Google Associate Cloud Engineer Quick Facts (2025)

Exam Domain Breakdown

Domain 1: Setting up a cloud solution environment (20% of the exam)

Setting up cloud projects and accounts.

• Creating a resource hierarchy
• Applying organizational policies to the resource hierarchy
• Granting members IAM roles within a project
• Managing users and groups in Cloud Identity (manually and automated)
• Enabling APIs within projects
• Provisioning and setting up products in Google Cloud’s operations suite
• Assessing quotas and requesting increases

Summary: In this section you learn how to create projects that serve as the foundation for all Google Cloud activities. It emphasizes building a clear resource hierarchy aligned to organizational needs, enforcing policies, and enabling APIs to unlock the services needed for workloads. This forms the groundwork for collaboration by assigning IAM roles to users and groups with precision and best practices.

More importantly, you gain the ability to manage teams effectively through Cloud Identity, ensuring secure authentication and access control. By assessing quotas and preparing for scaling, you become proactive in shaping a sustainable cloud environment. This knowledge ensures your Google Cloud projects start strong and adapt over time in ways that align with real business priorities.

Managing billing configuration.

• Creating one or more billing accounts
• Linking projects to a billing account
• Establishing billing budgets and alerts
• Setting up billing exports

Summary: This topic ensures you understand how financial enablement works in Google Cloud. Controlling billing accounts and linking them with projects allows for visibility and accountability across teams. Establishing budgets and alerts protects teams from unexpected costs and empowers proactive decision-making.

Exporting billing information equips you with tools for long-term cost analysis. This approach not only creates transparency but also empowers teams to align their strategies with cloud investments. By setting up solid billing configurations, you create an environment where teams innovate confidently while finances remain predictable and well managed.

Domain 2: Planning and configuring a cloud solution (17.5% of the exam)

Planning and configuring compute resources.

• Selecting appropriate compute choices for a given workload (e.g., Compute Engine, Google Kubernetes Engine, Cloud Run, Cloud Functions)
• Using Spot VM instances and custom machine types as appropriate

Summary: This section sharpens your ability to select the right compute service for different workloads. It emphasizes the range of options, from traditional virtual machines to container orchestration through GKE and serverless compute solutions with Cloud Run or Functions. Applying Spot VMs and custom machine types enables flexibility and cost optimization tailored to business priorities.

By identifying the best fit for each workload, you learn to design solutions that are both resilient and efficient. Matching needs to resources ensures that applications perform well, scale naturally, and remain cost effective. This ability builds confidence in balancing performance, adaptability, and economics in cloud environments.

Planning and configuring data storage options.

• Product choice (e.g., Cloud SQL, BigQuery, Firestore, Spanner, Bigtable)
• Choosing storage options (e.g., zonal Persistent Disk, regional Persistent Disk, Standard, Nearline, Coldline, Archive)

Summary: Mastering data storage begins with understanding the right fit among portfolio services. This section highlights how relational, NoSQL, and analytics-driven offerings provide tailored solutions, along with the different storage classes available in Cloud Storage. Each option ensures alignment with performance, durability, and long-term retention needs.

By learning when to use services like Cloud SQL, Firestore, or Spanner, you design solutions that reliably meet business needs. Incorporating zonal or regional storage strategies further improves resilience and performance. This foundation ensures stored data remains both accessible and cost optimized.

Planning and configuring network resources.

• Load balancing
• Availability of resource locations in a network
• Network Service Tiers

Summary: Understanding how to design networks for reliability and performance is an essential skill presented here. Load balancing provides global availability while Network Service Tiers allow flexibility between premium speed and standard options. With resource location planning, you maximize resilience and minimize latency for users across regions.

By applying these techniques, you ensure that services are not only stable but also highly available. This knowledge supports cloud solutions that adapt gracefully to user demands and enhance application performance without unnecessary overhead.

Domain 3: Deploying and implementing a cloud solution (25% of the exam)

Deploying and implementing Compute Engine resources.

• Launching a compute instance (e.g., assign disks, availability policy, SSH keys)
• Creating an autoscaled managed instance group by using an instance template
• Configuring OS Login
• Configuring VM Manager

Summary: This section equips you with the skills to stand up Compute Engine environments effectively. You learn how to specify instance attributes such as disks and policies along with SSH access and operating system configurations. By setting up auto scaled managed instance groups, you ensure workloads are able to handle diverse and changing demand.

Configuring OS Login and VM Manager improves governance and automation, keeping the environment secure and well managed. The result is a compute foundation that supports modern workloads with both flexibility and control in mind.

