PCD Designing highly scalable, available, and reliable cloud-native applications — Timed 20 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.

Answer

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

Answer

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.

Answer

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.

Answer

Automated backups are not enabled.

Answer

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

Answer

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.

Answer

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

Answer

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.

Answer

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

Answer

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.

Answer

Use preemptible VMs to reduce costs for the database layer.

Answer

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.

Answer

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

Answer

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.

Answer

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

Answer

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

Answer

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

Answer

Use instance groups with autohealing to automatically recreate instances

Answer

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

Answer

Enable HTTP keep-alive connections

Answer

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

Answer

Use synchronous replication across regions

Answer

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'.

Answer

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

Answer

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

Question 16

A company is designing a highly available application on Google Cloud using multiple regions. Which TWO strategies should they implement to achieve this?

Accepted Answer

Use a global load balancer to distribute traffic across regions.. Option B is correct because a global load balancer (e.g., Google Cloud External HTTPS Load Balancer) can distribute traffic across multiple regions, providing cross-region failover and low-latency routing. This is a fundamental pattern for multi-region high availability, as it allows traffic to be directed to healthy backends in any region, even if an entire region fails.

Answer

Use zonal persistent disks for stateful data.

Answer

Deploy a single instance group in one region for simplicity.

Answer

Store all data in a single Cloud Storage bucket.

Question 17

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.. Option B is correct because 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.

Answer

Deploy all pods in a single zone for simplicity.

Answer

Use a zonal cluster to reduce costs.

Question 18

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.. Option C is correct because 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.

Answer

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

Answer

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

Answer

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

Question 19

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.

Answer

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

Answer

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

Question 20

A company is designing a globally distributed application using Cloud Spanner. The application requires strong consistency and the ability to handle high read/write throughput. The team is concerned about inter-continental latency. Which two design choices would optimize performance while maintaining strong consistency? (Choose two.)

Accepted Answer

Enable leader-optimized routing to direct reads to the nearest leader region.. A is correct because leader-optimized routing directs read requests to the nearest region that contains the leader replica for the requested data, reducing inter-continental latency while still reading from the leader to ensure strong consistency. C is correct because placing a multi-region Spanner instance in geographic locations close to users minimizes network round-trip time, and Spanner's synchronous replication across regions maintains strong consistency even with high read/write throughput.

Answer

Use read-only replicas in each continent to serve reads locally.

Answer

Implement client-side caching with a short TTL for frequently accessed data.

Answer

Increase the number of nodes in the Spanner instance to improve throughput.