Cloud Digital Leader Practice Test 11 — 15 Questions

Question 1

A data analytics team needs to run a one-time transformation on 10 TB of data stored in Cloud Storage, then load the results into BigQuery. The transformation is a custom Java application that reads files, processes them, and writes to a new location. Which service should they use to minimize operational overhead?

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

Accepted Answer

Cloud Dataflow with Apache Beam Java SDK. Cloud Dataflow with Apache Beam Java SDK is the appropriate service for running custom Java transformations on large datasets in a fully managed, serverless manner. It reads from Cloud Storage, processes data, and can load results to BigQuery without provisioning clusters. Other options like Cloud Functions have execution limits, GKE requires cluster management, and Dataproc Serverless is intended for Spark jobs, not arbitrary custom Java applications.

Answer

Google Kubernetes Engine (GKE) with a custom container

Answer

Dataproc Serverless with Spark job

Answer

Cloud Functions triggered by Cloud Storage events

Question 2

A retail company stores petabytes of customer transaction data for compliance reasons. They access data less than once a year but must retain it for 10 years. They want the lowest-cost storage. Which storage class should they choose?

Accepted Answer

Archive storage class. Archive storage class is the correct choice because it is designed for data accessed less than once a year, with the lowest storage cost among Google Cloud storage classes. The customer's requirement of retaining data for 10 years with infrequent access aligns perfectly with Archive's 365-day minimum storage duration and retrieval costs that are higher but acceptable given the rare access pattern.

Answer

Coldline storage class

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Standard storage class

Answer

Nearline storage class

Question 3

What is the difference between a Service Level Indicator (SLI), a Service Level Objective (SLO), and a Service Level Agreement (SLA)?

Accepted Answer

SLI is the measured metric; SLO is the internal target for that metric; SLA is the contractual customer commitment.. It accurately defines the relationship: an SLI is a specific metric (e.g., request latency at the 99th percentile), an SLO is the internal target for that metric (e.g., 99.9% of requests under 200ms), and an SLA is the contractual commitment to a customer (e.g., 99.9% uptime with financial penalties). This aligns with Google Cloud's Site Reliability Engineering (SRE) practices, where SLIs are measured, SLOs are internal goals, and SLAs are legal agreements.

Answer

SLI is the contract with customers; SLO is the internal target; SLA is the measurement.

Answer

SLI, SLO, and SLA are all the same thing — different names for uptime guarantees.

Answer

SLA is measured in milliseconds; SLO is measured in percentage; SLI has no unit.

Question 4

A team deploys microservices on GKE with Horizontal Pod Autoscaler (HPA). They want to scale based on custom metrics from third-party monitoring. What must they do first?

Accepted Answer

Install the custom metrics API adapter.. B is correct because Horizontal Pod Autoscaler (HPA) in GKE relies on the custom.metrics.k8s.io API to retrieve custom metrics from external monitoring systems. To expose these metrics to the HPA, you must install a custom metrics API adapter (e.g., the Prometheus Adapter or Google Cloud's custom-metrics-stackdriver-adapter) that translates the third-party monitoring data into the format the Kubernetes API server expects. Without this adapter, the HPA cannot query the custom metrics and will fail to scale.

Answer

Use Cluster Autoscaler.

Answer

Enable Cloud Monitoring and configure custom metrics.

Answer

Use Vertical Pod Autoscaler.

Question 5

A regional hospital chain wants to improve patient outcomes by analyzing electronic health records (EHRs) from multiple departments, including radiology, pathology, and pharmacy. Currently, each department stores data in separate on-premises databases, making it difficult to correlate information. The hospital must comply with HIPAA and other data privacy regulations. They have a small IT team and limited budget for new hardware. They want to enable clinicians to run ad-hoc queries across all data and generate insights using machine learning, without managing infrastructure. Which solution best achieves these goals?

Accepted Answer

Use Cloud Healthcare API to ingest and standardize data from each department, store in BigQuery, and use BigQuery ML to build predictive models.. It leverages the Cloud Healthcare API to ingest and standardize data from disparate on-premises databases into a unified format, stores it in BigQuery for serverless ad-hoc querying, and uses BigQuery ML to build predictive models without managing infrastructure. This fully meets HIPAA compliance through built-in data residency and access controls, while the small IT team avoids hardware procurement and maintenance overhead.

Answer

Purchase additional on-premises servers and implement a data warehouse with ETL processes.

Answer

Deploy a third-party analytics SaaS tool and export data from each department manually.

Answer

Migrate all data to Cloud Storage and grant clinicians access to files for manual analysis.

Question 6

Google Cloud bills Compute Engine VMs per second (after a 1-minute minimum). A batch job runs for exactly 3 minutes and 47 seconds. How many minutes does Google Cloud charge for?

Accepted Answer

Exactly 3 minutes and 47 seconds of compute time.. Google Cloud Compute Engine bills per second after a 1-minute minimum. Since the job runs for 3 minutes and 47 seconds, the total billable time is exactly 3 minutes and 47 seconds — no rounding up to the nearest minute or any other interval. Option B correctly reflects this per-second billing model.

Answer

4 minutes (rounded up to the nearest minute).

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1 hour (traditional cloud billing minimum).

Answer

5 minutes (rounded up to the nearest 5-minute interval).

Question 7

A data analytics team uses BigQuery for large-scale queries. They notice that queries are scanning more data than necessary, leading to high costs. Which feature should they implement to reduce the amount of data scanned per query?

