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Managing Google Cloud costs practice questions

Practise Google Professional Cloud DevOps Engineer Managing Google Cloud costs practice questions — original exam-style scenarios with answer choices, explanations, and analysis of common mistakes.

Courseiva uses original exam-style practice questions designed for learning and revision. The goal is to understand the concepts, recognise exam patterns, and improve through explanations — not memorise copied exam dumps.

Reviewed byJohnson Ajibi· MSc IT Security

20 questionsDomain: Managing Google Cloud costs

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What the exam tests

What to know about Managing Google Cloud costs

Cloud concepts questions usually test the service model (IaaS/PaaS/SaaS) and deployment model (public/private/hybrid/community) appropriate for a given scenario.

IaaS, PaaS and SaaS responsibilities and examples.

Public, private, hybrid and community cloud deployment models.

On-premises vs cloud trade-offs: cost, control, scalability.

How cloud connectivity options (VPN, Direct Connect, ExpressRoute) work.

Watch out for

Common Managing Google Cloud costs exam traps

▸IaaS gives you infrastructure control; SaaS gives you only the application.
▸Hybrid cloud combines on-premises and public cloud — not two public clouds.
▸Cloud does not automatically mean cheaper or more secure.
▸Management responsibility shifts with each service model (IaaS → PaaS → SaaS).

Practice set

Managing Google Cloud costs questions

20 questions · select your answer, then reveal the explanation

Question 1mediummultiple choice

Read the full Managing Cloud costs explanation →

A company is using Google Kubernetes Engine (GKE) with multiple node pools. They notice that their monthly costs are higher than expected. Upon review, they find that several preemptible VMs are being recreated frequently, leading to sustained usage costs. What is the most cost-effective solution to reduce costs?

Trap 1: Purchase committed use discounts for the preemptible VMs.

Committed use discounts are not available for preemptible VMs.

Trap 2: Increase the number of preemptible VMs to spread the workload.

Adding more preemptible VMs would increase costs, not reduce them.

Trap 3: Enable sustained use discounts for the existing VMs.

Sustained use discounts are automatically applied and don't require enabling.

Study all Managing Google Cloud costs common traps →

A
Purchase committed use discounts for the preemptible VMs.
Why wrong: Committed use discounts are not available for preemptible VMs.
B
Increase the number of preemptible VMs to spread the workload.
Why wrong: Adding more preemptible VMs would increase costs, not reduce them.
C
Enable sustained use discounts for the existing VMs.
Why wrong: Sustained use discounts are automatically applied and don't require enabling.
D
Migrate to Spot VMs, which have a lower price and no maximum runtime.
Spot VMs are the recommended replacement for preemptible VMs and offer lower costs without the 24-hour limit.

Full breakdown with real-world context →

Question 2hardmultiple choice

Read the full Managing Cloud costs explanation →

A company runs a batch processing workload on Compute Engine that runs for 3 hours every night. They want to minimize costs while ensuring the job completes reliably. Which recommendation should they follow?

Trap 1: Use sole-tenant nodes to isolate the workload.

Sole-tenant nodes are for compliance or licensing, not cost savings.

Trap 2: Use standard (on-demand) VMs and enable sustained use discounts.

Sustained use discounts require running for a month; nightly 3-hour jobs don't benefit much.

Trap 3: Purchase 1-year committed use discounts for the VMs.

Committed use discounts require a 1-year commitment and are not cost-effective for short nightly jobs.

Study all Managing Google Cloud costs common traps →

A
Use sole-tenant nodes to isolate the workload.
Why wrong: Sole-tenant nodes are for compliance or licensing, not cost savings.
B
Use standard (on-demand) VMs and enable sustained use discounts.
Why wrong: Sustained use discounts require running for a month; nightly 3-hour jobs don't benefit much.
C
Use preemptible VMs and design the job to handle interruptions gracefully.
Preemptible VMs are up to 60% cheaper and suitable for fault-tolerant batch jobs.
D
Purchase 1-year committed use discounts for the VMs.
Why wrong: Committed use discounts require a 1-year commitment and are not cost-effective for short nightly jobs.

