PCDE Implementing Service Monitoring Strategies Practice Test 2 — 15 Questions

Question 1

A DevOps engineer wants to create an alerting policy that fires when the 99th percentile of request latency exceeds 2000 ms for any 5-minute window. Which metric type and aggregation should they use?

Accepted Answer

Use a distribution metric with reducer 99th percentile. The 99th percentile is a distribution metric. Cloud Monitoring supports distribution metrics and can compute percentiles. The correct approach is to use a metric of type distribution with reducer set to 99th percentile.

Answer

Use a GAUGE metric with reducer MAX

Answer

Use a CUMULATIVE metric with reducer DELTA

Answer

Use a DELTA metric with reducer COUNT

Question 2

An application running on GKE needs to send custom metrics to Cloud Monitoring. The team wants to use a vendor-neutral instrumentation approach that also supports traces and logs. Which solution should they choose?

Accepted Answer

Use OpenTelemetry SDK and OTel Collector to export to Cloud Monitoring and Cloud Trace. OpenTelemetry is a vendor-neutral standard for observability (metrics, traces, logs). The OpenTelemetry Collector can run as a DaemonSet on GKE and export data to Cloud Monitoring and Cloud Trace.

Answer

Use the Cloud Monitoring API directly from the application to write metrics

Answer

Use Prometheus client library and scrape metrics with Managed Service for Prometheus

Answer

Use the Stackdriver Monitoring client library

Question 3

A team wants to create a log-based metric that counts ERROR log entries grouped by the service name extracted from a JSON field. The log entries are structured JSON with a 'service' key. Which type of log-based metric should they create?

Accepted Answer

Counter metric with a label extracted from 'service' field. To count log entries and group by a label, a counter metric is appropriate. Distribution metrics are for histograms of numeric values, not counting.

Answer

Alerting policy with a condition on 'service' field

Answer

Gauge metric with the 'service' field as value

Answer

Distribution metric with a histogram of the 'service' field

Question 4

A company uses Cloud Logging and wants to receive real-time notifications when the number of 5xx errors exceeds 100 per minute. They need to set up an alerting policy. Which metric type and condition should they use?

Accepted Answer

Create a log-based counter metric and use a metric-threshold condition with rate alignment. A log-based counter metric can count errors per minute. The alert condition should be 'metric threshold' with 'CUMULATIVE' metric and 'rate' alignment to detect spikes.

Answer

Create a log-based counter metric and use a metric-absent condition

Answer

Use a Cloud Monitoring gauge metric with a custom value

Answer

Use a logs-based alert with a threshold on the log entry count

Question 5

Which Cloud Monitoring dashboard chart type is best suited to show the distribution of request latencies across multiple services over time?

Accepted Answer

Heatmap. Heatmap charts are ideal for showing distribution across two dimensions (e.g., service and time) with color intensity representing count or latency.

Answer

Scorecard

Answer

Line chart

Answer

Stacked bar chart

Question 6

A DevOps engineer needs to create a dashboard as code for Cloud Monitoring. They want to version-control the dashboard definition. Which method should they use?

Accepted Answer

Use the Cloud Monitoring API to create dashboards from a Terraform resource. Cloud Monitoring dashboards can be defined using the REST API or gcloud commands, and the JSON/YAML definition can be stored in version control.

Answer

Use gcloud alpha monitoring dashboards create command with a JSON file

Answer

Create the dashboard via the Cloud Console and export the JSON representation

Answer

Use Grafana with Cloud Monitoring data source and export dashboard JSON

Question 7

An application running on Cloud Run is experiencing high tail latency. The team wants to visualize which functions are consuming the most CPU time. Which Google Cloud tool should they use and how should they instrument the application?

Accepted Answer

Cloud Profiler with OpenTelemetry or Profiler agent. Cloud Profiler provides continuous profiling (CPU, heap, etc.) with low overhead. For Cloud Run, the Profiler can be enabled via the Cloud Profiler Java agent or OpenTelemetry.

Answer

Cloud Monitoring with custom metrics for CPU

Answer

Cloud Trace with automatic instrumentation

Answer

Cloud Logging with structured logs

Question 8

An engineer wants to automatically group similar error messages from an application and track trends, with the ability to link from an error to the corresponding log entries and trace. Which Google Cloud service should they use?

