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Google Associate-Cloud-Engineer Exam Syllabus Topics:

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

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Google Associate Cloud Engineer Exam Sample Questions (Q311-Q316):

NEW QUESTION # 311
You need to configure IAM access audit logging in BigQuery for external auditors. You want to follow Google-recommended practices. What should you do?

A. Add the auditor user accounts to the `logging.viewer' and `bigQuery.dataViewer' predefined IAM roles.
B. Add the auditor user accounts to two new custom IAM roles.
C. Add the auditors group to the `logging.viewer' and `bigQuery.dataViewer' predefined IAM roles.
D. Add the auditors group to two new custom IAM roles.

Answer: A

NEW QUESTION # 312
You are deploying an application to App Engine. You want the number of instances to scale based on request rate. You need at least 3 unoccupied instances at all times. Which scaling type should you use?

A. Basic Scaling with min_instances set to 3.
B. Automatic Scaling with min_idle_instances set to 3.
C. Manual Scaling with 3 instances.
D. Basic Scaling with max_instances set to 3.

Answer: B

Explanation:
App Engine calculates the number of instances necessary to serve your current application traffic based on scaling settings such as target_cpu_utilization and target_throughput_utilization. Setting min_idle_instances specifies the number of instances to run in addition to this calculated number.
For example, if App Engine calculates that 5 instances are necessary to serve traffic, and min_idle_instances is set to 2, App Engine will run 7 instances (5, calculated based on traffic, plus 2 additional per min_idle_instances).
https://cloud.google.com/appengine/docs/standard/go/config/appref

NEW QUESTION # 313
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 kubectlto examine the status of your Pod and observe that one of them is still in Pendingstatus:

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 pending Pod's resource requests are too large to fit on a single node of the cluster.
C. The node pool is configured with a service account that does not have permission to pull the container image used by the pending Pod.
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:
Reasons for a Pod Status Pending:
Troubleshooting Reason #1: Not enough CPU
Troubleshooting Reason #2: Not enough memory
Troubleshooting Reason #3: Not enough CPU and memory
https://managedkube.com/kubernetes/k8sbot/troubleshooting/pending/pod/2019/02/22/pending- pod.html

NEW QUESTION # 314
You are migrating a business critical application from your local data center into Google Cloud.
As part of your high-availability strategy, you want to ensure that any data used by the application will be immediately available if a zonal failure occurs. What should you do?

A. Store the application data on a regional persistent disk. If an outage occurs, create an instance in another zone with this disk attached.
B. Store the application data on a regional persistent disk. Create a snapshot schedule for the disk.
If an outage occurs, create a new disk from the most recent snapshot and attach it to a new VM in another zone.
C. Store the application data on a zonal persistent disk. Create a snapshot schedule for the disk. If an outage occurs, create a new disk from the most recent snapshot and attach it to a new VM in another zone.
D. Store the application data on a zonal persistent disk. If an outage occurs, create an instance in another zone with this disk attached.

Answer: A

Explanation:
When your are using regional persistent disks, the data is automatically replicated to two replicas without the requirement of maintaining application replication. There is no need to use a snapshot.

NEW QUESTION # 315
You need to create and manage service accounts for your workloads running on Google Cloud.
You want to follow Google-recommended practices. What should you do? (Choose two.)

A. Create single-purpose service accounts.
B. Create as few service accounts as possible.
C. Delete any unused service accounts immediately.
D. Use random names for the service accounts.
E. Manage service accounts as resources.

Answer: A,E

Explanation:
Create single-purpose service accounts.
Google recommends giving each workload its own service account (rather than sharing one account among many workloads). This ensures that you can grant each service account exactly the permissions it needs (and no more), and makes it easier to audit or revoke permissions for any one function.
Manage service accounts as resources.
Treat service accounts the same way you treat other GCP resources - track them in IAM policies, apply labels, automate their creation/deletion in Infrastructure-as-Code, and regularly review their roles. In other words, don't let service accounts "just sit there"; include them in your normal resource-management and auditing processes.

NEW QUESTION # 316
......

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