Full breakdown with real-world context →

Question 3easymultiple choice

Read the full Managing Cloud costs explanation →

A company uses Cloud Storage to store archival data. They want to minimize storage costs while maintaining availability. Which storage class should they use?

Trap 1: Nearline storage class.

Nearline is for data accessed less than once a month, but Archive is cheaper.

Trap 2: Standard storage class.

Standard is for frequently accessed data, not cost-efficient for archival.

Trap 3: Coldline storage class.

Coldline is for data accessed less than once a quarter, but Archive is cheaper.

Study all Managing Google Cloud costs common traps →

A
Nearline storage class.
Why wrong: Nearline is for data accessed less than once a month, but Archive is cheaper.
B
Standard storage class.
Why wrong: Standard is for frequently accessed data, not cost-efficient for archival.
C
Archive storage class.
Archive is the lowest-cost storage class for long-term archival data.
D
Coldline storage class.
Why wrong: Coldline is for data accessed less than once a quarter, but Archive is cheaper.

Full breakdown with real-world context →

Question 4mediummultiple choice

Read the full Managing Cloud costs explanation →

A company is using BigQuery for analytics and wants to control costs. They have many queries that scan large amounts of data. Which approach is most effective in reducing query costs?

Trap 1: Switch to flat-rate pricing to cap costs.

Flat-rate pricing caps total cost but does not reduce per-query cost; it may be more expensive for low usage.

Trap 2: Reserve BigQuery slots for dedicated capacity.

Reserving slots is for dedicated capacity, not cost reduction; it may increase costs.

Trap 3: Use clustering to organize data within partitions.

Clustering improves performance but does not directly reduce the amount of data scanned.

Study all Managing Google Cloud costs common traps →

A
Switch to flat-rate pricing to cap costs.
Why wrong: Flat-rate pricing caps total cost but does not reduce per-query cost; it may be more expensive for low usage.
B
Partition tables by date and use partition pruning in queries.
Partitioning limits the data scanned, reducing query costs.
C
Reserve BigQuery slots for dedicated capacity.
Why wrong: Reserving slots is for dedicated capacity, not cost reduction; it may increase costs.
D
Use clustering to organize data within partitions.
Why wrong: Clustering improves performance but does not directly reduce the amount of data scanned.

Full breakdown with real-world context →

Question 5hardmultiple choice

Read the full Managing Cloud costs explanation →

A company uses Cloud CDN to deliver content globally. They notice increasing egress costs. Which change will most effectively reduce egress costs?

Trap 1: Switch to a premium tier network for lower egress rates.

Premium tier has higher per-GB egress costs than standard tier.

Trap 2: Enable gzip compression for all responses.

Compression reduces data size but Cloud CDN charges per byte after compression; still, egress costs are based on the compressed size, so savings are limited.

Trap 3: Use Cloud Armor to block malicious traffic.

Cloud Armor protects against attacks but does not reduce legitimate egress costs.

Study all Managing Google Cloud costs common traps →

A
Switch to a premium tier network for lower egress rates.
Why wrong: Premium tier has higher per-GB egress costs than standard tier.
B
Enable gzip compression for all responses.
Why wrong: Compression reduces data size but Cloud CDN charges per byte after compression; still, egress costs are based on the compressed size, so savings are limited.
C
Use Cloud Armor to block malicious traffic.
Why wrong: Cloud Armor protects against attacks but does not reduce legitimate egress costs.
D
Configure Cloud CDN to cache more content and increase cache hit ratio.
Higher cache hit ratio reduces the amount of data fetched from the origin, lowering egress costs.

Full breakdown with real-world context →

Question 6mediummulti select

Read the full Managing Cloud costs explanation →

A company is using Google Cloud and wants to monitor and control costs. Which TWO actions should they take? (Choose two.)

