Cloud Digital Leader Practice Test 24 — 15 Questions

Question 1

A global financial services firm is migrating its risk analysis workloads to Google Cloud to accelerate new model deployments. Which cloud benefit most directly supports faster time-to-market?

Accepted Answer

Rapid provisioning and deployment. Rapid provisioning and deployment (B) directly accelerates time-to-market because it allows the firm to spin up risk analysis environments in minutes using Infrastructure as Code (IaC) tools like Terraform or Deployment Manager, rather than waiting weeks for hardware procurement. This speed enables data scientists to iterate on models faster, deploy new versions immediately, and respond to market changes without infrastructure bottlenecks.

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Security compliance

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Pay-as-you-go pricing

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Global infrastructure

Question 2

A multinational corporation must comply with data residency requirements that prohibit storing data outside specific geographic regions. They plan to use BigQuery for analytics. How can Google Cloud help enforce this requirement?

Accepted Answer

Use BigQuery’s location parameter to set dataset location and enforce via Organization Policy. BigQuery datasets are created with a specific location parameter (e.g., `us-central1` or `EU`), and Google Cloud Organization Policies can be used to restrict where datasets can be created. By defining a constraint like `constraints/bigquery.locationRestriction`, administrators can enforce that datasets must reside only in approved geographic regions, preventing any data from being stored outside those boundaries. This directly addresses data residency requirements without relying on detection or blocking mechanisms that don't control storage location.

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Use Cloud Audit Logs to detect and alert on cross-region data storage

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Use Cloud Data Loss Prevention to redact cross-region data

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Use VPC Service Controls to block access to BigQuery APIs from other regions

Question 3

A developer is troubleshooting a slow response from a Cloud Run service. Which Google Cloud service can they use to trace requests across microservices?

Accepted Answer

Cloud Trace. Cloud Trace is the correct service because it is specifically designed for distributed tracing, collecting latency data from applications and displaying it in a trace timeline. It can trace requests as they propagate across multiple microservices, including Cloud Run services, by using trace context propagation headers (e.g., `X-Cloud-Trace-Context`). This allows the developer to identify bottlenecks and slow components in a request path.

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Cloud Profiler

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Cloud Logging

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Cloud Debugger

Question 4

A business wants to reduce the time to market for new features by enabling developers to provision infrastructure without waiting for IT. Which cloud attribute supports this?

Accepted Answer

On-demand self-service. On-demand self-service (Option D) is the correct answer because it allows developers to provision infrastructure automatically without requiring human interaction from IT. This cloud attribute, defined by NIST SP 800-145, enables users to unilaterally provision computing resources as needed, directly reducing time to market by eliminating manual approval and setup delays.

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Disaster recovery

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Broad network access

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High availability

Question 5

Drag and drop the steps to migrate an on-premises MySQL database to Cloud SQL using Database Migration Service into the correct order.

Accepted Answer

Set up the destination Cloud SQL instance, then connect to the source database, then create and start the migration job, then promote the Cloud SQL instance to make it primary.. The migration process requires setting up the destination, connecting to the source, creating and starting the migration, then promoting.

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Connect to the source database, then set up the destination Cloud SQL instance, then create and start the migration job, then promote the Cloud SQL instance.

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Set up the destination Cloud SQL instance, then create and start the migration job, then connect to the source database, then promote the Cloud SQL instance.

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Set up the destination Cloud SQL instance, then connect to the source database, then promote the Cloud SQL instance, then create and start the migration job.

Question 6

Refer to the exhibit. A DevOps engineer wants to create a chart showing the rate of items sold per second over time. What is a limitation of this metric for that purpose?

Accepted Answer

The metric kind is GAUGE, so it cannot be used to calculate rate. A GAUGE metric type represents a point-in-time value (e.g., current number of items), not a cumulative counter. To calculate a rate (items per second), you need a CUMULATIVE counter metric that monotonically increases, allowing Cloud Monitoring to compute the derivative over time. GAUGE metrics lack the necessary monotonicity and cumulative semantics, so they cannot be used to derive a meaningful rate of change.

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The interval should include a startTime

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The metric has no labels to filter

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The value should be DOUBLE instead of INT64

Question 7

A company is running a latency-sensitive application on Compute Engine instances in a single zone. They want to improve availability without sacrificing low latency. Which strategy should they use?

Accepted Answer

Deploy instances in multiple zones within the same region. Deploying instances in multiple zones within the same region provides high availability by distributing workloads across physically separate data centers (zones) while keeping network latency low, as intra-region latency is typically under 1-2 ms. This approach protects against zonal failures without the added latency of cross-region communication, which can be 10-100 ms or more.

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Use Cloud CDN to cache content

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Use larger machine types with more vCPUs

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Deploy instances in multiple regions

Question 8

Drag and drop the steps to recover a Compute Engine VM from a snapshot in the correct order.

Accepted Answer

Stop the VM, create a disk from the snapshot, detach the old boot disk, attach the new boot disk, start the VM. The recovery process involves using the snapshot to create a disk, detaching the old boot disk, attaching the new one, and starting the VM.

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Create a disk from the snapshot, stop the VM, detach the old boot disk, attach the new boot disk, start the VM

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Stop the VM, detach the old boot disk, create a disk from the snapshot, attach the new boot disk, start the VM

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Stop the VM, detach the old boot disk, attach the new boot disk, create a disk from the snapshot, start the VM

Question 9

Drag and drop the steps to set up a Cloud SQL for MySQL instance with a private IP address into the correct order.

