Cloud Digital Leader Google Cloud Products and Services — 10 Questions

Question 1

A company stores sensitive data in Cloud Storage. They want to restrict access to only users from the company's corporate network (IP range 203.0.113.0/24) and ensure data is encrypted at rest using a customer-managed key. Which TWO configurations are required? (Select 2)

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

Accepted Answer

Set a bucket policy with an IP address condition. Option C is correct because a Cloud Storage bucket IAM policy can include a condition based on the request's source IP address (for example, using the `request.auth.accessLevels` or an IP-based condition via `resource.name`/`request.remoteIp` style conditions in IAM Conditions), which restricts access to the corporate range 203.0.113.0/24. Option E is correct because customer-managed encryption keys (CMEK) for Cloud Storage are created and managed in Cloud KMS, then referenced by the bucket's default KMS key so data at rest is encrypted with that customer-managed key. Option A is not correct because Cloud Armor protects HTTP(S) load-balanced applications, not direct Cloud Storage bucket access. Option B is not correct because VPC Service Controls provide a service perimeter against data exfiltration but do not by themselves enforce a specific source IP allowlist for bucket access. Option D is not correct because Cloud NAT provides outbound internet access for private instances and has no role in restricting inbound access to Cloud Storage or in encryption at rest.

Answer

Configure Cloud Armor with IP allowlist

Answer

Enable VPC Service Controls

Answer

Configure Cloud NAT

Question 2

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 Spanner is a globally distributed relational database for OLTP but not optimised for key-value time-series at this scale, and Firestore is for document data with hierarchical structure.

Answer

Firestore

Answer

BigQuery

Answer

Cloud Spanner

Question 3

A company is deploying a global web application and needs to serve users with low latency, protect against DDoS attacks, and scale automatically. Which two Google Cloud services should they combine? (Choose exactly 2.)

Accepted Answer

Cloud Armor. Cloud Armor (A) is correct because it provides edge security at the Google Cloud load balancer, including DDoS protection via Google's global infrastructure and WAF rules to filter malicious traffic. Cloud Load Balancing (D) is correct because it distributes incoming traffic across backend instances or services globally, supports automatic scaling, and provides the global anycast IP front end that Cloud Armor and Cloud CDN attach to for low-latency delivery. Together they meet the requirements of low latency, DDoS mitigation, and autoscaling. Cloud CDN (B) is not selected because, while it improves latency for cacheable content, it does not itself provide DDoS protection or autoscaling. Cloud NAT (C) is for outbound internet access from private instances, not inbound web serving, and Cloud DNS (E) only resolves domain names and does not provide security or scaling.

Answer

Cloud CDN

Answer

Cloud NAT

Answer

Cloud DNS

Question 4

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 Google's petabyte-scale, low-latency NoSQL wide-column store designed for time-series and IoT workloads, delivering single-digit millisecond latency at millions of reads/writes per second when the row key is designed for time-series access patterns. Its key-value structure with timestamped rows maps directly to the requirement.

Answer

BigQuery

Answer

Cloud Spanner

Answer

Firestore

Question 5

A company wants to set up a hybrid cloud network connecting their on-premises data center to Google Cloud with high bandwidth and low latency. They also need to provide DDoS protection for their applications. Which THREE services should they consider? (Choose THREE.)

Accepted Answer

Cloud VPN. Cloud VPN provides an encrypted tunnel for connectivity, Cloud Interconnect offers dedicated high-bandwidth, low-latency connections, and Cloud Armor protects against DDoS attacks. Together, these services fulfill the hybrid cloud networking and DDoS protection requirements.

Answer

Cloud CDN

Answer

Cloud VPC

Question 6

A data analyst wants to create interactive dashboards and reports from data stored in BigQuery. They need a free tool that does not require a license. Which TWO tools are appropriate? (Choose TWO.)

Accepted Answer

Google Sheets. Both Google Sheets and Looker Studio are free tools that can connect to BigQuery to create interactive dashboards and reports. Google Sheets offers Connected Sheets for live BigQuery data analysis, while Looker Studio provides a dedicated visualization platform. Dataflow is a data processing service, Looker is a paid BI tool, and BigQuery is a data warehouse.

Answer

Dataflow

Answer

Looker

Answer

BigQuery

Question 7

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 (option B) is correct because it is Google Cloud's fully managed, horizontally scalable NoSQL wide-column store designed for massive time-series and IoT workloads, delivering consistent single-digit millisecond latency at millions of reads/writes per second across petabytes of data with a simple row-key structure. BigQuery (A) is an analytics warehouse optimized for large scans and SQL aggregation, not low-latency point reads at millions of QPS. Cloud Spanner (C) is a strongly consistent relational database that scales well but is not optimized for petabyte-scale key-value time-series throughput at the lowest latency/cost. Firestore (D) is a document database suited to mobile/web app data at smaller scale, not petabytes of high-throughput time-series reads.

Answer

BigQuery

Answer

Cloud Spanner

Answer

Firestore

Question 8

A company uses Cloud SQL for MySQL to store transactional data. They want to run complex analytical queries that join multiple tables and aggregate millions of rows, but the queries are slow and impacting production performance. They need a solution that minimises impact on the transactional database. What is the BEST approach?

Accepted Answer

Export the data to Cloud Storage and load it into BigQuery for analysis. For complex analytical queries involving large aggregations and joins, BigQuery is the optimal solution because it is a fully managed, serverless data warehouse built for this type of workload. Exporting data to Cloud Storage and loading into BigQuery completely offloads analytics from the transactional database, avoiding any performance impact. While Cloud SQL read replicas can offload read traffic, they are not designed for heavy analytical processing and may still suffer from performance issues on complex queries over large datasets.

Answer

Create a Cloud SQL read replica and run analytical queries on the replica

Answer

Upgrade the primary Cloud SQL instance to a higher machine type

Answer

Enable Cloud SQL query caching on the primary instance

Question 9

An engineer needs to deploy a web application that runs on a custom runtime (e.g., Ruby on Rails with system dependencies). The application must automatically scale based on traffic and should not require managing the underlying infrastructure. Which Google Cloud compute service is MOST appropriate?

Accepted Answer

Cloud Run. Cloud Run is the best choice because it is a fully managed serverless platform that can run any container image, including custom runtimes like Ruby on Rails with system dependencies. It automatically scales based on traffic and requires no infrastructure management. App Engine Flexible also supports custom runtimes, but it uses VMs (cannot scale to zero) and is not recommended for new projects; Google advises using Cloud Run instead.

Answer

App Engine Standard environment

Answer

App Engine Flexible environment

Answer

Cloud Functions

Question 10

A company wants to store backup data that will be accessed infrequently (once a quarter) and can tolerate a retrieval time of several hours. The data is critical but regulatory compliance requires it to be retained for 10 years. Which Cloud Storage class is MOST cost-effective?

Accepted Answer

Coldline. Coldline storage is designed for data accessed at most once per quarter and offers lower cost than Nearline/Standard. Archive is cheaper but is intended for data accessed less than once per year, making it unsuitable for quarterly retrieval. The stated retrieval time of several hours is acceptable for both, but access frequency is the determining factor.

Answer

Standard

Answer

Nearline

Answer