Deploying and implementing Google Kubernetes Engine resources.

• Installing and configuring the command line interface (CLI) for Kubernetes (kubectl)
• Deploying a Google Kubernetes Engine cluster with different configurations (e.g., Autopilot, regional clusters, private clusters, GKE Enterprise)
• Deploying a containerized application to Google Kubernetes Engine

Summary: Here the focus is on orchestration of containers through GKE. You learn the technical details for configuring access via kubectl and standing up clusters in different modes such as Autopilot, private, or regional. These skills empower you to support workloads at scale with automated management features.

Deploying containerized applications completes the workflow, taking code from development to enterprise-ready platforms. Mastery of these patterns ensures that workloads are portable, scalable, and aligned with container-native best practices in Google Cloud.

Deploying and implementing Cloud Run and Cloud Functions resources.

• Deploying an application
• Deploying an application for receiving Google Cloud events (e.g., Pub/Sub events, Cloud Storage object change notification events, Eventarc)
• Determining where to deploy an application by using Cloud Run (fully managed), Cloud Run for Anthos, or Cloud Functions

Summary: This section adds event-driven and serverless options to your toolkit. You explore deployment choices across Cloud Run and Cloud Functions, with clear criteria for choosing between them. Event-driven solutions are highlighted as essential for real-time applications and automated workflows.

Learning these deployment options gives you flexibility to align workloads with the appropriate service level. Whether the requirement is high scalability, fast event processing, or managed runtime, these approaches minimize operational burden while maintaining performance excellence.

Deploying and implementing data solutions.

• Deploying data products (e.g., Cloud SQL, Firestore, BigQuery, Spanner, Pub/Sub, Dataflow, Cloud Storage, AlloyDB)
• Loading data (e.g., command line upload, load data from Cloud Storage, Storage Transfer Service)

Summary: This section introduces the deployment of data infrastructure on Google Cloud. From relational databases and real-time messaging systems to advanced analytics, deploying and managing these services is essential. You also practice different strategies for ingesting data which is vital for preparing systems for production workloads.

With these techniques, you gain a strong grip on building data-driven solutions that integrate across Google Cloud services. The emphasis is always on reliable deployments, smooth data transfer, and an architecture that enables innovation.

Deploying and implementing networking resources.

• Creating a VPC with subnets (e.g., custom mode VPC, Shared VPC)
• Creating ingress and egress firewall rules and policies (e.g., IP subnets, network tags, service accounts)
• Peering external networks (e.g., Cloud VPN, VPC Network Peering)

Summary: Networking resources provide the connective tissue of workloads and this section trains you to build them confidently. You practice creating VPCs and applying firewall rules to control traffic at both ingress and egress levels. Shared VPCs and peering ensure collaboration across projects and connectivity between environments.

By mastering these skills, you create reliable communication pathways that support both security and scalability. These networks make applications robust and highly available while integrating seamlessly with hybrid setups.

Implementing resources through infrastructure as code.

• Infrastructure as code tooling (e.g., Cloud Foundation Toolkit, Config Connector, Terraform, Helm)

Summary: This section emphasizes automation of infrastructure deployment through code-driven solutions. Tools like Terraform, Helm, and Config Connector create repeatable, version-controlled environments that increase speed and reliability.

By embracing infrastructure as code, you reduce manual work and enhance collaboration between teams. This helps produce consistent, high-quality deployments across projects, making the operational foundation of Google Cloud solutions more resilient.

Domain 4: Ensuring successful operation of a cloud solution (20% of the exam)

Managing Compute Engine resources.

• Remotely connecting to the instance
• Viewing current running VM inventory (e.g., instance IDs, details)
• Working with snapshots (e.g., create a snapshot from a VM, view snapshots, delete a snapshot, schedule a snapshot)
• Working with images (e.g., create an image from a VM or a snapshot, view images, delete an image)

Summary: This section strengthens your ability to manage running Compute Engine resources. You gain hands-on knowledge of connecting securely, managing instance inventories, and working with snapshots and images. These practices stabilize workloads and set the stage for ongoing maintenance.

With these capabilities, you build consistent approaches to recovery and scaling. They allow for confident operations and support an agile response to changing demands or unforeseen situations.

Managing Google Kubernetes Engine resources.

