Cloud Digital Leader Scaling with Google Cloud operations — 15 Questions

Question 1

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

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~7.2 hours

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~8.6 hours

Question 2

A SRE team wants to alert when their service is consuming error budget faster than expected, rather than alerting only when the SLO threshold is crossed. Which Cloud Monitoring alerting strategy supports this approach?

Accepted Answer

SLO burn rate alerting — alert when error budget is being consumed faster than the measurement window allows.. B is correct because SLO burn rate alerting is specifically designed to detect when error budget is being consumed faster than the measurement window allows, enabling proactive alerts before the SLO threshold is breached. This approach uses a burn rate (e.g., 2x, 10x) to trigger alerts when the error budget depletion rate exceeds a predefined multiple of the expected rate, allowing the team to respond early. It directly addresses the requirement of alerting on error budget consumption speed rather than waiting for a hard SLO violation.

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Threshold alerting — alert when error rate exceeds 0.1%.

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Uptime check alerting — alert when health checks fail.

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Log-based alerting — alert when specific error messages appear in logs.

Question 3

A company's on-premises IT team spends 70% of their time on routine maintenance tasks: patching servers, replacing failed hardware, and upgrading storage. After migrating to Google Cloud managed services, which operational outcome should they expect?

Accepted Answer

The IT team can redirect time from maintenance to higher-value activities like innovation and feature development.. By migrating to Google Cloud managed services like Compute Engine with sole-tenant nodes or fully managed services such as Cloud SQL and Google Kubernetes Engine, the cloud provider handles routine maintenance tasks (patching, hardware replacement, storage upgrades). This frees the IT team from approximately 70% of their previous workload, allowing them to focus on higher-value activities like application innovation, feature development, and optimizing cloud architecture. Option B correctly identifies this shift from operational overhead to strategic work.

Answer

The IT team will need to hire more staff to manage additional cloud infrastructure.

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The IT team will still perform the same tasks but remotely via the Cloud Console.

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The IT team will be fully automated out of their roles by Google's AI.

Question 4

A company has deployed a critical application on Google Cloud and wants to understand what happens to their workloads during a Google Cloud data center maintenance event (e.g., host system upgrades). What Google Compute Engine feature handles this automatically for most VMs?

Accepted Answer

Live migration transparently moves VMs to healthy hosts during maintenance with no VM downtime.. Google Compute Engine uses Live Migration to automatically move running VMs from a host undergoing maintenance (e.g., host system upgrades) to a healthy host without interrupting the VM. This process preserves the VM's memory, network connections, and disk state, resulting in zero VM downtime. It is enabled by default for most VM instances, except those with GPUs or certain machine types that explicitly opt out.

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VMs are terminated and restarted automatically on new hardware, causing a few minutes of downtime.

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VMs are snapshotted, the snapshot is restored on new hardware, and the VM is restarted.

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Customers must subscribe to Google Cloud support to receive advance notice and schedule their own maintenance windows.

Question 5

A company's application experiences traffic spikes every weekday morning when employees log in at 9 AM. The team wants their infrastructure to automatically handle these spikes without manual intervention and without over-provisioning resources all day. Which Google Cloud capability addresses this?

Accepted Answer

Configure autoscaling on the application's infrastructure to automatically scale up for load and scale down during off-peak hours.. Option B is correct because Google Cloud's managed instance groups (MIGs) with autoscaling can automatically adjust the number of VM instances based on load metrics (e.g., CPU utilization, requests per second). This handles the 9 AM traffic spike without manual intervention and avoids over-provisioning during off-peak hours by scaling down when demand decreases.

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Purchase reserved capacity for peak load and configure it to be active only on weekdays.

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Deploy additional VMs manually each weekday morning and terminate them at night.

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Use Cloud Monitoring to send an email alert when CPU exceeds 80% so the team can manually scale.

Question 6

A digital media company hosts video content globally. They want to reduce origin server load and deliver content faster to viewers worldwide. Their current architecture routes all viewer requests directly to the origin servers in `us-central1`, causing high latency for viewers in Asia and Europe. Which Google Cloud networking capability addresses this?

Accepted Answer

Enable Cloud CDN to cache video content at Google's global edge PoPs, serving viewers from the nearest location.. Cloud CDN uses Google's global edge Points of Presence (PoPs) to cache video content closer to viewers, reducing latency and offloading origin servers. When a viewer requests content, Cloud CDN serves it from the nearest edge cache if available, avoiding a direct trip to the origin in us-central1. This directly addresses the high latency for viewers in Asia and Europe without requiring server replication or bandwidth increases.

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Deploy identical origin servers in every Google Cloud region globally.

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Use Cloud VPN to route viewer traffic through a direct tunnel to the origin servers.

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Increase the origin servers' network bandwidth to handle more simultaneous viewer connections.

Question 7

Which Google Cloud service provides a centralized view of an application's performance metrics, logs, and traces — enabling teams to monitor system health, set up alerts, and diagnose issues from a single platform?

Accepted Answer

Cloud Monitoring (part of Google Cloud's operations suite). Cloud Monitoring (part of Google Cloud's operations suite) is the correct answer because it provides a unified platform for collecting and visualizing metrics, logs, and traces from applications and infrastructure. It enables teams to set up alerting policies, create dashboards, and diagnose performance issues using a single interface, integrating with services like Cloud Logging and Cloud Trace for end-to-end observability.

Answer

Cloud Security Command Center

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BigQuery

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Cloud Asset Inventory

Question 8

A company runs a mission-critical application that must be available 24/7. They want to ensure that if a Google Cloud region becomes unavailable (e.g., due to a natural disaster), the application automatically continues to serve users from another region. Which architecture pattern achieves this?