Accepted Answer

Error Reporting. Error Reporting automatically groups errors, shows trends, and integrates with Cloud Logging and Cloud Trace for full context.

Answer

Cloud Logging with log-based metrics

Answer

Cloud Trace

Answer

Cloud Monitoring with custom dashboards

Question 9

A company uses Cloud Profiler to analyze CPU usage of a Java application running on GKE. They see a function consuming 40% of CPU time. To investigate further, they want to see the exact line numbers in the source code. What should they do?

Accepted Answer

Enable debug symbols in the application and upload source code to Cloud Profiler. Cloud Profiler requires the source code to be available and configured for symbolication. The flame graph shows function names, but line numbers require source context.

Answer

Use Cloud Trace to trace the function call

Answer

Enable structured logging for the application

Answer

Switch to a different profiling tool

Question 10

Which notification channel can be used with Cloud Monitoring to trigger a custom workflow in Cloud Functions when an alert fires?

Accepted Answer

Cloud Pub/Sub. Cloud Pub/Sub is a notification channel that can trigger downstream services like Cloud Functions.

Answer

Slack via Pub/Sub

Answer

PagerDuty

Answer

Email

Question 11

An application is emitting structured JSON logs that include a 'request_id' field used for correlation. The team wants to enable log correlation with Cloud Trace so they can navigate from a log entry to its trace. What must they include in the log entry?

Accepted Answer

The trace ID in a field named 'trace' in the JSON payload. Cloud Logging automatically correlates logs with traces when the log entry contains the trace field with the correct format.

Answer

A logging label with key 'trace' and value set to the trace ID

Answer

The span ID in a field named 'span'

Answer

The request ID in a field named 'request_id'

Question 12

A company wants to set up an alert that fires if any Compute Engine instance has a CPU utilization above 80% for more than 5 minutes. They have thousands of instances. Which alerting condition type and configuration is most efficient?

Accepted Answer

Use a metric-threshold condition with resource group filter set to 'gce_instance' and a threshold of 80%. A metric-threshold condition using a policy with multiple conditions (one per instance) would be cumbersome. Instead, use a grouped alert with a threshold on the metric and apply to all instances via a monitored resource filter.

Answer

Use a logs-based alert on CPU logs

Answer

Create a separate alert for each instance using instance-specific conditions

Answer

Use a metric-absent condition to detect when CPU metric stops reporting

Question 13

A DevOps team is implementing distributed tracing for a microservices application on GKE. They want to ensure traces are exported to Cloud Trace with minimal overhead. Which TWO approaches should they consider? (Choose 2)

Accepted Answer

Instrument the application using the OpenTelemetry SDK and configure the OTel Collector to export to Cloud Trace. OpenTelemetry SDK and automatic instrumentation for GKE (via Anthos Service Mesh) are both valid. The Stackdriver Trace API is deprecated in favor of OpenTelemetry.

Answer

Configure a Prometheus metric to capture trace data

Answer

Use the Stackdriver Trace API directly from the application

Answer

Use the Cloud Monitoring API to send trace data

Question 14

An organization wants to monitor a batch processing job that runs daily on Compute Engine. They need to be alerted if the job fails to produce output within 24 hours. Which THREE components should they use? (Choose 3)

Accepted Answer

Create a log-based counter metric that increments upon job completion. A log-based metric counting success messages, an alert with metric-absent condition, and a notification channel. The metric-absent condition fires when the metric stops reporting (i.e., no success log within 24h).

Answer

Create a Cloud Monitoring dashboard to visualize the metric

Answer

Use Cloud Trace to trace the job execution

Question 15

A team wants to use OpenTelemetry to collect metrics, traces, and logs from their applications running on GKE. They plan to use the OTel Collector. Which TWO components should they configure in the Collector pipeline? (Choose 2)

Accepted Answer

Configure a receiver (e.g., OTLP receiver) to ingest telemetry from applications. The OTel Collector pipeline consists of receivers (data ingestion), processors (optional), and exporters (data output). For this scenario, they need a receiver to accept data and exporters to send to Google Cloud.

Answer

Configure a processor to transform data

Answer

Configure an exporter for Cloud Logging (logs)

Answer

Configure a sampler to reduce trace data volume