PCDOE Practice Test 9 — 10 Questions

Question 1

Your team is running a high-traffic web application on Google Kubernetes Engine (GKE) and has configured Horizontal Pod Autoscaling (HPA) based on CPU utilization. Recently, the application experienced intermittent latency spikes during traffic bursts. You suspect that the HPA is not scaling quickly enough. Which TWO actions would most effectively improve the autoscaling responsiveness?

Accepted Answer

Configure a custom metric in HPA based on the application's request latency (e.g., p99 latency).. Option B is correct because using a custom metric based on request latency (e.g., p99 latency) allows HPA to react to application performance degradation directly, rather than relying solely on CPU utilization which may lag behind traffic bursts. This provides a more immediate signal for scaling, as latency spikes often precede CPU saturation in web applications. Option D is correct because reducing the --horizontal-pod-autoscaler-upscale-stabilization window (default 5 minutes) to a lower value like 30 seconds decreases the time HPA waits before acting on scale-up recommendations, enabling faster response to sudden load increases.

Answer

Increase the target CPU utilization percentage to 90% so that pods are less likely to be added.

Answer

Set the maxReplicas of the HPA to a value lower than the expected peak traffic to force faster scaling.

Answer

Increase the --horizontal-pod-autoscaler-sync-period flag to 30 seconds and increase the --horizontal-pod-autoscaler-upscale-delay flag to 5 minutes.

Question 2

A company is running a stateful workload on Compute Engine and has configured a TCP health check on port 8080. The health check is failing, but the application is running and responding on port 8080 when tested manually from within the instance. What is the most likely cause of the health check failure?

Accepted Answer

The firewall rules are not allowing traffic from the health check probe IP ranges.. The health check probes originate from Google's health check systems, which use specific IP ranges (e.g., 35.191.0.0/16, 130.211.0.0/22). If firewall rules on the instance or VPC do not explicitly allow inbound traffic from these probe IP ranges on port 8080, the health check will fail even though the application is running and responding to manual tests from within the instance. This is the most common cause of health check failures when the application itself is healthy.

Answer

The health check is configured to use port 80 instead of port 8080.

Answer

The instance's DNS resolution is failing, causing the health check to use the wrong IP.

Answer

The health check response timeout is set too low (e.g., 1 second).

Question 3

A team uses Cloud Build with a Kaniko builder to containerize their application. The build fails with the error: 'failed to push to destination: failed to get credentials: failed to get credential from metadata service: failed to fetch metadata...' What is the most likely cause?

Accepted Answer

The Cloud Build service account does not have the storage.objectAdmin role on the Container Registry bucket.. The error indicates that Kaniko cannot authenticate to push the built image to Container Registry. Kaniko uses the Cloud Build service account's credentials to authenticate with the registry. By default, the Cloud Build service account has the storage.objectViewer role on the Container Registry bucket, which allows pulling images but not pushing. To push, the service account needs the storage.objectAdmin or storage.objectCreator role on the bucket. Option D correctly identifies this missing permission as the most likely cause.

Answer

Kaniko requires a running Docker daemon in the build step.

Answer

The base image specified in the Dockerfile is not accessible from the build environment.

Answer

The Dockerfile has an invalid instruction causing Kaniko to fail.

Question 4

A company uses Cloud Deploy to manage rollouts to GKE. They need to implement a deployment strategy where a new version receives 10% of traffic for 30 minutes, then automatically rolls forward to 100% if no issues are detected. Which THREE Cloud Deploy features are required? (Choose three.)

Accepted Answer

A canary deployment strategy with a 10% phase.. Option A is correct because a canary deployment strategy in Cloud Deploy allows you to define phases that gradually shift traffic to a new revision. A 10% phase is the first step in this strategy, ensuring only a small subset of users experience the new version initially, which aligns with the requirement to start with 10% traffic.

Answer

A manual approval gate before the 100% phase.

Answer

An Istio VirtualService configuration for traffic splitting.

Question 5

A DevOps engineer is setting up alerting policies for a critical API service. They want to receive an alert if the error rate exceeds 5% for at least 5 minutes, but only during business hours (9 AM to 5 PM). Which approach should they use?

