PCD Designing highly scalable, available, and reliable cloud-native applications Practice Test 1 — 15 Questions

Question 1

A company is designing a cloud-native application on Google Cloud that requires low-latency access to a global user base. The application serves static content and dynamic APIs. Which strategy best minimizes latency while maintaining high availability?

Accepted Answer

Use Cloud CDN to cache static content and deploy the API across multiple regions with global load balancing.. Option B is correct because it combines Cloud CDN for caching static content at edge locations worldwide, reducing latency for static assets, and deploys the dynamic API across multiple regions with global load balancing (using Google Cloud's global external HTTP(S) load balancer) to route users to the nearest healthy backend, minimizing latency for dynamic requests while ensuring high availability through regional redundancy.

Answer

Deploy the application in a single region and use Cloud Interconnect for global access.

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Use Cloud Armor to protect the application and rely on Google's backbone for low latency.

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Store all content in Cloud Storage and serve directly from there.

Question 2

A team is migrating a monolithic application to a microservices architecture on Google Kubernetes Engine (GKE). They want to ensure that failures in one microservice do not cascade to others. Which design pattern should they implement?

Accepted Answer

Implement a circuit breaker pattern that opens when failure thresholds are exceeded.. The circuit breaker pattern is the correct choice because it prevents cascading failures by monitoring inter-service calls and opening the circuit when failures exceed a threshold, allowing the system to fail fast and recover gracefully. In a GKE-based microservices architecture, this pattern is typically implemented using libraries like Resilience4j or Istio's circuit breaker, which can be configured to trip after a certain number of consecutive failures, thus protecting downstream services from being overwhelmed.

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Implement retry logic with exponential backoff for all inter-service calls.

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Use synchronous HTTP calls with timeouts to detect failures quickly.

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Use bulkheads to separate thread pools for each service.

Question 3

A company running a high-traffic e-commerce platform on Google Cloud experiences occasional data loss in their Cloud SQL database during failover events. The database is configured with a failover replica in a different zone. What is the most likely cause of the data loss?

Accepted Answer

The database is using asynchronous replication to the failover replica.. Cloud SQL uses synchronous replication for failover replicas by default, ensuring that transactions are committed on both the primary and the replica before acknowledging the write. If asynchronous replication is configured, the replica may lag behind the primary, and during a failover, any transactions not yet replicated are lost. This is the most likely cause of data loss during failover events.

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Automated backups are not enabled.

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The failover replica is configured as a read replica instead of a failover replica.

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The database is not using regional persistent disks.

Question 4

An organization wants to design a serverless data processing pipeline that is highly available and can automatically scale based on the number of incoming requests. The pipeline processes JSON messages from a Cloud Pub/Sub topic and writes results to BigQuery. Which service should be used as the compute component?

Accepted Answer

Cloud Run. Cloud Run is the correct compute component because it is a fully managed serverless platform that automatically scales from zero based on incoming HTTP requests, supports event-driven processing via Pub/Sub push subscriptions, and integrates natively with BigQuery. It provides high availability by default across zones and can handle burst traffic without provisioning overhead, making it ideal for a serverless pipeline that processes JSON messages and writes results to BigQuery.

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Cloud Dataflow

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Cloud Functions

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Compute Engine with managed instance groups

Question 5

A company is building a real-time analytics application on Google Cloud that ingests data from thousands of IoT devices. The data must be processed with sub-second latency and stored in a time-series database for querying. Which combination of services provides the best scalability and availability?

Accepted Answer

Cloud Pub/Sub, Cloud Dataflow, Cloud Bigtable. Cloud Bigtable is a fully managed, scalable NoSQL database designed for large analytical and operational workloads, offering sub-10ms latency for time-series data. Combined with Cloud Pub/Sub for ingesting high-throughput IoT data and Cloud Dataflow for stream processing, this combination provides the best scalability and availability for real-time analytics with sub-second latency requirements.

Answer

Cloud Pub/Sub, Cloud Dataflow, Cloud Datastore

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Cloud Pub/Sub, Cloud Functions, Cloud SQL

Answer

Cloud Pub/Sub, Cloud Dataflow, Cloud Storage

Question 6

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.

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

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Use Cloud Bigtable for reading data with strong consistency.

Question 7

An organization is migrating a critical application to Google Cloud and needs to ensure high availability and disaster recovery. The application runs on Compute Engine and uses a stateful database. Which three design choices should they make? (Choose three.)

Accepted Answer

Use managed instance groups distributed across multiple zones.. Option A is correct because managed instance groups (MIGs) distributed across multiple zones provide automatic failover and self-healing for the Compute Engine instances. If a zone fails, the MIG automatically recreates instances in healthy zones, ensuring high availability for the application layer. This aligns with Google Cloud's best practices for regional resilience.

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Use preemptible VMs to reduce costs for the database layer.

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Deploy all instances in a single zone and use snapshots for backup.

Question 8

A developer runs the command shown in the exhibit. They need to ensure that the application running on instance-3 can be restored quickly if it fails. What should they do?

Accepted Answer

Create a managed instance group using an instance template based on instance-3's boot disk.. Option C is correct because a managed instance group (MIG) with an instance template based on instance-3's boot disk provides automated health checking, auto-healing, and managed instance replacement. If instance-3 fails, the MIG automatically recreates it from the template, ensuring rapid restoration without manual intervention. This aligns with the goal of designing highly available and reliable applications on Google Cloud.

