PCDE Implementing Service Monitoring Strategies Practice Test 3 — 15 Questions

Question 1

A DevOps engineer wants to create a custom metric in Cloud Monitoring that represents the number of requests processed by a service, measured from the start of each request to its completion. The metric should increment by 1 for each request and must be queryable for the count in the last 24 hours. Which metric kind would best suit this requirement?

Accepted Answer

CUMULATIVE. A CUMULATIVE metric measures a value that increases over time, such as a count of requests. It is appropriate when you want to know the total count up to a point in time, which can be queried for any time range (e.g., last 24 hours) by subtracting the start value from the end value. GAUGE represents a snapshot value that can go up and down, DELTA represents a rate per time interval but does not accumulate.

Answer

DELTA

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COUNT

Answer

GAUGE

Question 2

An application running on Google Kubernetes Engine (GKE) emits structured logs in JSON format. The DevOps team wants to count the number of log entries that contain a specific error code (e.g., 'error_code': 500) in the last hour and use that count to trigger an alert if it exceeds a threshold. What is the most efficient way to achieve this?

Accepted Answer

Create a log-based counter metric in Cloud Logging with the filter jsonPayload.error_code=500, then set up an alerting policy on that metric.. Creating a log-based metric from the logs is the most efficient approach. You can define a counter metric that increments each time a log entry matches the filter (e.g., jsonPayload.error_code=500). Then you can set up an alerting policy on that metric. This avoids scanning logs in real-time and provides a metric that can be used for dashboards and alerts.

Answer

Use Cloud Logging's Logs Explorer to run a query every minute and use Cloud Scheduler to trigger a Cloud Function that checks the count.

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Export logs to BigQuery and run a scheduled query to count error codes, then use the result to trigger an alert via Cloud Monitoring.

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Configure a metric threshold alert directly on the log entries in Cloud Monitoring without creating a metric.

Question 3

You are designing a distributed tracing strategy for a multi-service application deployed on Cloud Run and GKE. You need to ensure that all traces are captured with 100% sampling for the first 10 minutes after a new deployment, and then reduce to 10% sampling to control costs. Which approach should you use?

Accepted Answer

Use OpenTelemetry SDK with a custom sampler that checks the deployment timestamp stored in an environment variable, and send traces to the OpenTelemetry Collector configured to export to Cloud Trace.. Cloud Trace supports probability-based sampling, but to change the sampling rate based on time since deployment, you need more control. Using OpenTelemetry with a custom sampler in the application allows you to implement a rule: sample 100% if the deployment timestamp is within the last 10 minutes, else sample 10%. The OTel Collector can then export to Cloud Trace. Cloud Trace's built-in sampling is static.

Answer

Use Stackdriver Trace's automatic instrumentation on GKE and Cloud Run, and adjust the sampling rate via the Cloud Trace API after deployment.

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Use Cloud Trace's built-in probabilistic sampler and configure it with 10% sampling in the configuration file.

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Enable Cloud Trace on all services and use Cloud Monitoring alert on trace count to trigger a Cloud Function that changes the sampling rate.

Question 4

A DevOps engineer wants to visualize the 99th percentile latency of an HTTP endpoint over the past week using Cloud Monitoring dashboards. The metric is available as a distribution from Cloud Trace. Which chart type should they use to display this percentile over time?

Accepted Answer

Line chart. A line chart is best for showing a metric value (like 99th percentile latency) over time. Heatmaps are for distributions, scatter plots show correlation, and stacked bars show contributions of components. The percentile over time is a single value per time point, so a line chart is appropriate.

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Heatmap

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Stacked bar chart

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Scatter chart

Question 5

You need to monitor a critical batch job that runs daily on Compute Engine. If the job does not complete within 2 hours, you want to be paged via PagerDuty. The job emits a custom metric 'batch_duration' as a GAUGE that records the duration of the last completed run. What alerting policy condition should you use?

