Cloud Digital Leader Scaling with Google Cloud operations Practice Test 5 — 15 Questions

Question 1

An operations team is performing a post-incident review after a production outage. The team lead insists that the review must follow a 'blameless postmortem' approach. What does this mean, and why is it important for organizational learning?

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

Accepted Answer

A blameless postmortem focuses on systemic root causes and improvement opportunities rather than individual fault — creating psychological safety for honest disclosure and leading to more effective prevention of future incidents. A blameless postmortem in Google Cloud operations (and SRE practice) shifts focus from individual human error to systemic root causes, such as misconfigured alerting thresholds, insufficient canary deployments, or gaps in monitoring coverage. This approach fosters psychological safety, encouraging engineers to report all contributing factors without fear of reprisal, which leads to more effective incident prevention and aligns with Google's Site Reliability Engineering (SRE) principles of learning from failures.

Answer

A blameless postmortem assigns full responsibility to the automated systems involved, not to human engineers, which protects the team from accountability

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A blameless postmortem means the incident is not formally documented to protect employees' privacy and career records

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A blameless postmortem can only be conducted by senior management who have authority to make systemic improvements

Question 2

A company's SRE team sets an SLO of 99.5% monthly availability for a non-critical internal tool. A business stakeholder argues the target should be 99.99%. The SRE team pushes back. Which SRE argument best supports keeping the 99.5% target?

Accepted Answer

For a non-critical internal tool, 99.99% reliability requires disproportionate engineering investment (redundancy, 24/7 on-call, chaos testing) compared to its business value; 99.5% matches the actual reliability need while preserving engineering capacity for higher-value work. Ly applies the SRE principle of aligning SLOs with business value. For a non-critical internal tool, the cost of achieving 99.99% availability—including redundant infrastructure, 24/7 on-call rotations, and chaos engineering—far exceeds the marginal benefit over 99.5%. This preserves engineering capacity for higher-value work, which is a core tenet of Google's SRE approach to error budgets and cost-benefit analysis.

Answer

Higher SLOs are always more expensive to achieve and the company cannot afford cloud infrastructure that provides 99.99% availability

Answer

Google Cloud cannot provide 99.99% availability for any service, so the SLO must be kept lower

Answer

The team should set 99.5% now and plan to increase it to 99.99% next quarter when the tool becomes more popular

Question 3

A company has a Google Cloud environment with 50 projects and 200 engineers. The security team wants to ensure that a new security policy — requiring all Cloud Storage buckets to have uniform bucket-level access enabled — applies to all existing and future buckets across all projects. Which approach scales to the entire organization?

Accepted Answer

Apply an Organization Policy constraint ('storage.uniformBucketLevelAccess') at the organization level to enforce the setting automatically across all current and future projects and buckets. Organization Policy constraints, such as `storage.uniformBucketLevelAccess`, are enforced at the organization level and automatically apply to all existing and future projects and resources within the organization. This ensures uniform compliance without manual intervention, scaling seamlessly across 50 projects and 200 engineers.

Answer

Send an email to all 200 engineers explaining the policy and asking them to manually enable uniform bucket-level access on their buckets

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Create a Cloud Function that checks bucket configurations hourly and enables uniform access on non-compliant buckets

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Grant the security team Owner access to all 50 projects so they can manually enforce the policy in each project

Question 4

A company uses committed use discounts (CUDs) for its production workload baseline. An engineer proposes also using sustained use discounts (SUDs) for the same VMs. Why is this incorrect?

Accepted Answer

CUDs and SUDs are mutually exclusive: VMs already covered by committed use discounts don't accrue sustained use discounts — you receive only the CUD, not both. Committed use discounts (CUDs) and sustained use discounts (SUDs) are mutually exclusive on the same VM. When a VM is covered by a CUD, it does not accrue SUDs; only the CUD discount is applied. This prevents double-discounting and ensures billing consistency.

Answer

CUDs and SUDs can be combined on the same VMs — applying both gives the maximum possible discount

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SUDs cannot be applied to production workloads — they are only available for development environments

Answer

Applying both CUDs and SUDs creates a billing conflict that could result in Google charging the company more than on-demand pricing

Question 5

An SRE team is practicing 'chaos engineering' by simulating a zone-level failure in their staging environment. They find that their application does not automatically recover — traffic is not redirected and the service remains down. What architectural component is most likely missing?

Accepted Answer

A load balancer with health checks across multiple zones is most likely missing — without it, there is no mechanism to detect the zone failure and automatically redirect traffic to healthy instances in surviving zones. In a zone-level failure, traffic cannot be redirected to healthy instances in surviving zones without a load balancer that performs health checks across multiple zones. Google Cloud's external or internal load balancers (e.g., HTTP(S) Load Balancer, TCP/UDP Network Load Balancer) use health checks to detect unhealthy instances and automatically route traffic only to healthy backends. Without this component, the application has no mechanism to detect the zone failure and reroute traffic, leaving the service down.

Answer

The application needs more replicas in the failing zone to survive the failure

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The application needs a larger machine type to handle the full traffic load without the failed zone's capacity

Answer

Cloud Monitoring alerts need to be configured to notify the team when a zone fails, enabling manual traffic redirection

Question 6

A company's cloud operations team is implementing a tagging strategy for cost allocation. They want to ensure that the 'cost-center' label is present on every Compute Engine VM and Cloud Storage bucket created in their Google Cloud organization. Currently, some resources are created without this label. Which combination of controls best enforces and remediates this requirement?

