Open the auxiliary access

Firefly Open Source Community

   Login   |   Register   |
New_Topic
Firefly Open Source Community › Embedded Board › ROC-RK3328-PC› Associate-Cloud-Engineer Probesfragen - Associate-Cl ...
New Topic
Print Previous Topic Next Topic

[General] Associate-Cloud-Engineer Probesfragen - Associate-Cloud-Engineer Testing Engine

royclar438

130

Credits

0

Prestige

0

Contribution

registered members

Rank: 2

Credits
130

【General】 Associate-Cloud-Engineer Probesfragen - Associate-Cloud-Engineer Testing Engine

Posted at 8 hour before      View：2 | Replies：0        Print      Only Author   [Copy Link] 1#
BONUS!!! Laden Sie die vollständige Version der ITZert Associate-Cloud-Engineer Prüfungsfragen kostenlos herunter: https://drive.google.com/open?id=12N5tW_MR6EZMsw6eAqRmN0_tNgYBhyFo
Nach den Forschungen in den letzten Jahren sind die Fragen und Antworten zur Google Associate-Cloud-Engineer Zertifizierungsprüfung von ITZert den realen Prüfung sehr ähnlich. ITZert verspricht, dass Sie zum ersten Mal die Google Associate-Cloud-Engineer (Google Associate Cloud Engineer Exam) Zertifizierungsprüfung 100% bestehen können.
Um die Google Associate-Cloud-Engineer-Zertifizierung zu erlangen, müssen Kandidaten ein gutes Verständnis für die GCP-Infrastruktur, Netzwerk- und Speicherdienste haben. Sie sollten auch Erfahrung im Bereitstellen und Verwalten von Anwendungen auf GCP haben. Die Zertifizierungsprüfung besteht aus Multiple-Choice-Fragen und praktischen Szenarien, die das Wissen und die Fähigkeiten des Kandidaten in diesen Bereichen testen.
Die Zertifizierungsprüfung besteht aus Multiple-Choice-Fragen, und die Kandidaten haben zwei Stunden Zeit, um die Prüfung abzuschließen. Die Fragen sollen das Wissen und die praktischen Fähigkeiten des Kandidaten im Cloud -Computing testen. Die Prüfung ist in mehreren Sprachen erhältlich und kann online oder in einem Testzentrum durchgeführt werden. Nachdem die Prüfung bestanden hat, erhalten die Kandidaten ein Zertifikat, das ihre Fähigkeiten und Kenntnisse in GCP -Lösungen bestätigt. Die Google Associate-Cloud-Engineer-Zertifizierungsprüfung bietet Cloud-Fachleuten eine hervorragende Gelegenheit, ihre Fähigkeiten zu verbessern und ihre Karriereaussichten im Bereich Cloud Computing voranzutreiben.
Neuester und gültiger Associate-Cloud-Engineer Test VCE Motoren-Dumps und Associate-Cloud-Engineer neueste Testfragen für die IT-PrüfungenWollen Sie die Google Associate-Cloud-Engineer Zertifizierungsprüfung schnell bestehen? Dann wählen Sie doch unseren ITZert, der Ihren Traum schnell verwirklichen kann. Unser ITZert bietet die genauen Prüfungsmaterialien zu den IT-Zertifizierungsprüfungen. Unser ITZert kann den IT-Fachleuten helfen, im Beruf befördert zu werden. Unsere Kräfte sind unglaublich stark. Sie können im Internet die Demo zur Google Associate-Cloud-Engineer Prüfung kostenlos herunterladen, so dass Sie die Glaubwürdigkeit von ITZert testen können.
Die Google Associate-Cloud-Engineer-Prüfung ist eine 2-stündige begleitete Prüfung, die aus 50 Multiple-Choice- und Multiple-Select-Fragen besteht. Die Prüfung kann persönlich in einem Testzentrum oder online von zu Hause oder aus dem Büro heraus abgelegt werden. Kandidaten müssen mindestens 70% erreichen, um die Prüfung zu bestehen und ihre Zertifizierung zu erhalten.
Google Associate Cloud Engineer Exam Associate-Cloud-Engineer Prüfungsfragen mit Lösungen (Q64-Q69):64. Frage
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 Kubernetes Service of type NodePort for your application, and a Kubernetes Ingress to expose this Service via a Cloud Load Balancer.
  • B. 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.
  • C. 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.
  • D. Create a Kubernetes Service of type ClusterIP for your application. Configure the public DNS name of your application using the IP of this Service.
Antwort: A
Begründung:
Explanation/Reference: https://cloud.google.com/kuberne ... rials/http-balancer