Accepted Answer

Partitioning. Partitioning divides a table into segments based on a column (e.g., date), allowing BigQuery to prune partitions during query execution. When a query includes a filter on the partitioning column, BigQuery scans only the relevant partitions, significantly reducing the bytes processed and lowering costs.

Answer

Materialized views

Answer

Streaming inserts

Answer

Clustering

Question 8

A company runs a web application on Google Kubernetes Engine (GKE) that experiences sudden traffic spikes. The operations team notices that the application's response time increases significantly during these spikes despite having Horizontal Pod Autoscaler (HPA) configured. They want to ensure consistent performance. What should they do?

Accepted Answer

Configure the HPA to use custom metrics based on request latency.. Configuring the HPA to use custom metrics based on request latency allows the autoscaler to react directly to the application's performance degradation. Unlike CPU-based metrics, which may not reflect actual user-facing latency during traffic spikes, custom metrics like request latency provide a more accurate signal for scaling decisions, ensuring consistent response times.

Answer

Increase the CPU request limit for all pods.

Answer

Create multiple node pools with different machine types.

Answer

Manually scale the deployment during expected spikes.

Question 9

A startup wants to automatically rotate encryption keys used for Cloud Storage objects every 90 days. Which service should they use?

Accepted Answer

Use Cloud Key Management Service (KMS) with automatic rotation schedule. Cloud KMS supports automatic key rotation with a configurable rotation period (e.g., every 90 days). When you create a key ring and key in Cloud KMS, you can set a rotation schedule, and Cloud KMS will automatically generate a new key version on the specified date. This allows the startup to meet the 90-day rotation requirement without manual intervention, and the new key version is used for encrypting new Cloud Storage objects while old versions remain available for decrypting existing data.

Answer

Use Cloud Secret Manager to store and rotate encryption keys

Answer

Use default Cloud Storage encryption (SSE-GCP)

Answer

Use Cloud HSM to store keys and rotate manually

Question 10

A company's web service has a Service Level Objective (SLO) of 99.9% monthly availability. In a 30-day month, how many minutes of downtime are allowed before the SLO is violated?

Accepted Answer

~43.2 minutes. The SLO of 99.9% monthly availability means the service can be unavailable for 0.1% of the total monthly time. In a 30-day month, total minutes are 30 × 24 × 60 = 43,200 minutes. 0.1% of 43,200 minutes is 43.2 minutes, so option B is correct.

Answer

~4.3 minutes

Answer

~7.2 hours

Answer

~8.6 hours

Question 11

A company wants to reduce latency for IoT devices located in remote areas with poor connectivity. They need to preprocess data locally before sending it to the cloud. Which architecture should they use?

Accepted Answer

Use edge computing devices that run Cloud IoT Edge and preprocess data.. Edge computing devices running Cloud IoT Edge allow local preprocessing of data, reducing the volume of data transmitted over poor connectivity links. This architecture minimizes latency by processing data closer to the source, which is critical for IoT devices in remote areas. Cloud IoT Edge extends Google Cloud's data processing capabilities to the edge, enabling real-time insights without constant cloud connectivity.

Answer

Deploy Cloud CDN to cache responses.

Answer

Use Cloud IoT Core with MQTT and process data on the server side.

Answer

Use a VPN to connect devices directly to the cloud.

Question 12

A startup needs to quickly deploy a web application with minimal infrastructure management. They want to focus on code, not servers. Which Google Cloud service model is most appropriate?

Accepted Answer

Platform as a Service (PaaS) using App Engine. App Engine is a fully managed Platform as a Service (PaaS) that abstracts away the underlying infrastructure, allowing developers to deploy web applications without managing servers or operating systems. It automatically handles scaling, load balancing, and patching, which aligns with the startup's requirement to focus on code rather than infrastructure management.

Answer

Software as a Service (SaaS) using Gmail

Answer

Function as a Service (FaaS) using Cloud Functions

Answer

Infrastructure as a Service (IaaS) using Compute Engine

Question 13

A small business wants to host a static website with minimal management overhead. They want high availability and low cost. Which Google Cloud service should they use?

Accepted Answer

Cloud Storage with a load balancer. Cloud Storage with a load balancer is ideal for hosting a static website because it serves content directly from object storage, requires no server management, and the load balancer provides high availability by distributing traffic across multiple regions. This combination offers low cost (pay only for storage and egress) and minimal operational overhead, as there are no virtual machines or application runtimes to maintain.

Answer

Compute Engine with Apache

Answer

App Engine Standard Environment

Answer

Cloud Run

Question 14

A retail company experiences huge traffic spikes during Black Friday and slow periods otherwise. They want to avoid over-provisioning servers and reduce costs. Which cloud feature directly addresses this need?

Accepted Answer

Auto-scaling based on CPU utilization. Auto-scaling based on CPU utilization dynamically adjusts the number of server instances in response to real-time demand. During Black Friday traffic spikes, it automatically adds capacity, and during slow periods, it scales down to reduce costs. This directly addresses the need to avoid over-provisioning while maintaining performance.

Answer

Purchasing committed use discounts

Answer

Load balancing across regions

Answer

Manual scaling with reserve instances

Question 15

A team notices that their Compute Engine instances are consistently running at low CPU utilization. They want to reduce costs by receiving recommendations to resize or stop idle VMs. Which service provides these recommendations?

Accepted Answer

Active Assist. Active Assist includes Recommender, which provides cost optimization recommendations such as rightsizing VMs, identifying idle resources, and suggesting committed use discounts.

Answer

Cost Management dashboard

Answer

Cloud Scheduler

Answer

Cloud Monitoring