Trap 1: Disable all unnecessary APIs at the organization level.

Disabling APIs globally may affect other projects; better to manage per project.

Trap 2: Export billing data to BigQuery for detailed analysis.

Exporting to BigQuery is for analysis, not direct cost control.

Trap 3: Grant billing account access to all project owners.

Granting billing access to all owners increases risk of accidental spending.

Study all Managing Google Cloud costs common traps →

A
Set up budget alerts to notify when spending exceeds thresholds.
Budget alerts help monitor and control costs by providing notifications.
B
Use labels to categorize resources and track costs by team.
Labels enable cost allocation and reporting, helping control costs.
C
Disable all unnecessary APIs at the organization level.
Why wrong: Disabling APIs globally may affect other projects; better to manage per project.
D
Export billing data to BigQuery for detailed analysis.
Why wrong: Exporting to BigQuery is for analysis, not direct cost control.
E
Grant billing account access to all project owners.
Why wrong: Granting billing access to all owners increases risk of accidental spending.

Full breakdown with real-world context →

Question 7hardmulti select

Read the full Managing Cloud costs explanation →

A company runs a web application on Google Kubernetes Engine (GKE) with multiple services. They want to reduce costs without impacting performance. Which THREE actions should they take? (Choose three.)

Trap 1: Enable cluster autoscaling and manually scale nodes based on peak…

Manual scaling is not efficient; node auto-provisioning is better for cost.

Trap 2: Deploy a service mesh like Istio to optimize traffic routing.

Service mesh adds overhead and cost, not reducing costs.

Study all Managing Google Cloud costs common traps →

A
Enable cluster autoscaling and manually scale nodes based on peak load.
Why wrong: Manual scaling is not efficient; node auto-provisioning is better for cost.
B
Deploy a service mesh like Istio to optimize traffic routing.
Why wrong: Service mesh adds overhead and cost, not reducing costs.
C
Enable node auto-provisioning to automatically adjust node pools.
Node auto-provisioning ensures the cluster uses the right size and type of nodes.
D
Right-size CPU and memory requests and limits for each service.
Right-sizing avoids over-provisioning and reduces node resource waste.
E
Use preemptible VMs for stateless, fault-tolerant workloads.
Preemptible VMs are cheaper and suitable for fault-tolerant stateless services.

Full breakdown with real-world context →

Question 8hardmultiple choice

Read the full Managing Cloud costs explanation →

You are a DevOps engineer at a large e-commerce company that runs its production workloads on Google Kubernetes Engine (GKE) in the us-central1 region. The cluster has 500 nodes, each with 8 vCPUs and 32 GB of memory, and uses preemptible VMs for cost savings. Over the past month, the monthly GKE cost has increased by 30% unexpectedly. Upon reviewing the billing reports, you notice a significant spike in Compute Engine costs, specifically for 'Sustained Use Discount' line items, but the total cost is higher than expected. You also observe that the cluster's node utilization is inconsistent, with some nodes running at 90% CPU and memory while others are below 20%. Your team has been deploying stateless microservices and using Cluster Autoscaler with default settings. The application traffic is variable but predictable, with peaks on weekends. You need to reduce the GKE costs without impacting performance. What should you do?

Trap 1: Increase the minimum number of nodes in the cluster to 300 and use…

Increasing minimum nodes and using larger machines increases costs and may lead to underutilization.

Trap 2: Switch the cluster to a single-zone configuration and reduce the…

Single-zone reduces availability and may cause downtime, and reducing nodes may not handle peak loads.

Trap 3: Reduce the number of preemptible VMs to 30% and use only on-demand…

Reducing preemptible VMs increases cost because on-demand VMs are more expensive.

