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Google Associate-Cloud-Engineer Exam Syllabus Topics:

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

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Google Associate Cloud Engineer Exam Sample Questions (Q304-Q309):

NEW QUESTION # 304
The storage costs for your application logs have far exceeded the project budget. The logs are currently being retained indefinitely in the Cloud Storage bucket myapp-gcp-ace-logs. You have been asked to remove logs older than 90 days from your Cloud Storage bucket. You want to optimize ongoing Cloud Storage spend. What should you do?

A. Write a lifecycle management rule in JSON and push it to the bucket with gsutil lifecycle set config-json-file.
B. Write a lifecycle management rule in XML and push it to the bucket with gsutil lifecycle set config-xml-file.
C. Write a script that runs gsutil Is -Ir gs://myapp-gcp-ace-logs/** to find and remove items older than 90 days. Repeat this process every morning.
D. Write a script that runs gsutil Is -| - gs://myapp-gcp-ace-logs/** to find and remove items older than 90 days. Schedule the script with cron.

Answer: A

Explanation:
You write a lifecycle management rule in XML and push it to the bucket with gsutil lifecycle set config-xml-file. is not right.
gsutil lifecycle set enables you to set the lifecycle configuration on one or more buckets based on the configuration file provided. However, XML is not a valid supported type for the configuration file.
Ref: https://cloud.google.com/storage/docs/gsutil/commands/lifecycle
Write a script that runs gsutil ls -lr gs://myapp-gcp-ace-logs/** to find and remove items older than 90 days. Repeat this process every morning. is not right.
This manual approach is error-prone, time-consuming and expensive. GCP Cloud Storage provides lifecycle management rules that let you achieve this with minimal effort.
Write a script that runs gsutil ls -l gs://myapp-gcp-ace-logs/** to find and remove items older than 90 days. Schedule the script with cron. is not right.
This manual approach is error-prone, time-consuming and expensive. GCP Cloud Storage provides lifecycle management rules that let you achieve this with minimal effort.
Write a lifecycle management rule in JSON and push it to the bucket with gsutil lifecycle set config-json-file. is the right answer.
You can assign a lifecycle management configuration to a bucket. The configuration contains a set of rules which apply to current and future objects in the bucket. When an object meets the criteria of one of the rules, Cloud Storage automatically performs a specified action on the object. One of the supported actions is to Delete objects. You can set up a lifecycle management to delete objects older than 90 days. gsutil lifecycle set enables you to set the lifecycle configuration on the bucket based on the configuration file. JSON is the only supported type for the configuration file. The config-json-file specified on the command line should be a path to a local file containing the lifecycle configuration JSON document.
Ref: https://cloud.google.com/storage/docs/gsutil/commands/lifecycle
Ref: https://cloud.google.com/storage/docs/lifecycle

NEW QUESTION # 305
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. Too many Pods are already running in the cluster, and there are not enough resources left to schedule the pending Pod.
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. The pending Pod's resource requests are too large to fit on a single node of the cluster.

Answer: B

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 # 306
2. Your auditor wants to view your organization's use of data in Google Cloud. The auditor is most interested in auditing who accessed data in Cloud Storage buckets. You need to help the auditor access the data they need. What should you do?

A. Assign the appropriate permissions, and then create a Data Studio report on Admin Activity Audit Logs
B. Turn on Data Access Logs for the buckets they want to audit, and Then build a query in the log viewer that filters on Cloud Storage
C. Use the export logs API to provide the Admin Activity Audit Logs in the format they want
D. Assign the appropriate permissions, and then use Cloud Monitoring to review metrics

Answer: D

NEW QUESTION # 307
You have an application that receives SSL-encrypted TCP traffic on port 443. Clients for this application are located all over the world. You want to minimize latency for the clients. Which load balancing option should you use?

A. Internal TCP/UDP Load Balancer. Add a firewall rule allowing ingress traffic from 0.0.0.0/0 on the target instances.
B. SSL Proxy Load Balancer
C. HTTPS Load Balancer
D. Network Load Balancer

Answer: B

Explanation:
Reference: https://cloud.google.com/load-balancing/docs/ssl
SSL Proxy Load Balancing support for the following ports: 25, 43, 110, 143, 195, 443, 465, 587, 700, 993,
995, 1883, 3389, 5222, 5432, 5671, 5672, 5900, 5901, 6379, 8085, 8099, 9092, 9200, and 9300. When you use Google- managed SSL certificates with SSL Proxy Load Balancing, the frontend port for traffic must be
443 to enable the Google-managed SSL certificates to be provisioned and renewed.
https://cloud.google.com/load-balancing/images/choose-lb.svg

NEW QUESTION # 308
You've just enabled an API for the developers. A couple of minutes later, one of the developers pastes a screenshot into Slack.
The screenshot indicates that the API isn't enabled. You can see that the project ID is correct. What is the most likely reason for this error?

A. The developer is using the wrong project.
B. The developer didn't run the gcloud refresh api command.
C. The API hasn't completed the process to become fully enabled yet.
D. The developer is trying to use the wrong API.

Answer: C

NEW QUESTION # 309
......

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