A Native App provider has released a new version of their application. After installation, some consumers report encountering 'SQL compilation errors' when using certain features that rely on Java UDFs. The provider has thoroughly tested the application and cannot reproduce the error in their development environment. What are the MOST LIKELY causes of this issue and how can the provider systematically troubleshoot and resolve it? (Select TWO)

• A. The consumer's Snowflake account has insufficient compute resources to execute the Java UDFs. The provider should instruct the consumer to upgrade their virtual warehouse size.
• B. The Java UDFs are encountering data type mismatches due to differences in regional settings or data formats between the provider's and consumer's environments. The provider should enforce strict data validation and type conversion within the UDFs.
• C. Consumer-side firewall rules are blocking access to external resources used by the Java UDF. The provider should thoroughly document the necessary network configurations for consumers.
• D. The provider's development environment is using a newer version of the Snowflake Java runtime than the consumer's environment. The provider should downgrade their development environment to match the oldest supported version and re-test the application.
• E. The Java UDFs are using external libraries that are not compatible with the consumer's Snowflake environment or are missing entirely. The provider should explicitly declare all dependencies in the application manifest and ensure they are properly packaged and deployed.

A data analytics company, 'Data Insights Pro', is developing a Snowflake Native Application to provide advanced customer segmentation analysis. They plan to monetize this application through the Snowflake Marketplace. They want to ensure that only a specific set of customer accounts can access and install their application during the initial beta testing phase. Which of the following steps must they perform to achieve this?

• A. Create a public listing on the Snowflake Marketplace and rely on Snowflake's built-in usage monitoring to identify the intended customer accounts.
• B. Publish the application directly to the Snowflake Marketplace without creating a listing, and then share the installation URL with the selected customer accounts.
• C. Use Snowflake's data sharing feature to share the application package with the customer accounts.
• D. Create a public listing with a very high price to deter unintended installations, then manually adjust the price to zero for beta testers.
• E. Create a private listing on the Snowflake Marketplace and share it with the specific customer accounts by explicitly granting access to their Snowflake account identifiers.

A customer has installed your Snowflake Native Application, which utilizes a IJDF that performs complex calculations. The customer reports performance issues and sporadic errors. As the application provider, how can you BEST establish telemetry and observability to diagnose the problem, without compromising the customer's data security or privacy?

• A. Request direct access to the customer's Snowflake account to inspect the IJDF execution logs and query performance metrics.
• B. Utilize Snowflake's Query History to track the IJDF's performance in the customer's account and provide recommendations based on the observed query patterns.
• C. Implement logging within the UDF to capture execution time, input parameters (anonymized), and error messages. Store this data in an Event Table within the application provider's account and expose aggregate statistics through a secure API endpoint for the consumer to monitor.
• D. Create a shared view on the UDF execution logs in the customer's account, granting you read-only access to the relevant information.
• E. Instruct the customer to enable verbose logging in their Snowflake account and provide you with the log files for analysis.

A Native Application developer is creating a data product to be sold on the Snowflake Marketplace. The application needs read access to a shared database called 'RETAIL DATA'. The application logic includes a function that reads a lookup table, 'PRODUCT CATEGORIES', within this shared database. Which sequence of actions, executed by the application provider, ensures the application can access this table at installation time and after updates, following least privilege principles?

• A. Grant 'IMPORTED PRIVILEGES' on to the application role. Grant 'SELECT on to the application role during the application's setup script.
• B. Grant USAGE on ' RETAIL_DATX to the application role during the application's setup script. Do not grant 'IMPORTED PRIVILEGES' on the database.
• C. Grant 'IMPORTED PRIVILEGES' on 'RETAIL DATA' to the application role. The application setup script should also GRANT USAGE on database RETAIL_DATA and then GRANT SELECT on to the application role.
• D. Grant 'IMPORTED PRIVILEGES' on 'RETAIL DATA to the application role. Rely on the consumer to grant 'SELECT access to tables within 'RETAIL DATA' to the application role.
• E. Grant 'SELECT on to the application role during the application's setup script. Do not grant 'IMPORTED PRIVILEGES' on the database.

A Snowflake Native Application, leveraging Snowpark Container Services (SPCS), is designed to perform complex data transformations on data residing within the customer's Snowflake account. The transformations require significant computational resources, and the container occasionally encounters resource constraints, leading to performance degradation. Which of the following strategies can you employ to optimize resource utilization and ensure the container runs efficiently within the customer's SPCS environment?

• A. Optimize the container image by removing unnecessary dependencies and libraries, reducing its overall size and startup time.
• B. Implement horizontal scaling within the container by deploying multiple replicas of the application and distributing the workload among them using a load balancer. The consumer must configure the number of replicas.
• C. Increase the size of the virtual warehouse associated with the SPCS compute pool. This directly provides more computational resources to the container.
• D. Rewrite the data transformation logic to utilize Snowflake's built-in SQL functions and stored procedures whenever possible. Move the transformation workload out of the container.
• E. Increase the memory and CPU limits specified in the 'spec.yaml' file for the Snowpark Container Services deployment. This provides the container with more resources within the allocated compute pool.