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| Section | Objectives |
|---|
| Ensure reliability, performance, and optimization | - Security and compliance
- 1. Encryption at rest and in transit
- 2. IAM roles and access control
- Performance optimization
- 1. Indexing, query optimization, and caching strategies
- 2. Workload tuning across database services
|
| Design scalable and highly available database solutions | - Design for high availability and disaster recovery
- 1. Replication strategies and failover design
- 2. Regional vs multi-regional architectures
- Select appropriate database services (relational, NoSQL, analytical)
- 1. Cloud SQL vs AlloyDB vs Spanner selection criteria
- 2. Bigtable use cases and schema design
- 3. Firestore and document database patterns
|
| Manage a database solution spanning multiple systems | - Operational database management
- 1. Capacity planning and scaling
- 2. Monitoring and performance tuning
- 3. Backup and restore strategies
|
| Migrate data solutions to Google Cloud | - Database migration strategies
- 1. Lift-and-shift vs re-platforming
- 2. Online vs offline migration tools (e.g., Database Migration Service)
|
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Exam Cram Professional-Cloud-Database-Engineer Pdf | Interactive Professional-Cloud-Database-Engineer Course
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Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q14-Q19):
NEW QUESTION # 14
You are choosing a database backend for a new application. The application will ingest data points from IoT sensors. You need to ensure that the application can scale up to millions of requests per second with sub-10ms latency and store up to 100 TB of history. What should you do?
- A. Use Memorystore for Memcached, and add nodes as necessary to achieve the required throughput.
- B. Use Firestore, and rely on automatic serverless scaling.
- C. Use Cloud SQL with read replicas for throughput.
- D. Use Bigtable, and add nodes as necessary to achieve the required throughput.
Answer: D
Explanation:
https://cloud.google.com/memorystore/docs/redis/redis-overview
NEW QUESTION # 15
Your company is migrating one of its monolithic applications to a microservices architecture on Google Cloud. The new architecture involves a user authentication service that runs on Google Kubernetes Engine (GKE) and needs to access Cloud SQL for PostgreSQL instances. Your developers need to access the databases for local development and debugging purposes. You need to design a centralized, secure, and scalable database connectivity and access management strategy for both application service interfaces and developers. What should you do-
- A. Configure the GKE and Compute Engine applications to use the Cloud SQL Auth Proxy for all database connections. Instruct developers to use their local clients with database-native user/password authentication.
- B. For all service interfaces and developers, create unique database-native user and password credentials directly on each database instance, and store the credentials in a centralized secret management tool.
- C. For GKE and Compute Engine services, create and grant dedicated IAM service accounts with least-privilege roles for Cloud SQL resources, and configure applications to use workload identity account credentials. For developers, use IAM authentication with Cloud SQL Auth Proxy for secure access.
- D. Enable public IP addresses for all database instances and configure firewall rules to restrict access based on the source IP addresses of the GKE cluster, Compute Engine VMs, and developers' machines.
Answer: C
Explanation:
The recommended approach for Cloud SQL connectivity is to use IAM-based authentication with the Cloud SQL Auth Proxy. For applications (GKE, Compute Engine), you assign dedicated IAM service accounts with least-privilege roles and use Workload Identity for secure, scalable credential management. For developers, IAM authentication through the Cloud SQL Auth Proxy provides secure access without exposing database-native credentials. This ensures centralized, secure, and scalable database access management for both services and developers.
NEW QUESTION # 16
You are designing a new gaming application that uses a highly transactional relational database to store player authentication and inventory data in Google Cloud. You want to launch the game in multiple regions. What should you do?
- A. Use Cloud Spanner to deploy the database.
- B. Use Cloud SQL with a regional read replica to deploy the database.
- C. Use Bigtable with clusters in multiple regions to deploy the database
- D. Use BigQuery to deploy the database
Answer: D
NEW QUESTION # 17
You are designing a database strategy for a new web application in one region. You need to minimize write latency. What should you do?
- A. Use Cloud Spanner in a regional configuration.
- B. Use high availability (HA) Cloud SQL with multiple zones.
- C. Use Cloud SQL with cross-region replicas.
- D. Use zonal Cloud SQL without high availability (HA).
Answer: C
NEW QUESTION # 18
Which Google Cloud database offers strongly consistent transactions, supports both relational and JSON data, and delivers globally distributed low latency across three continents?
- A. AlloyDB for PostgreSQL
- B. Cloud SQL for PostgreSQL
- C. Bigtable
- D. Cloud Spanner multi region
Answer: D
Explanation:
It delivers strongly consistent transactions, supports both relational schema and a JSON data type, and provides globally distributed low latency across continents.
This database offers true strong consistency with ACID transactions and synchronous replication, so reads and writes remain consistent even when distributed. It supports standard SQL with a relational model and includes native JSON support, which satisfies the requirement for both relational and JSON. Its multi region configuration replicates data across geographically separate regions to provide low latency access around the world while maintaining consistency.
NEW QUESTION # 19
......
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