Accepted Answer

Organization Policy custom constraint to prevent creation of resources without the 'cost-center' label (preventive), plus Cloud Asset Inventory to identify existing unlabeled resources for remediation (detective). A preventive control (org policy custom constraint requiring the label) stops future non-compliant resources. A detective/corrective control (Cloud Asset Inventory + Cloud Functions or Security Command Center) finds and remediates existing unlabeled resources. Both are needed for comprehensive enforcement.

Answer

Only organization policy — once new resources are blocked, existing unlabeled resources don't matter

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Only Cloud Asset Inventory monitoring — alerting on unlabeled resources is sufficient without preventing their creation

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Grant all engineers the 'Labels Admin' role to encourage them to add labels voluntarily

Question 7

A company's production database is running on a Compute Engine VM with a 500 GB Persistent Disk. The operations team wants to create a backup they can restore from in case of data corruption or accidental deletion. Which Google Cloud capability provides point-in-time backup for Persistent Disks?

Accepted Answer

Persistent Disk Snapshots, which capture the disk state at a point in time and enable restoration or creation of new disks from that snapshot. Persistent Disk Snapshots are the correct Google Cloud feature for creating point-in-time backups of Persistent Disks. They capture the disk's data and configuration at a specific moment, allowing you to restore the disk or create new disks from that snapshot. This is the native, recommended method for backup and disaster recovery of Compute Engine VM disks.

Answer

Cloud Storage bucket replication, by continuously copying the database files to a storage bucket

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Cloud SQL automated backups, which protect databases running on Compute Engine VMs

Answer

VM live migration, which moves the running VM between physical hosts, automatically creating a backup in the process

Question 8

A company's cloud cost has grown significantly. A FinOps analysis reveals the largest waste category is idle Cloud SQL instances — 12 database instances that were provisioned for projects that have since ended, but were never deleted. What process failure most directly caused this waste?

Accepted Answer

The absence of a resource decommissioning process: when projects end, there is no formal step to identify and delete associated cloud resources, allowing idle infrastructure to persist and accrue costs indefinitely. The root cause is the lack of a formal resource decommissioning process. When projects end, there is no automated or manual step to identify and delete associated Cloud SQL instances, so idle databases continue to incur costs. In Google Cloud, Cloud SQL instances do not auto-delete; they persist until explicitly removed, making a decommissioning workflow essential to prevent waste.

Answer

The company should have used a cheaper database service instead of Cloud SQL

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Cloud SQL pricing is too high compared to on-premises databases, making any unused capacity expensive

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The database administrators forgot to enable automatic deletion for idle Cloud SQL instances

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.

Answer

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.

Answer

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.

Answer

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

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.

Answer

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

Answer

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

Answer

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

Question 11

Match each Google Cloud security concept to its description.

Accepted Answer

Cloud IAM: Unified access control for Google Cloud resources. The correct matches are Cloud IAM (access control), Cloud KMS (key management), Cloud Security Command Center (threat detection), and Cloud DLP (data loss prevention). Common confusions include mixing up IAM with Security Command Center or KMS with Cloud Armor.

Answer

Cloud IAM: Security monitoring and threat detection

Answer

Cloud KMS: Web application firewall and DDoS protection

Question 12

Match each Google Cloud serverless compute option to its characteristic.

Accepted Answer

Cloud Functions: Executes code in response to events, scaling to zero when idle.. The correct matches are: Cloud Functions for event-driven execution, Cloud Run for containerized HTTP services, and App Engine for managed web applications. Common confusions involve swapping the event-driven nature of Cloud Functions with the container-based approach of Cloud Run, or pairing App Engine with event-driven triggers instead of web app hosting.

Answer

Cloud Functions: Runs containerized applications in a managed environment.

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Cloud Run: Fully managed platform that supports multiple programming languages for web apps.

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App Engine: Event-driven, short-lived execution of code in response to triggers.

Question 13

A company runs a web application on Compute Engine instances behind a managed instance group with autoscaling based on CPU utilization. After a marketing campaign, traffic spikes and the autoscaler adds instances quickly, but the application becomes slow. What is the most likely cause?

Accepted Answer

Autoscaler uses CPU utilization but the application is memory-bound. The autoscaler adds instances based on CPU utilization, but if the application is memory-bound, adding more instances does not alleviate memory pressure. Each new instance still runs the same memory-intensive workload, so CPU may remain low while memory is exhausted, causing slowdowns. The autoscaler fails to address the actual bottleneck, leading to poor performance despite scaling out.

Answer

Instances are in different zones causing inter-zone latency

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Autoscaling cooldown period is too short

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Health check interval is too long

Question 14

A developer needs to debug a production issue by analyzing logs from multiple microservices. Which Google Cloud service should they use to filter and search logs in real time?

Accepted Answer

Cloud Logging. Cloud Logging (formerly Stackdriver Logging) is the correct service because it provides a centralized log management system that can ingest logs from multiple microservices, filter them using advanced queries, and search them in real time. Its Logs Explorer interface supports custom filters, labels, and timestamps, enabling developers to pinpoint production issues across distributed services without delay.

Answer

Cloud Monitoring

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Error Reporting

Answer

Cloud Debugger

Question 15

A company wants to implement SLOs for their API service. They need to measure the proportion of successful requests over a 30-day window. Which metric should they use?

Accepted Answer

SLI = good events / total events. An SLI (Service Level Indicator) is defined as the ratio of good events to total events, which directly measures the proportion of successful requests over a 30-day window. This aligns with the requirement to track request success rate, not just system uptime. In Google Cloud operations, SLOs are built on SLIs that count discrete events like HTTP 200 responses versus all requests.

Answer

availability (uptime)

Answer

latency at 99th percentile

Answer

requests/success