PCD Practice Test 41 — 15 Questions

Question 1

Which TWO are best practices for setting up Cloud Monitoring alerting policies to minimize alert fatigue? (Select exactly 2.)

Accepted Answer

Use condition thresholds with an 'AND' combination of multiple metrics.. Option B is correct because combining multiple metrics with an 'AND' condition (e.g., high CPU AND high latency) makes the alert fire only when several signals co-occur, which filters out single-metric noise and reduces false positives that cause alert fatigue. Option E is correct because setting the 'for' parameter (the duration a condition must be continuously met before the incident opens) longer than typical transient spikes prevents short-lived blips from paging responders, so only sustained, actionable conditions trigger alerts. Option A is not a best practice because aggregating metrics across all projects blurs per-project context and can mask or merge unrelated issues, making alerts harder to act on. Option C is wrong because log-based metrics are not inherently less noisy than metric-based alerts; the choice should depend on the signal, not a blanket rule. Option D is wrong because creating a separate policy for every possible symptom multiplies notifications and is a primary cause of alert fatigue rather than a remedy.

Answer

Aggregate metrics across all projects before alerting.

Answer

Use log-based metrics for all alerts instead of metric-based alerts.

Answer

Create a separate alerting policy for each possible symptom.

Question 2

An e-commerce platform uses Cloud Spanner for transactions and Cloud Bigtable for session state and recommendations. They want to synchronize customer profile changes from Spanner to Bigtable in near real-time. Which three components should they use? (Choose 3)

Accepted Answer

Cloud Spanner change streams. Cloud Spanner change streams (C) is correct because it is the native Spanner feature that captures row-level data changes (inserts, updates, deletes) in near real-time, which is exactly what is needed to detect customer profile changes in Spanner. Cloud Dataflow (D) is correct because it provides a managed, autoscaling streaming pipeline that can read from Spanner change streams and write the transformed records into Cloud Bigtable. Cloud Pub/Sub (E) is correct because it serves as the durable, scalable messaging layer that decouples change capture from downstream processing, allowing Dataflow to consume change events and reliably fan them out toward Bigtable. Cloud Functions (A) is not appropriate here because a serverless function is not designed to run a continuous, high-throughput streaming pipeline from change streams to Bigtable. Cloud Scheduler (B) is not appropriate because it only triggers jobs on a cron schedule and cannot provide the near real-time, event-driven synchronization this scenario requires.

Answer

Cloud Functions

Answer

Cloud Scheduler

Question 3

A company needs to query data across Cloud SQL (MySQL) and Bigtable using BigQuery without moving the data. Which TWO configurations are required?

Accepted Answer

Create an external table in BigQuery that references the Bigtable table using a Bigtable URI.. Option C is correct because BigQuery supports external tables over Bigtable through the Bigtable URI (bigtable://project/instance/table) using the Bigtable external data source, which lets BigQuery query the Bigtable data in place without copying it. Option D is correct because BigQuery federated queries to Cloud SQL for MySQL are enabled by creating a Cloud SQL connection resource (a federated connection) and then an external table or EXTERNAL_QUERY that references that connection, so the Cloud SQL data is queried in place. Option A is not needed because BigQuery Omni is for querying data in other clouds such as AWS S3 or Azure Blob Storage, not for Cloud SQL or Bigtable within Google Cloud. Option B is not required because Dataflow replication would move/copy the data into BigQuery, which contradicts the requirement to query without moving the data. Option E is not required because BigQuery external tables and federated queries do not require the BigQuery dataset to be in the same region as the Cloud SQL instance or Bigtable instance, and co-location is not a configuration prerequisite for this scenario.

Answer

Enable BigQuery Omni for cross-cloud querying.

Answer

Use Dataflow to replicate Cloud SQL and Bigtable data to BigQuery.

Answer

Create a BigQuery dataset in the same region as Cloud SQL and Bigtable.

Question 4

A company is deploying a microservices application on Google Kubernetes Engine (GKE) and needs to ensure that services can discover each other without hardcoding IP addresses. Which approach should they use?

Accepted Answer

Use Cloud DNS with Kubernetes Services of type ClusterIP. Kubernetes Services of type ClusterIP provide a stable virtual IP and DNS name (via Cloud DNS) that resolves to the service's ClusterIP, enabling pods to discover each other without hardcoding IP addresses. GKE integrates with Cloud DNS to automatically register service DNS names in the format ..svc.cluster.local, allowing microservices to communicate reliably even if pods are rescheduled or IPs change.

