20+ practice questions focused on Designing highly scalable, available, and reliable cloud-native applications — one of the most tested topics on the Google Professional Cloud Developer exam. Each question includes a detailed explanation so you learn why the right answer is correct.
Start Designing highly scalable, available, and reliable cloud-native applications PracticeA 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?
Explanation: 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.
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?
Explanation: 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.
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?
Explanation: 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.
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?
Explanation: 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.
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?
Explanation: 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.
+15 more Designing highly scalable, available, and reliable cloud-native applications questions available
Practice all Designing highly scalable, available, and reliable cloud-native applications questions1. Baseline your knowledge
Start with 10 questions to gauge your current understanding of Designing highly scalable, available, and reliable cloud-native applications. This tells you whether you need a concept refresher or just practice.
2. Review every explanation
For each question — right or wrong — read the full explanation. Understanding why an answer is correct is more valuable than knowing the answer itself.
3. Focus on exam traps
Designing highly scalable, available, and reliable cloud-native applications questions on the PCD frequently use trap wording. Look for subtle differences in answers that test your precision, not just general knowledge.
4. Reach 80% consistently
Do repeated sessions until you score 80%+ three times in a row. Then move to mixed-mode practice to test cross-topic recall under realistic conditions.
The exact number varies per candidate. Designing highly scalable, available, and reliable cloud-native applications is tested as part of the Google Professional Cloud Developer blueprint. Practicing with targeted Designing highly scalable, available, and reliable cloud-native applications questions ensures you can handle any format or difficulty that appears.
Yes. Courseiva provides free PCD practice questions across all exam topics and domains. The platform includes topic-based practice, mock exams, missed-question review, bookmarked questions, and readiness tracking — no account required.
Difficulty is subjective, but Designing highly scalable, available, and reliable cloud-native applications is a high-priority exam concept tested in multiple ways — direct recall, scenario analysis, and command-output interpretation. Consistent practice is the best way to build confidence.
Launch a full Designing highly scalable, available, and reliable cloud-native applications practice session with instant scoring and detailed explanations.
Start Designing highly scalable, available, and reliable cloud-native applications Practice →