Snowflake NAS-C01 Exam : SnowPro Specialty - Native Apps

A provider is testing their Snowflake Native Application in a consumer environment. The application includes a Streamlit app that displays data from a table provisioned in the consumer account. The consumer reports that the Streamlit app is displaying an errorrelated to accessing the table. The 'streamlit.secretS dictionary is used to store the database connection details. The application role app_role' is designed to have access to the table. Which of the following could be potential causes of the problem, assuming the connection details are valid?

• A. The 'streamlit.secretS dictionary is not accessible to the application due to incorrect file permissions.
• B. The consumer has not shared the database containing the table with the provider account.
• C. The 'app_role' does not have the 'SELECT privilege on the table.
• D. The 'app_role' does not have the privilege on the database containing the table.
• E. The Streamlit app is not properly configured to assume the when executing queries.

You are developing a Snowflake Native Application that performs complex data transformations. You need to monitor the application's performance, identify bottlenecks, and track resource consumption. Which of the following approaches would effectively establish observability and telemetry for your application, ensuring you can gather granular insights into its operations?

• A. Implement custom logging within your application code, writing log messages to a temporary stage. Periodically download and analyze these log files using external tools.
• B. Leverage Snowflake's event tables and Streamlit to visualize the performance and consumption of resources used by the application.
• C. Integrate with a third-party monitoring service (e.g., Datadog, New Relic) by sending application metrics and logs via HTTP endpoints. Configure alerts and dashboards in the monitoring service.
• D. Log all application events directly to Snowflake tables using stored procedures. Analyze these tables periodically using SQL queries to identify trends and anomalies.
• E. Utilize Snowflake's Information Schema views (e.g., 'QUERY_HISTORY', to track query performance and resource usage. Correlate this data with application-specific events using custom logging.

You are developing a Snowflake Native Application with a custom setup script. Within the setup script, you need to perform different actions based on whether the application is being installed for the first time in a consumer's account, or if it's an upgrade from a previous version. Which of the following functions or techniques can you reliably use within the setup script to determine if the current execution is a fresh installation vs. an upgrade? (Assume the app version is maintained and accessible as a variable 'current_version' .)

• A. Use 'SYSTEM$GET_PREVIOUS_VERSION()' function inside the setup script. If it returns NULL, it is the first install.
• B. Query the 'INFORMATION_SCHEMAPPLICATIONS' view to check if the application name already exists in the consumer's account.
• C. Use the table 'APPLICATION_REGISTRY' function to check for an existing entry for the application in the current account.
• D. Check if the current version is '1.0', assuming the initial version of the application will always be '1.0'.
• E. Attempt to read a known persistent setting from the application's metadata. If the setting exists, it's an upgrade; otherwise, it's a fresh install. (Requires metadata setup in a previous version)

After publishing your Snowflake Native Application on the Marketplace, you discover that a critical security vulnerability has been identified in a third-party library included in your application package. You need to quickly address this issue and push an updated version to your consumers. What is the recommended sequence of steps to remediate this vulnerability with minimal disruption to your users?

• A. 1. Develop and test a new version with the updated library. 2. Publish the new version as a private listing to selected consumers for testing. 3. Once validated, publish the new version to the Marketplace. 4. Deprecate the vulnerable version. 5. Announce the new version to consumers.
• B. 1. Immediately unlist the current version of the application. 2. Develop and test a new version with the updated library. 3. Publish the new version to the Marketplace. 4. Announce the new version to consumers.
• C. 1. Create a patch for the existing application. 2. Deploy the patch to all consumer accounts. 3. Notify consumers of the updated patch.
• D. 1. Deprecate the current version of the application. 2. Develop and test a new version with the updated library. 3. Publish the new version to the Marketplace. 4. Announce the new version to consumers.
• E. 1. Develop and test a new version with the updated library. 2. Publish the new version to the Marketplace. 3. Deprecate the vulnerable version. 4. Announce the new version to consumers.

You are developing a Snowflake Native Application that uses Streamlit to provide a user interface for data analysts. The application accesses sensitive customer data residing in a managed database. To enhance security, you want to implement row-level security (RLS) based on the user's role. You have the following Streamlit code snippet:

Which of the following actions should you take to implement RLS in the Snowflake Native App, ensuring only authorized users can view specific rows of 'customer_data'? Assume the already contains necessary credentials. Choose the most secure and efficient method.

• A. Use Snowflake's masking policies combined with a secure view. The masking policy reveals data based on the user's role. Grant the Streamlit application's role access to the secure view.
• B. Modify the SQL query within the 'get_data' function to include a 'WHERE clause that filters data based on the current Streamlit user's username obtained using 'st.session_state.user.username' .
• C. Implement RLS directly within the Streamlit application by filtering the 'data' DataFrame based on the user's role before displaying it using 'st.dataframe'. Store user roles in a separate table and fetch them using a different database connection.
• D. Implement a custom Python decorator that checks user roles before executing the 'get_data' function. Raise an exception if the user lacks the necessary role.
• E. Create a secure view in Snowflake that implements RLS based on the role of the user executing the query. Grant the Streamlit user access to this view instead of the base table, and modify the 'get_data' function to query the view.