Accepted Answer

Configure private services access on the VPC network, then create the Cloud SQL for MySQL instance with a private IP address, then connect from a Compute Engine VM in the same VPC.. The process requires setting up the VPC first, then creating the Cloud SQL instance with a private IP, and finally connecting from a VM.

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Create the Cloud SQL for MySQL instance with a private IP address, then configure private services access on the VPC network, then connect from a Compute Engine VM in the same VPC.

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Connect from a Compute Engine VM in the same VPC, then configure private services access on the VPC network, then create the Cloud SQL for MySQL instance with a private IP address.

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Configure private services access on the VPC network, then connect from a Compute Engine VM in the same VPC, then create the Cloud SQL for MySQL instance with a private IP address.

Question 10

A media company has a web application that serves video content globally. The application is deployed on Compute Engine instances behind a TCP load balancer in a single region. Users in distant regions experience high latency. The company wants to improve performance for all users while keeping operational overhead low. They also need to handle sudden spikes in traffic during live events. What should they do?

Accepted Answer

Deploy additional instances in multiple regions and use a global HTTP(S) load balancer with Cloud CDN.. Deploying instances in multiple regions and using a global HTTP(S) load balancer with Cloud CDN reduces latency by serving content from edge locations close to users. Cloud CDN caches video content at Google's global edge points of presence (PoPs), while the global HTTP(S) load balancer provides anycast IP-based traffic distribution across regions, handling traffic spikes through automatic scaling and distributed capacity.

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Use Cloud Run for the application and enable automatic scaling globally.

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Move the application to Google Kubernetes Engine and use horizontal pod autoscaling.

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Increase the machine type of existing instances and add more instances in the same region.

Question 11

A multinational manufacturing company operates thousands of IoT sensors on factory equipment. These sensors generate over 50 TB of telemetry data daily. The company wants to implement predictive maintenance to reduce unplanned downtime. Their current on-premises infrastructure is maxed out, and they have a small IT team with limited data engineering expertise. They are evaluating cloud vs. on-premises options. The data is highly sensitive and must be encrypted at rest and in transit. Additionally, they need to run machine learning models near real-time and store historical data for trend analysis. The CTO is concerned about vendor lock-in, data sovereignty, and the ability to scale globally as they open new factories. Which course of action best addresses these requirements using Google Cloud?

Accepted Answer

Use Cloud Pub/Sub to ingest sensor data, Cloud Dataflow for stream processing, BigQuery for historical storage and analysis, and Vertex AI for predictive models, all in the desired region.. Use Cloud Pub/Sub to ingest streaming sensor data, Cloud Dataflow for processing, BigQuery for historical storage and analysis, and Vertex AI for predictive models. This provides near-real-time ML, encryption at rest and in transit, regional data sovereignty, and global scalability.

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Deploy Kubernetes on-premises to orchestrate microservices, and use Cloud Storage for backup only.

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Build a new on-premises data center with dedicated GPU servers for ML training, and hire additional data engineers.

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Store all sensor data in Cloud Storage and run ad-hoc queries using BigQuery without any streaming pipeline.

Question 12

Which Google Cloud service is a managed platform for building, training, and deploying ML models, including support for AutoML and custom models?

Accepted Answer

Vertex AI. Vertex AI is a unified ML platform that combines AutoML and custom model training, tuning, and serving.

Answer

BigQuery ML

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AI Platform (legacy)

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Cloud TPU

Question 13

A company is migrating its on-premises data center to Google Cloud. They want to avoid large upfront hardware costs and only pay for the resources they consume. Which cloud benefit does this represent?

Accepted Answer

Pay-as-you-go pricing. The scenario describes a shift from capital expenditure (CapEx) to operational expenditure (OpEx), which is the core of pay-as-you-go pricing. This model allows the company to avoid large upfront hardware costs and only pay for the compute, storage, and network resources actually consumed, aligning with Google Cloud's consumption-based billing model.

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Security

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High availability

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Scalability

Question 14

An engineer is setting up budgets and alerts to manage costs. They want to receive a notification when forecasted spend exceeds 80% of the budget amount. Which step is required to enable forecast-based alerts?

Accepted Answer

Select 'Forecasted spend' as the alert threshold type in the budget configuration. In the budget alert configuration, you can set alert thresholds based on actual or forecasted spend. To alert on forecasted spend, you must select the 'Forecasted spend' option when defining the threshold rules.

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Enable billing export to BigQuery and set up a scheduled query

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Create a Cloud Function that checks current spend every hour

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Use the Cost Management API to query forecast data

Question 15

Which THREE are required to achieve HIPAA compliance on Google Cloud?

Accepted Answer

Sign a Business Associate Agreement (BAA) with Google. HIPAA requires covered entities and their business associates to have a written agreement that establishes the permitted and required uses of protected health information (PHI). Google Cloud provides a standard Business Associate Agreement (BAA) that customers must sign to contractually bind Google to HIPAA obligations, including safeguarding ePHI and reporting breaches. Without a signed BAA, Google is not legally liable as a business associate under HIPAA, making this a foundational requirement for compliance.

Answer

Use a dedicated project for all PHI workloads

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Configure multi-factor authentication for all users