PCDOE Practice Exam 2 — 20 Questions

Question 1

Which THREE are recommended practices for setting up alerting on Google Cloud?

Accepted Answer

Set alert thresholds with a buffer (e.g., below SLO). Setting alert thresholds with a buffer below the SLO (e.g., alert at 99.9% when SLO is 99.99%) provides early warning before the SLO is breached. This proactive approach allows time for investigation and remediation, preventing actual SLO violations and ensuring service reliability targets are met.

Answer

Use multiple conditions with OR combiner to cover all scenarios

Answer

Use a single alerting policy for all services

Question 2

Based on the exhibit, what does the duration of 300s mean in this alerting policy?

Accepted Answer

The alert fires if CPU utilization is above 80% for at least 5 consecutive minutes.. In the Google Cloud Monitoring alerting policy shown in the exhibit, the duration of 300s (5 minutes) defines the minimum period during which the CPU utilization must continuously exceed the 80% threshold before the alert fires. This prevents transient spikes from triggering unnecessary alerts. Option A correctly states that the alert fires only if CPU utilization is above 80% for at least 5 consecutive minutes, matching the policy's configuration.

Answer

The alert fires after 300 seconds of sustained CPU utilization above 80% with a count of 1.

Answer

The alert fires if CPU utilization averaged over 5 minutes exceeds 80%.

Answer

The alert fires if CPU utilization is above 80% for any 5-minute window in the last hour.

Question 3

A service is deployed on Cloud Run. You need to monitor memory usage per revision. How can you create an alert?

Accepted Answer

Configure Cloud Run to send metrics to Cloud Monitoring and create an alert in Cloud Monitoring. Cloud Run automatically exports built-in metrics, including memory usage per revision, to Cloud Monitoring without any additional configuration. By creating an alerting policy in Cloud Monitoring based on the `run.googleapis.com/container/memory/utilizations` metric, you can monitor memory usage per revision directly. Option B correctly identifies this native integration, making it the most efficient and reliable approach.

Answer

Deploy a sidecar container that collects memory metrics and pushes to Cloud Monitoring

Answer

Use Cloud Console and navigate to Cloud Run services to set an alert directly

Answer

Use Cloud Logging to parse container logs for memory usage

Question 4

A team needs to monitor the availability of an HTTPS endpoint that requires a Bearer token in the request header. What is the simplest way to configure this with Cloud Monitoring?

Accepted Answer

Configure the Uptime Check to include a custom header with the Bearer token.. Cloud Monitoring's Uptime Checks natively support custom HTTP headers, including Authorization headers with Bearer tokens. This allows you to directly monitor an authenticated HTTPS endpoint without any additional infrastructure, scripting, or log-based workarounds. It is the simplest and most straightforward configuration for this requirement.

Answer

Deploy a sidecar container that handles the authentication and exposes a plain endpoint.

Answer

Use a synthetic monitor from Cloud Monitoring that handles authentication via a script.

Answer

Export the endpoint logs to Cloud Logging and set up a log-based metric for availability.

Question 5

A startup runs a web application on GKE. They notice that during traffic spikes, the application becomes unresponsive, and they want to automatically scale the number of pods based on CPU utilization. Which Kubernetes resource should they use?

Accepted Answer

Horizontal Pod Autoscaler (HPA). The Horizontal Pod Autoscaler (HPA) is designed to automatically scale the number of pods in a deployment based on metrics like CPU utilization. It directly addresses the need to handle traffic spikes by adding more replicas when demand increases, ensuring the application remains responsive.

Answer

Pod Disruption Budget (PDB)

Answer

Cluster Autoscaler

Answer

Vertical Pod Autoscaler (VPA)

Question 6

A team wants to ensure zero-downtime deployments for a Cloud Run service. They plan to gradually shift traffic from the current revision to the new one. What should they configure?

Accepted Answer

Use Cloud Run's traffic splitting feature to slowly increase traffic to the new revision. Cloud Run natively supports traffic splitting between revisions, allowing you to gradually shift a percentage of traffic to a new revision while the old revision continues serving the remainder. This enables canary or gradual rollouts with zero downtime, and you can adjust percentages incrementally via multiple updates until the new revision reaches 100%.

Answer

Use Cloud Build to directly replace the revision

Answer

Set traffic to 100% on the new revision gradually using multiple updates

Answer

Configure a rolling update strategy in Cloud Deploy

Question 7

Refer to the exhibit.

```yaml
name: projects/my-project/alertPolicies/12345
displayName: High Error Rate
combiner: OR
conditions:
- conditionThreshold:
    filter: metric.type="logging.googleapis.com/user/myapp/error_count" resource.type="k8s_container"
    aggregations:
    - alignmentPeriod: 60s
      perSeriesAligner: ALIGN_RATE
    duration: 120s
    comparison: COMPARISON_GT
    thresholdValue: 5
    trigger:
      count: 1
```

An engineer notices that this alert fires too frequently during normal operation. Which change would most likely reduce the noise?

