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Snowflake SnowPro Specialty - Native Apps Sample Questions:

1. A team developing a Snowflake Native Application is encountering performance issues. They suspect that the warehouse configuration might be suboptimal. They want to dynamically adjust the warehouse size based on the CPU utilization. Which of the following approaches can effectively address these performance concerns and allow dynamic warehouse resizing while adhering to security best practices?

A) Develop a Snowflake Script owned by a dedicated application role. The script queries the view to determine average CPU utilization and dynamically resizes the warehouse using SALTER WAREHOUSE based on predefined thresholds. Grant the 'MODIFY privilege on the warehouse to the application role.
B) Use an external task scheduling system (e.g., Airflow) to query the 'SNOWFLAKE.ACCOUNT USAGE.WAREHOUSE LOAD HISTORY view, calculate the average CPU utilization, and then execute ' ALTER WAREHOUSE using a Snowflake connector with credentials for a user with the ACCOUNTADMIN role.
C) Manually monitor warehouse CPU utilization and execute 'ALTER WAREHOUSE statements to resize the warehouse based on observed metrics. Use a dedicated Snowflake user for this purpose with the ACCOUNTADMIN role.
D) Directly use Snowflake's in-built auto-scaling features to dynamically resize based on load, if available, with appropriate resource monitors setup to control costs. Also, develop a Snowflake Script owned by a dedicated application role, that queries the view to determine average CPU utilization and dynamically resizes the warehouse using 'ALTER WAREHOUSE based on predefined thresholds. Grant the 'MODIFY privilege on the warehouse to the application role.
E) Develop a Snowflake script that queries the view, calculates the average CPU utilization over a period, and then executes 'ALTER WAREHOUSE' statement through the 'SYSTEM$WAIT' function to prevent resource contention. Assign the script's ownership to a dedicated application role.

2. You are developing a Snowflake Native Application and want to implement robust observability and telemetry. Which of the following approaches will enable you to effectively monitor the application's performance, identify errors, and collect usage metrics within the consumer's account?

A) Implement custom logging using 'SYSTEM$LOG' and store application logs in a separate table within the application's container. Configure grants to allow the application developer to access these logs.
B) Rely solely on Snowflake's built-in query history and resource monitoring features in the consumer's account, as these automatically capture all application activity.
C) Utilize to write log data to a secure table within the application and leverage views granted to the consumer to expose relevant metrics and error information. Ensure appropriate roles have access to the views.
D) Directly access the consumer's system tables (e.g., 'SNOWFLAKE.ACCOUNT USAGE.QUERY HISTORY) to extract application-related metrics based on query identifiers generated by the application.
E) The consumer is responsible for implementing observability and telemetry. The application developer cannot implement observability features that function within the consumer's account.

3. A software vendor is developing a Snowflake Native Application for fraud detection. They plan to distribute it via the Snowflake Marketplace. They have implemented robust data governance policies within their application. What steps must they take to ensure that these policies are enforced and clearly communicated to consumers using the application in their own Snowflake accounts, specifically related to data masking policies?

A) The vendor should create masking policies. Policies created with the 'OWNERSHIP clause will be granted to the application database role. If the application creates and then shares tables, the table owner (database role) will have the ability to grant 'APPLY MASKING POLICY on those objects.
B) Data governance policies are automatically inherited by consumer accounts when they install the application.
C) The vendor must create all masking policies using the WITH MASKING POLICY clause to ensure policies are enforced on the consumer side.
D) Data governance policies should be implemented within the application's UI and enforced programmatically through stored procedures.
E) The vendor should create a separate documentation detailing the data governance policies and provide it alongside the Snowflake Marketplace listing. Consumers are responsible for implementing these policies in their accounts.

4. A data science company is developing a Snowflake Native App that provides advanced fraud detection for financial institutions. The app requires secure access to sensitive transaction data within the consumer's Snowflake account. Which of the following approaches BEST aligns with Snowflake's recommended practices for managing data access and securing data within a Native App?

A) The app should request full ACCOUNTADMIN privileges in the consumer account to access all necessary data for fraud detection.
B) The app should use secure views created by the consumer that grant the app read-only access to only the specific transaction data needed for fraud detection.
C) The app should directly access tables containing transaction data using the consumer's own service account credentials, which are securely stored within the app's code.
D) The app should create and manage its own temporary tables in the consumer account and load transaction data into them for processing.
E) The app should directly access transaction data through data sharing from provider account.

5. Consider the following Snowflake Native Application design scenario: You are building a data enrichment application. This application requires a consumer to grant usage on a specific database in their account. The application will then use a user-defined function (UDF) to access and enrich the dat a. To minimize the risk of data exposure and adhere to best practices, which of the following approaches should you take when designing the UDF?

A) Create the UDF without any special keywords, relying solely on the consumer's permissions to control data access.
B) Create the UDF with the EXTERNAL_ACCESS' keyword to explicitly allow it to access data outside of the application package.
C) Create the UDF with the 'SECURE keyword and implement granular access control within the UDF code, restricting access based on the application role.
D) Create the UDF with the 'IMMUTABLE keyword to prevent any data modification within the consumer's database.
E) Create the UDF with the 'VOLATILE' keyword to ensure it only runs when explicitly called, limiting the potential for unintended data access.

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