Study all Managing Google Cloud costs common traps →

A
Enable node auto-provisioning and migrate baseline workloads to nodes covered by committed use discounts (1-year or 3-year).
Node auto-provisioning optimizes resource allocation based on pod requirements, and CUDs provide significant savings for stable workloads.
B
Increase the minimum number of nodes in the cluster to 300 and use a larger machine type to reduce the number of pods per node.
Why wrong: Increasing minimum nodes and using larger machines increases costs and may lead to underutilization.
C
Switch the cluster to a single-zone configuration and reduce the number of nodes to 200 to lower base costs.
Why wrong: Single-zone reduces availability and may cause downtime, and reducing nodes may not handle peak loads.
D
Reduce the number of preemptible VMs to 30% and use only on-demand VMs for the remaining nodes to improve reliability.
Why wrong: Reducing preemptible VMs increases cost because on-demand VMs are more expensive.

Full breakdown with real-world context →

Question 9hardmultiple choice

Read the full Managing Cloud costs explanation →

A company runs a critical application on Google Kubernetes Engine (GKE) with 3 nodes (e2-standard-4). To reduce costs, the team is considering right-sizing the nodes. The application is latency-sensitive and experiences periodic traffic spikes. What is the most cost-effective approach that maintains performance during spikes?

Trap 1: Use a single larger node (n2-standard-8) to reduce node count and…

This creates a single point of failure and may not handle spikes efficiently.

Trap 2: Switch to 3 n2-standard-2 nodes to reduce vCPU and memory, and rely…

This may cause resource contention during spikes as the smaller nodes have less capacity.

Trap 3: Keep current node size but use committed use discounts for 1 year…

Committed use discounts require upfront commitment and may not be optimal if right-sizing is possible.

Study all Managing Google Cloud costs common traps →

A
Use a single larger node (n2-standard-8) to reduce node count and network overhead.
Why wrong: This creates a single point of failure and may not handle spikes efficiently.
B
Switch to 3 n2-standard-2 nodes to reduce vCPU and memory, and rely on horizontal pod autoscaling.
Why wrong: This may cause resource contention during spikes as the smaller nodes have less capacity.
C
Create a node pool with smaller nodes (e2-standard-2) using preemptible VMs and enable cluster autoscaler.
Preemptible VMs are cheaper, and autoscaler adds nodes during spikes, maintaining performance.
D
Keep current node size but use committed use discounts for 1 year to reduce per-hour cost.
Why wrong: Committed use discounts require upfront commitment and may not be optimal if right-sizing is possible.

Full breakdown with real-world context →

Question 10mediummulti select

Read the full Managing Cloud costs explanation →

A DevOps team is analyzing Google Cloud costs and notices that spending on BigQuery has increased significantly. They want to reduce costs without impacting ongoing analytical workloads. Which TWO actions should they take? (Choose two.)

Trap 1: Switch to on-demand pricing to pay only for queries run.

On-demand may be more expensive for high-volume workloads; flat-rate is better.

Trap 2: Enable column-level security to restrict access to sensitive data.

This is a security measure, not directly cost-saving.

Trap 3: Delete unused datasets to reduce storage costs.

Deleting datasets removes data and may impact analytics; better to archive old data.

Study all Managing Google Cloud costs common traps →

A
Switch to on-demand pricing to pay only for queries run.
Why wrong: On-demand may be more expensive for high-volume workloads; flat-rate is better.
B
Enable column-level security to restrict access to sensitive data.
Why wrong: This is a security measure, not directly cost-saving.
C
Set custom cost controls like query quotas and maximum bytes billed per query.
Limits prevent expensive queries from running unbounded.
D
Delete unused datasets to reduce storage costs.
Why wrong: Deleting datasets removes data and may impact analytics; better to archive old data.
E
Implement flat-rate pricing with reservations for consistent workloads.
Flat-rate pricing caps costs for predictable usage, avoiding per-query charges.

Full breakdown with real-world context →

Question 11easymultiple choice

Read the full Managing Cloud costs explanation →

Refer to the exhibit. The output shows a recommendation from the Cloud Cost Optimization recommender for an instance in us-central1-a. The instance is a production web server that consistently runs at 25% CPU utilization during peak hours. What should the DevOps engineer do to implement this recommendation with minimal risk?

