Cloud Digital Leader Scaling with Google Cloud operations Practice Test 4 — 15 Questions

Question 1

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?

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

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 2

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. 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 3

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 4

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 5

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 6

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 7

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. 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 8

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. 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.

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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 9

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. 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 10

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

Question 11

An operations team has been asked to estimate the annual cost impact of a proposed new cloud architecture. The architecture would replace 50 on-demand n2-standard-4 VMs (running 24/7) with an autoscaling group that averages 10 VMs under normal load but scales to 50 during peak hours (approximately 8 hours per day). Which analytical approach best estimates the cost impact?

Accepted Answer

Model the actual usage pattern: calculate cost for (16 normal hours × 10 VMs) + (8 peak hours × 50 VMs) per day, compare to fixed cost of 50 VMs × 24 hours, and use Google Cloud Pricing Calculator to price the VM type. It accurately models the variable usage pattern of the autoscaling group: 16 hours at 10 VMs plus 8 peak hours at 50 VMs per day. This approach then compares the daily cost to the fixed 50 VMs × 24 hours baseline, using the Google Cloud Pricing Calculator to price the n2-standard-4 instance type. This reflects the pay-per-use billing model of Google Compute Engine, where autoscaling does not change per-VM pricing but reduces total cost by running fewer instances during off-peak hours.

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Assume the autoscaling group always runs at average load (10 VMs) and multiply by the annual hours to get the new cost

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Request a custom quote from Google Cloud sales since pricing for autoscaling groups is negotiated individually

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The cost will be identical since autoscaling groups use the same VM type as the fixed fleet

Question 12

A cloud team receives an alert that a critical production service's error rate has spiked. Following incident response best practices, what is the correct first priority action?

Accepted Answer

Mitigate user impact immediately (e.g., rollback, traffic rerouting, scaling) while beginning parallel investigation of the root cause. Incident response best practices prioritize reducing user impact first. In Google Cloud, this could involve rolling back a deployment via Cloud Deploy, rerouting traffic with a load balancer, or scaling up instances with Managed Instance Groups, all while a parallel investigation into the root cause begins. This aligns with the SRE principle of 'error budget' and the 'mitigate before diagnose' approach.

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Identify and fix the root cause before taking any other action to ensure the fix is complete

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Wait to understand the full scope of the issue and inform all stakeholders before taking any technical action

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Escalate to senior leadership and wait for their approval before making any production changes

Question 13

A company wants to reduce its Google Cloud costs without reducing its workload capacity. The team identifies that several production VMs consistently use less than 30% of their allocated CPU and memory. What is the most straightforward cost optimization action?

Accepted Answer

Right-size the VMs by migrating to smaller machine types that match actual CPU and memory consumption, reducing costs proportionally. Right-sizing VMs by migrating to smaller machine types that match actual CPU and memory consumption directly reduces the cost per hour while maintaining the same workload capacity. Since the VMs are consistently under-utilized, this approach eliminates wasted resources without affecting performance or availability.

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Delete the under-utilized VMs since low utilization indicates they are no longer needed

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Purchase Committed Use Discounts for the over-provisioned VMs to reduce their per-hour cost

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Enable sustained use discounts by ensuring VMs run continuously throughout the month

Question 14

A platform engineering team is designing a self-service cloud environment for development teams. They want developers to be able to provision approved cloud resources quickly without waiting for central IT approval for every request, while still ensuring compliance with security and cost policies. Which architectural approach best balances developer agility with governance?

Accepted Answer

Provide a self-service catalog of pre-approved, policy-compliant infrastructure templates with automated provisioning, budget alerts, and org policy guardrails — enabling developer agility while enforcing compliance automatically. It uses a self-service catalog with pre-approved, policy-compliant templates (e.g., Deployment Manager or Terraform configurations) combined with Organization Policy Service guardrails and automated budget alerts. This approach allows developers to provision resources on demand while enforcing security and cost policies automatically, balancing agility with governance without manual bottlenecks.

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Require all resource provisioning requests to be submitted as tickets to the central IT team for manual review and approval before any resources are created

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Give all developers Owner access to all Google Cloud projects so they can provision any resources without delays

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Allow developers to provision resources freely in a shared sandbox project only, keeping production entirely controlled by central IT

Question 15

A cloud team wants to understand their current Google Cloud resource inventory — specifically, which VMs are running in each region, their machine types, and whether they have public IP addresses. Which approach most efficiently provides this across all projects?

Accepted Answer

Use Cloud Asset Inventory to run a single org-wide query that returns all VM instances, their regions, machine types, and network configurations across all projects. Cloud Asset Inventory provides a single, unified API to query resources across all projects in an organization. By using the `gcloud asset search-all-resources` command with the `--asset-types=compute.googleapis.com/Instance` filter, you can retrieve all VM instances along with their regions, machine types, and network configurations (including public IP addresses) in one operation, without needing to access each project individually.

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Log into each Google Cloud project individually through the Console and manually record VM details in a spreadsheet

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Check the Cloud Billing reports, which list all resources that have incurred charges by resource type

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Enable VPC flow logs in each project to capture VM network activity