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Google Associate-Cloud-Engineer Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Setting up a cloud solution environment	20%	- Managing billing configuration 1. Set budgets and alerts 2. Create and manage billing accounts 3. Configure billing exports 4. Link projects to billing accounts - Setting up cloud projects and accounts 1. Manage IAM roles and permissions 2. Create resource hierarchy 3. Enable APIs 4. Apply organizational policies 5. Manage quotas and limits 6. Manage users and groups
Topic 2: Deploying and implementing a cloud solution	25%	- Deploying and implementing serverless resources 1. Deploy Cloud Run services 2. Create Cloud Functions - Deploying and implementing data solutions 1. Set up data processing pipelines 2. Provision databases - Deploying and implementing Google Kubernetes Engine resources 1. Configure networking for GKE 2. Deploy workloads 3. Create and manage clusters - Deploying and implementing Compute Engine resources 1. Create managed instance groups 2. Launch virtual machines 3. Manage images and snapshots 4. Configure access and security
Topic 3: Ensuring successful operation of a cloud solution	20%	- Monitoring and logging 1. Use Cloud Monitoring 2. Set up alerts 3. Use Cloud Logging - Managing cost and performance 1. Optimize resource usage 2. Analyze cost reports - Managing resources 1. Update configurations 2. Troubleshoot common issues 3. Scale resources
Topic 4: Planning and configuring a cloud solution	17.5%	- Planning and configuring storage resources 1. Select storage classes 2. Plan data durability and availability - Planning and configuring network resources 1. Plan hybrid connectivity 2. Plan firewall rules 3. Design VPC networks 4. Choose load balancing options - Planning and configuring compute resources 1. Plan instance configuration 2. Plan data storage solutions 3. Select compute options 4. Choose storage options
Topic 5: Configuring access and security	17.5%	- Managing data security 1. Manage access to data 2. Enable encryption - Managing IAM 1. Implement least privilege access 2. Manage service accounts 3. Define roles and permissions - Configuring network security 1. Secure VPC networks 2. Configure private access 3. Manage security controls

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Google Associate Cloud Engineer Exam Sample Questions (Q336-Q341):

NEW QUESTION # 336
You create a Deployment with 2 replicas in a Google Kubernetes Engine cluster that has a single preemptible node pool. After a few minutes, you use kubectl to examine the status of your Pod and observe that one of them is still in Pending status:

What is the most likely cause?

A. The pending Pod was originally scheduled on a node that has been preempted between the creation of the Deployment and your verification of the Pods' status. It is currently being rescheduled on a new node.
B. The node pool is configured with a service account that does not have permission to pull the container image used by the pending Pod.
C. The pending Pod's resource requests are too large to fit on a single node of the cluster.
D. Too many Pods are already running in the cluster, and there are not enough resources left to schedule the pending Pod.

Answer: D

Explanation:
* The pending Pods resource requests are too large to fit on a single node of the cluster. Too many Pods are already running in the cluster, and there are not enough resources left to schedule the pending Pod.
is the right answer.
* When you have a deployment with some pods in running and other pods in the pending state, more often than not it is a problem with resources on the nodes. Heres a sample output of this use case. We see that the problem is with insufficient CPU on the Kubernetes nodes so we have to either enable auto- scaling or manually scale up the nodes.

NEW QUESTION # 337
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 allAuthenticatedUsers principal on the dataset ' s IAM policy.
B. Grant the roles/bigquery.dataViewer role to the domain:terramearth.com 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: B

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 # 338
You need to run an important query in BigQuery but expect it to return a lot of records. You want to find out how much it will cost to run the query. You are using on-demand pricing. What should you do?

A. Use the command line to run a dry run query to estimate the number of bytes read. Then convert that bytes estimate to dollars using the Pricing Calculator.
B. Arrange to switch to Flat-Rate pricing for this query, then move back to on-demand.
C. Use the command line to run a dry run query to estimate the number of bytes returned. Then convert that bytes estimate to dollars using the Pricing Calculator.
D. Run a select count (*) to get an idea of how many records your query will look through. Then convert that number of rows to dollars using the Pricing Calculator.

Answer: A

Explanation:
Reference: https://cloud.google.com/bigquery/docs/estimate-costs
On-demand pricing Under on-demand pricing, BigQuery charges for queries by using one metric: the number of bytes processed (also referred to as bytes read). You are charged for the number of bytes processed whether the data is stored in BigQuery or in an external data source such as Cloud Storage, Drive, or Cloud Bigtable.
On-demand pricing is based solely on usage. https://cloud.google.com/bigquery/pricing#on_demand_pricing

NEW QUESTION # 339
You need to reduce GCP service costs for a division of your company using the fewest possible steps. You need to turn off all configured services in an existing GCP project. What should you do?

A. 1. Verify that you are assigned the Organizational Administrator IAM role for this project.
2. Locate the project in the GCP console, enter the project ID and then click Shut down.
B. 1. Verify that you are assigned the Organizational Administrators IAM role for this project.
2. Switch to the project in the GCP console, locate the resources and delete them.
C. 1. Verify that you are assigned the Project Owners IAM role for this project.
2. Switch to the project in the GCP console, locate the resources and delete them.
D. 1. Verify that you are assigned the Project Owners IAM role for this project.
2. Locate the project in the GCP console, click Shut down and then enter the project ID.

Answer: D

Explanation:
https://cloud.google.com/run/docs/tutorials/gcloud
https://cloud.google.com/resource-manager/docs/creating-managing-projects
https://cloud.google.com/iam/docs/understanding-roles#primitive_roles
You can shut down projects using the Cloud Console. When you shut down a project, this immediately happens: All billing and traffic serving stops, You lose access to the project, The owners of the project will be notified and can stop the deletion within 30 days, The project will be scheduled to be deleted after 30 days. However, some resources may be deleted much earlier.

NEW QUESTION # 340
You have a single binary application that you want to run on Google Cloud Platform. You decided to automatically scale the application based on underlying infrastructure CPU usage. Your organizational policies require you to use virtual machines directly. You need to ensure that the application scaling is operationally efficient and completed as quickly as possible. What should you do?

A. Use a set of third-party tools to build automation around scaling the application up and down, based on Stackdriver CPU usage monitoring.
B. Create a Google Kubernetes Engine cluster, and use horizontal pod autoscaling to scale the application.
C. Create an instance template, and use the template in a managed instance group with autoscaling configured.
D. Create an instance template, and use the template in a managed instance group that scales up and down based on the time of day.

Answer: C

Explanation:
Explanation
Managed instance groups offer autoscaling capabilities that let you automatically add or delete instances from a managed instance group based on increases or decreases in load (CPU Utilization in this case). Autoscaling helps your apps gracefully handle increases in traffic and reduce costs when the need for resources is lower.
You define the autoscaling policy and the autoscaler performs automatic scaling based on the measured load (CPU Utilization in this case). Autoscaling works by adding more instances to your instance group when there is more load (upscaling), and deleting instances when the need for instances is lowered (downscaling). Ref:
https://cloud.google.com/compute/docs/autoscaler

NEW QUESTION # 341
......

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