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Google Associate-Cloud-Engineer Exam Syllabus Topics:

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

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Google Associate Cloud Engineer Exam Sample Questions (Q389-Q394):

NEW QUESTION # 389
You just installed the Google Cloud CLI on your new corporate laptop. You need to list the existing instances of your company on Google Cloud. What must you do before you run the gcloud compute instances list command?
Choose 2 answers

A. Create a Google Cloud service account, and download the service account key. Place the key file in a folder on your machine where gcloud CLI can find it.
B. Run gcloud config set project $my_project to set the default project for gcloud CLI.
C. Download your Cloud Identity user account key. Place the key file in a folder on your machine where gcloud CLI can find it.
D. Run gcloud auth login, enter your login credentials in the dialog window, and paste the received login token to gcloud CLI.
E. Run gcloud config set compute/zone $my_zone to set the default zone for gcloud CLI.

Answer: B,D

Explanation:
Before you run the gcloud compute instances list command, you need to do two things: authenticate with your user account and set the default project for gcloud CLI.
To authenticate with your user account, you need to run gcloud auth login, enter your login credentials in the dialog window, and paste the received login token to gcloud CLI. This will authorize the gcloud CLI to access Google Cloud resources on your behalf1.
To set the default project for gcloud CLI, you need to run gcloud config set project $my_project, where
$my_project is the ID of the project that contains the instances you want to list. This will save you from having to specify the project flag for every gcloud command2.
Option B is not recommended, because using a service account key increases the risk of credential leakage and misuse. It is also not necessary, because you can use your user account to authenticate to the gcloud CLI3.
Option C is not correct, because there is no such thing as a Cloud Identity user account key. Cloud Identity is a service that provides identity and access management for Google Cloud users and groups4. Option D is not required, because the gcloud compute instances list command does not depend on the default zone. You can list instances from all zones or filter by a specific zone using the --filter flag.
1: https://cloud.google.com/sdk/docs/authorizing
2: https://cloud.google.com/sdk/gcloud/reference/config/set
3: https://cloud.google.com/iam/docs/best-practices-for-managing-service-account-keys
4: https://cloud.google.com/identity/docs/overview
5: https://cloud.google.com/sdk/gcloud/reference/compute/instances/list

NEW QUESTION # 390
You've been running your App Engine app for a few weeks with Autoscaling, and it's been working well. However, your marketing team is planning on a massive campaign, and they expect a lot of burst traffic. How would you go about ensuring there are always 4 idle instances?

A. Set the min_idle_instances property in the app.yaml.
B. Switch to manual scaling and use the burst_traffic_protection property to True in the app.yaml.
C. Switch to manual scaling and use the idle_instance_count property in the app.yaml.
D. Set the min_instances property in the app.yaml,

Answer: A

NEW QUESTION # 391
You are developing a new web application that will be deployed on Google Cloud Platform. As part of your release cycle, you want to test updates to your application on a small portion of real user traffic. The majority of the users should still be directed towards a stable version of your application. What should you do?

A. Deploy me application on App Engine For each update, create a new version of the same service Configure traffic splitting to send a small percentage of traffic to the new version
B. Deploy the application on Kubernetes Engine For a new release, update the deployment to use the new version
C. Deploy the application on Kubernetes Engine For a now release, create a new deployment for the new version Update the service e to use the now deployment.
D. Deploy the application on App Engine For each update, create a new service Configure traffic splitting to send a small percentage of traffic to the new service.

Answer: A

Explanation:
Keyword, Version, traffic splitting, App Engine supports traffic splitting for versions before releasing.

NEW QUESTION # 392
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. Too many Pods are already running in the cluster, and there are not enough resources left to schedule the pending Pod.
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 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.
D. The pending Pod's resource requests are too large to fit on a single node of the cluster.

Answer: A

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 # 393
Your company's accounting department needs to run an overnight batch workload every day. You must implement a solution that minimizes the cost to run this workload and automatically retries the batch if an execution fails. What should you do?

A. Develop an application that runs the batch workload, and deploy the application as a Google Kubernetes Engine (GKE) CronJob.
B. Develop a web application that listens for incoming requests, and deploy the application as a Cloud Run service. Use Cloud Scheduler to call the HTTP endpoint.
C. Develop a web application that listens for incoming requests, and deploy the application as a Google Kubernetes Engine (GKE) Deployment. Use Cloud Scheduler to call the HTTP endpoint.
D. Develop an application that runs the batch workload, and deploy the application as a Cloud Run job. Use Cloud Scheduler to trigger the job.

Answer: D

Explanation:
Developing an application that runs the batch workload and deploying it as a Cloud Run job is the best solution. Cloud Run jobs are serverless, cost-efficient, and automatically scale based on demand, allowing you to pay only for the resources used during execution. You can also use Cloud Scheduler to trigger the job on a schedule. Additionally, Cloud Run supports automatic retries, which meets the requirement for retrying the batch if an execution fails.

NEW QUESTION # 394
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