Accepted Answer

Create an alerting policy with a condition that triggers when the error rate is above 5% for 5 minutes, and configure the notification channel to only send notifications during business hours using a webhook receiver that checks time.. Option B is correct because it uses a single alerting policy with a condition that triggers when the error rate exceeds 5% for 5 minutes, and then controls notification delivery via a webhook receiver that checks the current time. This approach ensures the alert is evaluated continuously (so the 5-minute window is respected) but only notifications are suppressed outside business hours, which is the most reliable way to meet the requirement without missing alert evaluations or relying on external scheduling.

Answer

Create a log-based metric for errors and use a condition with a threshold, then set the alert policy to only run during business hours using the 'condition' schedule.

Answer

Create two separate alert policies, one for business hours and one for off-hours, each with different thresholds.

Answer

Use Cloud Scheduler to enable and disable the alerting policy at the start and end of business hours.

Question 6

Which THREE of the following are valid approaches to monitor a custom application metric in Cloud Monitoring? (Choose 3)

Accepted Answer

Use the Cloud Monitoring API to write time series data directly.. Option B is correct because the Cloud Monitoring API allows you to write custom metric data directly via the `projects.timeSeries.create` endpoint. This is the most direct programmatic approach, supporting arbitrary metric descriptors and time series data without requiring any agent or intermediary.

Answer

Install the Stackdriver Monitoring agent on a Windows VM and configure custom metric collection in the agent configuration file.

Answer

Use the built-in JMX plugin in the Cloud Monitoring agent to collect Java application metrics.

Question 7

You are using Cloud CDN with an external HTTPS load balancer. Users in Asia report slow load times for static assets. The origin is in us-central1. What should you do to improve performance?

Accepted Answer

Enable Cloud CDN and configure cache modes for static content.. Cloud CDN caches static assets at Google's global edge locations, reducing latency for users in Asia by serving content from a nearby point of presence instead of the us-central1 origin. Enabling Cloud CDN and configuring cache modes for static content (e.g., setting Cache-Control headers or using origin cache policies) ensures that frequently requested assets are served from cache, dramatically improving load times for geographically distant users.

Answer

Switch the load balancer to an internal HTTPS load balancer with gRPC.

Answer

Use premium tier networking for the load balancer.

Answer

Configure a serverless NEG to route traffic to Cloud Functions.

Question 8

A Cloud Run service is experiencing increased cold start latency. The service is written in Python and uses several large dependencies. Which action would most effectively reduce cold start latency?

Accepted Answer

Set a minimum number of instances to keep containers warm.. Option C is correct because setting a minimum number of instances ensures that the Cloud Run service always has a pool of warm containers ready to serve requests, eliminating the cold start penalty. Cold starts in Python are particularly severe due to the time required to import large dependencies (e.g., NumPy, TensorFlow) and initialize the runtime. By keeping containers alive, you bypass the entire initialization phase, directly addressing the root cause of increased latency.

Answer

Set concurrency to 1 to ensure each request gets a dedicated container.

Answer

Increase the CPU allocation to 4 vCPUs.

Answer

Increase memory to 2 GiB.

Question 9

Which THREE approaches can help reduce egress costs while improving performance for a multi-region application using Cloud Load Balancing? (Choose 3)

Accepted Answer

Optimize data transfer by compressing responses.. Option A is correct because compressing responses reduces the amount of data transferred over the network, which directly lowers egress costs charged by cloud providers. Smaller payloads also reduce latency and improve perceived performance for end users, as less data needs to travel across regions.

Answer

Increase the number of instances in each region.

Answer

Use premium tier networking for lower latency.

Question 10

You are using Memorystore for Redis as a cache for a high-traffic web application. You observe that cache hit ratio is low, causing high database load. What is the most effective way to improve cache hit ratio?

Accepted Answer

Use the allkeys-lru eviction policy to keep frequently accessed keys.. The allkeys-lru eviction policy is the most effective way to improve cache hit ratio because it automatically evicts the least recently used keys across the entire keyspace when memory is full, retaining the most frequently accessed data. This ensures that the cache always contains the hottest data, directly increasing the likelihood of cache hits without requiring manual intervention or additional resources.

Answer

Increase the instance size to store more data.

Answer

Migrate to Memorystore for Memcached for lower latency.

Answer

Set a longer TTL for all cache entries.