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Professional Cloud Architect
Determining software license implications and financial impact
An enterprise plans to migrate legacy Microsoft Windows Serv…

Professional Cloud Architect

Intrigued by the art of cloud architecture? Discover how to design, develop, and manage robust, secure, scalable, and dynamic solutions on Google Cloud as you prepare for the Professional Cloud Architect exam!

Intermediate

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Description
Sample Question
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Practice Test

Intermediate

Prepare and test your skills

Description
Sample Question
Free Trial
Practice Test

Byol Sole Tenant Nodes Licensing Feasibility

Section: Determining software license implications and financial impact

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Related questions

Keep the momentum going with these hand-picked practice scenarios

IntermediateProfessional Cloud Architect

An enterprise is planning to migrate hundreds of legacy on-premises Windows Server and Red Hat Enterprise Linux (RHEL) workloads to Google Compute Engine. Software licensing fees make up a significant portion of the total operating budget because OS vendor licenses are billed on a per-vCPU basis. During pre-migration discovery in Migration Center, performance data reveals that the on-premises servers are substantially over-provisioned. Additionally, the corporate compliance team requires automated, continuous auditing of deployed machine shapes and operating system licensing models post-migration to avoid contractual penalties. Which strategy should the cloud architect implement to optimize licensing costs and ensure ongoing license compliance?

Determining software license implications and financial impact

IntermediateProfessional Cloud Architect

An enterprise is planning to migrate 150 steady-state on-premises Windows Server and Red Hat Enterprise Linux (RHEL) workloads to Google Cloud Compute Engine. The financial operations (FinOps) team is conducting a Total Cost of Ownership (TCO) analysis to compare license-included (Pay-As-You-Go) images against custom-licensed (Bring Your Own License) options. Which architectural and financial consideration correctly guides their migration strategy?

Determining software license implications and financial impact

IntermediateProfessional Cloud Architect

An enterprise is deploying backend application workloads on Compute Engine virtual machine (VM) instances in a dedicated subnet. For security compliance, the VMs are configured with only internal RFC 1918 IP addresses and must remain isolated from unsolicited inbound internet traffic. The workload architecture has the following egress requirements: VM instances must interact directly with Google Cloud services (such as Cloud Storage and BigQuery) without traffic traversing the public internet. VM instances must initiate outbound HTTPS requests to an external, third-party software-as-a-service (SaaS) API for real-time payment validation. Which combination of network configurations should you implement to satisfy these requirements?

VPC design and load balancing (e.g., access to cloud, internet, and cloud adjacent services)

IntermediateProfessional Cloud Architect

A global financial technology enterprise is modernizing its core payment processing system on Google Cloud. The system requires an operational database architecture that satisfies the following technical requirements: Provide strict ACID transactional consistency across distributed tables globally Support standard relational schemas and ANSI SQL query dialect Offer horizontal scaling for both reads and writes across multiple geographic regions Deliver a high-availability Service Level Agreement (SLA) of up to 99.999% (five nines) Which database service should the enterprise select?

Choosing appropriate storage types (e.g., object, file, and databases)

IntermediateProfessional Cloud Architect

A solutions architect is designing a benchmarking strategy to evaluate whether a newly proposed managed database cluster on Google Cloud can meet a strict transactional throughput and latency Service Level Objective (SLO). The benchmark requires running multi-threaded OLTP test suites (such as pgbench or HammerDB) against the database instance over private networking. To ensure the benchmark produces valid baseline measurements and avoids client-side bottlenecks or networking anomalies, which setup should the architect implement?

Profiling and benchmarking

AdvancedProfessional Cloud DevOps Engineer

An e-commerce organization runs a legacy order processing service that outputs structured JSON logs to stdout. The operations team needs to define a Service Level Indicator (SLI) to track the 95th and 99th percentile latency across different checkout categories without refactoring the application code to add OpenTelemetry or Prometheus metric client libraries. A sample log payload emitted by the service contains: { "message": "Order processed successfully", "transaction_type": "express_checkout", "duration_ms": 245.8 } How should the DevOps engineer configure Google Cloud Observability to generate the required latency SLI metrics?

