PCD Multiple Select — 50 Questions

Question 1

A company is designing a cloud-native application on Google Kubernetes Engine. They want to ensure high availability and scalability for their microservices. Which two best practices should they follow?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Use horizontal pod autoscaling based on custom metrics.. Horizontal Pod Autoscaling (HPA) based on custom metrics allows the application to automatically scale the number of pod replicas in response to application-specific signals (e.g., requests per second, queue depth) rather than just CPU/memory. This ensures that each microservice can handle varying load efficiently, maintaining high availability and scalability without over-provisioning.

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Use a single cluster per region.

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Use a single replica for each service to reduce cost.

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Use stateful sets for all services.

Question 2

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.. Using multiple conditions with AND logic reduces false positives. Setting 'for' duration prevents transient spikes from alerting. Aggregating across projects first is not best practice; it's better to alert per project. Using log-based metrics for everything is not always appropriate. Synthetic monitors are for availability, not general alerting.

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Aggregate metrics across all projects before alerting.

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

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Create a separate alerting policy for each possible symptom.

Question 3

A developer is building a serverless application that processes user-uploaded images. The images are stored in Cloud Storage, and each upload should trigger a Cloud Function that performs image analysis and stores the result in Firestore. Which TWO Google Cloud services are essential for this integration? (Choose 2)

Accepted Answer

Cloud Pub/Sub. Cloud Storage is the source of events (uploaded images). Cloud Pub/Sub is used to deliver notifications from Cloud Storage to the Cloud Function. Cloud Tasks, Cloud Scheduler, and Eventarc are not required for this pattern.

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Cloud Tasks

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Eventarc

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Cloud Scheduler

Question 4

A company is building a data processing pipeline that needs to ingest events from multiple sources, process them in order, and handle failures with retry. They also need to schedule periodic tasks. Which THREE services should they use? (Choose 3)

Accepted Answer

Cloud Scheduler. Cloud Pub/Sub for ingesting events with ordering, Cloud Tasks for retry handling, and Cloud Scheduler for scheduling periodic tasks. Cloud Workflows is for orchestration, Cloud Logging is for logs.

Answer

Cloud Workflows

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Cloud Logging

Question 5

You are designing a serverless application using Cloud Functions that processes events from Cloud Storage and Cloud Pub/Sub. The function must be idempotent and handle duplicate events. Which three best practices should you implement? (Choose THREE.)

Accepted Answer

Generate a unique idempotency key for each event and store processed keys in a database.. Generating a unique idempotency key for each event and storing processed keys in a database (such as Cloud Firestore) ensures that if the same event is delivered multiple times (e.g., due to at-least-once delivery semantics in Cloud Pub/Sub or Cloud Storage notifications), the function can check the key before processing and skip duplicates. This pattern is essential for idempotent serverless functions, as Cloud Functions may be retried on failure or receive duplicate events from the source.

Answer

Invoke the function synchronously to avoid duplicates.

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Set the function timeout to maximum (540 seconds) to ensure processing completes.

Question 6

A development team is building a containerized application on Google Cloud. They want to implement a CI/CD pipeline that automatically builds and tests their application on every push to the main branch. Which TWO actions should they take to achieve this?

Accepted Answer

Configure a Cloud Build trigger to run on push events to the main branch.. Cloud Build triggers can be configured to automatically start a build whenever a push event occurs on a specific branch, such as main. This is the standard way to initiate a CI/CD pipeline in response to code changes in Google Cloud.

Answer

Enable Cloud Run for Anthos to automatically deploy after build.

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Use Cloud Scheduler to trigger a Cloud Build trigger every 5 minutes.

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Create a Cloud Source Repository and use Cloud Functions to build on push.

Question 7

You need to select a Google Cloud database for a global e-commerce platform that requires strong consistency for inventory updates, but can tolerate eventual consistency for product reviews. Which THREE services would you consider appropriate for the different parts of the platform?

Accepted Answer

Bigtable for real-time user behavior tracking. Bigtable is correct for real-time user behavior tracking as it is a fully managed, scalable NoSQL database designed for high-throughput, low-latency workloads, providing strong consistency for single-row operations. Firestore is suitable for product reviews because it supports eventual consistency for multi-region queries, meeting the tolerance requirement, while offering strong consistency within a single region. Cloud Spanner is ideal for inventory data because it provides global strong consistency and ACID transactions, crucial for inventory accuracy across regions.

