PCDE Practice Test 45 — 15 Questions

Question 1

You are investigating a performance issue in a distributed application. You want to identify the services causing high latency. Which TWO tools should you use together? (Choose two.)

Accepted Answer

Cloud Trace. Cloud Trace analyzes latency distributions and identifies slow requests. Cloud Profiler identifies hot functions consuming CPU/memory. Cloud Monitoring shows metrics but not traces, Cloud Logging shows logs, and Error Reporting shows errors.

Answer

Error Reporting

Answer

Cloud Logging

Answer

Cloud Monitoring

Question 2

Which Cloud Monitoring feature allows you to group log entries from the same request across multiple services using a common identifier?

Accepted Answer

Cloud Trace. Cloud Trace uses trace IDs to correlate requests across services. Logs can include the trace ID to enable correlation between logs and traces.

Answer

Cloud Profiler

Answer

Log-based metrics

Answer

Error Reporting

Question 3

An application is emitting custom metrics using OpenTelemetry. You want to collect and export these metrics to Cloud Monitoring. Which TWO components are required? (Select 2)

Accepted Answer

OpenTelemetry SDK in the application. The OpenTelemetry Collector can receive metrics from the application and export them to Cloud Monitoring using the Google Cloud Monitoring exporter.

Answer

Cloud Logging Agent

Answer

Cloud Monitoring Agent

Answer

Pub/Sub topic

Question 4

A Pub/Sub subscription is processing messages but the subscriber cannot keep up. The team notices that many messages are being resent. Which parameter should they adjust to reduce duplicate processing?

Accepted Answer

Increase the acknowledgement deadline. Increasing the acknowledgement deadline gives the subscriber more time to process and ack messages, reducing the chance that they expire and are redelivered.

Answer

Decrease the acknowledgement deadline

Answer

Increase the retention duration

Answer

Enable ordering keys

Question 5

A Cloud Spanner database uses a sequential customer ID as the primary key, causing frequent hotspotting on a single split. The team needs to eliminate hotspots. Which key design should they implement?

Accepted Answer

Add a hash prefix derived from the customer ID. Hotspots occur with monotonically increasing keys. Using a hash prefix or UUID spreads writes across splits. Bit-reverse is another technique for integers. The simplest is to add a hash prefix to the key.

Answer

Use a composite key with a monotonically increasing timestamp as the first part

Answer

Use a random UUID as the primary key

Answer

Keep the sequential key but add a secondary index

Question 6

A Cloud SQL for MySQL instance's storage utilization has reached 95%. The database is 5 TB and needs to grow. The operations team tries to increase storage via gcloud but receives an error. What is the likely cause?

Accepted Answer

The instance is at the maximum storage limit for its machine tier. Cloud SQL allows online storage increases but with limits: the maximum storage cannot exceed 30 TB, and the increase must be done in increments. However, the error is likely because the instance is using the maximum allowed storage for its tier, or the storage cannot be shrunk. But the most common issue is that the instance has an on-demand backup or restore operation in progress, which blocks resize. Another possibility is that the storage is already at the maximum for that machine type. However, the question implies a common misconfiguration: the instance may have a read replica that is replicating from it, and storage resize is not allowed if the replica is in a different region? Actually, storage resize is allowed regardless. More likely: the user has reached the maximum storage size for the current tier (e.g., db-n1-standard-8 supports up to 10 TB). The correct answer is tier storage limit.

Answer

The storage resize operation is only allowed during maintenance windows

Answer

The instance has binary logging enabled, which prevents storage increase

Answer

The instance has automatic storage increase disabled

Question 7

A Cloud Run service handles HTTP requests that each involve a short background task after the response is sent. The service currently has CPU throttled when not handling requests, causing background tasks to fail. Which configuration change ensures background tasks complete?

Accepted Answer

Set CPU to 'always on'. Setting CPU to 'always on' prevents Cloud Run from throttling CPU when the container is not actively serving a request, allowing background tasks to complete. Min instances reduce cold starts but don't affect CPU throttling. Concurrency controls request handling. Execution environment gen2 offers higher memory but doesn't change CPU throttling behavior.

Answer

Set concurrency to 1

Answer

Set execution environment to gen2

Answer

Set min instances to 1

Question 8

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

Question 9

A GKE cluster runs a mix of batch and latency-sensitive services. The batch jobs require occasional large CPU bursts, but the latency-sensitive services need consistent performance. The team wants to avoid CPU contention without over-provisioning nodes. Which approach should they take?

