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Snowflake NAS-C01 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Deployment and Marketplace Publishing	25%	- Distribution and lifecycle management 1. Version upgrades and release management 2. Marketplace listings and publishing
Topic 2: Installation, Testing and Troubleshooting	20%	- Validation and debugging 1. Tracing and troubleshooting workflows 2. Logging and event tables
Topic 3: Snowflake Native App Framework Overview	20%	- Native application concepts and architecture 1. Application packages and structure 2. Manifest files and setup scripts
Topic 4: Native Application Design and Creation	35%	- Application development workflow 1. Application roles and privileges 2. Building and versioning applications

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Snowflake SnowPro Specialty - Native Apps Sample Questions (Q195-Q200):

NEW QUESTION # 195
You are developing a Snowflake Native Application that processes sensitive customer dat a. You want to ensure that your application has undergone a thorough security review before it is listed on the Snowflake Marketplace. Which of the following steps are mandatory to ensure that your application meets Snowflake's security requirements for a secure native application?

A. Submit your application for Snowflake Native App Security Review by filling out the security review intake form with all the necessary documentation.
B. Ensure all sensitive data is encrypted at rest and in transit using Snowflake's built-in encryption features.
C. Implement data masking policies on all sensitive data within the application.
D. Enforce multi-factor authentication for all users accessing the application.
E. Obtain a third-party penetration test report for the application's code and infrastructure.

Answer: A

Explanation:
Submitting the application for Snowflake Native App Security Review is the core mandatory step. While options B, C, D, and E represent good security practices, the successful completion of the official security review process is a prerequisite to listing the application on the marketplace.

NEW QUESTION # 196
You're packaging a Snowflake Native Application that performs complex analytical computations on data within the consumer's account. This computation involves several intermediate tables and functions, all created within the application package. You want to optimize the application's performance and reduce storage costs in the consumer's account. Which of the following strategies can be employed to achieve these goals, especially considering that intermediate data is not intended to be directly accessible to the consumer?

A. Create all intermediate tables as transient tables. Transient tables do not support Time Travel or Fail-safe, which reduces storage costs, and grant appropriate privileges to application roles.
B. Use external tables to store the intermediate results in cloud storage (e.g., AWS S3), accessed through a secure integration. This minimizes the storage footprint within the consumer's Snowflake account.
C. Create all intermediate tables as temporary tables. Temporary tables are automatically dropped at the end of the session, minimizing storage costs and ensuring data privacy.
D. Create all intermediate tables as standard permanent tables, relying on Snowflake's automatic data compression and storage optimization features to minimize costs. Grant limited privileges to the consumer to control data access.
E. Implement data pruning techniques within the application's logic to delete intermediate data as soon as it is no longer needed, even if permanent tables are used for intermediate steps.

Answer: A,E

Explanation:
Options B and C are correct because they both contribute to optimizing performance and reducing storage costs without compromising data privacy. Transient tables (Option B) reduce storage costs by eliminating Time Travel and Fail-safe, while still allowing for persistence within the consumer's account. Data pruning (Option C) directly reduces the amount of data stored by deleting intermediate results as soon as they are no longer needed. Using temporary tables (Option A) might not be suitable if the application's computation spans multiple sessions or contexts. Using external tables (Option D) would introduce additional complexity and overhead related to data transfer and external storage management. Relying solely on Snowflake's automatic optimization features (Option E) might not be sufficient to minimize storage costs, especially for large intermediate datasets.

NEW QUESTION # 197
A Snowflake Native Application, 'Geolnsights', uses an external API to enrich location data provided by consumers. This API requires an API key for authentication. How can you securely manage and access this API key within the Native Application's code, ensuring that it is not directly exposed in the application package or code repository?