Answer

BigQuery for storing product reviews

Answer

Cloud SQL for inventory

Question 8

A startup is migrating a 100 GB PostgreSQL database from a self-managed VM to Cloud SQL. They want zero downtime during cutover. Which TWO features of Database Migration Service should they use?

Accepted Answer

Promote the Cloud SQL replica to standalone instance for cutover.. Continuous migration with CDC enables cutover with minimal downtime. Promoting the replica is the final step to make Cloud SQL the primary with zero downtime.

Answer

Use Cloud SQL Auth Proxy for source connectivity.

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Use VPC peering to connect source to Cloud SQL.

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One-time migration job.

Question 9

A company is using Cloud Bigtable for a high-throughput write workload. They notice periodic latency spikes. Which two metrics should they monitor to diagnose the issue? (Choose two.)

Accepted Answer

Error count. Request latency directly measures performance. Error count indicates failures or throttling. CPU utilization and disk usage are less direct indicators for write spikes. However, the question asks for two metrics to diagnose latency spikes; the most relevant are request latency and error count.

Answer

Disk bytes used

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Network throughput

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CPU utilization

Question 10

A company is designing a polyglot persistence architecture. They need to use Cloud SQL for transactions, Bigtable for real-time analytics, and BigQuery for reporting. They also need to keep data across these systems eventually consistent. Which TWO approaches should they use?

Accepted Answer

Implement a saga pattern with compensating transactions for each write.

Answer

Use two-phase commit across all databases.

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Use Cloud Spanner as a single database to avoid polyglot complexity.

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Write to all three databases in a single transaction using distributed transactions.

Question 11

You are designing a Cloud Bigtable schema for a time-series application. To optimize performance and avoid hot spots, which THREE row key design practices should you follow? (Choose 3)

Accepted Answer

Place the highest cardinality field (e.g., device ID) first in the row key. Reversing timestamps, salting keys, and promoting high-cardinality fields to the start of the row key are recommended to distribute writes evenly.

Answer

Use a single table for all data

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Use sequential integers as row keys

Question 12

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. Spanner change streams capture changes, Pub/Sub provides a scalable messaging channel, and Dataflow can transform and write to Bigtable. Cloud Functions could be used but are less suitable for high-throughput. Cloud Scheduler is batch-oriented.

Answer

Cloud Functions

Answer

Cloud Scheduler

Question 13

A team is deploying a microservice application on Google Kubernetes Engine (GKE). They want to ensure high availability and minimize downtime during rolling updates. Which TWO actions should they take? (Choose two.)

Accepted Answer

Configure pod disruption budgets to limit the number of pods that can be unavailable simultaneously.. PodDisruptionBudgets (PDBs) allow you to specify the minimum number of pods that must remain available during voluntary disruptions like rolling updates, ensuring high availability. Option D is correct because readiness probes control when a pod is added to a Service's endpoints; during rolling updates, they prevent traffic from being sent to a pod until it is ready, minimizing downtime.

Answer

Use Horizontal Pod Autoscaler to automatically adjust the number of pods based on CPU utilization.

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Enable liveness probes to automatically restart pods that become unresponsive.

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Enable node auto-repair to automatically replace unhealthy nodes.

Question 14

A financial services company uses BigQuery for analytics but needs to store transactional data with strong consistency and sub-millisecond latency. They are considering Cloud SQL, Cloud Spanner, Bigtable, Memorystore, and Firestore. Which service meets all requirements?

Accepted Answer

Cloud Spanner. Cloud Spanner is the only Google Cloud service that provides both strong consistency and sub-millisecond latency for transactional workloads. It uses TrueTime for global strong consistency and supports ACID transactions with low latency. Cloud SQL offers strong consistency but cannot achieve sub-millisecond latency at scale due to single-region limits. Bigtable provides low latency but only eventual consistency. Memorystore is a caching layer, not a transactional database. Firestore provides strong consistency but typically does not guarantee sub-millisecond latency for high-throughput transactional data, especially under financial workload requirements.