Accepted Answer

Deploy the application in multiple regions with a Global Load Balancer for automated failover.. Option B is correct because deploying the application in multiple regions behind a Global Load Balancer (GLB) enables automated failover. The GLB uses health checks to detect regional failures and routes traffic only to healthy backends, ensuring continuous availability even if an entire region goes down. This aligns with the requirement for a multi-region active-passive or active-active architecture for disaster recovery.

Answer

Deploy in a single region with a Managed Instance Group using 3 availability zones.

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Enable Cloud Armor on the load balancer to protect against regional failures.

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Use Cloud Storage multi-region buckets for application data.

Question 9

A company currently spends $200,000 annually on data center costs (hardware, power, cooling, staff). After migrating to Google Cloud, their cloud bill is $120,000 annually, but they also save $50,000 in data center costs they no longer pay. What is their net annual savings from the migration?

Accepted Answer

$80,000 annual savings ($200,000 previous cost minus $120,000 cloud cost). Option B is correct because the net annual savings are calculated as the difference between the previous total cost ($200,000) and the new total cost after migration. The new total cost is the cloud bill ($120,000) plus any remaining data center costs. Since the company saves $50,000 in data center costs they no longer pay, the remaining data center costs are $200,000 - $50,000 = $150,000. However, the question states they 'save $50,000 in data center costs they no longer pay,' meaning those costs are eliminated entirely, so the new total cost is just the cloud bill of $120,000. Thus, savings = $200,000 - $120,000 = $80,000.

Answer

$30,000 (cloud cost increase of $120K minus the $50K DC savings)

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$50,000 (only the data center cost savings count)

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$120,000 (the entire cloud bill is savings)

Question 10

A company's application is composed of 15 microservices. When a performance issue occurs, the team struggles to determine which service is causing latency since request traces span multiple services. Which Google Cloud service helps identify which specific service in a microservices chain is causing slowdowns?

Accepted Answer

Cloud Trace — captures distributed request traces showing end-to-end latency across all microservices.. Cloud Trace is designed specifically for distributed tracing in microservices architectures. It captures end-to-end latency data for each request as it traverses multiple services, allowing you to pinpoint which service in the chain is introducing the most delay. This directly addresses the problem of identifying the specific service causing slowdowns in a 15-service application.

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Cloud Logging — search logs for error messages across all 15 services.

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Cloud Monitoring dashboards — create per-service CPU utilization graphs.

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Security Command Center — scan for misconfigurations causing performance issues.

Question 11

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.. Option B is correct because 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.

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

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

Question 12

After a major production outage, the engineering team conducts a review of what happened, why it happened, and how to prevent it in the future. This document is shared with all engineering teams. What is this practice called, and why does Google's SRE culture emphasize it?

Accepted Answer

Blameless postmortem — documenting the incident, root causes, and preventive actions to drive systemic learning without individual blame.. Option B is correct because a blameless postmortem is a core SRE practice that focuses on documenting incidents, root causes, and preventive actions without assigning individual blame. Google's SRE culture emphasizes this to foster psychological safety, enabling teams to openly share failures and drive systemic improvements, which is essential for maintaining high reliability in large-scale distributed systems.

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Performance review — identifying which engineers caused the outage for disciplinary action.

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Capacity planning review — ensuring enough servers are provisioned to prevent future outages.

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Change advisory board (CAB) review — approving that the outage fix is safe to deploy.

Question 13

A company running critical applications on Google Cloud wants access to technical support with a response time under 1 hour for critical issues and a dedicated Technical Account Manager (TAM). Which Google Cloud support tier should they purchase?

Accepted Answer

Premium support. Premium support is the only Google Cloud tier that includes a dedicated Technical Account Manager (TAM) and a response time under 1 hour for critical (P1) issues. Basic and Standard support offer slower SLAs and no TAM, while Enhanced support is not a valid Google Cloud tier.

Answer

Basic support

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Standard support

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Enhanced support

Question 14

A company wants to optimize their Google Cloud spending. They have baseline compute workloads that run continuously 24/7 for at least one year. Which pricing option provides the greatest savings for these stable, long-running workloads?

Accepted Answer

Committed Use Discounts (CUDs) — 1-year or 3-year commitment for up to 55% savings.. Committed Use Discounts (CUDs) are ideal for stable, long-running workloads because they offer significant savings (up to 55% for 1-year or 3-year commitments) in exchange for a predictable resource usage commitment. Since the workloads run continuously 24/7 for at least one year, a 1-year CUD directly matches this usage pattern and provides the greatest savings among the listed options for such non-preemptible, always-on VMs.

Answer

Spot VMs — up to 91% savings over on-demand pricing.

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On-demand pricing — pay per minute with no commitment.

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Sustained Use Discounts — automatically applied to all running VMs.

Question 15

A company has multiple teams deploying to Google Cloud and wants to allocate cloud costs by team. Each team should see only their own costs and be accountable for their spending. Which Google Cloud feature enables this cost allocation and visibility?

Accepted Answer

Use separate projects per team within a folder structure, with resource labels for sub-team cost attribution.. Option B is correct because Google Cloud's resource hierarchy allows you to create separate projects per team within a folder structure, and resource labels provide granular cost attribution for sub-teams or environments. This enables each team to see only their own costs via billing export and cost breakdowns in the Cloud Billing console, ensuring accountability without manual splitting.

Answer

Create one large project for all teams and split the bill manually at month-end.

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Purchase dedicated hardware for each team so costs are inherently separate.

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Use Cloud Identity to create separate accounts for each team and bill separately.