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Google Associate-Cloud-Engineer Exam Syllabus Topics:

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

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Google Associate Cloud Engineer Exam Sample Questions (Q77-Q82):

NEW QUESTION # 77
You are planning to migrate your on-premises VMs to Google Cloud. You need to set up a landing zone in Google Cloud before migrating the VMs. You must ensure that all VMs in your production environment can communicate with each other through private IP addresses. You need to allow all VMs in your Google Cloud organization to accept connections on specific TCP ports. You want to follow Google-recommended practices, and you need to minimize your operational costs. What should you do?

A. Create individual VPCs for each Google Cloud project. Peer all the VPCs together. Apply hierarchical firewall policies on the organization level.
B. Create a host VPC project with each production project as its service project. Apply organization policies on the organization level.
C. Create a host VPC project with each production project as its service project. Apply hierarchical firewall policies on the organization level.
D. Create individual VPCs per Google Cloud project. Peer all the VPCs together. Apply organization policies on the organization level.

Answer: C

Explanation:
The goal is to create a landing zone facilitating private IP communication across production projects and apply organization-wide firewall rules, following best practices and minimizing operational costs.
Network Structure:Individual VPCs with Peering (A, B): While VPC Peering allows private connectivity, managing a full mesh or complex peering topology across many projects becomes operationally complex and can hit peering limits. It's not the recommended pattern for centralized connectivity in a landing zone.
Shared VPC (C, D): This is the Google-recommended practice for scenarios where resources from multiple projects need to communicate privately within a common VPC network. A central host project owns the network, and service projects use it. This simplifies network administration and connectivity.
Firewall Rules:Organization Policies (A, C): These enforce organizational constraints (e.g., disable external IPs, restrict locations) but do not define specific network firewall rules (like allowing TCP ports).
Hierarchical Firewall Policies (B, D): These allow defining firewall rules at the Organization or Folder level, which are inherited by resources in descendant projects/folders. This is the mechanism to apply consistent firewall rules (like allowing specific TCP ports) across all VMs in the organization (or a specific folder) efficiently, without managing rules in each individual VPC or project.
Combining Shared VPC for the network structure (best practice for cross-project private communication and central management) with Hierarchical Firewall Policies (for applying organization-wide firewall rules) meets all requirements efficiently and follows Google recommendations.
References:
Shared VPC Overview: "Shared VPC allows an organization to connect resources from multiple projects to a common Virtual Private Cloud (VPC) network..." - https://cloud.google.com/vpc/docs/shared-vpc Hierarchical firewall policies: "Hierarchical firewall policies let you create and enforce a consistent firewall policy across your organization... They can be configured to explicitly deny traffic, or allow traffic..." -
https://cloud.google.com/firewall/docs/hierarchical-firewall-policies
Google Cloud security foundations guide: Often recommends Shared VPC and centralized firewall management (using Hierarchical Firewalls or traditional firewalls with tags in the host project) as part of a secure landing zone. - (Conceptual reference, specific document may vary)

NEW QUESTION # 78
Your team is building a website that handles votes from a large user population. The incoming votes will arrive at various rates. You want to optimize the storage and processing of the votes. What should you do?

A. Save the incoming votes to a JSON file on Cloud Storage. Process the votes in a batch at the end of the day.
B. Save the incoming votes to Firestore. Use Cloud Scheduler to trigger a Cloud Functions instance to periodically process the votes.
C. Use a dedicated instance to process the incoming votes. Send the votes directly to this instance.
D. Save the incoming votes to Pub/Sub. Use the Pub/Sub topic to trigger a Cloud Functions instance to process the votes.

Answer: C

Explanation:
Pub/Sub is a scalable and reliable messaging service that can handle large volumes of data from different sources at different rates. It allows you to decouple the producers and consumers of the data, and provides a durable and persistent storage for the messages until they are delivered. Cloud Functions is a serverless platform that can execute code in response to events, such as messages published to a Pub/Sub topic. It can scale automatically based on the load, and you only pay for the resources you use. By using Pub/Sub and Cloud Functions, you can optimize the storage and processing of the votes, as you can handle the variable rates of incoming votes, process them in real time or near real time, and avoid managing servers or VMs. References:
* Pub/Sub documentation
* Cloud Functions documentation
* Choosing a messaging service for Google Cloud

NEW QUESTION # 79
Your team maintains the infrastructure for your organization. The current infrastructure requires changes. You need to share your proposed changes with the rest of the team. You want to follow Google's recommended best practices. What should you do?

A. Use Deployment Manager templates to describe the proposed changes and store them in Cloud Source Repositories.
B. Use Deployment Manager templates to describe the proposed changes and store them in a Cloud Storage bucket.
C. Apply the change in a development environment, run gcloud compute instances list, and then save the output in a shared Storage bucket.
D. Apply the change in a development environment, run gcloud compute instances list, and then save the output in Cloud Source Repositories.

Answer: A

NEW QUESTION # 80
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 auditors group to two new custom IAM roles.
B. Add the auditors group to the 'logging.viewer' and 'bigQuery.dataViewer' predefined IAM roles.
C. Add the auditor user accounts to two new custom IAM roles.
D. Add the auditor user accounts to the 'logging.viewer' and 'bigQuery.dataViewer' predefined IAM roles.

Answer: B

Explanation:
https://cloud.google.com/iam/docs/job-functions/auditing#scenario_external_auditors Because if you directly add users to the IAM roles, then if any users left the organization then you have to remove the users from multiple places and need to revoke his/her access from multiple places. But, if you put a user into a group then its very easy to manage these type of situations. Now, if any user left then you just need to remove the user from the group and all the access got revoked The organization creates a Google group for these external auditors and adds the current auditor to the group. This group is monitored and is typically granted access to the dashboard application. During normal access, the auditors' Google group is only granted access to view the historic logs stored in BigQuery. If any anomalies are discovered, the group is granted permission to view the actual Cloud Logging Admin Activity logs via the dashboard's elevated access mode. At the end of each audit period, the group's access is then revoked. Data is redacted using Cloud DLP before being made accessible for viewing via the dashboard application. The table below explains IAM logging roles that an Organization Administrator can grant to the service account used by the dashboard, as well as the resource level at which the role is granted.

NEW QUESTION # 81
You are using Google Kubernetes Engine with autoscaling enabled to host a new application. You want to expose this new application to the public, using HTTPS on a public IP address. What should you do?

A. Create a HAProxy pod in the cluster to load-balance the traffic to all the pods of the application.Forward the public traffic to HAProxy with an iptable rule. Configure the DNS name of your application using the public IP of the node HAProxy is running on.
B. Create a Kubernetes Service of type ClusterIP for your application. Configure the public DNS name of your application using the IP of this Service.
C. Create a Kubernetes Service of type NodePort for your application, and a Kubernetes Ingress to expose this Service via a Cloud Load Balancer.
D. Create a Kubernetes Service of type NodePort to expose the application on port 443 of each node of the Kubernetes cluster. Configure the public DNS name of your application with the IP of every node of the cluster to achieve load-balancing.

Answer: C

Explanation:
Reference: https://cloud.google.com/kubernetes-engine/docs/tutorials/http-balancer Create a Kubernetes Service of type ClusterIP for your application. Configure the public DNS name of your application using the IP of this Service. is not right.
Kubernetes Service of type ClusterIP exposes the Service on a cluster-internal IP. Choosing this value makes the Service only reachable from within the cluster so you can not route external traffic to this IP.
Ref: https://kubernetes.io/docs/concepts/services-networking/service/

NEW QUESTION # 82
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