65. Frage
You are managing several Google Cloud Platform (GCP) projects and need access to all logs for the past 60 days. You want to be able to explore and quickly analyze the log contents. You want to follow Google- recommended practices to obtain the combined logs for all projects. What should you do?
  • A. Create a Stackdriver Logging Export with a Sink destination to Cloud Storage. Create a lifecycle rule to delete objects after 60 days.
  • B. Create a Stackdriver Logging Export with a Sink destination to a BigQuery dataset. Configure the table expiration to 60 days.
  • C. Configure a Cloud Scheduler job to read from Stackdriver and store the logs in BigQuery. Configure the table expiration to 60 days.
  • D. Navigate to Stackdriver Logging and select resource.labels.project_id="*"
Antwort: B
Begründung:
* Navigate to Stackdriver Logging and select resource.labels.project_id=*. is not right.
Log entries are held in Stackdriver Logging for a limited time known as the retention period which is 30 days (default configuration). After that, the entries are deleted. To keep log entries longer, you need to export them outside of Stackdriver Logging by configuring log sinks.
Ref: https://cloud.google.com/blog/pr ... cloud-audit-logging
* Configure a Cloud Scheduler job to read from Stackdriver and store the logs in BigQuery. Configure the table expiration to 60 days. is not right.
While this works, it makes no sense to use Cloud Scheduler job to read from Stackdriver and store the logs in BigQuery when Google provides a feature (export sinks) that does exactly the same thing and works out of the box.Ref: https://cloud.google.com/logging/docs/export/configure_export_v2
* Create a Stackdriver Logging Export with a Sink destination to Cloud Storage. Create a lifecycle rule to delete objects after 60 days. is not right.
You can export logs by creating one or more sinks that include a logs query and an export destination.
Supported destinations for exported log entries are Cloud Storage, BigQuery, and Pub/Sub.Ref: https://cloud.
google.com/logging/docs/export/configure_export_v2
Sinks are limited to exporting log entries from the exact resource in which the sink was created: a Google Cloud project, organization, folder, or billing account. If it makes it easier to exporting from all projects of an organication, you can create an aggregated sink that can export log entries from all the projects, folders, and billing accounts of a Google Cloud organization.Ref: https://cloud.google.com/logging/docs/export
/aggregated_sinks
Either way, we now have the data in Cloud Storage, but querying logs information from Cloud Storage is harder than Querying information from BigQuery dataset. For this reason, we should prefer Big Query over Cloud Storage.
* Create a Stackdriver Logging Export with a Sink destination to a BigQuery dataset. Configure the table expiration to 60 days. is the right answer.
You can export logs by creating one or more sinks that include a logs query and an export destination.
Supported destinations for exported log entries are Cloud Storage, BigQuery, and Pub/Sub.Ref: https://cloud.
google.com/logging/docs/export/configure_export_v2
Sinks are limited to exporting log entries from the exact resource in which the sink was created: a Google Cloud project, organization, folder, or billing account. If it makes it easier to exporting from all projects of an organication, you can create an aggregated sink that can export log entries from all the projects, folders, and billing accounts of a Google Cloud organization.Ref: https://cloud.google.com/logging/docs/export
/aggregated_sinks
Either way, we now have the data in a BigQuery Dataset. Querying information from a Big Query dataset is easier and quicker than analyzing contents in Cloud Storage bucket. As our requirement is to Quickly analyze the log contents, we should prefer Big Query over Cloud Storage.
Also, You can control storage costs and optimize storage usage by setting the default table expiration for newly created tables in a dataset. If you set the property when the dataset is created, any table created in the dataset is deleted after the expiration period. If you set the property after the dataset is created, only new tables are deleted after the expiration period.For example, if you set the default table expiration to 7 days, older data is automatically deleted after 1 week.Ref: https://cloud.google.com/bigquery/docs/best-practices- storage

66. Frage
You've created a Pod using the kubectl run command. Now you're attempting to remove the Pod, and it keeps being recreated. Which command might help you as you attempt to remove the pod?
  • A. gcloud container describe pods
  • B. kubectl get secrets
  • C. kubectl get deployments
  • D. kubectl get pods
Antwort: C