A. Use a Snowflake Secret to store the API key and retrieve it within the application's UDF using the 'SYSTEM$GET SECRET function.
B. Pass the API key as a parameter to the UDF from the consumer's environment.
C. Store the API key in an external key management system (e.g., AWS KMS, Azure Key Vault) and retrieve it within the UDF using a custom external function, ensuring the function has appropriate access permissions.
D. Hardcode the API key within the UDF itself after obfuscating it using a basic encoding algorithm (e.g., Base64).
E. Store the API key directly in a configuration file within the application package and encrypt the application package during deployment.

Answer: A,C

Explanation:
Storing the API key directly in the application package (A) or hardcoding it (E) is highly insecure and should be avoided. Passing it as a parameter from the consumer (C) places the burden of security on the consumer and might not be feasible in all scenarios. The most secure approaches are using Snowflake Secrets (B) or an external key management system (D). Snowflake Secrets provide a built-in mechanism for securely storing and retrieving sensitive information within the Snowflake environment. Storing in an external Key Management System also provides strong security, assuming you configure the external function and its permissions correctly. Both options provide robust security and control over the API key, preventing its exposure in the application package.

NEW QUESTION # 198
You are developing a Snowflake Native App that needs to perform asynchronous tasks in the consumer's account. Which of the following approaches is the MOST suitable and secure way to achieve this, ensuring minimal impact on the consumer's resources and maintaining data integrity?

A. The Native App can create task and warehouse in the consumer account to execute the code using CREATE APPLICATION command. The application uses SNOWFLAKE.CORE.AUTHZ.PASS PRIVILEGES() to execute these tasks.
B. Create a Snowflake Task that is executed within the consumer's account, triggered by events within the application, and configured to run on a Snowflake-managed compute pool.
C. Implement a Snowpark UDF that starts a new thread to handle the asynchronous task within the consumer's compute environment.
D. Utilize an external message queue (e.g., AWS SQS, Azure Queue Storage) to offload asynchronous tasks, requiring the consumer to configure network policies to allow egress traffic to the queue.
E. Implement a scheduled stored procedure that polls for new tasks every minute and processes them, potentially consuming significant compute resources in the consumer's account. The stored procedure is deployed in the consumer's account using CREATE APPLICATION.

Answer: B

Explanation:
Using Snowflake Tasks (Option A) is the recommended approach for asynchronous task execution within a Snowflake Native App. The task is managed within the consumer's account but still deployed as part of app package, avoiding the need for external dependencies or extensive consumer configuration. Option B introduces complexity and security concerns with external message queues. Option C can be resource-intensive and inefficient. Option D is incorrect as apps are not allowed to create warehouses. Option E is not supported, UDFs do not run in separate threads.

NEW QUESTION # 199
You are creating a Snowflake Native Application that uses Snowpark Container Services. The application needs to process large datasets and requires a Compute Pool with specific GPU resources. You use the following SQL command to create a compute pool:

After creating the compute pool, you notice that your Snowpark Container Service is unable to start. Upon inspecting the 'SYSTEM$GET CP POLICY' for the allowed instance families list does not contain 'GPU NV M'. What is the MOST likely reason for this and how do you rectify it?

A. The COMPUTE POOL needs to be explicitly associated to the application package by running ALTER APPLICATION PACKAGE ADD COMPUTE POOL my_compute_poor.
B. GPU instance types are automatically enabled as part of SPCS and there is no account restriction.
C. The account does not have access to GPU-based instance families. Contact Snowflake support to enable GPU instance families for your account.
D. You need to explicitly grant the 'USAGE privilege on the instance family to the application role used by the container service using "GRANT USAGE ON INSTANCE FAMILY GPU NV M TO ROLE
E. The specified instance family is invalid or not supported in your region. Use 'SYSTEM$GET_CP POLICY to verify the available instance families and choose a supported one.

Answer: C

Explanation:
GPU instance families are not automatically enabled for all accounts. Access must be explicitly granted. Without the necessary account permissions, the compute pool creation might succeed, but the container service will fail to start. The account admin needs to contact Snowflake to enable it.

NEW QUESTION # 200
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