Google PCA Analysing and Optimising Technical and Business Processes Practice Test 3 — 15 Questions

Question 1

A company is moving a legacy application to Compute Engine. The application has inconsistent resource usage and the team wants to optimise costs without performance degradation. They are evaluating committed use discounts (CUDs) and other discount types. Which THREE statements are correct about CUDs? (Choose 3)

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Spend-based CUDs are applied automatically to all eligible projects in the billing account. CUDs offer discounts for 1-year or 3-year commitments. Resource-based CUDs apply to specific machine types in a region. Spend-based CUDs apply to total compute spend. CUDs can be combined with sustained use discounts, but sustained use discounts are automatic and not required to be purchased.

Answer

CUDs require a minimum of 10 instances to qualify

Answer

CUDs cannot be combined with sustained use discounts

Question 2

A company is designing a disaster recovery plan for a critical application running on Compute Engine. The application requires a Recovery Point Objective (RPO) of 15 minutes and a Recovery Time Objective (RTO) of 4 hours. Which TWO strategies meet these requirements? (Choose 2)

Accepted Answer

Warm standby: run a scaled-down version of the environment in another region. Pilot light involves replicating data and having a minimal environment ready to scale. Warm standby maintains a partially scaled environment. Both can achieve RPO of 15 minutes and RTO of 4 hours with proper setup. Multi-region deployment and active-passive are not defined in terms of RPO/RTO.

Answer

Multi-region deployment with Cloud Load Balancing

Answer

Backup and restore: daily backups to Cloud Storage

Answer

Cold standby: periodic snapshots to another region

Question 3

A company needs to store petabytes of time-series IoT sensor data and query it with single-digit millisecond latency at millions of reads per second. The data has a simple key-value structure with timestamps. Which Google Cloud database is MOST appropriate?

Accepted Answer

Cloud Bigtable. Cloud Bigtable is designed for exactly this use case — petabyte-scale, low-latency (single-digit ms), high-throughput NoSQL storage for time-series, IoT, and financial data. It scales horizontally by adding nodes. BigQuery is optimised for analytics (seconds-to-minutes latency), Cloud SQL is for OLTP (limited to tens of thousands of QPS), and Firestore is for document data with hierarchical structure.

Answer

Cloud Spanner

Answer

BigQuery

Answer

Firestore

Question 4

An organization wants to reduce costs for a batch data processing job that runs nightly and is resilient to interruptions. The job can be restarted from checkpoints. Which Compute Engine VM pricing model should be used?

Accepted Answer

Preemptible VMs. Preemptible VMs and Spot VMs are significantly cheaper than standard VMs and can be terminated by Google Cloud at any time. Since the job is batch and can resume from checkpoints, interruptions are acceptable. Sustained use discounts apply automatically to standard VMs, but preemptible/spot VMs offer the lowest cost for fault-tolerant workloads.

Answer

On-demand VMs

Answer

Sustained use discounts

Answer

Committed use discounts (1-year)

Question 5

A team uses BigQuery for analytics. They notice that queries against a table with billions of rows are slow and expensive. The table is partitioned by ingestion time and has no clustering. Queries frequently filter on a 'customer_id' column. Which optimization would MOST reduce query cost and latency?

Accepted Answer

Cluster the table on customer_id. Clustering on 'customer_id' will physically co-locate rows with the same customer_id within each partition. This allows BigQuery to prune blocks, reducing the amount of data scanned for queries that filter on customer_id. Partitioning alone is not enough; clustering on the filter column is key.

Answer

Use a materialized view pre-aggregated by customer_id

Answer

Switch to on-demand pricing

Answer

Add a clustered index on customer_id

Question 6

A company is migrating 500 TB of on-premises file server data to Cloud Storage. The on-premises network has a 1 Gbps link to Google Cloud, but the migration must complete within 30 days. What is the MOST cost-effective and reliable method?

Accepted Answer

Use Transfer Appliance. Transfer Appliance is a physical device that Google ships to the customer; they load data onto it and return it for upload. For 500 TB over a 1 Gbps link, the theoretical transfer time is ~46 days (500 TB * 8 / 1 Gbps / 86400 sec/day), exceeding the 30-day window. Transfer Appliance avoids network transfer and meets the timeline. Storage Transfer Service is for cloud-to-cloud or HTTP(S) sources, not on-prem. Migrate for Compute Engine is for VM migration.

Answer

Use Storage Transfer Service over a dedicated interconnect

Answer

Deploy a VPN and use gsutil rsync

Answer

Use Database Migration Service

Question 7

An application running on Compute Engine frequently makes connection requests to a Cloud SQL for PostgreSQL instance. The connections are short-lived and many are created per second. What should be implemented to reduce latency and connection overhead?

Accepted Answer

Deploy PgBouncer on the application server or as a sidecar. Connection pooling reuses database connections instead of creating new ones for each request. PgBouncer is a lightweight connection pooler for PostgreSQL. Cloud SQL Auth Proxy is for secure connections but does not pool.

Answer

Increase the number of vCPUs on the Cloud SQL instance

Answer

Enable connection scaling in Cloud SQL

Answer

Use Cloud SQL Auth Proxy with private IP

Question 8

A company runs a global e-commerce platform on Google Kubernetes Engine (GKE) with a Cloud SQL for MySQL database. During promotions, traffic spikes cause database connection limits to be exceeded, leading to errors. The application uses the Cloud SQL Auth Proxy. What is the MOST scalable and cost-effective solution?