67. Frage
You need to reduce GCP service costs for a division of your company using the fewest possible steps. You need to turn off all configured services in an existing GCP project. What should you do?
  • A. 1. Verify that you are assigned the Organizational Administrators IAM role for this project.
    2. Switch to the project in the GCP console, locate the resources and delete them.
  • B. 1. Verify that you are assigned the Organizational Administrator IAM role for this project.
    2. Locate the project in the GCP console, enter the project ID and then click Shut down.
  • C. 1. Verify that you are assigned the Project Owners IAM role for this project.
    2. Locate the project in the GCP console, click Shut down and then enter the project ID.
  • D. 1. Verify that you are assigned the Project Owners IAM role for this project.
    2. Switch to the project in the GCP console, locate the resources and delete them.
Antwort: B

68. Frage
(Your company has a rapidly growing social media platform and a user base primarily located in North America. Due to increasing demand, your current on-premises PostgreSQL database, hosted in your United States headquarters data center, no longer meets your needs. You need to identify a cloud-based database solution that offers automatic scaling, multi-region support for future expansion, and maintains low latency.)
  • A. Use Cloud SQL for PostgreSQL.
  • B. Use Spanner.
  • C. Use Bigtable.
  • D. Use BigQuery.
Antwort: B
Begründung:
Comprehensive and Detailed In Depth Explanation:
Let's evaluate each database option against the requirements: automatic scaling, multi-region support, and low latency for a growing social media platform:
A: Bigtable: Bigtable is a highly scalable NoSQL database designed for large analytical and operational workloads with low latency. It offers excellent horizontal scalability and can be deployed across multiple regions for high availability and lower latency for a global user base. However, it's a NoSQL database and might require significant changes to your existing PostgreSQL data model and application code.
B: BigQuery: BigQuery is a fully managed, serverless data warehouse optimized for analytical queries on large datasets. It's not designed for low-latency transactional workloads that a social media platform would require for real-time user interactions. While it's globally available, its primary use case is not operational database needs.
C: Spanner: Spanner is a globally distributed, horizontally scalable relational database service with strong consistency. It offers automatic scaling, built-in multi-region and multi-continental configurations for high availability and low latency across a global user base, and supports standard SQL (with some extensions).
This makes it a strong candidate for a rapidly growing platform needing scalability, global presence, and low latency. While it's not directly PostgreSQL, it offers a relational model and tools to aid migration.
D: Cloud SQL for PostgreSQL: Cloud SQL offers managed PostgreSQL instances with automatic scaling capabilities. It supports high availability within a region and cross-region read replicas for disaster recovery and read scaling. However, its multi-region capabilities for write operations and automatic scaling across regions are more limited compared to Spanner. For a rapidly growing platform with a primarily North American user base but future global expansion in mind and a need for low latency, Spanner's architecture is better suited for true multi-region write capabilities and consistent low latency globally.
Considering the requirements for automatic scaling, multi-region support for both reads and writes with low latency for a growing user base, Spanner is the most appropriate choice.
Google Cloud Documentation References:
Cloud Spanner Overview: https://cloud.google.com/spanner/docs/overview - This document highlights Spanner's global scalability, strong consistency, and multi-region capabilities.
Cloud Bigtable Overview: https://cloud.google.com/bigtable/docs/overview - While scalable and low-latency, it's a NoSQL database, which might require significant application changes.
BigQuery Overview: https://cloud.google.com/bigquery/docs/introduction - Focuses on analytics, not low- latency transactional workloads.
Cloud SQL for PostgreSQL Overview: https://cloud.google.com/sql/docs/postgres/overview - While it offers scaling and regional HA, its multi-region write capabilities are not as robust as Spanner's.

69. Frage
......
Associate-Cloud-Engineer Testing Engine: https://www.itzert.com/Associate-Cloud-Engineer_valid-braindumps.html
Übrigens, Sie können die vollständige Version der ITZert Associate-Cloud-Engineer Prüfungsfragen aus dem Cloud-Speicher herunterladen: https://drive.google.com/open?id=12N5tW_MR6EZMsw6eAqRmN0_tNgYBhyFo
https://www.pass4leader.com
Reply

Use props Report

Return to List
High mode
B Color Image Link Quote Code Smilies
You need to log in before you can reply Login | Register

This forum Credits Rules

  •  

Service Hotline : (+86)18688117175
Contact us
E-mail : global@t-firefly.com
Copyright © 2014-2022, FIREFLY TECHNOLOGY CO.,LTD. All Rightts Reserved. 粤ICP备14022046号-2
Quick Reply Back to top Back to list