Google Associate Cloud Engineer - Practice Test 2
You are an Associate Cloud Engineer responsible for managing several Google Cloud projects. To streamline your workflow and efficiently switch between these projects using the Google Cloud SDK command-line interface (CLI), what is the most effective approach?
The most efficient way to manage multiple Google Cloud projects with the gcloud CLI is to create a separate configuration for each project. You can then use `gcloud config configurations activate` to quickly switch between these predefined configurations, ensuring your commands are executed in the correct project context without manual re-initialization.
You need to provision a new Compute Engine instance within a Google Cloud project that does not yet exist. Which sequence of steps should you follow?
Before any resources like Compute Engine instances can be created, a Google Cloud project must first exist and have billing enabled. Subsequently, the specific API for the service (Compute Engine in this case) needs to be enabled within that project. The Cloud SDK provides the necessary commands to perform these actions sequentially.
Your organization needs to migrate several PostgreSQL databases from an on-premises data center to Google Cloud. The primary goals are to achieve significant performance improvements, minimize changes to existing data schemas and application code, and handle data volumes exceeding 150 TB per geographical region. You also want to adhere to Google-recommended practices and optimize operational costs. Which Google Cloud database service should you choose for this migration?
AlloyDB for PostgreSQL is the ideal choice for this scenario. It offers significant performance improvements for PostgreSQL workloads while maintaining full compatibility, thus minimizing schema and application code changes. As a fully managed service, it aligns with Google-recommended practices for large-scale enterprise databases and helps reduce operational overhead.
You are managing a web application hosted on Google App Engine standard environment. You need to introduce a new experimental version of the website and direct 1% of your user traffic to it, while minimizing operational complexity. Which approach should you take?
App Engine's traffic splitting feature is designed for this exact scenario, allowing you to easily direct a percentage of traffic to different versions within the same application. Using the `--splits` option with appropriate weights provides a straightforward and low-complexity solution for A/B testing or canary deployments. Other options involve creating new applications or external load balancers, which introduce unnecessary complexity for this specific requirement.
You are managing a critical web application hosted on Google Compute Engine. Your operations team requires automatic notifications if users experience elevated latency for a sustained period of at least 5 minutes. You need to implement a Google-recommended solution that incurs no additional development costs. What is the most appropriate action to take?
The requirement for 'automatic notification' and 'no development cost' points directly to Cloud Monitoring's built-in alerting capabilities. Option 2, creating an alert policy, directly addresses these needs by automatically sending notifications based on predefined thresholds without requiring custom code or development. Options involving BigQuery/Looker Studio or App Engine incur development/setup costs and/or require manual intervention, which contradicts the problem statement.