Accepted Answer

Create separate node pools: one with high-CPU machines for batch jobs and one with general-purpose machines for latency-sensitive services, and use taints/tolerations. Node pools with different machine types allow separating workloads onto appropriate hardware. Using taints and tolerations ensures that batch pods only run on the batch node pool, preventing interference with latency-sensitive services on the general pool. This approach avoids over-provisioning by right-sizing each pool. VPA and HPA adjust resources/replicas but do not prevent CPU contention between different workloads on the same node. PDBs control disruptions, not resource contention.

Answer

Configure a PodDisruptionBudget for the latency-sensitive services

Answer

Use Vertical Pod Autoscaler (VPA) for all pods

Answer

Use Horizontal Pod Autoscaler (HPA) with CPU target

Question 10

A DevOps engineer is optimizing a Cloud Run service that performs background data processing tasks triggered by Pub/Sub messages. The tasks are CPU-intensive and can run up to 10 minutes each. The service currently experiences cold starts causing delays. Which configuration should the engineer apply to minimize cold starts and ensure the background tasks are not throttled?

Accepted Answer

Set min instances to 1, CPU always-on, concurrency to 1. Setting a minimum number of instances ensures that at least one instance is always warm, eliminating cold starts. Setting CPU always-on prevents the CPU from being throttled during background processing, which is necessary for tasks that are not triggered by an HTTP request. Concurrency should be set to 1 to avoid multiple tasks competing for CPU on the same instance.

Answer

Set min instances to 1, CPU throttled, concurrency to 80

Answer

Set min instances to 0, CPU always-on, concurrency to 1000

Answer

Set min instances to 0, CPU always-on, concurrency to 1

Question 11

You are deploying a batch job on Compute Engine that processes large datasets and can tolerate interruptions. The job runs for about 6 hours every night. Which option would minimize cost while ensuring the job completes within the 6-hour window?

Accepted Answer

Use preemptible VMs to get up to 80% discount, with checkpointing to resume if preempted.. Preemptible VMs are significantly cheaper (up to 80% discount) but can be terminated at any time. For fault-tolerant batch jobs, preemptible VMs are ideal; if preempted, the job can resume on another preemptible VM. Committed use discounts provide cost savings for steady-state usage (1- or 3-year commitment), but are not suitable for a nightly 6-hour job. Custom machine types or standard VMs would be more expensive.

Answer

Use standard VMs with committed use discounts for 1 year.

Answer

Use custom machine types to optimize cost.

Answer

Use sole-tenant nodes for dedicated hardware.

Question 12

A company is designing a monitoring strategy for a microservices application on Google Kubernetes Engine. They need to capture traces, metrics, and logs using a vendor-neutral approach. Which TWO components should they consider? (Choose 2)

Accepted Answer

OpenTelemetry Collector as a DaemonSet

Answer

Cloud Logging agent

Answer

Stackdriver agents on each node

Answer

Cloud Trace automatic instrumentation

Question 13

A company uses Artifact Registry to store Docker images. They want to enforce that only images signed by a trusted authority can be deployed to their GKE cluster. Which service should they use with Artifact Registry?

Accepted Answer

Binary Authorization. Binary Authorization enforces deployment-time policy based on image signatures. Container Analysis scans for vulnerabilities, not enforcements; IAM controls access; Cloud Build is the CI service.

Answer

Identity and Access Management (IAM)

Answer

Container Analysis

Answer

Cloud Build

Question 14

A gaming company ingests player clickstream data in real time via Cloud Pub/Sub. They need to aggregate events per player session in BigQuery with exactly-once semantics. Which architecture minimizes latency and cost?

Accepted Answer

Use Cloud Dataflow with exactly-once processing to BigQuery. Cloud Dataflow with exactly-once processing is the correct choice because it provides a unified stream and batch processing model that guarantees exactly-once semantics when writing to BigQuery via the BigQuery I/O connector. This minimizes latency by processing events in micro-batches or streaming mode while avoiding duplicate data, and it is cost-effective as Dataflow auto-scales based on the Pub/Sub throughput.

Answer

Use Cloud Functions to write each message directly to BigQuery

Answer

Use Cloud Pub/Sub subscription to write to BigQuery directly

Answer

Use Cloud Dataproc to run Spark streaming jobs

Question 15

Your Cloud Spanner instance is experiencing high write latency and hot spots on a table that uses an auto-incrementing integer as the primary key. Which change would best mitigate the hot spots?

Accepted Answer

Change the primary key to a random UUID.. Monotonically increasing keys (like auto-incrementing integers) cause all writes to go to the same tablet (hot spot) in Cloud Spanner. Using a key with uniform distribution, such as a random UUID or a hash prefix, spreads writes across splits. Bit-reverse index is an alternative for sequential keys, but a random key is simpler. Interleaved tables and secondary indexes do not address the root cause.

Answer

Add a secondary index on the auto-incrementing column.

Answer

Increase the number of splits by raising the number of nodes.

Answer

Use interleaved tables to store related data together.