Practice Test Google Associate Cloud Engineer

The Google Associate Cloud Engineer practice test contains 150 questions and covers the following objectives: 

Setting up a cloud solution environment - 30 questions

Setting up cloud projects and accounts. Considerations include:

• 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

Managing billing configuration. Considerations include:

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

Planning and configuring a cloud solution - 26 questions

Planning and configuring compute resources. Considerations include:

• 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

Planning and configuring data storage options. Considerations include:

•  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)

Planning and configuring network resources. Considerations include:

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

Deploying and implementing a cloud solution - 38 questions

Deploying and implementing Compute Engine resources. Considerations include:

• 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

Deploying and implementing Google Kubernetes Engine resources. Considerations include:

• 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

Deploying and implementing Cloud Run and Cloud Functions resources. Considerations include:

• 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

Deploying and implementing data solutions. Considerations include:

• 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)

Deploying and implementing networking resources. Considerations include:

• 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)

Implementing resources through infrastructure as code. Considerations include:

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

Ensuring successful operation of a cloud solution - 30 questions

Managing Compute Engine resources. Considerations include:

• 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)

Managing Google Kubernetes Engine resources. Considerations include:

• 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

Managing Cloud Run resources. Considerations include:

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

Managing storage and database solutions. Considerations include:

• 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)

Managing networking resources. Considerations include:

• 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

Monitoring and logging. Considerations include:

• 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

Configuring access and security - 26 questions

Managing Identity and Access Management (IAM). Considerations include:

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

Managing service accounts. Considerations include:

• 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