PCD Designing highly scalable, available, and reliable cloud-native applications Practice Test 7 — 15 Questions

Question 1

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?

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

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 2

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.

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Cloud Pub/Sub, Cloud Dataflow, Cloud Datastore

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Cloud Pub/Sub, Cloud Functions, Cloud SQL

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Cloud Pub/Sub, Cloud Dataflow, Cloud Storage

Question 3

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.

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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 4

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.. 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 5

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

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Cloud CDN

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Internal TCP/UDP Load Balancer

Question 6

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.

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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 7

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 8

A team is deploying a critical application on Google Kubernetes Engine (GKE) and needs to ensure high availability and disaster recovery. Which THREE actions should they take?

Accepted Answer

Use a regional cluster with control plane replicated across zones.. A regional cluster in GKE replicates the control plane across multiple zones within a region, ensuring that if one zone fails, the control plane remains available. This is essential for high availability and disaster recovery, as it eliminates a single point of failure for cluster management operations.

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Deploy all pods in a single zone for simplicity.

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Use a zonal cluster to reduce costs.

Question 9

A company is deploying a microservices-based application on Google Kubernetes Engine (GKE). The application consists of several stateless services that experience unpredictable traffic spikes. The team wants to ensure high availability and scalability while minimizing costs. Which design should they implement?

Accepted Answer

Deploy a Regional GKE cluster with cluster autoscaling and Horizontal Pod Autoscaler for each deployment.. A Regional GKE cluster provides multi-zone high availability, cluster autoscaling dynamically adjusts node pool size to handle unpredictable traffic spikes, and Horizontal Pod Autoscaler (HPA) scales individual pod replicas based on CPU/memory or custom metrics. This combination ensures both scalability and cost efficiency by only provisioning resources when needed.

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Deploy a Regional GKE cluster with node auto-provisioning and a fixed number of replicas per service.

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Use a Regional GKE cluster with preemptible VMs and static pod counts.

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Use a single-zone GKE cluster with a large fixed node pool to handle peak load.

Question 10

You are troubleshooting a web application deployed on Compute Engine instances behind a target pool. Users report intermittent timeouts when accessing the application via the forwarding rule's IP address. Based on the exhibit, what is the most likely cause of the issue?

Accepted Answer

The target pool lacks health checks, causing traffic to be sent to unhealthy instances.. The target pool in a legacy HTTP(S) load balancer does not automatically perform health checks unless they are explicitly configured. Without health checks, the load balancer continues to send traffic to all instances in the pool, including those that are unhealthy or unresponsive. This causes intermittent timeouts when users hit an unhealthy instance, as the forwarding rule distributes connections across the entire pool without verifying instance health.

Answer

The forwarding rule is missing a backend service.

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The port range is set to 80-80, which restricts traffic to port 80 only.

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The forwarding rule should use a backend service instead of a target pool for HTTP traffic.

Question 11

A team is building a serverless event-driven application using Cloud Functions and Cloud Pub/Sub. The function processes messages from a Pub/Sub subscription and writes results to Firestore. During peak hours, the function experiences high latency and some messages are being retried multiple times. Which three steps should the team take to improve reliability and scalability? (Choose three.)

Accepted Answer

Enable retry policy on the Pub/Sub subscription to automatically retry failed messages.. Enabling a retry policy on the Pub/Sub subscription ensures that messages that fail to be processed (e.g., due to transient errors or timeouts) are automatically retried. This prevents message loss and improves reliability by allowing the Cloud Function to reprocess messages without manual intervention. The retry policy works with the subscription's acknowledgement deadline, so messages are redelivered if not acknowledged in time.

Answer

Batch multiple Pub/Sub messages into a single Cloud Function invocation.

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Increase the Cloud Function timeout to the maximum allowed value.

Question 12

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.

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Use environment variables injected into each pod

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Use a ConfigMap to store service endpoints

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Use Cloud Load Balancing to route traffic between services

Question 13

A developer is designing a serverless event-driven application that processes messages from Pub/Sub and writes results to BigQuery. The workload is unpredictable but must scale to zero when idle. Which compute option should they choose?

Accepted Answer

Cloud Functions with Pub/Sub trigger. Cloud Functions with a Pub/Sub trigger is the correct choice because it is purpose-built for event-driven, serverless workloads that scale to zero when idle. It automatically scales from zero to thousands of concurrent invocations based on the volume of Pub/Sub messages, and it natively integrates with Pub/Sub via a background function that is invoked for each message, making it ideal for unpredictable, bursty workloads that must process messages and write results to BigQuery.

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Cloud Run with Pub/Sub push subscription

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Compute Engine with managed instance groups

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Google Kubernetes Engine with Horizontal Pod Autoscaler

Question 14

Drag and drop the steps to create a Cloud Run service in the correct order.

Accepted Answer

Select container image, then configure service settings, then deploy the service. Creating a Cloud Run service involves selecting the container image and configuring settings before deployment.

Answer

Configure service settings, then select container image, then deploy the service

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Deploy the service, then select container image, then configure service settings

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Select container image, then deploy the service, then configure service settings

Question 15

Drag and drop the steps to set up a Cloud Function triggered by a Cloud Storage event in the correct order.

Accepted Answer

Write the Cloud Function code, then Deploy the function with the Cloud Storage bucket as trigger, then Upload a file to the Cloud Storage bucket, then Check the Cloud Function logs to verify execution. Cloud Functions can be triggered by Cloud Storage events; deployment includes specifying the bucket trigger.

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Deploy the function with the Cloud Storage bucket as trigger, then Write the Cloud Function code, then Upload a file to the Cloud Storage bucket, then Check the Cloud Function logs to verify execution

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Upload a file to the Cloud Storage bucket, then Write the Cloud Function code, then Deploy the function with the Cloud Storage bucket as trigger, then Check the Cloud Function logs to verify execution

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Check the Cloud Function logs to verify execution, then Write the Cloud Function code, then Deploy the function with the Cloud Storage bucket as trigger, then Upload a file to the Cloud Storage bucket