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| Section | Objectives |
|---|---|
| Topic 1: Designing scalable and highly available cloud database solutions | - Select appropriate database services
|
| Topic 2: Migrating data solutions | - Plan and execute migrations
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| Topic 3: Securing and ensuring compliance of database solutions | - Implement security best practices
|
| Topic 4: Optimizing database performance | - Improve database efficiency
|
| Topic 5: Managing database solutions | - Deploy and administer databases
|
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NEW QUESTION # 143
Your e-learning platform runs on a Cloud SQL for PostgreSQL instance (16 VCPUs, 60 GB memory and 1TB SSD) serving users in North America. Your analytics team runs complex reporting queries that often consume 80% of CPU resources, causing slow response times for student transactions during peak hours. Current workload includes 8,000 transactions per second with 60% reads and 40% writes. The reporting queries involve JOIN operations across multiple large tables with millions of rows requiring highly efficient analytical processing. The platform also experiences sudden spikes in analytical reporting demand, requiring an elastic scaling of read capacity. You need to improve the query performance for your analytics team to run their reports efficiently without impacting transactional users. You also need to plan for future traffic growth.
What should you do-
Answer: B
Explanation:
Migrating to AlloyDB for PostgreSQL with the columnar engine is the best option for this mixed workload. The columnar engine accelerates analytical queries such as multi-table JOINs on large datasets, while the primary instance continues handling transactional traffic. Using read pools isolates analytical reporting from transactional operations and provides elastic scaling to handle sudden spikes in reporting demand. This ensures efficient reporting without degrading transactional performance and supports future growth.
NEW QUESTION # 144
You are building an application that allows users to customize their website and mobile experiences. The application will capture user information and preferences. User profiles have a dynamic schema, and users can add or delete information from their profile. You need to ensure that user changes automatically trigger updates to your downstream BigQuery data warehouse. What should you do?
Answer: C
Explanation:
Use Firestore in Datastore mode for new server projects. Firestore in Datastore mode allows you to use established Datastore server architectures while removing fundamental Datastore limitations. Datastore mode can automatically scale to millions of writes per second. Use Firestore in Native mode for new mobile and web apps. Firestore offers mobile and web client libraries with real-time and offline features. Native mode can automatically scale to millions of concurrent clients.
NEW QUESTION # 145
Your team uses thousands of connected IoT devices to collect device maintenance data for your oil and gas customers in real time. You want to design inspection routines, device repair, and replacement schedules based on insights gathered from the data produced by these devices. You need a managed solution that is highly scalable, supports a multi-cloud strategy, and offers low latency for these IoT devices. What should you do?
Answer: C
Explanation:
This scenario has BigTable written all over it - large amounts of data from many devices to be analysed in realtime. I would even argue it could qualify as a multicloud solution, given the links to HBASE. BUT it does not support SQL queries and is not therefore compatible (on its own) with Looker. Firestore + Looker has the same problem. Spanner + Data Studio is at least a compatible pairing, but I agree with others that it doesn't fit this use-case - not least because it's Google-native. By contrast, MongoDB Atlas is a managed solution (just not by Google) which is compatible with the proposed reporting tool (Mongo's own Charts), it's specifically designed for this type of solution and of course it can run on any cloud.
NEW QUESTION # 146
You are the primary DBA of a Cloud SQL for PostgreSQL database that supports 6 enterprise applications in production. You used Cloud SQL Insights to identify inefficient queries and now need to identify the application that is originating the inefficient queries. You want to follow Google-recommended practices.
What should you do?
Answer: C
Explanation:
https://cloud.google.com/sql/docs/postgres/using-query-insights#filter_by_query_tags
NEW QUESTION # 147
Your organization is currently updating an existing corporate application that is running in another public cloud to access managed database services in Google Cloud. The application will remain in the other public cloud while the database is migrated to Google Cloud. You want to follow Google-recommended practices for authentication. You need to minimize user disruption during the migration. What should you do?
Answer: B
NEW QUESTION # 148
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