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

Prepare and test your skills

Intermediate

Prepare and test your skills

Running Stateless Containers on Cloud Run

Section: Cloud-first design approach

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Explanations

...

View source documentation

Keep the momentum going with these hand-picked practice scenarios

IntermediateProfessional Cloud Architect

An enterprise is planning to migrate its core application workloads from an on-premises data center to Google Cloud. In their current on-premises environment, the company incurs large upfront capital expenditures (CapEx) to procure hardware sized for peak annual traffic, resulting in low average hardware utilization throughout most of the year. The leadership team wants to understand the financial implications of moving to a cloud consumption model and how this shift affects Total Cost of Ownership (TCO) and organizational financial agility. Which statement accurately describes the economic impact of transitioning from fixed-cost infrastructure to a cloud variable-cost structure?

Cost optimization/resource optimization (CapEx/OpEx)

IntermediateProfessional Cloud Architect

GKE Workload Identity

Identity and Access Management (IAM)

AdvancedProfessional Cloud DevOps Engineer

Your enterprise organization manages multiple environments across staging and production folders in Google Cloud. To prevent data exfiltration and enforce infrastructure standards across all development teams, your DevOps team must implement a Policy-as-Code guardrail with the following requirements: Restrict creation and updates of cloud resources to enforce specific configuration attributes. Provide human-readable violation messages when unauthorized API calls are blocked. Ensure the guardrail definition is registered at the organization level and can be enforced or overridden hierarchically. How should you define and enforce this guardrail using Google Cloud Organization Policy custom constraints?

Managing configuration and policy

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Last updated September 11, 2026

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

Prepare and test your skills

Intermediate

Prepare and test your skills

Running Stateless Containers on Cloud Run

Section: Cloud-first design approach

An organization is modernizing its web-based applications following a cloud-first design approach. The team currently operates several containerized, stateless microservices on self-managed virtual machines in Compute Engine. Maintaining these workloads involves significant operational toil, including OS security patching, manual capacity provisioning, and managing custom autoscaling scripts.

The engineering leadership wants to achieve the following:

Eliminate infrastructure and OS-level maintenance overhead (operational offloading)
Automatically scale resources dynamically with incoming traffic, including scaling to zero during idle periods
Reduce long-term technical debt by utilizing managed, cloud-native runtime services

Which compute solution should the organization adopt to meet these requirements?

...

Migrate the containerized workloads to Cloud Run

...

Deploy the containerized services onto a Google Kubernetes Engine (GKE) Standard cluster with manual node pool management

...

Maintain individual standalone Compute Engine virtual machines and deploy startup scripts to manage container lifecycles

...

Deploy the containers across Compute Engine Managed Instance Groups (MIGs) with custom autoscaler policies

...

Explanations

What Cloud Run Is

Cloud Run is a fully managed, serverless compute platform that enables you to run stateless containers directly on top of Google Cloud's scalable infrastructure without needing to provision, manage, or maintain the underlying virtual machines or cluster software.

How It Meets the Requirements

Operational Offloading: Cloud Run abstracts all infrastructure management. Google handles server provisioning, operating system maintenance, security patches, networking, and runtime environments, allowing engineering teams to focus solely on containerized application code.
Automated Scaling (Including Scale-to-Zero): Cloud Run features native, request-driven autoscaling. When incoming traffic increases, it rapidly spins up container instances to handle the load; when traffic drops to zero, it automatically scales down to zero instances, eliminating idle compute costs.
Reduction of Long-Term Technical Debt: By moving away from custom scaling scripts and self-managed VM configurations to standard Open Container Initiative (OCI) containers running on managed APIs, organizations eliminate proprietary infrastructure glue code and configuration drift.

Key Advantages and Capabilities

Zero Server Management: Eliminates routine operational toil such as kernel upgrades, OS patching, and host-level monitoring.
Granular Pay-per-Use Billing: Charges are computed down to the hundredth of a millisecond only when requests are actively being processed (by default).
Developer Agility: Developers deploy standard container images with declarative configurations, simplifying CI/CD pipelines.
Built-in Resilience: Provides automatic high availability and regional distribution without complex load balancer orchestration.

Why This Is Optimal

Compared to IaaS-based options or full cluster management, Cloud Run aligns directly with the cloud-first design approach by maximizing managed services adoption, completely eliminating server toil, and providing out-of-the-box scaling to zero.

...

View source documentation

Keep the momentum going with these hand-picked practice scenarios

IntermediateProfessional Cloud Architect

Cloud Pub/Sub Event-Driven Architecture

Cloud-first design approach

IntermediateProfessional Cloud Architect

Cloud Run vs GKE Refactoring Strategy

Cloud-first design approach

IntermediateProfessional Cloud Architect

Dataproc vs Dataflow

Data processing and compute provisioning

IntermediateProfessional Cloud Architect

An enterprise is planning to migrate its core application workloads from an on-premises data center to Google Cloud. In their current on-premises environment, the company incurs large upfront capital expenditures (CapEx) to procure hardware sized for peak annual traffic, resulting in low average hardware utilization throughout most of the year. The leadership team wants to understand the financial implications of moving to a cloud consumption model and how this shift affects Total Cost of Ownership (TCO) and organizational financial agility. Which statement accurately describes the economic impact of transitioning from fixed-cost infrastructure to a cloud variable-cost structure?

