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NEW QUESTION # 86
You need to transfer approximately 300 TB of data from your company's on-premises data center to Cloud Storage. You have 100 Mbps internet bandwidth, and the transfer needs to be completed as quickly as possible. What should you do?
Answer: B
Explanation:
Comprehensive and Detailed In-Depth Explanation:
Transferring 300 TB over a 100 Mbps connection would take an impractical amount of time (over 300 days at theoretical maximum speed, ignoring real-world constraints like latency). Google Cloud provides the Transfer Appliance for large-scale, time-sensitive transfers.
* Option A: Cloud Client Libraries over the internet would be slow and unreliable for 300 TB due to bandwidth limitations.
* Option B: The gcloud storage command is similarly constrained by internet speed and not designed for such large transfers.
* Option C: Compressing and splitting across multiple providers adds complexity and isn't a Google- supported method for Cloud Storage ingestion.
NEW QUESTION # 87
You are migrating data from a legacy on-premises MySQL database to Google Cloud. The database contains various tables with different data types and sizes, including large tables with millions of rowsand transactional data. You need to migrate this data while maintaining data integrity, and minimizing downtime and cost.
What should you do?
Answer: A
Explanation:
Using Database Migration Service (DMS) to replicate the MySQL database to a Cloud SQL for MySQL instance is the best approach. DMS is a fully managed service designed for migrating databases to Google Cloud with minimal downtime and cost. It supports continuous data replication, ensuring data integrity during the migration process, and handles schema and data transfer efficiently. This solution is particularly suited for large tables and transactional data, as it maintains real-time synchronization between the source and target databases, minimizing downtime for the migration.
NEW QUESTION # 88
You are designing a BigQuery data warehouse with a team of experienced SQL developers. You need to recommend a cost-effective, fully-managed, serverless solution to build ELT processes with SQL pipelines.
Your solution must include source code control, environment parameterization, and data quality checks. What should you do?
Answer: B
Explanation:
Comprehensive and Detailed In-Depth Explanation:
The solution must support SQL-based ELT, be serverless and cost-effective, and include advanced features like version control and quality checks. Let's dive in:
* Option A: Cloud Data Fusion is a visual ETL tool, not SQL-centric (uses plugins), and isn't fully serverless (requires instance management). It lacks native source code control and parameterization.
* Option B: Dataform is a serverless, SQL-based ELT platform for BigQuery. It uses SQLX scripts, integrates with Git for version control, supports environment variables (parameterization), and offers assertions for data quality-all meeting the requirements cost-effectively.
* Option C: Dataproc is for Spark/MapReduce, not SQL ELT, and requires cluster management, contradicting serverless and cost goals.
NEW QUESTION # 89
You have a Cloud SQL for PostgreSQL database that stores sensitive historical financial data. You need to ensure that the data is uncorrupted and recoverable in the event that the primary region is destroyed. The data is valuable, so you need to prioritize recovery point objective (RPO) over recovery time objective (RTO). You want to recommend a solution that minimizes latency for primary read and write operations. What should you do?
Answer: A
Explanation:
Comprehensive and Detailed In-Depth Explanation:
The priorities are data integrity, recoverability after a regional disaster, low RPO (minimal data loss), and low latency for primary operations. Let's analyze:
* Option A: Multi-region backups store point-in-time snapshots in a separate region. With automated backups and transaction logs, RPO can be near-zero (e.g., minutes), and recovery is possible post- disaster. Primary operations remain in one zone, minimizing latency.
* Option B: Regional HA (failover to another zone) with hourly cross-region backups protects against zone failures, but hourly backups yield an RPO of up to 1 hour-too high for valuable data. Manual backup management adds overhead.
* Option C: Synchronous replication to another zone ensures zero RPO within a region but doesn't protect against regional loss. Latency increases slightly due to sync writes across zones.
NEW QUESTION # 90
You work for a global financial services company that trades stocks 24/7. You have a Cloud SGL for PostgreSQL user database. You need to identify a solution that ensures that the database is continuously operational, minimizes downtime, and will not lose any data in the event of a zonal outage. What should you do?
Answer: D
Explanation:
Configuring a high-availability (HA) Cloud SQL instance ensures continuous operation, minimizes downtime, and prevents data loss in the event of a zonal outage. In this setup, the primary instance is located in one zone (e.g., zone A), and a synchronous secondary instance is located in a different zone within the same region. This configuration ensures that all data is replicated to the secondary instance in real-time. In the event of a failure in the primary zone, the system automatically promotes the secondary instance to primary, ensuring seamless failover with no data loss and minimal downtime. This is the recommended approach for mission-critical, highly available databases.
NEW QUESTION # 91
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