Question 1

You are developing an application that retrieves large datasets from BigQuery. The application needs to process these results in manageable chunks while maintaining consistent performance. What is the recommended approach for implementing pagination?

Accepted Answer

Use LIMIT and OFFSET clauses in SQL queries to paginate results, Implement row-based pagination using physical row numbers, Use the pageToken parameter with maximum rows per page in the Jobs.getQueryResults method, Cache query results in temporary tables and implement custom pagination logic

Question 2

Your team is developing a new e-commerce service that will be deployed on Cloud Run. You need to implement a feature flag system to control the rollout of new shopping cart functionality. The system needs to be highly available, provide real-time updates, and support A/B testing. Which approach should you implement?

Accepted Answer

Store feature flags in a Cloud Storage bucket and have the application check the bucket periodically for updates, Use Firebase Remote Config to manage feature flags and implement the Firebase SDK in your application, Store feature flags in environment variables and redeploy the application when changes are needed, Implement feature flags using Cloud Pub/Sub topics and subscriptions

Question 3

Your team is migrating a legacy Java application to Google Cloud and needs to implement feature toggles for gradual rollout of new functionality. The solution must support dynamic updates, maintain an audit trail of all feature flag changes, and integrate well with Java applications. Which approach should you use?

Accepted Answer

Use Cloud Functions with Cloud Firestore for feature flag management and Cloud Audit Logs for tracking, Implement feature flags using Cloud Build with Cloud Storage for configuration storage, Use a managed feature flag service like LaunchDarkly or Split.io integrated with Cloud Audit Logs, Store feature flags in Cloud SQL with a custom caching layer and implement change tracking

Question 4

A development team is setting up their local development environments to work on a new microservices application. They need to test their code against Google Cloud APIs without incurring costs or requiring internet connectivity. Which combination of tools should they use? (Select Two)

Accepted Answer

Install the Cloud SDK and use gcloud beta emulators to emulate Google Cloud services locally, Configure a local Kubernetes cluster using minikube and connect it to Google Cloud services, Set up a development project in Google Cloud and use actual cloud resources with quotas, Configure Cloud Shell as the primary development environment with built-in cloud tools, Use Cloud Code in their IDE to access local emulators for Google Cloud services

Question 5

Your company has deployed a microservices application on GKE that includes a new payment processing service. You need to gradually introduce the new service to production traffic while maintaining the ability to quickly revert if issues are detected. The A/B testing implementation must capture detailed metrics about service performance. What should you do?

Accepted Answer

Configure Cloud Build to deploy two separate services and use Cloud Load Balancing to distribute traffic, Use Kubernetes Ingress controllers to route traffic between different deployment versions, Implement Istio traffic splitting with VirtualService resources and configure Cloud Monitoring for metrics collection, Deploy both versions to Cloud Run and use Traffic Director for request distribution

Question 6

While developing a payment processing application locally, you need to test both message queuing functionality and NoSQL database operations without incurring cloud costs. Which combination of local emulators should you use? (Select Two)

Accepted Answer

Use the Pub/Sub emulator to test asynchronous message processing, Use the Cloud SQL proxy to test database operations locally, Use the Cloud Storage emulator to simulate message queues, Use the Firestore emulator to test NoSQL document operations, Use Redis cache locally to simulate message queuing

Question 7

A retail application needs to query product data from multiple Google Cloud services including Cloud Storage, Firestore, and BigQuery. You need to implement efficient pagination across these different data sources while minimizing API costs and latency. Which approaches should you implement? (Select Two)

Accepted Answer

Implement cursor-based pagination for Firestore and page tokens for other services, Implement batch requests using the appropriate Cloud Client Libraries for each service, Store complete result sets in Cloud Memory Store for subsequent access, Set appropriate page sizes based on the data volume and performance requirements of each API, Store all paginated results in Cloud Storage and serve them through a CDN

Question 8

Your team needs to optimize the container image build process in Cloud Build to reduce build times and costs. The application consists of multiple microservices with separate Dockerfiles. What should you implement?

Accepted Answer

Use Cloud Build's parallel execution feature to build multiple images simultaneously, Build all images sequentially in a single Cloud Build step, Create separate Cloud Build triggers for each microservice, Build images locally and upload them to Artifact Registry

Question 9

A team is developing a microservices-based e-commerce platform on Google Cloud. The order processing service needs to communicate with multiple downstream services including inventory, payment, and shipping. The team wants to ensure loose coupling between services while maintaining data consistency and handling service failures gracefully. Which architecture pattern should they implement?

Accepted Answer

Implement synchronous REST calls between services with circuit breakers and retry logic, Use Pub/Sub to implement event-driven communication between services with dead-letter topics for failed messages, Implement gRPC streaming between services with bi-directional communication, Store service state in Cloud Spanner and poll for updates between services

Question 10

Your team is developing a workflow for processing insurance claims that involves multiple microservices and needs to maintain reliable state across long-running operations. The workflow includes document validation, fraud detection, payment processing, and customer notification steps that must execute in a specific order. Some steps may take several minutes to complete. You need to implement this workflow following Google best practices while minimizing operational complexity. What should you do?