Cost optimization/resource optimization (CapEx/OpEx)

IntermediateProfessional Cloud Architect

GKE Workload Identity

Identity and Access Management (IAM)

AdvancedProfessional Cloud DevOps Engineer

Your enterprise organization manages multiple environments across staging and production folders in Google Cloud. To prevent data exfiltration and enforce infrastructure standards across all development teams, your DevOps team must implement a Policy-as-Code guardrail with the following requirements: Restrict creation and updates of cloud resources to enforce specific configuration attributes. Provide human-readable violation messages when unauthorized API calls are blocked. Ensure the guardrail definition is registered at the organization level and can be enforced or overridden hierarchically. How should you define and enforce this guardrail using Google Cloud Organization Policy custom constraints?

Managing configuration and policy

Want more questions like this?

Get a free certification question every week.

Last updated September 11, 2026

An organization is modernizing its web-based applications following a cloud-first design approach. The team currently operates several containerized, stateless microservices on self-managed virtual machines in Compute Engine. Maintaining these workloads involves significant operational toil, including OS security patching, manual capacity provisioning, and managing custom autoscaling scripts.

The engineering leadership wants to achieve the following:

Eliminate infrastructure and OS-level maintenance overhead (operational offloading)
Automatically scale resources dynamically with incoming traffic, including scaling to zero during idle periods
Reduce long-term technical debt by utilizing managed, cloud-native runtime services

Which compute solution should the organization adopt to meet these requirements?

Migrate the containerized workloads to Cloud Run

Deploy the containerized services onto a Google Kubernetes Engine (GKE) Standard cluster with manual node pool management

Maintain individual standalone Compute Engine virtual machines and deploy startup scripts to manage container lifecycles

Deploy the containers across Compute Engine Managed Instance Groups (MIGs) with custom autoscaler policies

Migrate the containerized workloads to Cloud Run

What Cloud Run Is

Cloud Run is a fully managed, serverless compute platform that enables you to run stateless containers directly on top of Google Cloud's scalable infrastructure without needing to provision, manage, or maintain the underlying virtual machines or cluster software.

How It Meets the Requirements

Operational Offloading: Cloud Run abstracts all infrastructure management. Google handles server provisioning, operating system maintenance, security patches, networking, and runtime environments, allowing engineering teams to focus solely on containerized application code.
Automated Scaling (Including Scale-to-Zero): Cloud Run features native, request-driven autoscaling. When incoming traffic increases, it rapidly spins up container instances to handle the load; when traffic drops to zero, it automatically scales down to zero instances, eliminating idle compute costs.
Reduction of Long-Term Technical Debt: By moving away from custom scaling scripts and self-managed VM configurations to standard Open Container Initiative (OCI) containers running on managed APIs, organizations eliminate proprietary infrastructure glue code and configuration drift.

Key Advantages and Capabilities

Zero Server Management: Eliminates routine operational toil such as kernel upgrades, OS patching, and host-level monitoring.
Granular Pay-per-Use Billing: Charges are computed down to the hundredth of a millisecond only when requests are actively being processed (by default).
Developer Agility: Developers deploy standard container images with declarative configurations, simplifying CI/CD pipelines.
Built-in Resilience: Provides automatic high availability and regional distribution without complex load balancer orchestration.

Why This Is Optimal

Compared to IaaS-based options or full cluster management, Cloud Run aligns directly with the cloud-first design approach by maximizing managed services adoption, completely eliminating server toil, and providing out-of-the-box scaling to zero.

Deploy the containerized services onto a Google Kubernetes Engine (GKE) Standard cluster with manual node pool management

Maintain individual standalone Compute Engine virtual machines and deploy startup scripts to manage container lifecycles

Deploy the containers across Compute Engine Managed Instance Groups (MIGs) with custom autoscaler policies

Professional Cloud Architect

Running Stateless Containers on Cloud Run

Related questions

Cloud Pub/Sub Event-Driven Architecture

Cloud Run vs GKE Refactoring Strategy

Dataproc vs Dataflow

GKE Workload Identity

Professional Cloud Architect

Running Stateless Containers on Cloud Run

What Cloud Run Is

How It Meets the Requirements

Key Advantages and Capabilities

Why This Is Optimal

Related questions

Cloud Pub/Sub Event-Driven Architecture

Cloud Run vs GKE Refactoring Strategy

Dataproc vs Dataflow

GKE Workload Identity

What Cloud Run Is

How It Meets the Requirements

Key Advantages and Capabilities

Why This Is Optimal