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Explanation:

The correct answer is C. This option configures a filter to view only Compute Engine logs and then creates an export that sends these logs to BigQuery. This method ensures that only relevant logs are exported, which minimizes unnecessary data transfer and storage costs. It is a straightforward solution with minimal setup and cost.

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In order to perform an analysis, it is essential to send all the logs generated by your Compute Engine instances to a BigQuery dataset named platform-logs. It should be noted that the Cloud Logging agent has already been installed on all instances. Given the need to minimize costs, what steps should you take to achieve this?

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Give the BigQuery Data Editor role on the platform-logs dataset to the service accounts used by your instances. 2. Update your instances' metadata to add the following value: logs-destination: bq://platform-logs.

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In Cloud Logging, create a logs export with a Cloud Pub/Sub topic called logs as a sink. 2. Create a Cloud Function that is triggered by messages in the logs topic. 3. Configure that Cloud Function to drop logs that are not from Compute Engine and to insert Compute Engine logs in the platform-logs dataset.

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In Cloud Logging, create a filter to view only Compute Engine logs. 2. Click Create Export. 3. Choose BigQuery as Sink Service, and the platform-logs dataset as Sink Destination.

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Create a Cloud Function that has the BigQuery User role on the platform-logs dataset. 2. Configure this Cloud Function to create a BigQuery Job that executes this query: INSERT INTO dataset.platform-logs (timestamp, log) SELECT timestamp, log FROM compute.logs WHERE timestamp > DATE_SUB(CURRENT_DATE(), INTERVAL 1 DAY) 3. Use Cloud Scheduler to trigger this Cloud Function once a day.