A Snowflake Native App provider wants to grant a consumer access to a secure view within their application. The provider's application package is named and the secure view is named 'sensitive_data_view'. The consumer's account identifier is 'XYZ12345'. Which of the following is the MOST secure and appropriate method to grant this access using Snowflake's Native App Framework?

• A. Grant SELECT on sensitive data view to account XYZ12345;
• B. Grant USAGE on database containing sensitive_data_view to account XYZI 2345;
• C. Grant imported privileges on my_app_package to share with account XYZI 2345;
• D. Create a share and grant SELECT on sensitive_data_view to the share, then grant usage on the share to account XYZI 2345;
• E. Create a role within the application package, grant SELECT on sensitive_data_view to the role, and create an authorization grant to account XYZ12345 for that role.

You are tasked with configuring a Snowflake Native Application that leverages Snowpark Container Services for a data transformation pipeline. The pipeline requires access to a public API to enrich dat a. However, the consumer's environment has strict network egress policies. The API endpoint is 'https://api.example.com/vl/data'. Which combination of Snowflake objects and configurations would best enable the container service to access this external API while adhering to the security policies ?

• A. Create a Snowflake external function that calls the API. Then, call the external function from within the Snowpark Container Service.
• B. Configure a Snowflake network rule specifying 'https://api.example.com/vl/data' as the allowed egress endpoint. Associate this rule with a network policy and assign the network policy to the container service.
• C. Configure an API integration in Snowflake and then use it within the Snowpark Container Service to authenticate and access the API.
• D. Create a Snowflake stage with external access integration pointing to 'https://api.example.com/vl/data'. Mount this stage in the container service.
• E. Use the role to bypass network policies and directly access the API from the container service.

Consider the following scenario: You're developing a Snowflake Native Application that requires both data loading and complex analytical queries. You plan to use separate warehouses to optimize performance and manage resources effectively. Given the requirements, which of the following warehouse configurations is the MOST appropriate?

• A. Two warehouses: one with 'AUTO SUSPEND = 60' for data loading and another with 'AUTO SUSPEND = 3600' for analytical queries.
• B. One warehouse sized 'X-SMALL' for data loading and another sized URGE' for analytical queries.
• C. Two warehouses: one dedicated to data loading configured with "WAREHOUSE_SIZE = X-SMALL' and another for analytical queries configured with 'WAREHOUSE SIZE = LARGE and 'MAX CONCURRENCY LEVEL = 8'.
• D. One large warehouse to handle both data loading and analytical queries, sharing resources to minimize costs.
• E. Two warehouses: one dedicated to data loading, configured with to save costs and other warehouse for analytical queries.

You are developing a Snowflake Native Application that leverages user-defined functions (UDFs) and stored procedures. During the security scanning process before listing on the Snowflake Marketplace, you encounter a 'Failed to Detect Secrets' error. After investigation, you determine that the error stems from hardcoded API keys within a Python UDF that are being used to interact with a third-party service. Which of the following strategies would be MOST effective and secure to resolve this issue and pass the security scan?

• A. Store the API keys in a separate, secured table within the application's data container and access them dynamically within the Python UDF using SQL queries.
• B. Obfuscate the API keys within the Python UDF using a string manipulation technique. This will make it harder for unauthorized users to discover the keys.
• C. Encrypt the API keys within the Python UDF using a symmetric encryption algorithm and store the encryption key in a secure string within the application package.
• D. Remove the Python UDF entirely and rewrite the logic in SQL stored procedures. Store the API keys as environment variables within the stored procedure's definition.
• E. Replace the hardcoded API keys with references to Snowflake secrets and grant the necessary privileges to the application role. Access the secrets within the UDF using the 'SYSTEM$GET SECRET function.

You are developing a Snowflake Native Application that uses Streamlit for its user interface. The application needs to access a custom Python module named 'my_module' which resides within your application package. You have correctly packaged the module. However, when running the Streamlit application, you encounter an 'ImportError: No module named What is the most likely reason for this error and how can you resolve it?

• A. The correct handler is not specified in the 'manifest.ymr file.
• B. The Streamlit application is not aware of the application package's Python environment. You need to set the environment variable within the Streamlit application to point to the directory containing 'my_module'.
• C. Streamlit does not support custom Python modules within Snowflake Native Applications. You must use only built-in Python modules or those available through Anaconda.
• D. The 'my_module' is not located in the correct directory structure within the application package. Ensure it's placed in the 'src' directory (or the directory specified in 'package-name' in 'setup.py') and the directory structure mirrors the package structure required for import.
• E. The 'my_module' is not included in the file for your application package. Add it to the 'packages' list in 'setup.py'.