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Google Professional-Cloud-Developer Prüfungsplan:

ThemaEinzelheiten
Thema 1
  • Defining Database Schemas For Google-Managed Databases
  • Re-Architecting Applications From Local Services To Google Cloud Platform
Thema 2
  • Deploying Applications And Services On Google Kubernetes Engine
  • Deploying Applications And Services On Google Kubernetes Engine
Thema 3
  • Launching A Compute Instance Using GCP Console And Cloud SDK
  • Creating An Autoscaled Managed Instance Group Using An Instance Template
Thema 4
  • Eploying Applications And Services On Compute Engine
  • Deploying An Application To App Engine
Thema 5
  • Designing Highly Scalable, Available, And Reliable Cloud-Native Applications
  • Geographic Distribution Of Google Cloud Services
Thema 6
  • Automating Resource Provisioning With Deployment Manager
  • Creating An Instance With A Startup Script That Installs Software
Thema 7
  • Developing An Integration Pipeline Using Services
  • Emulating GCP Services For Local Application Development
Thema 8
  • Security Mechanisms That Protect Services And Resources
  • Choosing Data Storage Options Based On Use Case Considerations
Thema 9
  • Reading And Updating An Entity In A Cloud Datastore Transaction From An Application
  • Using Apis To Read
  • Write To Data Services

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Google Certified Professional - Cloud Developer Professional-Cloud-Developer Prüfungsfragen mit Lösungen (Q181-Q186):

181. Frage
You have a mixture of packaged and internally developed applications hosted on a Compute Engine instance that is running Linux. These applications write log records as text in local files. You want the logs to be written to Cloud Logging. What should you do?

  • A. Pipe the content of the files to the Linux Syslog daemon.
  • B. Install a Google version of collectd on the Compute Engine instance.
  • C. Using cron, schedule a job to copy the log files to Cloud Storage once a day.
  • D. Install a Google version of fluentd on the Compute Engine instance.

Antwort: D


182. Frage
Case Study
Company Overview
HipLocal is a community application designed to facilitate communication between people in close proximity. It is used for event planning and organizing sporting events, and for businesses to connect with their local communities. HipLocal launched recently in a few neighborhoods in Dallas and is rapidly growing into a global phenomenon. Its unique style of hyper-local community communication and business outreach is in demand around the world.
Executive Statement
We are the number one local community app; it's time to take our local community services global. Our venture capital investors want to see rapid growth and the same great experience for new local and virtual communities that come online, whether their members are 10 or 10000 miles away from each other.
Solution Concept
HipLocal wants to expand their existing service, with updated functionality, in new regions to better serve their global customers. They want to hire and train a new team to support these regions in their time zones. They will need to ensure that the application scales smoothly and provides clear uptime data.
Existing Technical Environment
HipLocal's environment is a mix of on-premises hardware and infrastructure running in Google Cloud Platform.
The HipLocal team understands their application well, but has limited experience in global scale applications.
Their existing technical environment is as follows:
* Existing APIs run on Compute Engine virtual machine instances hosted in GCP.
* State is stored in a single instance MySQL database in GCP.
* Data is exported to an on-premises Teradata/Vertica data warehouse.
* Data analytics is performed in an on-premises Hadoop environment.
* The application has no logging.
* There are basic indicators of uptime; alerts are frequently fired when the APIs are unresponsive.
Business Requirements
HipLocal's investors want to expand their footprint and support the increase in demand they are seeing. Their requirements are:
* Expand availability of the application to new regions.
* Increase the number of concurrent users that can be supported.
* Ensure a consistent experience for users when they travel to different regions.
* Obtain user activity metrics to better understand how to monetize their product.
* Ensure compliance with regulations in the new regions (for example, GDPR).
* Reduce infrastructure management time and cost.
* Adopt the Google-recommended practices for cloud computing.
Technical Requirements
* The application and backend must provide usage metrics and monitoring.
* APIs require strong authentication and authorization.
* Logging must be increased, and data should be stored in a cloud analytics platform.
* Move to serverless architecture to facilitate elastic scaling.
* Provide authorized access to internal apps in a secure manner.
HipLocal wants to reduce the number of on-call engineers and eliminate manual scaling.
Which two services should they choose? (Choose two.)

  • A. Use Knative to build and deploy serverless applications.
  • B. Use a large Google Compute Engine cluster for deployments.
  • C. Use serverless Google Cloud Functions.
  • D. Use Google App Engine services.
  • E. Use Google Kubernetes Engine for automated deployments.

Antwort: A,C

Begründung:
Explanation/Reference:


183. Frage
You have an HTTP Cloud Function that is called via POST. Each submission's request body has a flat, unnested JSON structure containing numeric and text dat a. After the Cloud Function completes, the collected data should be immediately available for ongoing and complex analytics by many users in parallel. How should you persist the submissions?

  • A. Persist each POST request's JSON data as an individual file within Cloud Storage, with the file name containing the request identifier.
  • B. Transform the POST request's JSON data, and stream it into BigQuery.
  • C. Transform the POST request's JSON data, and store it in a regional Cloud SQL cluster.
  • D. Directly persist each POST request's JSON data into Datastore.

Antwort: A


184. Frage
Your organization has recently begun an initiative to replatform their legacy applications onto Google Kubernetes Engine. You need to decompose a monolithic application into microservices. Multiple instances have read and write access to a configuration file, which is stored on a shared file system. You want to minimize the effort required to manage this transition, and you want to avoid rewriting the application code.
What should you do?

  • A. Create a new Cloud Storage bucket, and mount it via FUSE in the container.
  • B. Create a new Filestore instance, and mount the volume as an NFS PersistentVolume.
  • C. Create a new persistent disk, and mount the volume as a shared PersistentVolume.
  • D. Create a new ConfigMap and volumeMount to store the contents of the configuration file.

Antwort: D

Begründung:
Explanation
https://cloud.google.com/kubernetes-engine/docs/concepts/configmap
ConfigMaps bind non-sensitive configuration artifacts such as configuration files, command-line arguments, and environment variables to your Pod containers and system components at runtime.
A ConfigMap separates your configurations from your Pod and components, which helps keep your workloads portable. This makes their configurations easier to change and manage, and prevents hardcoding configuration data to Pod specifications.


185. Frage
Your team develops stateless services that run on Google Kubernetes Engine (GKE). You need to deploy a new service that will only be accessed by other services running in the GKE cluster. The service will need to scale as quickly as possible to respond to changing load. What should you do?

  • A. Use a Horizontal Pod Autoscaler to scale the containers, and expose them via a NodePort Service.
  • B. Use a Vertical Pod Autoscaler to scale the containers, and expose them via a NodePort Service.
  • C. Use a Vertical Pod Autoscaler to scale the containers, and expose them via a ClusterIP Service.
  • D. Use a Horizontal Pod Autoscaler to scale the containers, and expose them via a ClusterIP Service.

Antwort: D

Begründung:
Explanation
https://cloud.google.com/kubernetes-engine/docs/concepts/service


186. Frage
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