Cloud Digital Leader Scaling with Google Cloud operations Practice Test 3 — 15 Questions

Question 1

A company's cloud team is asked to demonstrate that their infrastructure changes are repeatable and auditable. They use Terraform configuration files committed to a Git repository to define all cloud resources. Which operational practice does this exemplify?

Accepted Answer

Infrastructure as Code (IaC) managed through version control, providing repeatable and auditable infrastructure changes. By storing Terraform configuration files in a Git repository, the team treats infrastructure definitions as code, enabling version control, peer review, and a complete audit trail of changes. This is the core principle of Infrastructure as Code (IaC), which ensures that every infrastructure change is repeatable because the exact same configuration can be applied multiple times, and auditable because Git history records who changed what and when.

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Manual change management, where each infrastructure change is recorded in a spreadsheet for audit purposes

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Disaster recovery planning, using configuration files to document what needs to be rebuilt after a failure

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Cost optimization, by defining infrastructure in code to enable automatic right-sizing of resources

Question 2

A product team is discussing how to handle a planned 48-hour maintenance window for a critical customer-facing service. The SRE team argues the maintenance window is unnecessary with proper cloud architecture. Which cloud capability eliminates the need for planned downtime maintenance windows?

Accepted Answer

Zero-downtime deployment strategies like rolling updates and blue/green deployments, combined with cloud live migration for infrastructure maintenance. Option B is correct because cloud platforms like Google Cloud support zero-downtime deployment strategies (rolling updates, blue/green deployments) and live migration for infrastructure maintenance. Live migration transparently moves running VMs between hosts without interrupting the OS or applications, while blue/green deployments allow traffic to be switched to a fully updated environment before the old one is taken down. Together, these capabilities eliminate the need for planned downtime maintenance windows entirely.

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Longer maintenance windows scheduled during off-peak hours to minimize customer impact

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Notifying customers in advance of the maintenance window and offering service credits for the downtime

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Backing up all data before the maintenance window to ensure recovery if something goes wrong

Question 3

An operations team tracks the following metrics for their customer portal: request latency p99, error rate, and requests per second. In Site Reliability Engineering terminology, what are these metrics called, and what do they collectively define?

Accepted Answer

Service Level Indicators (SLIs), which measure specific dimensions of service behavior from the user's perspective and collectively define how reliability is quantified. In Site Reliability Engineering (SRE), the metrics p99 latency, error rate, and requests per second are classified as Service Level Indicators (SLIs). SLIs are carefully chosen quantitative measures of specific aspects of the service's behavior, such as availability, latency, or throughput, as experienced by the end user. Collectively, these SLIs define how reliability is quantified and are used to set and monitor Service Level Objectives (SLOs).

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Key Performance Indicators (KPIs) that define the overall health of the business

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Service Level Agreements (SLAs), defining the contractual commitments made to customers

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Operational metrics that are only relevant to the infrastructure team and not to business stakeholders

Question 4

A company's cloud costs have grown faster than its business. The FinOps team is implementing cloud cost governance. Which practice most effectively ensures that individual teams are accountable for their cloud spending?

Accepted Answer

Implementing consistent resource labeling and chargeback reporting so each team's cloud spending is visible and attributed to them. Option B is correct because implementing consistent resource labeling and chargeback reporting directly enables cost attribution to individual teams. In Google Cloud, labels are key-value pairs attached to resources, and when combined with billing export to BigQuery, they allow granular cost breakdowns per team. This creates clear accountability by making each team's spending visible and chargeable back to their budget, which is the core principle of cloud cost governance.

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Requiring all teams to use only the cheapest available cloud service options regardless of technical requirements

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Consolidating all cloud accounts under a single centralized IT team that controls all cloud resource creation

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Disabling all non-production environments to eliminate spending outside of production

Question 5

An operations team wants to receive an automated alert when their web application's HTTP error rate exceeds 5% for more than 5 minutes. Which Google Cloud product is used to configure this type of metric-based alert?

Accepted Answer

Cloud Monitoring, by creating an alerting policy on the HTTP error rate metric with a 5-minute evaluation window and notification channel. Cloud Monitoring is the correct service because it is purpose-built for creating alerting policies based on metrics like HTTP error rates. You can define a condition that triggers when the error rate exceeds 5% for a specified evaluation window (e.g., 5 minutes) and route the alert through a notification channel (e.g., email, Slack). This directly matches the requirement for a metric-based alert with a time-based threshold.

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Cloud Logging, by configuring a log-based metric and email notification

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Cloud Trace, by setting a trace sampling threshold for error requests

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Security Command Center, by configuring a finding for high error rates

Question 6

A company is evaluating whether to adopt a multi-cloud strategy (using two or more cloud providers for different workloads). An engineer lists the following arguments: (1) resilience against a single cloud provider outage, (2) negotiating leverage on pricing, (3) using best-of-breed services from each provider. A cloud architect cautions that multi-cloud also introduces significant challenges. What is the most significant operational challenge of a multi-cloud approach?