Answer

Use environment variables injected into each pod

Answer

Use a ConfigMap to store service endpoints

Answer

Use Cloud Load Balancing to route traffic between services

Question 5

A developer needs to ensure that environment variables containing secrets are securely passed to a Cloud Function during deployment. Which approach should they use?

Accepted Answer

Use Secret Manager. Secret Manager is the recommended Google Cloud service for securely storing and accessing secrets such as API keys, passwords, and certificates. It provides encryption at rest and in transit, fine-grained IAM access control, and versioning, allowing the Cloud Function to reference secrets by name at deployment time without exposing them in source code or configuration files.

Answer

Store in source code

Answer

Use Cloud KMS

Answer

Use runtime environment variables

Question 6

Refer to the exhibit. A developer deployed a Cloud Run service as shown. Authenticated requests from another service in the same project using a service account receive 403 Forbidden. What is the most likely cause?

Accepted Answer

The service account used to authenticate is not granted the roles/run.invoker role on the Cloud Run service. The Cloud Run service requires the IAM role `roles/run.invoker` on the service itself for any principal (including a service account) to invoke it. Since the service was deployed with `--no-allow-unauthenticated`, only explicitly granted principals can invoke it. The service account used for authentication lacks this role, causing the 403 Forbidden response.

Answer

The Cloud Run service requires the 'allAuthenticatedUsers' member to be added

Answer

The --no-allow-unauthenticated flag blocks all requests including authenticated ones

Answer

The container image was built without proper authentication headers

Question 7

A team is migrating a monolithic app to microservices. They need to handle distributed transactions across services. Which pattern should they use?

Accepted Answer

Saga pattern. The Saga pattern is the correct choice for managing distributed transactions across microservices because it breaks a long-lived transaction into a sequence of local transactions, each with a compensating action to roll back if a subsequent step fails. This avoids the tight coupling and performance bottlenecks of distributed locking or two-phase commit, which are unsuitable for cloud-native, highly scalable environments. Sagas can be orchestrated (via a coordinator) or choreographed (via events), and they align with eventual consistency principles required for high availability.

Answer

Eventual consistency with compensation

Answer

Distributed lock manager

Answer

Two-phase commit

Question 8

Which TWO strategies can be used to reduce cold start latency in Cloud Run? (Choose 2)

Accepted Answer

Set a minimum number of instances (min-instances) to keep instances warm.. Setting a minimum number of instances (min-instances) ensures that a specified number of container instances are always running and ready to serve requests, eliminating the cold start latency that occurs when an instance must be started from scratch. This pre-warming strategy directly reduces the time users wait for the first request to be processed.

Answer

Increase the maximum number of concurrent requests per instance.

Answer

Deploy the Cloud Run service in a region closer to the users.

Answer

Use a VPC connector to access resources in a VPC network.

Question 9

A company wants to design a highly available web application that serves users globally. They plan to use Cloud Load Balancing. Which two design choices should they make to ensure high availability and low latency? (Choose two.)

Accepted Answer

Enable Cloud CDN to cache static content closer to users.. Option A is correct because enabling Cloud CDN caches static content at Google's globally distributed edge points of presence, reducing latency for users and offloading requests from backend services. Option B is correct because a global external HTTPS Load Balancer uses Google's global anycast IP and routes traffic to the closest healthy backend service across multiple regions, providing both low latency and high availability through multi-region failover. Option C is incorrect because a single-zone backend instance group creates a single point of failure and does not provide high availability. Option D is incorrect because Cloud Armor provides security filtering against DDoS and application-layer attacks, but it does not directly improve latency or availability. Option E is incorrect because deploying separate regional load balancers with DNS-based routing adds complexity and DNS failover is slower and less reliable than a single global load balancer with multi-region backends.

Answer

Use a single-zone backend instance group for simplicity.

Answer

Use Cloud Armor to filter malicious traffic.

Answer

Deploy separate regional load balancers in each region and use DNS-based routing.

Question 10

A DevOps team is deploying a critical application on GKE. To ensure application performance monitoring and reliability, which three actions should they take? (Choose three.)

