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

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Associate-Cloud-Engineer PrüfungGuide, Google Associate-Cloud-Engineer Zertifikat - Google Associate Cloud Engineer Exam

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Google Associate Cloud Engineer Exam Associate-Cloud-Engineer Prüfungsfragen mit Lösungen (Q87-Q92):

87. Frage
You are planning to migrate your on-premises data to Google Cloud. The data includes:
- 200 TB of video files in SAN storage
- Data warehouse data stored on Amazon Redshift
- 20 GB of PNG files stored on an S3 bucket
You need to load the video files into a Cloud Storage bucket, transfer the data warehouse data into BigQuery, and load the PNG files into a second Cloud Storage bucket. You want to follow Google-recommended practices and avoid writing any code for the migration. What should you do?

A. Use Cloud Data Fusion for the video files, Dataflow for the data warehouse data, and Storage Transfer Service for the PNG files.
B. Use Storage Transfer Service for the video files, BigQuery Data Transfer Service for the data warehouse data, and Storage Transfer Service for the PNG files.
C. Use gcloud storage for the video files, Dataflow for the data warehouse data, and Storage Transfer Service for the PNG files.
D. Use Transfer Appliance for the videos, BigQuery Data Transfer Service for the data warehouse data, and Storage Transfer Service for the PNG files.

Antwort: D

Begründung:
Transfer Appliance for Video Files: Given the large size of the video files (200 TB) in SAN storage, using Google's Transfer Appliance is a practical solution. Transfer Appliance is a hardware solution provided by Google for transferring large amounts of data. It is well-suited for scenarios where uploading data over the internet is too slow or not feasible.
BigQuery Data Transfer Service for Data Warehouse Data: To migrate data from Amazon Redshift to BigQuery, the BigQuery Data Transfer Service is the appropriate tool. It automates the migration of data from several sources, including Amazon Redshift, into BigQuery.
Storage Transfer Service for PNG Files: The Storage Transfer Service is ideal for moving data from Amazon S3 to Google Cloud Storage. It simplifies the process of importing your PNG files from S3 to a Cloud Storage bucket.

88. Frage
You created a Google Cloud Platform project with an App Engine application inside the project. You initially configured the application to be served from the us-central region. Now you want the application to be served from the asia-northeast1 region. What should you do?

A. Create a second App Engine application in the existing GCP project and specify asia-northeast1 as the region to serve your application.
B. Create a new GCP project and create an App Engine application inside this new project. Specify asia-northeast1 as the region to serve your application.
C. Change the default region property setting in the existing GCP project to asia-northeast1.
D. Change the region property setting in the existing App Engine application from us-central to asia-northeast1.

Antwort: B

Begründung:
https://cloud.google.com/appengine/docs/flexible/managing-projects-apps-billing#:~:text=Each%20Cloud%20pr Two App engine can't be running on the same project: you can check this easy diagram for more info:
https://cloud.google.com/appengine/docs/standard/an-overview-of-app-engine#components_of_an_application And you can't change location after setting it for your app Engine.
https://cloud.google.com/appengine/docs/standard/locations
App Engine is regional and you cannot change an apps region after you set it. Therefore, the only way to have an app run in another region is by creating a new project and targeting the app engine to run in the required region (asia-northeast1 in our case).
Ref: https://cloud.google.com/appengine/docs/locations

89. Frage
You have a virtual machine that is currently configured with 2 vCPUs and 4 GB of memory. It is running out of memory. You want to upgrade the virtual machine to have 8 GB of memory. What should you do?

A. Use gcloud to add metadata to the VM. Set the key to required-memory-size and the value to 8 GB.
B. Stop the VM, increase the memory to 8 GB, and start the VM.
C. Rely on live migration to move the workload to a machine with more memory.
D. Stop the VM, change the machine type to n1-standard-8, and start the VM.

Antwort: B

Begründung:
In Google compute engine, if predefined machine types don't meet your needs, you can create an instance with custom virtualized hardware settings. Specifically, you can create an instance with a custom number of vCPUs and custom memory, effectively using a custom machine type. Custom machine types are ideal for the following scenarios: 1. Workloads that aren't a good fit for the predefined machine types that are available to you. 2. Workloads that require more processing power or more memory but don't need all of the upgrades that are provided by the next machine type level.In our scenario, we only need a memory upgrade. Moving to a bigger instance would also bump up the CPU which we don't need so we have to use a custom machine type. It is not possible to change memory while the instance is running so you need to first stop the instance, change the memory and then start it again. See below a screenshot that shows how CPU/Memory can be customized for an instance that has been stopped.Ref: https://cloud.google.com/compute/docs/instances
/creating-instance-with-custom-machine-type

90. Frage
You want to select and configure a solution for storing and archiving data on Google Cloud Platform. You need to support compliance objectives for data from one geographic location. This data is archived after 30 days and needs to be accessed annually. What should you do?

A. Select Multi-Regional Storage. Add a bucket lifecycle rule that archives data after 30 days to Coldline Storage.
B. Select Regional Storage. Add a bucket lifecycle rule that archives data after 30 days to Coldline Storage.
C. Select Multi-Regional Storage. Add a bucket lifecycle rule that archives data after 30 days to Nearline Storage.
D. Select Regional Storage. Add a bucket lifecycle rule that archives data after 30 days to Nearline Storage.

Antwort: B

Begründung:
Google Cloud Coldline is a new cold-tier storage for archival data with access frequency of less than once per year. Unlike other cold storage options, Nearline has no delays prior to data access, so now it is the leading solution among competitors.
The Real description is about Coldline storage Class:
Coldline Storage
Coldline Storage is a very-low-cost, highly durable storage service for storing infrequently accessed data.
Coldline Storage is a better choice than Standard Storage or Nearline Storage in scenarios where slightly lower availability, a 90-day minimum storage duration, and higher costs for data access are acceptable trade-offs for lowered at-rest storage costs.
Coldline Storage is ideal for data you plan to read or modify at most once a quarter. Note, however, that for data being kept entirely for backup or archiving purposes, Archive Storage is more cost-effective, as it offers the lowest storage costs.
https://cloud.google.com/storage/docs/storage-classes#coldline

91. Frage
You want to add a new auditor to a Google Cloud Platform project. The auditor should be allowed to read, but not modify, all project items.
How should you configure the auditor's permissions?

A. Select the built-in IAM service Viewer role. Add the user's account to this role.
B. Create a custom role with view-only project permissions. Add the user's account to the custom role.
C. Create a custom role with view-only service permissions. Add the user's account to the custom role.
D. Select the built-in IAM project Viewer role. Add the user's account to this role.

Antwort: D

Begründung:
roles/Viewer role provides access to all resources under the projects but do not alter the state of these resources.
https://cloud.google.com/resource-manager/docs/access-control-proj

92. Frage
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