Accepted Answer

Use Cloud Tasks to create individual tasks for each step and implement task handlers in Cloud Run services that pass task tokens between services, Implement a Cloud Workflows definition that coordinates the execution flow between services, handles error conditions, and maintains workflow state, Create a Pub/Sub topic for each step and have services publish messages to trigger the next service in the sequence, Deploy a centralized service on GKE that maintains workflow state in Cloud SQL and coordinates execution between microservices

Question 11

Your team needs to ensure software supply chain security for a critical application. Which combination of security measures provides the most comprehensive protection? (Select Two)

Accepted Answer

Implement Binary Authorization with build provenance verification, Use manual deployment processes, Store credentials in plaintext configuration files, Configure Cloud Build with hermetic builds and automated testing, Rely on basic access controls without verification

Question 12

Your application makes frequent API calls to Google Cloud services and needs to optimize network bandwidth usage while ensuring reliable data retrieval. Which combination of techniques should you implement? (Select Three)

Accepted Answer

Implement field masks and pagination to retrieve only required fields, Enable gzip compression for API requests and responses, Cache responses with appropriate TTL and use ETags for validation, Fetch all available data in single batch requests, Use synchronous blocking calls for all API requests

Question 13

You are deploying a Cloud Run service from source code that requires sensitive configuration values. You need to ensure these values are securely stored and accessed during deployment and runtime. Which configuration approaches should you implement? (Select Two)

Accepted Answer

Store sensitive values in Secret Manager and reference them in your Cloud Run service configuration using secret references, Include the sensitive values directly in your cloudbuild.yaml file as encrypted strings, Store sensitive values as environment variables in the Cloud Build trigger configuration, Assign a service account to the Cloud Run service and grant it the Secret Manager Secret Accessor role on the secret, Store sensitive values in a Cloud Storage bucket with limited access

Question 14

Your application uses the Cloud Run Admin API to list services in a Google Cloud project that contains a very large number of services. The list operation returns a result set that is too large to fit in a single response. What is the most efficient and reliable way to implement the pagination logic to retrieve all the services?

Accepted Answer

Use a fixed page size and calculate offsets manually, Retrieve all services in a single API call and implement client-side pagination, Store service lists in Cloud Firestore and implement custom pagination, Use the pageSize parameter and continue requests with pageToken until no token is returned

Question 15

A financial services company requires all internal service-to-service communication in their GKE cluster to be encrypted and authenticated. The security team wants to implement mutual TLS (mTLS) authentication between services while following Google-recommended practices. Which approach should they implement?

Accepted Answer

Configure Network Policies to enforce TLS encryption between pods and use Kubernetes Secrets to store certificates, Install Anthos Service Mesh, enable automatic mTLS, and configure AuthorizationPolicies to control service-to-service access, Deploy a sidecar container with an Nginx proxy in each pod to handle TLS termination using certificates stored in Secret Manager, Use Cloud KMS to generate certificates and implement custom certificate management logic in each microservice

Question 16

You are examining call traces from your application that makes requests to Cloud Storage. The traces show that some operations take significantly longer than expected because of repeated retries. Which approach should you implement to optimize the retry behavior?

Accepted Answer

Create a custom retry handler that implements random jitter between retry attempts, Configure the application to use exponential backoff with a multiplier of 10 for each retry, Implement exponential backoff with jitter and a maximum retry count of 10, Use a combination of exponential backoff and jitter, capping maximum retries at 5 and maximum delay at 32 seconds

Question 17

A development team wants to gain insights into their containerized application's performance running on Google Kubernetes Engine. They need to track HTTP request latencies, database query times, and external API call durations across multiple microservices. They want to minimize code changes while implementing distributed tracing. What should they do?

Accepted Answer

Add Cloud Monitoring agents to each GKE node and configure custom metrics collection for HTTP requests and API calls, Implement OpenTelemetry instrumentation with auto-instrumentation agents for their programming language and configure export to Cloud Trace, Write custom logging statements for all HTTP requests and API calls, then analyze the logs using Cloud Logging, Deploy Prometheus and Grafana to the cluster and create custom dashboards for tracking request metrics

Question 18

A global retail company runs a high-traffic e-commerce application on GKE that requires user session management. The application needs to handle millions of concurrent users across multiple regions while maintaining session consistency and low latency. Which approach should you implement?

Accepted Answer

Store session data in-memory within application pods and use sticky sessions on the load balancer, Use Memorystore for Redis Cluster with cross-region replication, directing user traffic to the nearest region, Store session data in Cloud Spanner with multi-region configuration, Use Cloud Storage buckets in each region to store session data with object lifecycle management

Question 19

Your team is developing a new microservices application that must meet SLSA Level 3 requirements. Which build system configuration should you implement?

Accepted Answer

Use Jenkins with manual approval steps and store artifacts in local storage, Configure Cloud Build with source provenance, hermetic builds, and automated testing in Artifact Registry, Implement a custom build system with basic logging enabled, Use GitLab CI/CD with basic container scanning

Question 20

Your team is implementing an order processing system that needs to handle thousands of orders per minute during peak times. Each order requires several processing steps, and some steps may fail and need to be retried. The system must ensure that no orders are lost and that processing capacity can scale automatically with demand. Which service should you use?

Accepted Answer

Create Cloud Run services and use Eventarc to trigger them based on order events, Deploy the processing logic to GKE and use HorizontalPodAutoscaler for scaling, Implement Cloud Tasks queues with automatic scaling and retry policies, Use Cloud Functions with Pub/Sub triggers for each processing step

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