Network Topology

Trap 1: Ignore the recommendation because the instance is production and…

The recommendation is based on low utilization, and a machine type change can be done with a brief restart.

Trap 2: Add a second n2-standard-4 instance behind a load balancer to…

This would increase cost, not reduce it.

Trap 3: Use a custom machine type with 4 vCPUs and 32 GB memory to ensure…

The recommendation is for n2-standard-4 (16 GB RAM), and over-provisioning RAM may not be needed.

Study all Managing Google Cloud costs common traps →

A
Stop the instance, change the machine type to n2-standard-4, and start it again.
This directly implements the recommendation with minimal risk.
B
Ignore the recommendation because the instance is production and any change might cause downtime.
Why wrong: The recommendation is based on low utilization, and a machine type change can be done with a brief restart.
C
Add a second n2-standard-4 instance behind a load balancer to distribute load.
Why wrong: This would increase cost, not reduce it.
D
Use a custom machine type with 4 vCPUs and 32 GB memory to ensure enough RAM.
Why wrong: The recommendation is for n2-standard-4 (16 GB RAM), and over-provisioning RAM may not be needed.

Full breakdown with real-world context →

Question 12mediumdrag order

Read the full Managing Cloud costs explanation →

Arrange the steps to troubleshoot a high latency issue on a Google Cloud HTTP(S) Load Balancer.

Drag steps to the numbered slots on the right, or tap a step then tap a slot.

Steps

Order

1Step 1

2Step 2

3Step 3

4Step 4

5Step 5

Question 13mediumdrag order

Read the full Managing Cloud costs explanation →

Order the steps to respond to a Google Cloud security incident involving a compromised service account key.

Drag steps to the numbered slots on the right, or tap a step then tap a slot.

Steps

Order

1Step 1

2Step 2

3Step 3

4Step 4

5Step 5

Question 14mediummatching

Read the full Managing Cloud costs explanation →

Match each SRE term to its description.

Drag a concept onto its matching description — or click a concept then click the description.

Concepts

Matches

Actual measured service performance

Target reliability level for a service

Contractual commitment to customers

Allowed downtime before SLO breach

Manual, repetitive operational work

Question 15mediummatching

Read the full Managing Cloud costs explanation →

Match each cost optimization practice to its description.

Drag a concept onto its matching description — or click a concept then click the description.

Concepts

Matches

Discount for 1- or 3-year resource commitment

Automatic discounts for running instances most of month

Short-lived, low-cost instances for batch jobs

Adjusting machine type to match workload needs

Notifications when spending exceeds thresholds

Question 16mediummultiple choice

Read the full Managing Cloud costs explanation →

A company uses Compute Engine with committed use discounts for 1-year. They need to reduce costs further. What should they do?

Trap 1: Use sustained use discounts instead.

Sustained use discounts apply automatically and cannot be used as a replacement for committed use discounts.

Trap 2: Use preemptible VMs for all workloads.

Preemptible VMs can be terminated at any time and are not suitable for all workloads.

Trap 3: Increase committed use discount term to 3 years.

Increasing commitment may provide higher discounts but requires longer commitment and may not address overprovisioning.

Study all Managing Google Cloud costs common traps →

A
Use sustained use discounts instead.
Why wrong: Sustained use discounts apply automatically and cannot be used as a replacement for committed use discounts.
B
Use preemptible VMs for all workloads.
Why wrong: Preemptible VMs can be terminated at any time and are not suitable for all workloads.
C
Rightsize their VMs based on recommender recommendations.
Rightsizing reduces resource usage, directly lowering costs.
D
Increase committed use discount term to 3 years.
Why wrong: Increasing commitment may provide higher discounts but requires longer commitment and may not address overprovisioning.

