Cloud Digital Leader Scaling with Google Cloud operations Practice Test 6 — 15 Questions

Question 1

A company is migrating to Google Cloud and wants to reduce operational overhead for managing their infrastructure. Which Google Cloud service allows them to define infrastructure as code and automate provisioning?

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

Accepted Answer

Cloud Deployment Manager. Cloud Deployment Manager is the correct answer because it is a Google Cloud service that allows you to define your infrastructure as code using declarative templates (in YAML, Python, or Jinja2). It automates the provisioning and management of Google Cloud resources, reducing manual operational overhead by enabling repeatable, version-controlled deployments.

Answer

Google Cloud SDK

Answer

Cloud Console

Answer

Cloud Shell

Question 2

An organization has multiple projects and wants to aggregate logs from all projects into a single bucket for long-term retention and compliance. What should they do?

Accepted Answer

Use log sinks to route logs to a Cloud Storage bucket in a central project. Log sinks in Cloud Logging can route logs from multiple source projects to a centralized Cloud Storage bucket in a separate project. This meets the requirement for long-term retention and compliance, as Cloud Storage provides durable, cost-effective archival storage with lifecycle management policies.

Answer

Use log sinks to route logs to a BigQuery dataset

Answer

Enable VPC Flow Logs

Answer

Use Cloud Logging's aggregation view

Question 3

A developer is troubleshooting a slow response from a Cloud Run service. Which Google Cloud service can they use to trace requests across microservices?

Accepted Answer

Cloud Trace. Cloud Trace is the correct service because it is specifically designed for distributed tracing, collecting latency data from applications and displaying it in a trace timeline. It can trace requests as they propagate across multiple microservices, including Cloud Run services, by using trace context propagation headers (e.g., `X-Cloud-Trace-Context`). This allows the developer to identify bottlenecks and slow components in a request path.

Answer

Cloud Profiler

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Cloud Logging

Answer

Cloud Debugger

Question 4

A company uses Cloud Functions and notices that some functions are taking longer than expected. They want to identify which functions have the highest latency. What should they use?

Accepted Answer

Cloud Monitoring metrics. Cloud Monitoring metrics, specifically the 'execution_time' metric for Cloud Functions, provide the precise latency data needed to identify functions with the highest execution duration. Unlike logs or error reports, metrics are designed for numerical aggregation and can be used to create dashboards or alerts that rank functions by their p50, p95, or p99 latency values.

Answer

Cloud Audit Logs

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Error Reporting

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Cloud Logging queries

Question 5

A company wants to automatically scale their Compute Engine managed instance group based on the number of requests per second. Which metric should they use?

Accepted Answer

custom metric from Cloud Monitoring. The company needs to scale based on requests per second, which is a custom application-level metric. Cloud Monitoring allows you to create custom metrics from your application, and managed instance groups can use these custom metrics for autoscaling, enabling precise scaling based on actual request throughput rather than proxy indicators.

Answer

CPU utilization

Answer

HTTP load balancing serving capacity

Answer

Instance group size

Question 6

A company uses Cloud Monitoring to collect metrics from their applications running on Google Kubernetes Engine (GKE). They want to create custom dashboards and set up alerting policies. Which THREE capabilities are available in Cloud Monitoring? (Choose THREE.)

Accepted Answer

Define custom metrics via the Monitoring API. The Cloud Monitoring API allows you to define and write custom metrics, which can then be used in dashboards and alerting policies. This is essential for capturing application-specific data that is not automatically collected by the default GKE integration, such as business KPIs or custom performance counters.

Answer

Query logs using Logging Query Language

Answer

Automatically remediate incidents with Cloud Functions

Question 7

Which THREE of the following are best practices for managing operations in Google Cloud? (Choose THREE.)

Accepted Answer

Set up budget alerts to monitor costs. Setting up budget alerts in Google Cloud allows you to monitor costs proactively by triggering notifications when spending exceeds defined thresholds. This is a fundamental operational best practice to avoid unexpected bills and maintain financial control over your cloud resources.

Answer

Use Cloud Logging to store all logs indefinitely to ensure compliance

Answer

Use a single project for all workloads to simplify management

Question 8

Refer to the exhibit. The autoscaler is configured to maintain a target CPU utilization of 0.6. Currently the group has 10 instances, but the autoscaler is not scaling up even though CPU utilization is above 0.8. What is the most likely reason?

Accepted Answer

The maximum number of instances is set to 10. The autoscaler is configured to maintain a target CPU utilization of 0.6, but the current CPU utilization is above 0.8. Despite this, the autoscaler is not scaling up. The most likely reason is that the maximum number of instances is set to 10, and the group has already reached that limit. In Google Cloud, the autoscaler will not create new instances beyond the configured maximum, even if the target utilization is exceeded.

Answer

The autoscaler is disabled

Answer

The instance template is misconfigured

Answer

The autoscaler cooldown period is preventing new instances

Question 9

Refer to the exhibit. A DevOps engineer notices that the alert fires even when there is only a single 5-second spike of errors that lasts for one minute. What is the most likely cause?

