Snowflake GES-C01 : SnowPro® Specialty: Gen AI Certification Exam

An organization is planning to deploy Snowflake Cortex Agents for sensitive financial reporting, requiring strict adherence to data governance policies and clear understanding of cost drivers. Which of the following statements about governance and cost considerations for Cortex Agents are true?

• A. Monitoring of Cortex Agent interactions for debugging and refinement is exclusively performed through internal Snowflake system logs, with no external SDK support.
• B. To use a semantic model with Cortex Agents, the role executing the agent request requires only the SNOWFLAKE .CORTEX_AGENT_USER role, as it implicitly inherits all necessary privileges for semantic model access.
• C. Cortex Agents are powered by Snowflake-hosted LLMs by default, ensuring that all customer data and prompts remain within Snowflake's governance boundary.
• D. Usage costs for Cortex Agents are primarily driven by the number of tokens processed by the underlying LLMs for orchestration and the compute/service costs of tools like Cortex Analyst and Cortex Search.
• E. The CORTEX_DOCUMENT_PROCESSING_USAGE_HISTORY view provides detailed credit consumption for Cortex Agent activities, including orchestration steps and tool usage.

An enterprise is deploying a new RAG application using Snowflake Cortex Search on a large dataset of customer support tickets. The operations team is concerned about managing compute costs and ensuring efficient index refreshes for the Cortex Search Service, which needs to be updated hourly. Which of the following considerations and configurations are relevant for optimizing cost and performance of the Cortex Search Service in this scenario?

• A. The
  
• B. For optimal performance and cost efficiency, Snowflake recommends using a dedicated warehouse of size no larger than MEDIUM for each Cortex Search Service.
• C. The primary cost driver for Cortex Search is the number of search queries executed against the service, with the volume of indexed data (GBImonth) having a minimal impact on overall billing.
• D. CHANGE_TRACKING
• E. For embedding text, selecting a model like
  

A global enterprise has Snowflake accounts in various regions, including a US East (Ohio) account where a critical application is deployed. They need to use AI_COMPLETE with the claude-3-5-sonnet model for real-time customer support, but this model is not natively available in US East (Ohio) for direct AI_COMPLETE usage. The Snowflake administrator considers enabling cross-region inference. Which statements accurately reflect the considerations and characteristics of cross-region inference in Snowflake Cortex?

• A. Setting the CORTEX_ENABLED_CROSS_REGION account parameter to 'ANY_REGION' in the US East (Ohio) account would enable inference requests for claude-3-5- sonnet to be processed in any region where it is natively available.
• B. Cross-region inference automatically caches user inputs and generated outputs to reduce latency for subsequent requests to the same model.
• C. Cross-region inference is not supported in U.S. SnowGov regions for either inbound or outbound inference requests.
• D. The CORTEX_ENABLED_CROSS_REGION parameter can be configured at the session level to temporarily enable cross-region inference for specific workloads.
• E. Latency between regions for cross-region inference is negligible and consistently low, irrespective of cloud provider infrastructure.

A Data Engineer is responsible for deploying machine learning models using Snowpark Container Services. They need to ensure that a specific role, model_deployer_role, has the appropriate permissions to create a Snowpark Container Service that uses an image from an existing image repository named my_inferenc_ images. Which of the following SQL commands grant the necessary privileges 'on the image repository' for this purpose?

• A.
  
• B.
  
• C.
  
• D.
  
• E.
  

A development team is evaluating Snowpark Container Services (SPCS) for deploying various AI/ML workloads, including custom LLMs and GPU-accelerated model training. They need to understand its core benefits and operational characteristics compared to traditional container orchestration platforms. Which of the following statements accurately describe the benefits and/or operational characteristics of Snowpark Container Services for deploying third-party models and AI applications?

• A. SPCS supports both long-running services (e.g., web applications) and finite-lifespan job services (e.g., GPU-accelerated machine learning model training).
• B. SPCS primarily supports applications written in Python and Java, with limited experimental support for other programming languages.
• C. Compute clusters within SPCS are designed to auto-scale dynamically based on workload demand, automatically adjusting the number of instances.
• D. SPCS provides a fully managed OCI runtime execution environment, allowing users to run containerized workloads directly within Snowflake without managing underlying Docker or Kubernetes infrastructure.
• E. Snowpark Container Services ensures that data remains within Snowflake's security and governance boundaries, eliminating the need to move data out of the environment for processing.