Full breakdown with real-world context →

Question 17easymultiple choice

Read the full Managing Cloud costs explanation →

A team wants to receive a notification when their monthly spending exceeds 80% of the budget. Which GCP feature should they configure?

Trap 1: Committed use discounts.

Committed use discounts provide discounts in exchange for commitments, not notifications.

Trap 2: Cloud Storage bucket for cost exports.

Exporting cost data to Cloud Storage enables analysis but does not automatically send notifications.

Trap 3: Cloud Monitoring cost insights dashboard.

Cost insights provide historical analysis, not real-time notifications.

Study all Managing Google Cloud costs common traps →

A
Committed use discounts.
Why wrong: Committed use discounts provide discounts in exchange for commitments, not notifications.
B
Budget alert with threshold rule at 0.8.
Budget alerts can be configured with threshold percentages to notify when spend reaches that level.
C
Cloud Storage bucket for cost exports.
Why wrong: Exporting cost data to Cloud Storage enables analysis but does not automatically send notifications.
D
Cloud Monitoring cost insights dashboard.
Why wrong: Cost insights provide historical analysis, not real-time notifications.

Full breakdown with real-world context →

Question 18hardmultiple choice

Read the full Managing Cloud costs explanation →

A company uses BigQuery for analytics with many queries scanning terabytes daily. They need to reduce query costs without reducing usage. What is the most effective strategy?

Trap 1: Reserve capacity in specific regions.

Reserving capacity changes pricing model but does not reduce data scanned.

Trap 2: Use flat-rate pricing with slots.

Flat-rate pricing provides predictable costs but does not reduce actual query data processing.

Trap 3: Use standard SQL instead of legacy SQL.

Query cost is based on data scanned, not SQL dialect.

Study all Managing Google Cloud costs common traps →

A
Reserve capacity in specific regions.
Why wrong: Reserving capacity changes pricing model but does not reduce data scanned.
B
Use flat-rate pricing with slots.
Why wrong: Flat-rate pricing provides predictable costs but does not reduce actual query data processing.
C
Partition and cluster tables.
Partitioning and clustering limit the data scanned per query, reducing cost.
D
Use standard SQL instead of legacy SQL.
Why wrong: Query cost is based on data scanned, not SQL dialect.

Full breakdown with real-world context →

Question 19easymultiple choice

Read the full Managing Cloud costs explanation →

A DevOps engineer notices that the monthly compute cost is higher than expected for a Kubernetes Engine cluster. They want to identify which namespaces or workloads are contributing most to the cost. What should they do?

Trap 1: Enable Logging for all containers and analyze logs.

Logs do not provide cost information.

Trap 2: Use Cloud Monitoring dashboards with Kubernetes metrics.

Cloud Monitoring shows resource usage, not cost allocation.

Trap 3: Add labels to nodes and use Cost Table reports.

Labels on nodes apply to the whole node, not per workload.

Study all Managing Google Cloud costs common traps →

A
Enable Logging for all containers and analyze logs.
Why wrong: Logs do not provide cost information.
B
Use Cloud Monitoring dashboards with Kubernetes metrics.
Why wrong: Cloud Monitoring shows resource usage, not cost allocation.
C
Add labels to nodes and use Cost Table reports.
Why wrong: Labels on nodes apply to the whole node, not per workload.
D
Enable GKE Usage Metering and export to BigQuery.
GKE Usage Metering provides cost attribution by namespace and workload.

Full breakdown with real-world context →

Question 20hardmultiple choice

Read the full Managing Cloud costs explanation →

A company uses Cloud Storage with standard storage class for all data. They want to automatically move data that has been accessed more than 30 days ago to a lower-cost storage class, and after 90 days to archive. What should they configure?

Trap 1: Bucket lock.

Bucket lock protects objects from deletion, not cost optimization.

Trap 2: Retention policy.

Retention policy prevents object deletion, not automatic storage class transitions.

Trap 3: Object versioning.

