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Google Associate-Cloud-Engineer Exam Syllabus Topics:

SectionWeightObjectives
Configuring Access and Security15-20%- Viewing audit logs
  • 1. Configuring audit log policies
  • 2. Accessing and analyzing Cloud Audit Logs
- Managing service accounts
  • 1. Creating and managing service accounts
  • 2. Assigning service accounts to resources
  • 3. Using service account keys
- Managing IAM resources
  • 1. Applying IAM policies to resources
  • 2. Creating and managing IAM roles
  • 3. Defining custom IAM roles
Ensuring Successful Operation15-20%- Managing storage and data solutions
  • 1. Managing Cloud Storage buckets and objects
  • 2. Configuring CORS and encryption
  • 3. Setting lifecycle policies
- Managing Cloud Run resources
  • 1. Configuring resource limits
  • 2. Managing revisions and traffic splitting
- Managing Compute Engine resources
  • 1. Managing instances, disks, and snapshots
  • 2. Attaching and detaching disks
  • 3. Resizing instances and persistent disks
- Managing Kubernetes Engine resources
  • 1. Scaling clusters and node pools
  • 2. Managing workloads (Deployments, Services, HPA)
  • 3. Upgrading clusters
- Managing logging and monitoring
  • 1. Viewing and analyzing logs
  • 2. Using Cloud Monitoring and Logging
  • 3. Creating metrics and alerts
Planning and Configuring a Cloud Solution20-25%- 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. Designing VPC networks
  • 2. Configuring load balancing and firewall rules
- Planning and configuring data storage options
  • 1. Choosing between Cloud Storage, Filestore, Persistent Disk
  • 2. Selecting appropriate storage classes
- Planning and configuring compute resources
  • 1. Selecting appropriate machine types and zones
  • 2. Configuring persistent disks and local SSDs
Deploying and Implementing a Cloud Solution20-25%- Deploying and managing Cloud Run resources
  • 1. Deploying containerized applications to Cloud Run
  • 2. Configuring memory limits and scaling settings
- Deploying and managing Kubernetes Engine resources
  • 1. Deploying workloads with Deployments and Services
  • 2. Creating and managing GKE clusters
  • 3. Configuring kubectl for cluster access
- Deploying and managing Compute Engine resources
  • 1. Creating and managing instances with startup scripts
  • 2. Creating and managing managed instance groups
  • 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 Cloud Functions
  • 1. Configuring triggers and environment variables
  • 2. Creating and triggering Cloud Functions
Setting Up a Cloud Solution Environment20-25%- Setting up cloud projects and accounts
  • 1. Managing billing budgets and alerts
  • 2. Creating and managing projects
  • 3. Assigning IAM roles to users and groups
- Managing billing configuration
  • 1. Creating billing accounts
  • 2. Linking billing to projects
  • 3. Setting up budget alerts and notifications

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Google Associate Cloud Engineer Exam Sample Questions (Q167-Q172):

NEW QUESTION # 167
You deployed a new application inside your Google Kubernetes Engine cluster using the YAML file specified below.

You check the status of the deployed pods and notice that one of them is still in PENDING status:

You want to find out why the pod is stuck in pending status. What should you do?

Answer: D

Explanation:
https://kubernetes.io/docs/tasks/debug-application-cluster/debug-application/#debugging-pods


NEW QUESTION # 168
Your web application is hosted on Cloud Run and needs to query a Cloud SQL database. Every morning during a traffic spike, you notice API quota errors in Cloud SQL logs. The project has already reached the maximum API quota. You want to make a configuration change to mitigate the issue. What should you do?

Answer: C

Explanation:
The issue is Cloud SQL API quota errors caused by too many new Cloud Run instances being created simultaneously during a traffic spike. Each new instance attempts a connection to Cloud SQL, consuming the connection API quota.
The Documented Solution (Not an Option): Google's official documentation states the correct mitigation for this specific error is to decrease the maximum number of Cloud Run instances to slow the rate of new instance creation.
Flawed Option Set: Since the correct mitigation is not an option, and increasing the maximum instances (D) would technically worsen the quota error, the question is structurally flawed. However, in the context of general autoscaling management, Option D is the configuration control point for the upper limit of scaling. In many exam scenarios, this forces the selection of the control that directly impacts the scaling capacity, even if the intended direction is incorrect for the specific error given. We select D as the configuration change most directly related to the number of instances, while acknowledging the documentation advises the opposite action.
Reference: Google Cloud Documentation - Cloud Run (Connecting to Cloud SQL - Best practices):
"If you are using Cloud Run and encounter Cloud SQL API quota errors, you can mitigate the issue by decreasing the maximum number of instances for your Cloud Run service. This prevents too many new instances from being created at once..."


NEW QUESTION # 169
You create a new Google Kubernetes Engine (GKE) cluster and want to make sure that it always runs a supported and stable version of Kubernetes. What should you do?

Answer: B

Explanation:
Creating or upgrading a cluster by specifying the version as <latest> does not provide automatic upgrades. Enable automatic node upgrades to ensure that the nodes in your cluster up to date with the latest stable version.
https://cloud.google.com/kubernetes-engine/versioning-and-upgrades


NEW QUESTION # 170
Your company uses a multi-cloud strategy that includes Google Cloud. You want to centralize application logs in a third-party software-as-a-service (SaaS) tool from all environments. You need to integrate logs originating from Cloud Logging, and you want to ensure the export occurs with the least amount of delay possible. What should you do?

Answer: A

Explanation:
Exporting logs via a Cloud Logging sink to a Pub/Sub topic is the best option when you need low- latency, near real-time delivery of logs. Pub/Sub is designed for streaming data and can immediately deliver logs to the third-party SaaS tool that subscribes to the topic.


NEW QUESTION # 171
You are using Looker Studio to visualize a table from your data warehouse that is built on top of BigQuery. Data is appended to the data warehouse during the day. At night, the daily summary is recalculated by overwriting the table. You just noticed that the charts in Looker Studio are broken, and you want to analyze the problem. What should you do?

Answer: A


NEW QUESTION # 172
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