Accepted Answer

Metric absent condition: with duration of 2 hours on the 'batch_duration' metric.. Since the metric only has a value when the job completes, you need to detect the absence of data. If the job fails or doesn't run, the metric will stop reporting. A 'metric absent' condition triggers if no data is received for a specified duration (e.g., 2 hours). This is more reliable than a threshold on the gauge value, which might still show an old value.

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Forecast condition: predict that duration will exceed 2 hours.

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Log-based metric alert: count log entries indicating job failure.

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Metric threshold condition: threshold > 7200 (seconds) on the 'batch_duration' metric.

Question 6

A company wants to use Cloud Monitoring dashboards to display real-time metrics for their application, but they also need to version control the dashboard configurations. Which approach should they use?

Accepted Answer

Define dashboards as code using the Cloud Monitoring API and store the configuration in a Git repository.. Cloud Monitoring dashboards can be defined as JSON or YAML and managed via the Monitoring API or Terraform. This allows version control and CI/CD. Manually creating dashboards in the console is not reproducible.

Answer

Manually create dashboards in the Cloud Monitoring console and export them periodically.

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Use Grafana with the Cloud Monitoring data source and export dashboard JSON.

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Use Cloud Monitoring's built-in 'Clone' feature to backup dashboards.

Question 7

Your team uses PagerDuty for incident notifications. You need to configure Cloud Monitoring to send alerts to PagerDuty. Which notification channel type should you select?

Accepted Answer

PagerDuty. Cloud Monitoring supports PagerDuty as a notification channel type directly. You can configure it by providing the PagerDuty integration key. No other channel types (email, Slack, Pub/Sub) are needed.

Answer

Slack

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Cloud Pub/Sub

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SMS

Question 8

An engineer needs to troubleshoot a performance issue where a specific function in a Go application is consuming excessive CPU. They want to identify the exact lines of code causing the bottleneck with minimal overhead. Which Google Cloud tool should they use?

Accepted Answer

Cloud Profiler. Cloud Profiler continuously profiles CPU, heap, and other resources with very low overhead (~0.5%). It provides flame graphs that show which functions consume the most CPU, helping identify hot functions. Error Reporting focuses on errors, Cloud Trace on latency, and Cloud Monitoring on metrics.

Answer

Error Reporting

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Cloud Monitoring

Answer

Cloud Trace

Question 9

A DevOps engineer wants to create a dashboard that shows the number of 5xx errors per service over time. The errors are logged in Cloud Logging. What is the most efficient way to create this dashboard?

Accepted Answer

Create a log-based counter metric for 5xx errors, then add a chart in Cloud Monitoring using that metric.. First, create a log-based metric that counts log entries with severity ERROR and status code 5xx. Then, in Cloud Monitoring, create a dashboard with a chart using that metric, grouped by service. This avoids querying logs directly and provides a reusable metric.

Answer

Write a custom application that sends the error count to Cloud Monitoring as a custom metric via API.

Answer

Export logs to BigQuery and use Data Studio to create a dashboard.

Answer

Use Cloud Logging's metrics explorer to create a chart and embed it in a dashboard.

Question 10

You have a Cloud Monitoring alerting policy that triggers when CPU usage exceeds 80% for 5 minutes. You want to add documentation to the alert that includes a link to a runbook and labels indicating the affected service. How can you achieve this?

Accepted Answer

Edit the alerting policy and add documentation with the runbook URL and labels under the 'Documentation' section.. Cloud Monitoring alerting policies support documentation fields where you can provide markdown text including links and labels. This is done when creating or editing the policy in the console or via API. Labels can be attached to the alert policy to help with filtering and routing.

Answer

Create a separate Cloud Storage bucket and reference it in the alert.

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Use Cloud Logging to store runbook URLs and attach them to alerts via log-based metrics.

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Use Cloud Monitoring's notification channel to include a link in the email body.