Accepted Answer

The trigger count is set to 1, so a single minute of high rate fires the alert. The correct answer is A: the trigger count is set to 1, so a single minute of high rate fires the alert. In Cloud Monitoring alerting policies, the trigger count specifies how many consecutive alignment periods must violate the condition before the alert fires; with a count of 1, even one 60-second window containing a brief 5-second error spike is enough to trigger the alert. This matches the scenario where a single short spike lasting one minute causes the alert to fire. Option B is wrong because a 60s alignment period is not inherently too short and would not by itself cause firing on one spike. Option C is wrong because the threshold value of 5 relates to the metric condition, not the number of periods required to fire. Option D is wrong because a trigger count of 2 would require two consecutive violating periods, which would actually suppress firing on a single one-minute spike.

Answer

The alignment period is too short (60s)

Answer

The threshold value (5) is too low

Answer

The trigger count is set to 2, so two consecutive periods are needed

Question 10

Refer to the exhibit. A DevOps engineer wants to create a chart showing the rate of items sold per second over time. What is a limitation of this metric for that purpose?

Accepted Answer

The metric kind is GAUGE, so it cannot be used to calculate rate. A GAUGE metric type represents a point-in-time value (e.g., current number of items), not a cumulative counter. To calculate a rate (items per second), you need a CUMULATIVE counter metric that monotonically increases, allowing Cloud Monitoring to compute the derivative over time. GAUGE metrics lack the necessary monotonicity and cumulative semantics, so they cannot be used to derive a meaningful rate of change.

Answer

The interval should include a startTime

Answer

The metric has no labels to filter

Answer

The value should be DOUBLE instead of INT64

Question 11

A company runs a web application on Compute Engine. During seasonal sales, traffic spikes unpredictably. The operations team wants to ensure the application scales automatically without manual intervention while minimizing cost. Which solution should they implement?

Accepted Answer

Use a managed instance group with autoscaling based on CPU utilization.. A managed instance group (MIG) with autoscaling based on CPU utilization is the correct solution because it automatically adjusts the number of VM instances in response to real-time traffic spikes, ensuring the application scales out during high demand and scales in during low demand. This eliminates manual intervention and optimizes cost by only running the necessary number of instances based on a target CPU utilization threshold (e.g., 60-80%).

Answer

Create a managed instance group with a fixed number of instances.

Answer

Use an unmanaged instance group and manually add instances.

Answer

Use a single large VM with vertical scaling.

Question 12

A global gaming company uses Cloud Spanner for their leaderboard. They notice that write latency spikes during peak hours. The database is currently deployed in a single region. Which scaling strategy should they implement to reduce write latency globally?

Accepted Answer

Use Cloud Spanner multi-region configuration.. Cloud Spanner's multi-region configuration is designed to reduce write latency for globally distributed users by placing write-capable replicas in multiple geographic regions. This allows writes to be committed at the nearest replica, leveraging Spanner's TrueTime and Paxos-based replication to maintain strong consistency across regions. A single-region deployment forces all writes to a single location, causing high latency for distant clients during peak hours.

Answer

Implement application-level caching with Memorystore.

Answer

Change to Cloud Bigtable for higher throughput.

Answer

Add more nodes to the existing Spanner instance.

Question 13

A startup is building a read-heavy mobile backend. They want a database that can scale out reads without downtime. Which database service should they choose?

Accepted Answer

Cloud SQL with read replicas.. Cloud SQL with read replicas is the correct choice because it allows you to offload read traffic to one or more read replicas, scaling out reads without downtime. Read replicas are asynchronous replicas of the primary instance, and you can promote them to standalone instances if needed, making this ideal for a read-heavy mobile backend that requires high availability.

Answer

Cloud Firestore.

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Cloud Spanner.

Answer

Cloud Bigtable.

Question 14

You are monitoring Compute Engine instances with Cloud Monitoring. You notice that autoscaling is not triggering even though CPU utilization is above 80% for several minutes. The managed instance group has autoscaling based on CPU utilization with a target of 0.8. What is the most likely cause?

Accepted Answer

The maximum number of instances is already reached.. The most likely cause is that the managed instance group has already reached its configured maximum number of instances. When the maximum instance count is hit, the autoscaler cannot add more instances even if CPU utilization exceeds the target of 0.8 (80%). This is a common boundary condition in autoscaling logic where the scaling policy is overridden by the hard limit.

Answer

The autoscaler is disabled.

Answer

The minimum number of instances is set too high.

Answer

The cool-down period is too long.

Question 15

A company runs batch processing jobs using preemptible VMs to reduce costs. They need to ensure these jobs can scale out significantly during peak hours. Which Compute Engine pricing model should they combine with autoscaling to optimize cost for these workloads?

Accepted Answer

Preemptible VMs with no further discounts.. Preemptible VMs already provide significant cost savings (up to 60-91% off standard VMs) and are ideal for fault-tolerant batch jobs. Combining them with autoscaling allows scaling during peak hours without any additional discounts. Sustained use discounts do not apply to preemptible VMs, and committed use discounts require upfront commitments unsuitable for variable workloads. Sole-tenant nodes are designed for dedicated hardware, not cost optimization. Therefore, using preemptible VMs with no further discounts is the optimal cost-effective solution.

Answer

Sole-tenant nodes.

Answer

Sustained use discounts.

Answer

Committed use discounts.