Accepted Answer

Significantly increased operational complexity: teams need expertise in multiple providers' tools, security models, and APIs, while governance, monitoring, and cost management must span inconsistent environments. Option B is correct because multi-cloud environments inherently increase operational complexity. Teams must master distinct APIs, security models (e.g., IAM policies differ between AWS and GCP), monitoring tools (e.g., CloudWatch vs. Cloud Monitoring), and cost management consoles. Governance and compliance must be enforced consistently across heterogeneous platforms, which often requires custom tooling or third-party solutions, making day-to-day operations significantly more challenging than a single-cloud approach.

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Multi-cloud requires purchasing separate hardware for each cloud provider's environment

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Cloud providers refuse to allow customers to use competing providers simultaneously

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Multi-cloud makes it impossible to use any managed services because applications must be portable across providers

Question 7

A cloud operations team wants to ensure that all cloud resources created in their Google Cloud organization comply with company naming standards and required cost allocation labels. Which Google Cloud capability can automatically enforce these standards on resource creation?

Accepted Answer

Organization Policy Service with custom constraints or required label policies that prevent resource creation if naming and label standards are not met. Organization Policy Service with custom constraints or required label policies is correct because it provides a preventive control that blocks resource creation if the resource does not meet defined naming and label standards. This is enforced at the Google Cloud resource hierarchy level before any resource is provisioned, ensuring compliance automatically without relying on post-creation detection or manual processes.

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Cloud Billing reports, which flag resources missing required labels after they are created

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Cloud Monitoring alerts that notify the team when non-compliant resources are detected

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Cloud IAM roles that only grant resource creation permissions to employees who have passed a naming standards training

Question 8

A company's cloud environment has grown rapidly and the team is struggling to understand what cloud resources exist across dozens of projects. Which Google Cloud product provides a unified inventory of all cloud assets across an organization's projects and folders?

Accepted Answer

Cloud Asset Inventory, which provides a searchable, unified inventory of all resources and IAM policies across an organization's projects and folders. Cloud Asset Inventory is the correct answer because it is the Google Cloud service specifically designed to provide a unified, searchable inventory of all cloud assets (resources and IAM policies) across an organization's projects, folders, and organization nodes. It supports real-time and historical snapshots, enabling teams to discover and track resources as the environment scales. This directly addresses the need to understand what resources exist across dozens of projects.

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Cloud Billing console, which lists all resources that have incurred charges

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Google Cloud Console project dashboard, which shows resources within a single project

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Security Command Center, which lists security vulnerabilities in cloud resources

Question 9

A DevOps team wants to implement a release process where a new application version is first deployed to 5% of production traffic, monitored for errors, then gradually increased to 100% if metrics remain healthy. Which deployment strategy does this describe?

Accepted Answer

Canary deployment, where a new version receives a small percentage of traffic first and is progressively rolled out as metrics confirm it is healthy. This describes a canary deployment, where the new version is initially exposed to a small subset of users (e.g., 5% of traffic) and then gradually rolled out to 100% only if key metrics (latency, error rate, CPU usage) remain within acceptable thresholds. Google Cloud's Deployment Manager and GKE support canary deployments via traffic splitting with services like Istio or native GKE ingress, allowing fine-grained control over the rollout percentage.

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Blue/green deployment, where two identical environments run simultaneously and traffic is switched atomically

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Rolling deployment, where instances are updated sequentially one at a time until all run the new version

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Recreate deployment, where the old version is terminated before the new version is deployed

Question 10

An SRE team analyzes that their service had 47 minutes of downtime in the past 30 days. Their SLO is 99.9% monthly availability. How should the team characterize their performance relative to the SLO?

Accepted Answer

The SLO was missed: 99.9% availability allows approximately 43.2 minutes of downtime in a 30-day month, so 47 minutes exceeded the error budget by about 3.8 minutes. The SLO of 99.9% monthly availability allows a maximum downtime of 43.2 minutes in a 30-day month (30 days × 24 hours × 60 minutes × 0.001 = 43.2 minutes). Since the actual downtime was 47 minutes, the error budget was exceeded by 3.8 minutes, meaning the SLO was missed. This calculation is standard for Google Cloud SRE practices, where error budgets are derived directly from the SLO percentage.

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The SLO was met because 47 minutes is less than 1 hour of downtime per month

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The SLO cannot be evaluated because downtime minutes are not the correct unit for measuring availability

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The SLO was met with margin because 47 minutes represents less than 0.5% downtime

Question 11

A company's cloud team is asked to reduce the cost of a batch data processing workload that runs for 4–6 hours each night and can tolerate interruptions. The workload currently uses standard on-demand Compute Engine VMs. Which pricing option should the team evaluate first?