Accepted Answer

Enable Cloud Monitoring to collect container metrics. Option A is correct because enabling Cloud Monitoring on GKE (via Google Cloud Managed Service for Prometheus or the built-in GKE metrics pipeline) collects container-level metrics such as CPU, memory, and network usage, which are essential for performance monitoring and reliability. Option C is correct because readiness probes determine whether a pod is ready to receive traffic; when a probe fails, the pod is removed from the Service endpoints, ensuring users are only routed to healthy, ready pods. Option E is correct because liveness probes detect containers that are running but unhealthy (e.g., deadlocked), and kubelet restarts them automatically, improving application reliability. Option B is not appropriate because Cloud Debugger is a debugging tool, not a performance/reliability monitoring mechanism, and it is generally not recommended to run it in production for this purpose. Option D is not selected because Cloud Profiler is a continuous CPU/heap profiling tool for code optimization, not a core action for ensuring application performance monitoring and reliability in this scenario.

Answer

Enable Cloud Debugger in production to debug code

Answer

Use Cloud Profiler to continuously profile CPU usage

Question 11

Which TWO statements about Cloud Run for Anthos are correct? (Choose 2)

Accepted Answer

Cloud Run for Anthos allows users to autoscale their containerized applications without worrying about underlying GKE nodes.. Cloud Run for Anthos leverages the Knative Serving autoscaler to automatically scale container instances up or down based on incoming request traffic, including scaling to zero when idle. This autoscaling operates at the pod level within the GKE cluster, abstracting away the underlying node management from the user.

Answer

Cloud Run for Anthos is a multi-region service by default.

Answer

Cloud Run for Anthos supports only HTTP requests, not gRPC.

Answer

Cloud Run for Anthos requires you to bring your own load balancer.

Question 12

A mobile app startup needs a serverless, scalable NoSQL database that supports offline sync and real-time updates. Which database should they choose?

Accepted Answer

Firestore in Native mode. Firestore (Native mode) provides serverless NoSQL document storage, offline sync for mobile clients, and real-time listeners for updates. It is the ideal choice for mobile and web apps.

Answer

Bigtable

Answer

Cloud SQL

Answer

Memorystore

Question 13

A developer wants to view real-time latency metrics for their App Engine application. Where can they find this data?

Accepted Answer

Cloud Monitoring - Metrics Explorer. Cloud Monitoring's Metrics Explorer allows you to view real-time latency metrics for App Engine by querying the `appengine.googleapis.com/http/server/response_latencies` metric. This provides a time-series view of request latency distributions, enabling immediate observation of performance changes as they occur.

Answer

Cloud Profiler

Answer

Cloud Logging

Answer

Cloud Trace

Question 14

Your company uses Cloud SQL for MySQL to store transactional data. You need to perform a point-in-time recovery (PITR) to recover from a logical error that occurred 30 minutes ago. Which two prerequisites must be met? (Choose TWO.)

Accepted Answer

Binary logging is enabled.. Option B is correct because Cloud SQL for MySQL performs point-in-time recovery by replaying binary log (binlog) events on top of a base backup, so binary logging must be enabled for PITR to work. Option C is correct because PITR requires a base automated backup to which the binary logs can be applied; without automated backups enabled, there is no recovery point to start from. Option A is not required because high availability is about failover to a standby instance, not about PITR capability. Option D is not required because the backup window only controls when automated backups run; PITR can recover to any point within the retention period regardless of the window. Option E is not required because a read replica is for read scaling and does not provide the binary-log-based recovery mechanism needed for PITR.

Answer

High availability (HA) is configured.

Answer

The backup window is set to a time before the incident.

Answer

A read replica is configured.

Question 15

Your Cloud Spanner database runs a query that uses a secondary index. The query plan shows an 'Index Join' operation. What can you do to eliminate this join and improve query performance?

Accepted Answer

Use the STORING clause to include the needed columns in the index. The 'Index Join' operation in Cloud Spanner occurs when a secondary index does not contain all the columns needed by the query, forcing Spanner to join the index with the base table to retrieve the missing data. By using the STORING clause (also known as covering index), you include the required columns directly in the index, allowing Spanner to satisfy the query entirely from the index without accessing the base table, thus eliminating the join and improving performance.

Answer

Change the index to a local index

Answer

Create a new interleaved table

Answer

Rewrite the query as a join