Object versioning preserves previous versions but does not automatically change storage class.

Study all Managing Google Cloud costs common traps →

A
Lifecycle management rules.
Lifecycle management enables automated transitions to reduce costs.
B
Bucket lock.
Why wrong: Bucket lock protects objects from deletion, not cost optimization.
C
Retention policy.
Why wrong: Retention policy prevents object deletion, not automatic storage class transitions.
D
Object versioning.
Why wrong: Object versioning preserves previous versions but does not automatically change storage class.

Full breakdown with real-world context →

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Frequently asked questions

What does the PCDOE exam test about Managing Google Cloud costs?: Cloud concepts questions usually test the service model (IaaS/PaaS/SaaS) and deployment model (public/private/hybrid/community) appropriate for a given scenario.
How should I use these practice questions?: Select your answer before revealing the explanation. Then read why each option is right or wrong — this active recall approach builds retention far faster than re-reading notes.
Can I practise just Managing Google Cloud costs questions in a focused session?: Yes — the session launcher on this page draws every question from the Managing Google Cloud costs domain. Use a 10-question session first to gauge your baseline, then move to 20 or 30 once the weak spots are clear.
Where can I practise other PCDOE topics?: Use the topic links above to move to related areas, or go back to the PCDOE question bank to see all topics.
Are these real exam questions or dumps?: These are original practice questions written to test the same concepts the PCDOE exam covers. They are not copied from any real exam or dump site.

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All PCDOE questions Managing Google Cloud costs domain overview PCDOE exam guide

Exam traps to avoid

▸IaaS gives you infrastructure control; SaaS gives you only the application.
▸Hybrid cloud combines on-premises and public cloud — not two public clouds.
▸Cloud does not automatically mean cheaper or more secure.
▸Management responsibility shifts with each service model (IaaS → PaaS → SaaS).

Managing Google Cloud costs practice questions

What to know about Managing Google Cloud costs

Common Managing Google Cloud costs exam traps

Managing Google Cloud costs questions

A company runs a batch processing workload on Compute Engine that runs for 3 hours every night. They want to minimize costs while ensuring the job completes reliably. Which recommendation should they follow?

A company uses Cloud Storage to store archival data. They want to minimize storage costs while maintaining availability. Which storage class should they use?

A company is using BigQuery for analytics and wants to control costs. They have many queries that scan large amounts of data. Which approach is most effective in reducing query costs?

A company uses Cloud CDN to deliver content globally. They notice increasing egress costs. Which change will most effectively reduce egress costs?

A company is using Google Cloud and wants to monitor and control costs. Which TWO actions should they take? (Choose two.)

A company runs a web application on Google Kubernetes Engine (GKE) with multiple services. They want to reduce costs without impacting performance. Which THREE actions should they take? (Choose three.)

A DevOps team is analyzing Google Cloud costs and notices that spending on BigQuery has increased significantly. They want to reduce costs without impacting ongoing analytical workloads. Which TWO actions should they take? (Choose two.)

Arrange the steps to troubleshoot a high latency issue on a Google Cloud HTTP(S) Load Balancer.

Order the steps to respond to a Google Cloud security incident involving a compromised service account key.

Match each SRE term to its description.

Match each cost optimization practice to its description.

A company uses Compute Engine with committed use discounts for 1-year. They need to reduce costs further. What should they do?

A team wants to receive a notification when their monthly spending exceeds 80% of the budget. Which GCP feature should they configure?

A company uses BigQuery for analytics with many queries scanning terabytes daily. They need to reduce query costs without reducing usage. What is the most effective strategy?

A DevOps engineer notices that the monthly compute cost is higher than expected for a Kubernetes Engine cluster. They want to identify which namespaces or workloads are contributing most to the cost. What should they do?

A company uses Cloud Storage with standard storage class for all data. They want to automatically move data that has been accessed more than 30 days ago to a lower-cost storage class, and after 90 days to archive. What should they configure?

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