GCP Professional Cloud Architect Practice Question

Your organization is containerizing its payment processing platform and deploying it to a multi-node Google Kubernetes Engine cluster. Today you only monitor host CPU usage and archive application logs to a local syslog server. Leadership asks for true observability in Google Cloud so engineers can 1) watch infrastructure and service-level metrics, 2) search application logs in real time, and 3) follow a single customer transaction across microservices. Which solution provides these three observability pillars with the least ongoing operational effort?

Install the Ops Agent on each GKE node to export system and container metrics to Cloud Monitoring, route container logs to Cloud Logging, and enable Cloud Trace for distributed request tracing.
Use Error Reporting to derive operational metrics from crashes, stream logs through Datastream to Pub/Sub, and rely on uptime checks for distributed tracing.
Deploy Prometheus exporters in every pod for metrics, forward logs to BigQuery via Fluent Bit, and use Cloud Profiler to visualize end-to-end request latency.
Turn on VPC Flow Logs for metrics, archive application logs to Cloud Storage, and use Cloud Debugger snapshots to track request paths.

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Answer Description

Observability is achieved when you have correlated metrics, logs, and traces. Installing the Ops Agent on GKE nodes automatically streams system and container metrics to Cloud Monitoring and container stdout/stderr to Cloud Logging with minimal maintenance. Enabling Cloud Trace (with standard service instrumentation) supplies distributed tracing across microservices, completing the triad without operators running additional collectors or managing storage. The alternative approaches either fail to capture one of the three data types (for example, Cloud Profiler does not provide traces, VPC Flow Logs are not service metrics) or require you to operate extra components such as Prometheus sidecars and custom log pipelines, increasing operational burden.

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