Accepted Answer

Increase duration to 300s.. Increasing the duration to 300s means the condition (error rate > 5 per second) must be sustained for a full 5 minutes before the alert fires. This reduces noise by filtering out transient spikes that occur during normal operation, which are shorter than the new duration window. The original 120s duration allowed short-lived bursts to trigger the alert too frequently.

Answer

Change combiner to AND.

Answer

Change perSeriesAligner to ALIGN_MEAN.

Answer

Decrease thresholdValue to 1.

Question 8

A DevOps team wants to serve static content from a Cloud Storage bucket with low latency globally. They also need TLS termination. Which load balancer type should they use?

Accepted Answer

External HTTP(S) Load Balancer. External HTTP(S) Load Balancer is the correct choice because it provides global anycast IP addresses, TLS termination at the Google Front End (GFE), and integrates directly with Cloud Storage buckets as a backend. This enables low-latency content delivery worldwide while offloading SSL decryption to the load balancer.

Answer

External Network Load Balancer

Answer

SSL Proxy Load Balancer

Answer

Internal HTTP(S) Load Balancer

Question 9

A Cloud Run service experiences high latency during cold starts. The service is memory-intensive. Which configuration change will most effectively reduce cold start latency?

Accepted Answer

Set a minimum number of instances.. Setting a minimum number of instances ensures that a baseline of pre-warmed instances is always running, eliminating cold starts for the initial requests. For a memory-intensive service, this avoids the latency penalty of loading large libraries or datasets into memory on first invocation. This is the most direct and effective configuration change to reduce cold start latency.

Answer

Decrease the container concurrency setting.

Answer

Increase the max instances limit.

Answer

Enable CPU boost for the service.

Question 10

An e-commerce platform uses Cloud SQL for its database. The team notices that read queries are slow. They want to improve read performance without significant cost increase. Which action should they take?

Accepted Answer

Add a read replica. Adding a read replica is the most cost-effective way to improve read query performance in Cloud SQL. A read replica offloads SELECT queries from the primary instance, reducing contention and latency for read-heavy workloads, without requiring a more expensive primary instance. This approach scales read capacity horizontally while keeping the primary instance's compute and storage unchanged.

Answer

Increase the number of vCPUs on the instance

Answer

Increase the storage size

Answer

Enable binary logging

Question 11

A company uses Compute Engine with committed use discounts for 1-year. They need to reduce costs further. What should they do?

Accepted Answer

Rightsize their VMs based on recommender recommendations.. Rightsizing VMs based on Google Cloud's Recommender recommendations is the correct next step because committed use discounts (CUDs) lock in a discount on a committed spend or resource amount, but if the VMs are over-provisioned, you are still paying for unused capacity. Rightsizing reduces the baseline resource consumption, which lowers both on-demand and committed costs. This is the standard FinOps practice after securing a discount.

Answer

Use sustained use discounts instead.

Answer

Use preemptible VMs for all workloads.

Answer

Increase committed use discount term to 3 years.

Question 12

During a Cloud Build pipeline, a build step fails because the Docker image tag already exists in Container Registry. The team wants to avoid overwriting tags. What is the best practice to resolve this?

Accepted Answer

Use the commit SHA as the image tag in the build step.. Using the commit SHA as the image tag guarantees uniqueness because each commit produces a distinct SHA. This prevents tag collisions in Container Registry without overwriting, as the SHA is immutable for that commit. It also provides traceability back to the exact source code version that produced the image.

Answer

Specify the :latest tag and always push to that tag.

Answer

Add a step to pull the image before building to ensure it's present.

Answer

Configure the build to retry on failure with a backoff.

Question 13

A GKE cluster node fails, causing pods to be rescheduled. However, some pods remain in 'CrashLoopBackOff' state. After examining logs, you find the application has a dependency on local SSD that was ephemeral. What is the best long-term solution?

Accepted Answer

Use PersistentVolumes with ReadWriteOnce access mode.. The application's dependency on local SSD (ephemeral storage) means that when the node fails, the data is lost, causing the pods to crash. PersistentVolumes (PVs) with ReadWriteOnce (RWO) access mode provide durable, node-independent storage that survives node failures, ensuring pods can be rescheduled on any node and access their data. This is the best long-term solution because it decouples storage from the node lifecycle, preventing CrashLoopBackOff due to missing local data.

Answer

Configure pod anti-affinity.

Answer

Increase the node pool size.

Answer

Use a DaemonSet to run the application.

Question 14

Which Cloud Run setting controls the maximum number of requests a container can handle concurrently?

Accepted Answer

concurrency. The `concurrency` setting in Cloud Run defines the maximum number of simultaneous requests that a single container instance can process at any given time. This directly controls how many requests are routed to a single container before Cloud Run spins up additional instances, optimizing resource utilization and preventing overload.

Answer

timeout

Answer

max-instances

Answer

min-instances

Question 15

An SRE team created the above logs-based metric. They expect it to count the number of HTTP 500 errors per instance. However, the metric shows no data. What is the most likely cause?