Answer

Cloud SQL

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Bigtable

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Memorystore

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Firestore

Question 15

A company is designing a web application that must scale horizontally to handle variable traffic. Which two practices should they implement to ensure the application is stateless and can scale without issues?

Accepted Answer

Offload session state to the user's browser using encrypted cookies.. To achieve statelessness, session state should either be stored in an external cache (e.g., Memorystore) or offloaded to the client (e.g., using cookies). Sticky sessions tie a client to a specific instance, preventing scaling. Using a database like Cloud SQL for session persistence creates a bottleneck. Regional managed instance groups improve availability but do not directly address statelessness.

Answer

Persist session data in Cloud SQL to ensure durability.

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Deploy the application across multiple regional managed instance groups.

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Use sticky sessions to maintain client affinity.

Question 16

A company is using Cloud Run for a stateless API. They want to ensure that the service can handle sudden traffic spikes. Which two features should they configure?

Accepted Answer

Enable container concurrency.. Enabling container concurrency allows a single Cloud Run container instance to handle multiple requests simultaneously, up to the configured concurrency limit (default 80, max 1000). This improves throughput and resource utilization during traffic spikes without requiring additional instances. Option D is correct because setting max instances to a high value ensures the service can scale out to handle sudden load by creating more container instances, up to the configured maximum, preventing cold starts and request queuing.

Answer

Use Cloud Load Balancing.

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Enable CPU always on allocation.

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Set min instances to zero to save cost.

Question 17

Which TWO are best practices for reducing the cost of Cloud Logging for a high-traffic application?

Accepted Answer

Use exclusion filters to drop debug logs.. Exclusion filters in Cloud Logging allow you to drop specific log entries (e.g., debug-level logs) before they are ingested, which directly reduces the volume of logs billed. Since Cloud Logging charges based on the amount of data ingested, excluding high-volume, low-value logs like debug messages is a primary cost-saving measure.

Answer

Route all logs to BigQuery for long-term storage.

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Use log sinks to export logs to Cloud Storage and delete from Logging.

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Disable default logs for all services.

Question 18

A company is designing a scalable web application on Google Cloud. They expect variable traffic and want to automatically scale resources based on load. Which two services can automatically scale? (Choose two.)

Accepted Answer

Cloud Run. Cloud Run is a fully managed serverless compute platform that automatically scales your containerized applications based on incoming traffic, including scaling to zero when there is no traffic. This autoscaling is handled by the Knative serving layer, which adjusts the number of container instances based on request concurrency and CPU utilization.

Answer

Compute Engine unmanaged instance group

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Cloud Dataproc

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Cloud SQL

Question 19

A company uses Cloud Load Balancing to distribute traffic to HTTP backends. They want to protect against application-layer DDoS attacks (e.g., HTTP flood). Which TWO services should they combine?

Accepted Answer

Cloud Armor. Cloud Armor is correct because it provides Web Application Firewall (WAF) capabilities and DDoS protection at the application layer, allowing you to create security policies that filter HTTP/HTTPS traffic based on IP addresses, geo-locations, or custom rules (e.g., rate limiting) to mitigate HTTP flood attacks. Cloud CDN is correct because it caches content at edge locations, absorbing a significant portion of malicious traffic before it reaches the backend, reducing the load on origin servers and acting as a first line of defense against volumetric application-layer attacks.

Answer

Cloud Firewall rules

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Cloud NAT

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Cloud Endpoints

Question 20

A team is designing a globally distributed application on Google Cloud that requires strong consistency for writes but can tolerate eventual consistency for reads. The application expects millions of concurrent users. Which two strategies should they implement? (Choose two.)

Accepted Answer

Use Cloud Spanner for write operations requiring strong consistency.. Cloud Spanner provides strongly consistent writes globally through synchronous replication using the TrueTime API and Paxos-based consensus. This ensures that all write operations are immediately consistent across regions, meeting the requirement for strong consistency on writes.

Answer

Use Firestore in multi-region mode for all operations.

Answer

Deploy Cloud SQL with cross-region replication for read scalability.

Answer

Use Cloud Bigtable for reading data with strong consistency.