Accepted Answer

Use a connection pooler such as ProxySQL deployed in the GKE cluster. Connection pooling (e.g., using PgBouncer for PostgreSQL, but for MySQL, similar poolers like ProxySQL or built-in connection pooling) allows the application to reuse connections and handle many concurrent requests without hitting database connection limits. Increasing the database tier or proxy instances adds cost and may not address the underlying issue of connection churn.

Answer

Configure the Cloud SQL Auth Proxy to use private IP and increase pool size

Answer

Upgrade the Cloud SQL instance to a higher tier with more connections

Answer

Increase the number of Cloud SQL Auth Proxy replicas

Question 9

A team wants to automatically move data from Cloud Storage Standard class to Nearline class after 30 days, and to Archive class after 365 days. Which GCP feature should be used?

Accepted Answer

Cloud Storage lifecycle management policies. Cloud Storage lifecycle management policies allow you to define rules for automatic transitions between storage classes based on object age. Option A refers to the specific `gsutil lifecycle set` command used to apply these policies, but the feature itself is called lifecycle management policies (option D). Cloud Storage Transfer Service is for moving data between buckets or from external sources, not for lifecycle transitions. Google Cloud Armor is a security service, unrelated to storage class transitions.

Answer

Cloud Storage Object Lifecycle Management (via gsutil lifecycle set)

Answer

Cloud Storage Transfer Service

Answer

Google Cloud Armor

Question 10

A company wants to analyze the total cost of ownership (TCO) for migrating their on-premises data center to Google Cloud. They need to compare compute, storage, and network costs, including operational expenses like maintenance and power. Which tool should they use?

Accepted Answer

Google Cloud TCO Calculator. Google Cloud's TCO calculator allows you to input on-premises infrastructure details and estimate cloud costs, including compute, storage, network, and operational savings. The Pricing Calculator is for estimating cloud costs but does not compare on-prem vs cloud. Active Assist is for optimization recommendations, not TCO analysis.

Answer

Google Cloud Pricing Calculator

Answer

Cloud Billing reports

Answer

Active Assist cost optimization recommendations

Question 11

A startup is building a real-time multiplayer game with global players. They need a database that provides strong consistency across regions and can handle millions of concurrent users. They anticipate rapid growth and want to avoid downtime for scaling. Which database service meets these requirements?

Accepted Answer

Cloud Spanner. Cloud Spanner is a globally distributed, strongly consistent relational database with automatic horizontal scaling. It provides strong consistency across regions and can handle millions of transactions per second. Firestore is eventually consistent (or strong within a region) and not designed for relational data. Bigtable does not support strong consistency across regions. Cloud SQL is regional with limited scalability.

Answer

Cloud SQL with cross-region replication

Answer

Cloud Bigtable

Answer

Cloud Firestore

Question 12

An engineer wants to migrate an on-premises MySQL database (5.6) to Cloud SQL for MySQL with minimal downtime. Which service should they use?

Accepted Answer

Database Migration Service. Database Migration Service (DMS) supports continuous replication from on-premises MySQL to Cloud SQL, enabling minimal downtime migration. Velostrata (Migrate for Compute Engine) is for VM migration. Storage Transfer Service is for file/object data. BigQuery Data Transfer Service is for analytics data.

Answer

Migrate for Compute Engine (formerly Velostrata)

Answer

Storage Transfer Service

Answer

BigQuery Data Transfer Service

Question 13

A company runs a web application behind a Cloud HTTP(S) Load Balancer. Static content (images, CSS, JS) is served from Cloud Storage. They want to reduce latency for users worldwide. Which action is MOST effective?

Accepted Answer

Enable Cloud CDN on the backend bucket. Cloud CDN caches content at global edge locations, reducing latency for users. Enabling Cloud CDN on the backend bucket serves static content from the edge. Using a multi-region bucket provides regional redundancy but does not reduce latency as effectively as CDN. Increasing machine size does not help with static content serving.

Answer

Increase the number of frontend instances

Answer

Use Cloud Armor to block high-latency requests

Answer

Use a multi-regional Cloud Storage bucket

Question 14

A company uses BigQuery for large-scale analytics. They have a fixed monthly budget and want to ensure predictable costs for query processing, even when many users run concurrent queries. Which BigQuery pricing model should they use?

Accepted Answer

Flat-rate pricing with slot reservations. BigQuery slot reservations (fixed capacity) provide predictable pricing by purchasing a set number of slots. On-demand pricing charges per byte scanned, which can vary with usage. Flat-rate pricing via reservations is best for predictable costs. Committed use discounts apply to slot reservations, but the core model is reservations.

Answer

On-demand pricing with flat-rate discounts

Answer

Autoscaling slot reservations

Answer

On-demand pricing with committed use discounts

Question 15

An application uses Cloud Bigtable and experiences high latency for reads. The row key is a timestamp prefix followed by a random ID. Queries often scan a range of timestamps for a specific ID. What design change would MOST improve read performance?

Accepted Answer

Change the row key to start with the random ID followed by timestamp. For Bigtable, row key design is critical. Scanning a range of timestamps for a specific ID is inefficient if the key starts with timestamp (scans across all IDs). Prepending the ID ensures all data for that ID is contiguous, making range scans efficient. Adding nodes increases throughput but doesn't fix the key design issue. Using a column family is about grouping columns, not performance.

Answer

Add more Bigtable nodes

Answer

Use a separate column family for the ID

Answer

Enable Bigtable replication