Creating custom metrics, including log-based metrics

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Last updated August 28, 2026

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50 questions in the full practice test

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Professional Cloud Architect

Provider: Google Cloud
Passing score: 80%
Questions: 50
Duration: 90 minutes

Other sections in this exam

Designing and planning a cloud solution architecture
Managing and provisioning a cloud solution infrastructure
Designing for security and compliance
Analyzing and optimizing technical and business processes
Managing implementation
Ensuring solution and operations excellence

Ask Scout

Still curious? Scout, our AI tutor, can explain this concept further and answer your follow-up questions.

An enterprise plans to migrate legacy Microsoft Windows Server and SQL Server enterprise databases from an on-premises data center to Google Cloud. The existing software licenses are licensed per physical core and per physical socket under an enterprise agreement that supports Bring Your Own License (BYOL).

The migration must satisfy the following requirements:

Comply with vendor software licensing rules requiring physical hardware isolation and physical core visibility for audit purposes
Reuse existing on-premises software licenses to avoid purchasing new cloud licenses
Ensure high availability during underlying infrastructure maintenance without manual workload rescheduling
Minimize capital expenditure and unnecessary infrastructure operational costs

Which Compute Engine deployment strategy should you recommend?

Deploy the virtual machines on Compute Engine sole-tenant nodes configured with node affinity labels and a default host maintenance policy.

Deploy the virtual machines on standard multi-tenant Compute Engine instances using custom machine types to match on-premises vCPU counts.

Deploy the workloads onto a Google Kubernetes Engine (GKE) cluster utilizing node taints and tolerations to isolate workloads to dedicated node pools.

Provision new license-included Compute Engine instances and retire existing on-premises software licenses upon migration.

Deploy the virtual machines on Compute Engine sole-tenant nodes configured with node affinity labels and a default host maintenance policy.

What Sole-Tenant Nodes Are

Compute Engine sole-tenant nodes provide dedicated physical Compute Engine servers allocated exclusively for use by a single customer project. They give organizations visibility into the underlying physical hardware, including physical sockets, cores, and server hardware characteristics.

How It Meets The Requirements

Physical Hardware Isolation and Licensing Compliance: Vendor licenses that are tied to physical processor sockets or physical cores require strict isolation and consistent hardware tracking. Sole-tenant nodes ensure that no other tenant shares the physical hardware, allowing organizations to license the physical host under Bring Your Own License (BYOL) terms and satisfy compliance audits.
Reuse Existing Licenses (BYOL): Organizations avoid the capital and operational expense of repurchasing pay-as-you-go software licenses by bringing existing perpetual licenses directly to dedicated hardware in the cloud.
High Availability and Maintenance: With the default host maintenance policy, Compute Engine live-migrates sole-tenant workloads to another dedicated node within the same node group during host maintenance events, maintaining uptime without administrative intervention.
Cost Optimization: Consolidating multiple VMs onto dedicated sole-tenant nodes maximizes core density and minimizes total hardware and licensing costs.

Key Advantages

Hardware Visibility: Provides full access to physical core and socket metrics required for vendor compliance reporting.
Affinity and Anti-Affinity Labels: Allows granular control over how virtual machines are scheduled across dedicated physical hosts.
Live Migration Support: Supports uninterrupted maintenance through automated live migration within dedicated node groups.
Committed Use Discounts: Compatible with committed use discounts (CUDs) to further optimize baseline infrastructure expenses.

Deploy the virtual machines on standard multi-tenant Compute Engine instances using custom machine types to match on-premises vCPU counts.

Deploy the workloads onto a Google Kubernetes Engine (GKE) cluster utilizing node taints and tolerations to isolate workloads to dedicated node pools.

Provision new license-included Compute Engine instances and retire existing on-premises software licenses upon migration.