Question 11

A team is using OpenTelemetry to instrument their microservices and wants to export traces to Cloud Trace. They have deployed the OpenTelemetry Collector as a DaemonSet on GKE. What configuration is needed on the Collector to send traces to Cloud Trace?

Accepted Answer

Configure the 'googlecloud' exporter with a project ID and service account credentials.. The OpenTelemetry Collector needs an exporter configured for Google Cloud Trace. The 'googlecloud' exporter (or 'stackdriver' exporter) sends traces to Cloud Trace. The Collector must also have the appropriate IAM permissions (e.g., roles/cloudtrace.agent).

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No configuration needed; the Collector automatically detects GKE and exports to Cloud Trace.

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Configure the 'logging' exporter in the Collector to write traces to stdout, and use a sidecar to forward them.

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Use the 'otlp' exporter to send traces to Cloud Trace's OTLP endpoint.

Question 12

Your organization mandates that all application logs must be structured JSON and include a trace ID for correlation with Cloud Trace. Developers are using various logging libraries. Which approach ensures consistent structured logging across all services with minimal code changes?

Accepted Answer

Adopt OpenTelemetry SDK and use its logging API to produce structured logs with trace context.. The OpenTelemetry SDK provides a unified way to instrument logging, metrics, and traces. By using the OTel logging SDK, developers can emit structured logs that include trace context automatically. This ensures consistency across polyglot environments without requiring custom code.

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Use a centralized logging agent (e.g., Fluentd) to parse unstructured logs and add trace IDs.

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Require developers to manually format JSON logs and include trace IDs from environment variables.

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Use Cloud Logging's automatic trace ID extraction from log entries.

Question 13

A DevOps team needs to set up alerting for a critical application that runs on Compute Engine. They want to be notified if the application process crashes (i.e., stops sending heartbeats) for more than 5 minutes. The application emits a custom metric 'app_heartbeat' as a GAUGE with value 1 every 60 seconds. Which TWO configurations should they use? (Choose 2)

Accepted Answer

Duration: 5 minutes. To detect a crash, you need a metric absent condition (no data for 5 minutes) because the gauge value will stop reporting. Setting the duration to 5 minutes ensures timely notification. A threshold condition on the gauge value would not trigger if the value stays at 1. The alignment period and reducer are not relevant for absent conditions.

Answer

Alignment period: 60 seconds

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Metric threshold condition: threshold < 1

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Reducer: MEAN

Question 14

You are designing a monitoring strategy for a hybrid cloud environment where on-premises services send metrics to Cloud Monitoring via the Monitoring API. The on-premises network has limited outbound connectivity and can only reach Google Cloud through a few static IPs. You need to ensure that custom metrics are ingested reliably and cost-effectively. Which THREE actions should you take? (Choose 3)

Accepted Answer

Use a service account with roles/monitoring.metricWriter on the on-premises application. To handle limited connectivity, using a Cloud VPN tunnel ensures secure and reliable connectivity. The Monitoring API requires authentication via a service account, and a VPC Service Controls perimeter can protect data exfiltration. Pushing metrics from on-premises is the standard approach. Pulling is not supported.

Answer

Enable Cloud NAT to provide outbound connectivity

Answer

Use Cloud Monitoring's Agent to pull metrics from on-premises

Question 15

A company wants to use Cloud Logging to monitor for a specific error pattern in their application logs. They want to create a metric that counts occurrences of the error and then set up an alert when the count exceeds 100 in 5 minutes. Which TWO components are required? (Choose 2)

Accepted Answer

Alerting policy with metric threshold condition. A log-based counter metric counts matching log entries. An alerting policy can then be configured to trigger when the metric exceeds a threshold. The metric itself does not need to be distribution-based (that's for histogram values). The alignment period is part of the alert condition, not a separate component.

Answer

Notification channel (e.g., email)

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Log-based distribution metric

Answer

Cloud Monitoring dashboard