Accepted Answer

The log entries might not have the 'status' field in jsonPayload; it could be in a different location or format.. The most likely reason for a logs-based metric showing no data is that the log entries do not contain the expected 'status' field in jsonPayload, or it is located in a different field (e.g., httpRequest.status) or formatted as a string instead of an integer. Cloud Logging metrics rely on exact field paths defined in the metric descriptor; if the field is missing or misnamed, no data points are generated.

Answer

The metric kind is DELTA but should be CUMULATIVE.

Answer

The metric name does not follow the required naming convention.

Answer

The labelExtractors must use regex instead of JSON path.

Question 16

You are the DevOps engineer for a large gaming company. Your game backend runs on Compute Engine instances behind a global HTTP(S) Load Balancer. You have set up Cloud Monitoring with an uptime check for the load balancer's IP address, and you are using logging to capture 404 errors. Recently, a new game update caused a surge in traffic, and you started receiving many alerts from your uptime check indicating that the site is down. However, you verify that the backend instances are healthy and the load balancer is responding correctly, though some requests are timing out due to the increased load. Your alerting policy currently triggers when 2 consecutive checks fail. What is the most likely reason for the false positive alerts?

Accepted Answer

The uptime check's timeout is too short for the current response times.. The uptime check's timeout is too short for the current response times. When a surge in traffic causes some requests to time out, the load balancer may still respond correctly to most requests, but the uptime check—which has a fixed timeout (default 10 seconds)—fails if the response does not arrive within that window. Since the alert triggers after 2 consecutive failures, the check falsely reports the site as down even though the backend and load balancer are healthy.

Answer

The global load balancer's health check is failing due to the surge.

Answer

The monitoring project has reached its limit for concurrent uptime checks.

Answer

The uptime check is configured to check a specific URL that is returning a 503 status code.

Question 17

A company runs a high-traffic web application on GKE. Which three practices can help optimize performance under load? (Select THREE.)

Accepted Answer

Use a global load balancer. Option A (Use a global load balancer) is correct because a Google Cloud global external load balancer distributes traffic across multiple regions using anycast IP and Google's global edge network, reducing latency and absorbing load spikes for a high-traffic web application on GKE. Option C (Store session state in Cloud Memorystore) is correct because externalizing session state to a managed Redis/Memcached service makes pods stateless, allowing horizontal scaling and even distribution of requests without session affinity bottlenecks. Option D (Enable HorizontalPodAutoscaler with custom metrics) is correct because HPA with custom metrics (e.g., via Stackdriver/Cloud Monitoring adapters) scales pod replicas based on application-level signals like requests per second or queue depth, matching capacity to real load rather than just CPU. Option B (Use a multi-cluster ingress) is not among the correct answers because it addresses multi-cluster traffic routing and failover rather than directly optimizing performance under load for a single GKE workload. Option E (Increase the number of nodes to maximum) is not among the correct answers because blindly maximizing node count is costly and inefficient without autoscaling policies tied to actual demand.

Answer

Use a multi-cluster ingress

Answer

Increase the number of nodes to maximum

Question 18

A data processing company runs nightly batch jobs that can tolerate interruptions. They want to minimize compute costs. Which compute option should they use?

Accepted Answer

Preemptible VMs. Preemptible VMs are the correct choice because they offer the lowest cost for interruptible workloads. They are priced significantly lower than standard VMs (up to 80% discount) but can be terminated by Google Cloud at any time, with a 30-second warning, and have a maximum lifetime of 24 hours. Since the batch jobs can tolerate interruptions, preemptible VMs align perfectly with the cost-minimization goal.

Answer

VMs with committed use discounts

Answer

Standard VMs with sustained use discounts

Answer

Sole-tenant nodes

Question 19

A team implements canary deployments using Cloud Deploy and deploys to GKE. They want to automatically roll back if the canary release's error rate exceeds 5% within 10 minutes. Which approach should they use?

Accepted Answer

Set up Cloud Deploy with a rollout strategy that uses Cloud Monitoring metrics to automatically rollback.. Cloud Deploy supports rollout strategies that can reference Cloud Monitoring metrics to automatically roll back a canary release if error rates exceed a threshold. This native integration allows defining a canary deployment with automated rollback based on metrics like error rate within a specified time window, directly meeting the requirement.

Answer

Deploy using Spinnaker on GKE with a canary pipeline that includes an automated rollback step.

Answer

Configure a Cloud Build step to monitor the canary and rollback if needed.

Answer

Use a GKE rolling update strategy within the deployment manifest.

Question 20

In Google's incident management process, which role is responsible for communication with stakeholders and users during an incident?

Accepted Answer

Communications Lead.. In Google's incident management process, the Communications Lead is explicitly responsible for managing all external and internal communications, including updates to stakeholders and users. This role ensures that accurate, timely information is disseminated while the Incident Commander focuses on coordinating the response. The Communications Lead does not engage in technical troubleshooting or operational tasks, which are handled by other roles.

Answer

Incident Commander.

Answer

Technical Lead.

Answer

Operations Lead.