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

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Google Associate Cloud Engineer Exam Sample Questions (Q142-Q147):

NEW QUESTION # 142
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. Too many Pods are already running in the cluster, and there are not enough resources left to schedule the pending Pod.
D. The pending Pod's resource requests are too large to fit on a single node of the cluster.

Answer: C

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 # 143
Your company publishes large files on an Apache web server that runs on a Compute Engine instance. The Apache web server is not the only application running in the project. You want to receive an email when the egress network costs for the server exceed 100 dollars for the current month as measured by Google Cloud Platform (GCP). What should you do?

A. Set up a budget alert on the billing account with an amount of 100 dollars, a threshold of 100%, and notification type of "email."
B. Export the billing data to BigQuery. Create a Cloud Function that uses BigQuery to sum the egress network costs of the exported billing data for the Apache web server for the current month and sends an email if it is over 100 dollars. Schedule the Cloud Function using Cloud Scheduler to run hourly.
C. Set up a budget alert on the project with an amount of 100 dollars, a threshold of 100%, and notification type of "email."
D. Use the Stackdriver Logging Agent to export the Apache web server logs to Stackdriver Logging. Create a Cloud Function that uses BigQuery to parse the HTTP response log data in Stackdriver for the current month and sends an email if the size of all HTTP responses, multiplied by current GCP egress prices, totals over 100 dollars. Schedule the Cloud Function using Cloud Scheduler to run hourly.

Answer: B

Explanation:
https://blog.doit-intl.com/the-truth-behind-google-cloud-egress-traffic-6e8f57b5c2f8

NEW QUESTION # 144
You need to set up permissions for a set of Compute Engine instances to enable them to write data into a particular Cloud Storage bucket. You want to follow Google-recommended practices.
What should you do?

A. Create a service account and add it to the IAM role `storage.objectCreator' for that bucket.
B. Create a service account with an access scope.
Use the access scope `https://www.googleapis.com/ auth/devstorage.write_only'.
C. Create a service account with an access scope.
Use the access scope `https://www.googleapis.com/ auth/cloud-platform'.
D. Create a service account and add it to the IAM role `storage.objectAdmin' for that bucket.

Answer: A

Explanation:
The question ask us to grant write object permission.
You should not give a more broader permission as asked because it's against the principle of least privilege.
objectCreator has this description:
Allows users to create objects. Does not give permission to view, delete, or replace objects.
objectAdmin has this description:
Grants full control over objects, including listing, creating, viewing, and deleting objects.
The objectAdmin has unnecessary permissions that doesn't needed by the question context.
https://cloud.google.com/storage/docs/access-control/iam-roles

NEW QUESTION # 145
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 separate billing account per sandbox project and enable BigQuery billing exports.
Create a Data Studio dashboard to plot the spending per billing account.
B. 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.
C. Create a budget per project and configure budget alerts on all of these budgets.
D. Create a single budget for all projects and configure budget alerts on this budget.

Answer: C

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

NEW QUESTION # 146
You have several hundred microservice applications running in a Google Kubernetes Engine (GKE) cluster. Each microservice is a deployment with resource limits configured for each container in the deployment. You've observed that the resource limits for memory and CPU are not appropriately set for many of the microservices. You want to ensure that each microservice has right sized limits for memory and CPU. What should you do?

A. Configure a Horizontal Pod Autoscaler for each microservice.
B. Configure GKE cluster autoscaling.
C. Configure a Vertical Pod Autoscaler for each microservice.
D. Modify the cluster's node pool machine type and choose a machine type with more memory and CPU.

Answer: C

Explanation:
Right-Sizing Resources: VPA is designed to automatically adjust the resource requests and limits (CPU and memory) for pods based on their actual usage. This ensures that pods have enough resources to run efficiently without being over-provisioned, which can lead to wasted resources and higher costs.
Automated Optimization: VPA continuously monitors the resource usage of your pods and recommends optimal settings. You can choose to apply these recommendations automatically or manually, giving you flexibility and control over the process.
Microservice-Specific Tuning: By configuring a VPA for each microservice, you can fine-tune the resource allocation for each individual service based on its specific needs and usage patterns.
This is more efficient than making blanket changes to the entire cluster or node pool.

NEW QUESTION # 147
......

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