• Viewing current running cluster inventory (e.g., nodes, Pods, Services)
• Configuring Google Kubernetes Engine to access Artifact Registry
• Working with node pools (e.g., add, edit, or remove a node pool)
• Working with Kubernetes resources (e.g., Pods, Services, Statefulsets)
• Managing Horizontal and Vertical autoscaling configurations

Summary: The focus in this section is operational excellence in Kubernetes environments. You explore how to view and manage cluster resources, ensure image access through Artifact Registry, and configure node pools to meet evolving needs. Kubernetes resource management including Pods and Statefulsets strengthens your ability to deliver robust services.

By balancing horizontal and vertical autoscaling configurations, you prepare workloads for growth without disruption. The outcome is a powerful foundation for containerized applications that adapt dynamically to business requirements.

Managing Cloud Run resources.

• Deploying new versions of an application
• Adjusting application traffic splitting parameters
• Setting scaling parameters for autoscaling instances

Summary: With Cloud Run management, you learn how to deploy new versions seamlessly while controlling traffic splitting for phased rollouts. This brings agility to application delivery by continuously improving services.

Setting autoscaling ensures apps meet demand effectively, scaling up or down with ease. These capabilities create confidence in operating a serverless environment consistently and securely.

Managing storage and database solutions.

• Managing and securing objects in Cloud Storage buckets
• Setting object lifecycle management policies for Cloud Storage buckets
• Executing queries to retrieve data from data instances (e.g., Cloud SQL, BigQuery, Spanner, Firestore, AlloyDB)
• Estimating costs of data storage resources
• Backing up and restoring database instances (e.g., Cloud SQL, Firestore)
• Reviewing job status (e.g., Dataflow, BigQuery)

Summary: This section revolves around effective long-term management of storage and database solutions. You gain the ability to secure objects, manage lifecycles, and query data from multiple systems with confidence. Applying lifecycle rules keeps costs both predictable and efficient.

With backup and restore strategies plus tracking job statuses, you amplify reliability. This ensures that mission-critical data workflows maintain continuity while remaining efficient and economical.

Managing networking resources.

• Adding a subnet to an existing VPC
• Expanding a subnet to have more IP addresses
• Reserving static external or internal IP addresses
• Working with Cloud DNS and Cloud NAT

Summary: As workloads expand, so does the need to manage networking resources effectively. This section shows you how to add and expand subnets, secure predictable IP addresses, and configure critical resources like Cloud DNS and Cloud NAT.

This knowledge supports both everyday operations and enterprise-scale setups. It ensures that changes can be accommodated smoothly while keeping networks reliable and accessible.

Monitoring and logging.

• Creating Cloud Monitoring alerts based on resource metrics
• Creating and ingesting Cloud Monitoring custom metrics (e.g., from applications or logs)
• Exporting logs to external systems (e.g., on-premises, BigQuery)
• Configuring log buckets, log analytics, and log routers
• Viewing and filtering logs in Cloud Logging
• Viewing specific log message details in Cloud Logging
• Using cloud diagnostics to research an application issue
• Viewing Google Cloud status
• Configuring and deploying Ops Agent
• Deploying Managed Service for Prometheus
• Configuring audit logs

Summary: Monitoring and logging are at the heart of operational excellence. You learn how to configure alerts, capture custom metrics, and export logs to other systems. This enables proactive monitoring and detailed diagnostics.

Using Cloud Logging and Monitoring tools ensures visibility into workloads and improves decision making. With advanced configurations like Ops Agent and Managed Service for Prometheus, you enhance observability and design a system that operates with clarity and resilience.

Domain 5: Configuring access and security (17.5% of the exam)

Managing Identity and Access Management (IAM).

• Viewing and creating IAM policies
• Managing the various role types and defining custom IAM roles (e.g., basic, predefined, custom)

Summary: IAM is a foundational aspect of security in Google Cloud. This section trains you to view, create, and manage policies while handling role assignments. By configuring roles effectively, you implement best practices and ensure users have the right level of access.

This mindset improves governance and keeps projects secure while maintaining flexibility. Learning IAM in depth gives you control of security at the organizational and project levels.

Managing service accounts.

• Creating service accounts
• Using service accounts in IAM policies with minimum permissions
• Assigning service accounts to resources
• Managing IAM of a service account
• Managing service account impersonation
• Creating and managing short-lived service account credentials

Summary: Here you learn how to manage service accounts, which are essential for enabling applications and services to interact securely. The emphasis on minimum permissions enforces the principle of least privilege. Assigning accounts to resources ensures workloads function as intended while remaining under strict access control.

By also learning about account impersonation and short-lived credentials, you adopt practices that enhance both security and flexibility. These tools protect services and keep operations streamlined with minimal administrative overhead.