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Google Associate-Cloud-Engineer Exam Syllabus Topics:

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

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Google Associate Cloud Engineer Exam Sample Questions (Q204-Q209):

NEW QUESTION # 204
You have downloaded and installed the gcloud command line interface (CLI) and have authenticated with your Google Account. Most of your Compute Engine instances in your project run in the europe-west1-d zone. You want to avoid having to specify this zone with each CLI command when managing these instances. What should you do?

A. Create a Metadata entry on the Compute Engine page with key compute/zone and value europe-west1-d.
B. Set the europe-west1-d zone as the default zone using the gcloud config subcommand.
C. In the CLI installation directory, create a file called default.conf containing zone=europe-west1-d.
D. In the Settings page for Compute Engine under Default location, set the zone to europe-west1-d.

Answer: B

Explanation:
Change your default zone and region in the metadata server Note: This only applies to the default configuration. You can change the default zone and region in your metadata server by making a request to the metadata server. For example: gcloud compute project-info add-metadata \ --metadata google-compute-default-region=europe-west1,google-compute-default-zone=europe-west1-b The gcloud command-line tool only picks up on new default zone and region changes after you rerun the gcloud init command. After updating your default metadata, run gcloud init to reinitialize your default configuration. https://cloud.google.com/compute/docs/gcloud-compute#change_your_default_zone_and_region_in_the_metadata_server

NEW QUESTION # 205
You are deploying a large multi-tiered application with more than 1,000 IP addresses in a Google Cloud project that needs to be securely isolated. The application includes the:
* web tier with frontend servers for public traffic
* application tier with servers running core application logic that only need access from the web tier and
* database tier with database servers that only need access from the application tierYou want to minimize cost, complexity, and administrative overhead in the network architecture. What should you do?
database tier with database servers that only need access from the application tierYou want to minimize cost, complexity, and administrative overhead in the network architecture. What should you do?

A. Create one custom mode /16 VPC with three subnets. Place each tier in its own subnet and use firewall rules that reference IP subnets to control traffic.
B. Deploy each tier in a /24 VPC by using network tags to identify instances. Implement firewall rules for fine-grained network segmentation.
C. Deploy each tier into a separate custom mode VPC. Use VPC Network Peering to securely connect each Custom mode VPC. Manage firewall rules individually in each VPC.
D. Create a /24 Shared VPC with separate subnets for each tier. Use firewall rules that reference network tags to control traffic.

Answer: A

Explanation:
For a large, multi-tiered application within a single Google Cloud project, the most efficient and low- overhead solution is to use a single large custom VPC with subnets for network segmentation.
* Single Custom VPC and Subnets: A single custom VPC with subnets for each tier (Web, App, DB) is the least complex and lowest cost solution. A /16 VPC provides 65,536 available IP addresses, easily accommodating "more than 1,000 IP addresses."
* Firewall Rules and IP Subnets: Using Firewall Rules that reference the IP address ranges of the subnets (e.g., allow traffic from the Web subnet's CIDR range to the App subnet's CIDR range) is the recommended and simplest method for defining the necessary secure traffic flow between the tiers (Web $\to$ App $\to$ DB), minimizing administrative overhead compared to managing many network tags.
* Alternatives: Option C (VPC Peering) adds complexity and cost for connectivity. Option A (Shared VPC) is unnecessary if the application is in a single project. Option D suggests three small /24 VPCs, which is not sufficient for a large application.
Reference: Google Cloud VPC Network documentation and Network Security/Firewall Rules best practices.
Recommended practice for network segmentation is to use custom subnets and configure firewall rules based on subnet IP ranges.

NEW QUESTION # 206
Your company ' s Human Resources department publishes a BigQuery dataset with anonymized information about company sales and products. All employees in your company are managed in the terramearth.com Cloud Identity account and must be able to view this dataset as an authenticated user. You need to grant all employees in your company read-only access to this BigQuery dataset. What should you do?

A. Grant the roles/bigquery.dataViewer role to the domain:terramearth.com principal on the dataset ' s IAM policy.
B. Grant the roles/bigquery.dataViewer role to the allAuthenticatedUsers principal on the dataset ' s IAM policy.
C. Grant the roles/bigquery.dataViewer role to the allUsers principal on the dataset ' s IAM policy.
D. Grant the roles/bigquery.dataViewer role to a new service account on the dataset ' s IAM policy.

Answer: A

Explanation:
The correct answer is A because the requirement is company-wide access for employees in one Cloud Identity domain, not public or cross-domain access. The BigQuery Data Viewer role provides read-only access to dataset resources, including reading and querying table data when granted at the dataset level. Using the domain principal domain:terramearth.com grants access to authenticated users in that organization's domain. allUsers would include unauthenticated public access, and allAuthenticatedUsers would include any authenticated Google account, which is far broader than the company boundary. A service account represents an application identity, not all human employees.

NEW QUESTION # 207
Your company has developed a new application that consists of multiple microservices. You want to deploy the application to Google Kubernetes Engine (GKE), and you want to ensure that the cluster can scale as more applications are deployed in the future. You want to avoid manual intervention when each new application is deployed. What should you do?

A. Create a GKE cluster with autoscaling enabled on the node pool. Set a minimum and maximum for the size of the node pool.
B. Deploy the application on GKE, and add a HorizontalPodAutoscaler to the deployment.
C. Deploy the application on GKE, and add a VerticalPodAutoscaler to the deployment.
D. Create a separate node pool for each application, and deploy each application to its dedicated node pool.

Answer: A

Explanation:
https://cloud.google.com/kubernetes-engine/docs/how-to/cluster-autoscaler#adding_a_node_pool_with_autoscaling

NEW QUESTION # 208
You are responsible for a web application on Compute Engine. You want your support team to be notified automatically if users experience high latency for at least 5 minutes. You need a Google- recommended solution with no development cost. What should you do?

A. Implement an App Engine service which invokes the Cloud Monitoring API and sends a notification in case of anomalies.
B. Use the Cloud Monitoring dashboard to observe latency and take the necessary actions when the response latency exceeds the specified threshold.
C. Create an alert policy to send a notification when the HTTP response latency exceeds the specified threshold.
D. Export Cloud Monitoring metrics to BigQuery and use a Looker Studio dashboard to monitor your web application's latency.

Answer: C

Explanation:
https://cloud.google.com/monitoring/alerts#alerting-example

NEW QUESTION # 209
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