 4expert · hard

   A company is onboarding multiple data sources, including Office 365 and Databricks. They want to ensure that the data is available for analysis even if one of the data sources fails. What should they do?

   • AStore all data in a single storage account.
   • BUse a single ingestion path for all data sources to simplify management.
   • CRely on the data source's built-in redundancy.
   • DConfigure redundant ingestion paths for critical data sources.
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6. 5expert · hard

   A company has onboarded an AI source that provides real-time threat scoring. The security team wants to use this AI source to automatically block traffic, but they are concerned about false positives causing business disruption. They also need to ensure that the AI source does not exceed its API rate limits. What should they configure?

   • ASet up a high-confidence threshold for blocking actions and implement rate limiting on the AI source API calls.
   • BSet up a low-confidence threshold for blocking actions to catch more threats.
   • CUse the AI source only for alerting, not for automatic blocking.
   • DDisable rate limiting to ensure the AI source is always available.
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