An enterprise operations team is implementing system telemetry collection and log archiving across a fleet of Compute Engine virtual machines. They require detailed operating system metrics (including memory and swap utilization) and must forward critical audit logs to a centralized BigQuery dataset in a security management project. Which two actions should the Cloud Engineer perform to satisfy these operational requirements following Google Cloud recommended practices? (Select TWO answers.)
- Install and configure the Google Cloud Ops Agent on each Compute Engine VM instance to collect extended system metrics and logs.Cevap
- Create a Log Router sink targeting the BigQuery dataset and grant the sink's unique writer identity service account the BigQuery Data Editor role on the destination project/dataset.Cevap
- CInstall the legacy Stackdriver Monitoring agent on the VM instances to enable custom OS-level memory and disk usage metric collection.
- DGrant the Compute Engine default service account the primitive Owner role to ensure the telemetry collection agent has sufficient authority to push metrics and logs.
Cevap
The correct actions are installing the Google Cloud Ops Agent on the VM instances to gather extended OS metrics and configuring a Log Router sink to BigQuery while assigning the sink's writer identity service account the BigQuery Data Editor role on the target destination.
The unified Google Cloud Ops Agent is the recommended solution to collect OS-level telemetry (memory and disk metrics) and logs from Compute Engine instances. When exporting logs to external targets like BigQuery via Log Router sinks, Google Cloud uses a unique writer identity service account for the sink that requires appropriate target IAM permissions (such as BigQuery Data Editor) on the destination project/dataset.
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Compute Engine telemetry collection using the unified Google Cloud Ops Agent and IAM role delegation for Log Router sinks.