Discover the best approach to determine integration points with Microsoft services in Azure AI Solutions, focusing on storage, security, and workflow automation.
Table of Contents
Question
How would you identify the integration points needed with other Microsoft services?
A. Use Azure SQL Server.
B. Use SonarQube to get a list of potential services.
C. Review requirements for storage, security, and the potential for automating workflows.
D. Open the code and replace calls to external systems.
Answer
C. Review requirements for storage, security, and the potential for automating workflows.
Explanation
To identify integration points with other Microsoft services in Azure AI solutions:
Review Storage Requirements
Determine if solutions like Azure Blob Storage, Azure SQL Database, or Azure Cosmos DB are needed for data persistence, retrieval, or analytics.
Assess Security Needs
Integrate with Azure Active Directory (AAD) for authentication/authorization and Azure Key Vault for secrets management to ensure compliance and data protection.
Evaluate Workflow Automation Potential
Use Azure Logic Apps, Power Automate, or Azure Functions to orchestrate processes across services (e.g., triggering AI model retraining via Azure Machine Learning pipelines).
Why Other Options Are Incorrect
A. Azure SQL Server is a specific storage tool, not a methodology for identifying integrations.
B. SonarQube analyzes code quality, not service dependencies.
D. Replacing external calls is a code-level fix, not a design-phase integration strategy.
By systematically analyzing these requirements, you ensure seamless interoperability with services like Azure Cognitive Services, Power BI, or Dynamics 365 while aligning with best practices for scalability and maintainability.
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