Answer

Add instance-3 to an unmanaged instance group.

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Configure Cloud DNS with a health check pointing to instance-3.

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Take a snapshot of instance-3's disk and use it to create a new instance manually.

Question 9

A developer finds the JSON key shown in the exhibit in a Cloud Storage bucket that is publicly accessible. Which security best practice was violated?

Accepted Answer

The key was stored in a publicly accessible Cloud Storage bucket.. Option D is correct because storing a JSON key (a service account private key) in a publicly accessible Cloud Storage bucket directly violates the principle of least privilege and exposes sensitive credentials to unauthorized users. Any entity with read access to the bucket can retrieve the key and impersonate the service account, potentially gaining unauthorized access to Google Cloud resources.

Answer

The key is not rotated regularly.

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The key was created as a user-managed key instead of a Google-managed key.

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The key was not encrypted using Cloud KMS.

Question 10

A company is designing a global e-commerce platform on Google Cloud. The application requires low-latency access for users worldwide and must be highly available. Which load balancing solution should they use?

Accepted Answer

External HTTP(S) Load Balancer. The External HTTP(S) Load Balancer is the correct choice because it is a global, proxy-based Layer 7 load balancer that terminates HTTP/HTTPS traffic at Google's edge points of presence (PoPs) and routes requests to the nearest healthy backend. This provides low-latency access for users worldwide by leveraging Google's global network and anycast IPs, while also offering built-in high availability, SSL offloading, and content-based routing.

Answer

External TCP/UDP Network Load Balancer

Answer

Cloud CDN

Answer

Internal TCP/UDP Load Balancer

Question 11

A team is migrating a monolithic application to microservices on Google Kubernetes Engine (GKE). They want to ensure that if one microservice fails, it does not cascade to other services. Which design pattern should they implement?

Accepted Answer

Circuit Breaker pattern. The Circuit Breaker pattern is correct because it prevents cascading failures by monitoring for failures in a downstream microservice and, once a threshold is exceeded, immediately failing requests to that service without attempting the call. In GKE, this can be implemented using tools like Istio or Envoy sidecar proxies, which can be configured with circuit breaker settings to stop traffic to unhealthy pods, allowing the system to recover gracefully.

Answer

Event-driven architecture

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Retry with exponential backoff

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Bulkhead pattern

Question 12

A company runs a stateful application on Compute Engine instances with local SSDs. They need to perform maintenance that requires stopping the instances. What is the best approach to ensure data durability and minimal downtime?

Accepted Answer

Migrate data to persistent disks and configure the application to use persistent disks. Local SSDs provide ephemeral storage that is tied to the lifecycle of the Compute Engine instance. When an instance is stopped or terminated, data on local SSDs is permanently lost. To ensure data durability during maintenance that requires stopping the instance, the application must use persistent disks, which are durable network-attached storage that persists independently of the instance. Option D is correct because migrating the application to persistent disks ensures data survives the stop and allows the instance to be restarted with the same data, minimizing downtime.

Answer

Create a snapshot of the local SSD before stopping the instance

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Use instance groups with autohealing to automatically recreate instances

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Enable live migration on the instance

Question 13

An application running on Cloud Run experiences cold starts causing latency spikes. What is the most cost-effective solution to reduce cold starts?

Accepted Answer

Set a minimum number of instances. Setting a minimum number of instances ensures that Cloud Run always keeps at least one instance warm (idle) to serve incoming requests instantly, eliminating cold start latency. This is the most cost-effective solution because you only pay for the minimum instances when they are idle (at a reduced rate), whereas other options increase per-request cost or do not address the root cause of cold starts.

Answer

Increase the container's CPU allocation

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Enable HTTP keep-alive connections

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Use a larger container memory size

Question 14

A team is designing a disaster recovery plan for a critical application on Google Cloud. The application runs on Compute Engine with a regional persistent disk. They want to minimize data loss in case of a regional outage. Which strategy should they use?

Accepted Answer

Use persistent disk snapshot replication to another region. Persistent disk snapshot replication to another region is the correct strategy because snapshots are stored in Cloud Storage and can be replicated across regions. This allows you to restore the disk from a snapshot in a different region if the primary region experiences an outage, minimizing data loss by ensuring the backup is geographically separate. Regional persistent disks are synchronous within a region but do not provide cross-region replication, so snapshots are the recommended approach for cross-region disaster recovery.

Answer

Create a snapshot schedule and store snapshots in the same region

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Use synchronous replication across regions

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Configure a managed instance group with autohealing

Question 15

An administrator runs the above command to create a Compute Engine instance. However, the nginx service does not start. What is the most likely cause?

Accepted Answer

The instance has no external IP address and cannot reach the internet to download packages.. The command likely creates a Compute Engine instance without specifying an external IP address (e.g., using `--no-address` or omitting `--address`). Without an external IP, the instance cannot reach the internet to download the nginx package from repositories, causing the startup script that installs and starts nginx to fail. This is the most direct cause of the nginx service not starting.

Answer

The metadata key is misspelled; it should be 'startup-script-url'.

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The instance does not have the compute.instance.update permission.

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The startup script runs before the boot disk is fully mounted.