Accepted Answer

Spot VMs, which offer up to 91% discount for workloads that can tolerate interruption and checkpoint/resume their work. Spot VMs are the correct first evaluation because the workload runs for a fixed 4–6 hour nightly window, can tolerate interruptions, and can checkpoint/resume its work. Spot VMs offer up to a 91% discount compared to standard on-demand VMs, making them the most cost-effective option for fault-tolerant batch processing that does not require continuous availability.

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Committed Use Discounts (CUDs), by committing to 1 or 3 years of VM usage

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Sustained Use Discounts (SUDs), which automatically apply when VMs run for more than 25% of a month

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Reserved Instances, by purchasing capacity reservation for the nightly batch window

Question 12

A cloud team performs a quarterly review of its Compute Engine instances and discovers 15 VMs that have had zero CPU utilization for over 90 days. What is the recommended operational response to these idle resources?

Accepted Answer

Investigate whether each VM is still needed; delete confirmed unused VMs to eliminate wasted spend, potentially saving thousands per month. Option B is correct because the recommended operational response to idle Compute Engine instances is to investigate their necessity and delete them if unused. Idle VMs with zero CPU utilization for over 90 days incur ongoing costs for persistent disks, static IPs, and other attached resources, even if the CPU is idle. Deleting confirmed unused VMs eliminates this wasted spend, potentially saving thousands per month, aligning with Google Cloud's cost optimization best practices.

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Leave the VMs running in case they are needed for future workloads — storage costs are minimal for idle VMs

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Upgrade the idle VMs to larger machine types so they can handle future workloads if needed

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Apply committed use discounts to the idle VMs to reduce their cost while keeping them available

Question 13

A company's SRE team is debating whether to automate a frequently performed manual operational task. The automation would take 4 weeks of engineering time to build. The manual task takes 30 minutes per occurrence and happens approximately 20 times per month. Using the SRE concept of 'toil,' how should the team approach this decision?

Accepted Answer

Build the automation: eliminating toil permanently is a core SRE principle, and the 4-week investment pays back within approximately 16 months while freeing engineers for higher-value reliability work indefinitely. Option B is correct because automating toil aligns with the core SRE principle of eliminating repetitive, manual work to free engineers for higher-value reliability tasks. The 4-week build cost is justified: 20 occurrences/month × 0.5 hours = 10 hours/month, so the payback period is 4 weeks × 40 hours/week ÷ 10 hours/month = 16 months, after which the team gains indefinite time savings. This decision does not require exact salary data, as the primary goal is reducing toil, not purely cost optimization.

Answer

Do not automate — the manual task is only 10 hours per month and the 4-week build cost is too high to justify

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Hire an additional junior engineer to perform the manual task more efficiently instead of automating

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The team cannot make this decision without knowing the exact annual salary cost of the engineers who perform the manual task

Question 14

A company runs a customer-facing web application with a published SLA of 99.95% monthly availability. In the past month, the application experienced two outages: a 12-minute outage and a 7-minute outage. Did the company meet its SLA?

Accepted Answer

Yes — 99.95% availability in a 30-day month allows approximately 21.6 minutes of downtime; total outage of 19 minutes is within the budget, meaning the SLA was met. Option B is correct because the SLA of 99.95% monthly availability permits a maximum downtime of approximately 21.6 minutes in a 30-day month (total minutes in month × (1 - 0.9995) = 43,200 × 0.0005 = 21.6 minutes). The combined outage of 19 minutes (12 + 7) is within this budget, so the SLA was met. This calculation assumes a 30-day month; if the month had 31 days, the allowable downtime would be about 22.3 minutes, still exceeding 19 minutes.

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No — the company missed the SLA because any outage automatically constitutes an SLA breach

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The answer cannot be determined without knowing the cause of the outages

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No — two separate outages in one month always constitute an SLA breach regardless of duration

Question 15

A cloud architect is reviewing logs from a production incident. She wants to search all log entries across multiple Google Cloud projects for error messages containing a specific string. Which Google Cloud product enables centralized log searching and analysis across an entire organization?

Accepted Answer

Cloud Logging, which centralizes logs from all Google Cloud services and projects and supports powerful filtering and search queries across an organization. Cloud Logging (formerly Stackdriver Logging) is the Google Cloud service designed to ingest, store, and analyze log data from all Google Cloud services and projects. It supports centralized log aggregation across an entire organization via aggregated sinks and the Logs Explorer, enabling powerful filtering and search queries (e.g., using the `textPayload` or `jsonPayload` fields) to find specific error strings across multiple projects without needing to export data elsewhere.

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Cloud Monitoring, which provides metric dashboards and alerting

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BigQuery, by exporting logs to a dataset and running SQL queries to find matching error entries

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Cloud Trace, which provides distributed request tracing for latency analysis