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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Application Installation & Testing | 20% | - Testing strategies and validation - Debugging and troubleshooting - Installation procedures and dependencies - Provider and consumer workflows |
| Topic 2: Application Deployment & Distribution | 25% | - Upgrades and lifecycle management - Versioning and release management - Publishing to Snowflake Marketplace - Listing types and monetization |
| Topic 3: Advanced Features & Management | 20% | - Billing events and cost monitoring - Event logging and telemetry - Integration with Snowpark and external services - Governance and compliance |
| Topic 4: Application Design & Creation | 35% | - Setup scripts and application logic - Security and access control - Manifest files and configuration - Native App Framework architecture - Application packages and objects |
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NEW QUESTION # 166
You've developed a Snowflake Native Application and are preparing to release a new version. You want to ensure that if any critical issues are detected after the upgrade, you can quickly revert users back to the previous stable version. Which combination of Snowflake features and best practices should you implement to facilitate a seamless rollback process? Select all that apply.
Answer: B,D
Explanation:
Options C and E are the correct approaches. Implementing robust logging and monitoring (Option C) is crucial for quickly identifying and diagnosing issues after the upgrade. Keeping the previous stable version staged and using release directives to revert users back to it (Option E) provides a clean and controlled rollback mechanism. Option A is not feasible and cost prohibitive due to backup across multiple consumers. Option B, 'UNSTAGE_VERSION' is not designed for that rollback approach and it is too aggressive. Option D, downgrading using lower version number, will also cause confusion. Maintaining a stable version and dynamically switching using release directives is the best approach.
NEW QUESTION # 167
Consider the following SQL code snippet intended to be part of a Snowflake Native Application. This application aims to provide data quality checks. Identify potential security vulnerabilities and recommend secure coding practices to mitigate them. Assume the application uses user-supplied input for filtering the data.
Answer: C,D
Explanation:
Option B and C are correct: Parameterized queries prevent SQL injection because the database treats the input as data, not as executable code. Strict input validation limits the possibility of malicious input being used to alter the SQL query's intent. Option A is incorrect since Snowflake does not automatically sanitize user input. Option D is beneficial for error handling but does not prevent SQL injection. Option E is risky, regular expressions are not guaranteed to catch all injection attempts.
NEW QUESTION # 168
Within a Snowflake Native Application, you need to implement a feature that is only available in the latest version of the application, and the usage of that feature needs to be tracked. How would you accomplish this within the application code, considering that you want to avoid exposing internal details about version numbers directly to the consumer?
Answer: B
Explanation:
The correct answer is (A). Using 'APPLICATION$VERSION' within a stored procedure allows you to conditionally enable the feature based on the application version. Logging the usage to a separate table (within the producer account) provides valuable insights into feature adoption without exposing version details to the consumer. Resource monitors (D) track resource consumption but not specific feature usage. Roles (B) can control access but don't directly provide usage tracking. Option E relies too much on consumer action. While UDFs (C) can check the version, doing so in SQL queries for conditional enabling might not be the most performant or maintainable approach. All logs should be captured within Producer account.
NEW QUESTION # 169
You are building a Snowflake Native Application that relies on a complex transformation pipeline. This pipeline involves multiple SQL scripts and User-Defined Functions (UDFs). To manage this complexity, you want to ensure that the deployment process is automated and repeatable. Which approach would you consider to manage the deployment and versioning of your application code and its database objects?
Answer: B
Explanation:
Using a deployment tool like Flyway or Liquibase (C) enables you to manage database schema changes and versioning in an automated and repeatable manner. These tools allow you to define migrations, apply them in a controlled sequence, and track changes over time. Executing scripts manually (A) is prone to errors and not scalable. A single large SQL file (B) becomes difficult to manage and troubleshoot. Storing SQL scripts external to the application (D) increases risk as the application is tightly linked to external artifacts. Snowflake itself does not provide build-in schema version control(E).
NEW QUESTION # 170
You are developing a Snowflake Native App that performs complex data transformations and offers different pricing tiers based on usage. You plan to use Snowflake Usage Metering Events to track consumer usage. Which of the following is the MOST appropriate approach to track usage and associate it with the correct pricing tier in your setup script and application code?
Answer: E
Explanation:
Using a fixed event name (A) doesn't allow for differentiation between pricing tiers. Relying on query history (C) or resource monitoring (D) is not reliable or precise for application-specific usage. Calling 'SYSTEM$METER_USAGE from a view (E) isn't the intended way to track usage. The best approach is to use dynamic event names that reflect the pricing tier and complexity, enabling accurate tracking and billing (B).
NEW QUESTION # 171
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