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Google Associate-Cloud-Engineer Exam Syllabus Topics:

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

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Google Associate Cloud Engineer Exam Sample Questions (Q264-Q269):

NEW QUESTION # 264
You are building a product on top of Google Kubernetes Engine (GKE). You have a single GKE cluster. For each of your customers, a Pod is running in that cluster, and your customers can run arbitrary code inside their Pod. You want to maximize the isolation between your customers' Pods. What should you do?

A. Use Binary Authorization and whitelist only the container images used by your customers' Pods.
B. Create a GKE node pool with a sandbox type configured to gvisor. Add the parameter runtimeClassName: gvisor to the specification of your customers' Pods.
C. Use the Container Analysis API to detect vulnerabilities in the containers used by your customers' Pods.
D. Use the cos_containerd image for your GKE nodes. Add a nodeSelector with the value cloud.google.com/gke-os-distribution: cos_containerd to the specification of your customers' Pods.

Answer: B

Explanation:
Reference:
GKE Sandbox provides an extra layer of security to prevent untrusted code from affecting the host kernel on your cluster nodes when containers in the Pod execute unknown or untrusted code. Multi-tenant clusters and clusters whose containers run untrusted workloads are more exposed to security vulnerabilities than other clusters. Examples include SaaS providers, web-hosting providers, or other organizations that allow their users to upload and run code. When you enable GKE Sandbox on a node pool, a sandbox is created for each Pod running on a node in that node pool. In addition, nodes running sandboxed Pods are prevented from accessing other Google Cloud services or cluster metadata. Each sandbox uses its own userspace kernel. With this in mind, you can make decisions about how to group your containers into Pods, based on the level of isolation you require and the characteristics of your applications.
Ref: https://cloud.google.com/kubernetes-engine/docs/concepts/sandbox-pods

NEW QUESTION # 265
You are using Container Registry to centrally store your company's container images in a separate project. In another project, you want to create a Google Kubernetes Engine (GKE) cluster. You want to ensure that Kubernetes can download images from Container Registry. What should you do?

A. Configure the ACLs on each image in Cloud Storage to give read-only access to the default Compute Engine service account.
B. In the project where the images are stored, grant the Storage Object Viewer IAM role to the service account used by the Kubernetes nodes.
C. Create a service account, and give it access to Cloud Storage. Create a P12 key for this service account and use it as an imagePullSecrets in Kubernetes.
D. When you create the GKE cluster, choose the Allow full access to all Cloud APIs option under 'Access scopes'.

Answer: B

Explanation:
Configure the ACLs on each image in Cloud Storage to give read-only access to the default Compute Engine service account. is not right.
As mentioned above, Container Registry ignores permissions set on individual objects within the storage bucket so this isnt going to work.
Ref: https://cloud.google.com/container-registry/docs/access-control

NEW QUESTION # 266
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?

A. Increase the maximum number of Cloud Run instances.
B. Set a minimum concurrent requests environment variable for the application.
C. Use traffic splitting
D. Modify the minimum number of Cloud Run instances.

Answer: A

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
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 # 267
Your company has a 3-tier solution running on Compute Engine. The configuration of the current infrastructure is shown below.

Each tier has a service account that is associated with all instances within it. You need to enable communication on TCP port 8080 between tiers as follows:
* Instances in tier #1 must communicate with tier #2.
* Instances in tier #2 must communicate with tier #3.
What should you do?

A. 1. Create an ingress firewall rule with the following settings:* Targets: all instances with tier #2 service account* Source filter: all instances with tier #1 service account* Protocols: allow all2. Create an ingress firewall rule with the following settings:* Targets: all instances with tier #3 service account* Source filter: all instances with tier #2 service account* Protocols: allow all
B. 1. Create an egress firewall rule with the following settings:* Targets: all instances* Source filter: IP ranges (with the range set to 10.0.2.0/24)* Protocols: allow TCP: 80802. Create an egress firewall rule with the following settings:* Targets: all instances* Source filter: IP ranges (with the range set to 10.0.1.0/24)* Protocols: allow TCP: 8080
C. 1. Create an ingress firewall rule with the following settings:* Targets: all instances* Source filter: IP ranges (with the range set to 10.0.2.0/24)* Protocols: allow all2. Create an ingress firewall rule with the following settings:* Targets: all instances* Source filter: IP ranges (with the range set to 10.0.1.0/24)* Protocols: allow all
D. 1. Create an ingress firewall rule with the following settings:* Targets: all instances with tier #2 service account* Source filter: all instances with tier #1 service account* Protocols: allow TCP:80802. Create an ingress firewall rule with the following settings:* Targets: all instances with tier #3 service account* Source filter: all instances with tier #2 service account* Protocols: allow TCP: 8080

Answer: D

Explanation:
1. Create an ingress firewall rule with the following settings: "* Targets: all instances with tier #2 service account "* Source filter: all instances with tier #1 service account "* Protocols: allow TCP:8080 2. Create an ingress firewall rule with the following settings:
"* Targets: all instances with tier #3 service account "* Source filter: all instances with tier #2 service account "* Protocols: allow TCP: 8080

NEW QUESTION # 268
You are setting up a Windows VM on Compute Engine and want to make sure you can log in to the VM via RDP. What should you do?

A. After the VM has been created, use gcloud compute reset-windows-password to retrieve the login credentials for the VM.
B. After the VM has been created, download the JSON private key for the default Compute Engine service account. Use the credentials in the JSON file to log in to the VM.
C. When creating the VM, add metadata to the instance using `windows-password' as the key and a password as the value.
D. After the VM has been created, use your Google Account credentials to log in into the VM.

Answer: A

Explanation:
https://cloud.google.com/sdk/gcloud/reference/beta/compute/reset-windows-password

NEW QUESTION # 269
......

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