PCDOE Timed Practice Test 4 — 10 Questions

Question 1

An application on GKE frequently reads the same data from a Cloud Storage bucket. The data changes rarely. Which solution will best improve read performance and reduce costs?

Accepted Answer

Deploy a sidecar container that caches the data in an emptyDir volume.. Correct: Use a sidecar container with a shared emptyDir volume to cache data from Cloud Storage using a tool like gcsfuse with caching. Option A is wrong because persistent volumes are for stateful workloads. Option C is wrong because read replicas are for databases. Option D is wrong because increasing node count does not improve per-pod read speed.

Answer

Configure a Cloud SQL read replica for the data.

Answer

Increase the number of nodes in the cluster.

Answer

Use a StatefulSet with a persistent volume claim to store the data.

Question 2

Refer to the exhibit. After applying the shown firewall rule, users report increased latency to a web application. What is the most likely cause?

Accepted Answer

The rule contains both allow and deny for the same traffic, creating a conflict.. Correct: The rule has both allow and deny with same ports, and the rule is contradictory; the deny overrides because deny rules are evaluated after allow? Actually in VPC firewall rules, allow and deny cannot both be specified in the same rule. This is an invalid combination. The rule may cause unexpected behavior. Option A is wrong because logging alone does not cause latency. Option B is wrong because source range is all. Option D is wrong because priority is not high.

Answer

The rule priority is set to 1000, which is too low.

Answer

The source range covers all IPs, causing excessive traffic.

Answer

The firewall rule has logging enabled, which adds overhead.

Question 3

An application running on App Engine standard environment has high instance startup latency, leading to slow first requests. What is the most effective configuration change to reduce cold starts?

Accepted Answer

Set min_idle_instances to a value greater than 0. Setting a minimum number of idle instances ensures that instances are always ready to serve traffic, eliminating startup delays. Manual scaling (A) requires manual capacity planning; increasing memory (C) may not reduce startup time; Cloud Endpoints (D) is for API management.

Answer

Use manual scaling instead of automatic scaling

Answer

Use Cloud Endpoints for request authentication

Answer

Increase the memory limit per instance

Question 4

A web application frequently reads the same set of reference data from Cloud SQL. This causes high database load and slow responses. Which design change would most improve performance?

Accepted Answer

Implement caching with Memorystore for Redis. Implementing caching with Memorystore reduces database load by serving repeated reads from memory, which is faster than SQL queries. Increasing machine size or adding read replicas helps but still involves database I/O; Cloud Spanner is overkill for reference data.

Answer

Increase Cloud SQL machine size

Answer

Add a read replica

Answer

Use Cloud Spanner for higher throughput

Question 5

Which TWO metrics from Cloud Monitoring would best indicate that a GKE workload is experiencing CPU throttling due to a resource quota? (Choose 2)

Accepted Answer

container/cpu/throttled_time. Option B is correct because `container/cpu/throttled_time` directly measures the cumulative time a container's CPU usage was throttled due to exceeding its assigned CPU quota (CFS quota). Option D is correct because `container/cpu/usage_time` shows the actual CPU time used by the container; when compared against the quota limit, a high usage_time relative to the quota indicates that throttling is likely occurring. Together, these two metrics confirm both the occurrence and the cause of CPU throttling.

Answer

node/cpu/usage_time

Answer

container/memory/usage_bytes

Answer

container/accelerator/duty_cycle

Question 6

You are designing a globally distributed application using Cloud Spanner. The application has a write-heavy workload. You notice that write latency increases as the number of nodes increases. What is the most likely cause?

Accepted Answer

The workload has many cross-node transactions due to split rows.. Option B is correct because in Cloud Spanner, write-heavy workloads with many cross-node transactions cause increased write latency as nodes are added. This occurs because Spanner splits rows across nodes, and transactions that span multiple splits require two-phase commit (2PC) coordination between nodes, which adds network overhead and latency. Adding more nodes increases the likelihood that a transaction touches multiple splits, exacerbating the coordination cost.

Answer

The instance is using a multi-region configuration with too many read-only replicas.

Answer

The application is using stale reads for write transactions.

Answer

The number of splits is too low, causing hotspots.

Question 7

Which THREE factors should you consider when designing a Cloud Run service for optimal performance under unpredictable traffic patterns? (Choose 3)

Accepted Answer

Set a minimum number of instances to reduce cold starts.. Option B is correct because setting a minimum number of instances ensures that Cloud Run always keeps a baseline of warm instances ready to serve requests. This eliminates cold starts for the first requests during traffic spikes, which is critical for unpredictable traffic patterns where latency spikes from cold starts would degrade user experience.

Answer

Use HTTP/2 for faster connection reuse.

Answer

Configure VPC egress through Cloud NAT for lower latency.

Question 8

Your organization requires that all new Google Cloud projects are automatically configured with a common set of VPC networks and subnets, and that these networks must be created before any resources are deployed. What is the best approach to enforce this requirement across the organization?

Accepted Answer

Use Organization Policies with a custom constraint to enforce that all projects must have a specific VPC network configuration.. Organization Policies with custom constraints allow you to enforce that all new projects automatically include specific VPC networks and subnets before any resources are deployed. This is the only approach that provides mandatory, organization-wide enforcement at the project creation level, ensuring compliance without relying on manual templates or post-creation configuration.

Answer

Create a Cloud Deployment Manager template and share it with all project owners.

Answer

Set up VPC Network Peering between all projects to enforce network connectivity.

Answer

Configure a shared VPC host project and attach all new service projects to it.

Question 9

A development team wants to automatically run unit tests and static code analysis on every push to a Cloud Source Repository, but only run integration tests on merges to the main branch. Which Cloud Build trigger configuration should they use?

Accepted Answer

Create two triggers: one with a branch filter for '^main$' that runs integration tests, and another with a branch filter for '^.*$' that runs unit tests.. Option C is correct because Cloud Build triggers allow you to define separate triggers with branch filters to execute different build configurations based on the branch. By creating one trigger with a branch filter of '^main$' for integration tests and another with '^.*$' for unit tests, you ensure unit tests run on every push to any branch, while integration tests run only on merges to main. This approach directly maps the desired behavior without requiring conditional logic or manual intervention.

Answer

Use a single trigger with a substitution variable like '_BRANCH' and set it to 'main' for integration tests.

Answer

Create one trigger with a build config that uses the 'branchName' substitution to conditionally skip integration test steps.

Answer

Configure one trigger with no branch filter and rely on developers to manually trigger integration tests.

Question 10

An organization uses Cloud Build with a private pool to build container images that require access to on-premises Artifactory. After moving to a new VPC, builds fail with 'Connection refused' when fetching dependencies. What is the best step to troubleshoot?

Accepted Answer

Verify that VPC Network Peering is established between the Cloud Build private pool's service producer VPC and the customer VPC, and that routes to on-premises are present.. The error 'Connection refused' indicates that the Cloud Build private pool's worker VMs cannot reach the on-premises Artifactory server. Private pools are deployed in a Google-managed service producer VPC that must be connected to the customer VPC via VPC Network Peering. Without this peering and the correct routes to the on-premises network (e.g., via Cloud VPN or Dedicated Interconnect), traffic from the private pool is dropped, causing the connection refusal.

Answer

Verify that the Cloud Build service account has the dns.networks.bindPrivateZone permission.

Answer

Check that the Cloud Build service account has the storage.objectViewer role on the Artifactory bucket.

Answer

Ensure that Cloud NAT is configured in the private pool's VPC.