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Google Associate-Cloud-Engineer Exam Syllabus Topics:

Section	Weight	Objectives
Ensuring Successful Operation	15-20%	- Managing Compute Engine resources 1. Managing instances, disks, and snapshots 2. Attaching and detaching disks 3. Resizing instances and persistent disks - Managing logging and monitoring 1. Viewing and analyzing logs 2. Creating metrics and alerts 3. Using Cloud Monitoring and Logging - Managing storage and data solutions 1. Setting lifecycle policies 2. Configuring CORS and encryption 3. Managing Cloud Storage buckets and objects - Managing Cloud Run resources 1. Managing revisions and traffic splitting 2. Configuring resource limits - Managing Kubernetes Engine resources 1. Scaling clusters and node pools 2. Upgrading clusters 3. Managing workloads (Deployments, Services, HPA)
Planning and Configuring a Cloud Solution	20-25%	- Planning and configuring compute resources 1. Selecting appropriate machine types and zones 2. Configuring persistent disks and local SSDs - Planning and configuring network resources 1. Designing VPC networks 2. Configuring load balancing and firewall rules - Planning and estimating GCP product usage 1. Reading documentation for compute, storage, and network resources 2. Using GCP Pricing Calculator - Planning and configuring data storage options 1. Choosing between Cloud Storage, Filestore, Persistent Disk 2. Selecting appropriate storage classes
Setting Up a Cloud Solution Environment	20-25%	- Managing billing configuration 1. Linking billing to projects 2. Setting up budget alerts and notifications 3. Creating billing accounts - Setting up cloud projects and accounts 1. Managing billing budgets and alerts 2. Assigning IAM roles to users and groups 3. Creating and managing projects
Deploying and Implementing a Cloud Solution	20-25%	- Deploying and managing Cloud Functions 1. Creating and triggering Cloud Functions 2. Configuring triggers and environment variables - Deploying and managing Kubernetes Engine resources 1. Configuring kubectl for cluster access 2. Creating and managing GKE clusters 3. Deploying workloads with Deployments and Services - Deploying and managing Compute Engine resources 1. Creating and managing custom machine types 2. Creating and managing instances with startup scripts 3. Creating and managing managed instance groups - Deploying and managing Cloud Run resources 1. Configuring memory limits and scaling settings 2. Deploying containerized applications to Cloud Run - Deploying applications with Cloud Deployment Manager 1. Creating deployment configurations 2. Using templates for resource provisioning
Configuring Access and Security	15-20%	- Managing service accounts 1. Assigning service accounts to resources 2. Using service account keys 3. Creating and managing service accounts - Viewing audit logs 1. Configuring audit log policies 2. Accessing and analyzing Cloud Audit Logs - Managing IAM resources 1. Defining custom IAM roles 2. Creating and managing IAM roles 3. Applying IAM policies to resources

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Google Associate Cloud Engineer Exam Sample Questions (Q60-Q65):

NEW QUESTION # 60
You are the team lead of a group of 10 developers. You provided each developer with an individual Google Cloud Project that they can use as their personal sandbox to experiment with different Google Cloud solutions. You want to be notified if any of the developers are spending above $500 per month on their sandbox environment. What should you do?

A. Create a budget per project and configure budget alerts on all of these budgets.
B. Create a separate billing account per sandbox project and enable BigQuery billing exports.
Create a Data Studio dashboard to plot the spending per billing account.
C. Create a single billing account for all sandbox projects and enable BigQuery billing exports.
Create a Data Studio dashboard to plot the spending per project.
D. Create a single budget for all projects and configure budget alerts on this budget.

Answer: A

Explanation:
https://cloud.google.com/billing/docs/how-to/budgets

NEW QUESTION # 61
Your organization has created hundreds of service accounts for different applications hosted on-premises and in other clouds that use Google Cloud APIs. You need to audit the service account keys that have been created and identify the keys that are older than 90 days. What should you do?

A. Execute the gcloud iam service-accounts list --filter= " createTime < [DATE_90_DAYS_AGO] " command.
B. Execute the gcloud asset search-all-resources --scope= " organizations/[ORG_ID] " --query= " createTime < [DATE_90_DAYS_AGO] " --asset-types= " apikeys.googleapis.com/Key " --order-by= " createTime " command.
C. Execute the gcloud kms keys list --filter= " createTime < [DATE_90_DAYS_AGO] " command.
D. Execute the gcloud asset search-all-resources --scope= " organizations/[ORG_ID] " --query= " createTime < [DATE_90_DAYS_AGO] " --asset-types= " iam.googleapis.com/ServiceAccountKey " -- order-by= " createTime " command.

Answer: D

Explanation:
The correct answer is C because Cloud Asset Inventory can search resources across an organization and filter by asset type and creation time. The asset type iam.googleapis.com/ServiceAccountKey directly targets service account keys, which is exactly what must be audited. Using organization scope is important because the question says there are hundreds of service accounts across applications, likely distributed across projects. Cloud KMS keys are encryption keys, not service account keys, so option A searches the wrong resource type. Listing service accounts only identifies service accounts, not their individual keys or key ages. API keys are different credentials from service account keys, so option D also targets the wrong asset type. Cloud Asset Inventory is the most scalable audit method here.

NEW QUESTION # 62
You are building an application that stores relational data from users. Users across the globe will use this application. Your CTO is concerned about the scaling requirements because the size of the user base is unknown. You need to implement a database solution that can scale with your user growth with minimum configuration changes. Which storage solution should you use?

A. Cloud Spanner
B. Cloud Datastore
C. Cloud SQL
D. Cloud Firestore

Answer: A

Explanation:
Explanation
Cloud Spanner is a relational database and is highly scalable. Cloud Spanner is a highly scalable, enterprise-grade, globally-distributed, and strongly consistent database service built for the cloud specifically to combine the benefits of relational database structure with a non-relational horizontal scale. This combination delivers high-performance transactions and strong consistency across rows, regions, and continents with an industry-leading 99.999% availability SLA, no planned downtime, and enterprise-grade security Ref: https://cloud.google.com/spanner Graphical user interface, application, Teams Description automatically generated

NEW QUESTION # 63
A colleague handed over a Google Cloud Platform project for you to maintain. As part of a security checkup, you want to review who has been granted the Project Owner role. What should you do?

A. Navigate to Identity-Aware Proxy and check the permissions for these resources.
B. Enable Audit Logs on the IAM & admin page for all resources, and validate the results.
C. Use the command gcloud projects get-iam-policy to view the current role assignments.
D. In the console, validate which SSH keys have been stored as project-wide keys.

Answer: D

Explanation:
Explanation/Reference: https://cloud.google.com/compute/docs/instances/adding-removing-ssh-keys

NEW QUESTION # 64
Your company has workloads running on Compute Engine and on-premises. The Google Cloud Virtual Private Cloud (VPC) is connected to your WAN over a Virtual Private Network (VPN). You need to deploy a new Compute Engine instance and ensure that no public Internet traffic can be routed to it. What should you do?

A. Create the instance without a public IP address.
B. Create the instance with Private Google Access enabled.
C. Create a route on the VPC to route all traffic to the instance over the VPN tunnel.
D. Create a deny-all egress firewall rule on the VPC network.

Answer: B

Explanation:
Get private access to Google services, such as storage, big data, analytics, or machine learning, without having to give your service a public IP address. Reference: https://cloud.google.com/vpc

NEW QUESTION # 65
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