これだけで合格!Google Cloud Associate Cloud Engineer模擬試験問題集(4回200問)

Google Cloud Associate Cloud Engineer Certification: Master Essential Cloud Skills

The Google Cloud Associate Cloud Engineer certification validates your foundational skills and knowledge in deploying, operating, and managing enterprise solutions on the Google Cloud Platform (GCP). This is a crucial certification for anyone looking to build a career in cloud engineering. The exam covers a broad range of topics and has recently shifted towards more scenario-based, longer-form questions, requiring a deeper understanding of cloud architecture.

Exam Details:

• Duration: 2 hours
• Registration Fee: $125 (excluding tax)
• Passing Score: Not publicly disclosed
• Number of Questions: 50

This comprehensive course is designed to prepare you for the Google Cloud Associate Cloud Engineer exam by providing hands-on experience with various question formats and covering the key areas assessed. We've structured the course around 5 core categories, ensuring you're ready to confidently tackle the certification.

Core Exam Domains:

1. Setting up Cloud Solution Environments:

• 1.1 Cloud Project and Account Configuration: Learn to create and manage GCP projects, assign users with predefined IAM roles, utilize Cloud Identity for user management (manual & automated), enable APIs, and provision Stackdriver workspaces.
• 1.2 Billing Configuration Management: Master creating billing accounts, linking projects to billing accounts, setting up budgets and alerts, and configuring billing exports for cost analysis.
• 1.3 Command Line Interface (CLI) with Cloud SDK: Install and configure the Cloud SDK (specifically, the Cloud Shell) for managing your GCP resources (e.g., setting the default project).

2. Planning and Configuring Cloud Solutions:

• 2.1 Cost Estimation with Pricing Calculator: Utilize the GCP Pricing Calculator to plan and estimate the cost of using various GCP products.
• 2.2 Compute Resource Planning & Configuration: Plan and configure compute resources, considering the selection of appropriate compute services (Compute Engine, GKE, App Engine, Cloud Run, Cloud Functions), leveraging preemptible VMs and custom machine types.
• 2.3 Data Storage Options Planning & Configuration: Choose the right data storage products (Cloud SQL, BigQuery, Cloud Spanner, Cloud Bigtable) and storage options (Standard, Nearline, Coldline, Archive) for your needs.
• 2.4 Network Resource Planning & Configuration: Plan and configure network resources, including understanding load balancing options, determining resource locations for availability, and configuring Cloud DNS.

3. Deploying and Implementing Cloud Solutions:

• 3.1 Compute Engine Deployment & Implementation: Deploy and implement Compute Engine resources using the Cloud Console and Cloud SDK, including creating instances with various configurations (disks, availability policies, SSH keys), creating managed instance groups with instance templates, and managing SSH keys. Configure Stackdriver Monitoring and Logging.
• 3.2 Google Kubernetes Engine (GKE) Deployment & Implementation: Deploy and implement GKE resources, including deploying container applications using Pods, configuring monitoring and logging for GKE applications.
• 3.3 App Engine, Cloud Run & Cloud Functions Deployment & Implementation: Deploy and implement applications using App Engine, Cloud Run, and Cloud Functions, including configuring scaling, versions, and traffic splitting. Deploy applications to respond to Google Cloud events.
• 3.4 Data Solution Deployment & Implementation: Initialize data systems using products like Cloud SQL, Cloud Datastore, BigQuery, Cloud Spanner, Cloud Pub/Sub, Cloud Bigtable, Cloud Dataproc, Cloud Dataflow, and Cloud Storage. Learn to load data using various methods (command-line, API, import/export, streaming).
• 3.5 Networking Resource Deployment & Implementation: Create VPCs (custom and shared), launch Compute Engine instances with custom network configurations, create firewall rules, and establish VPN connections. Implement load balancing for application traffic.
• 3.6 Deploying Solutions with Cloud Marketplace: Browse and deploy solutions from the Cloud Marketplace.
• 3.7 Deploying Applications with Cloud Deployment Manager: Develop and deploy infrastructure using Deployment Manager templates.

4. Ensuring Successful Operation of Cloud Solutions:

• 4.1 Managing Compute Engine Resources: Manage Compute Engine instances (start, stop, configure, delete), connect via SSH/RDP, manage snapshots and images, and manage instance groups.
• 4.2 Managing Google Kubernetes Engine (GKE) Resources: Manage GKE clusters (nodes, pods, services), browse container image repositories, and manage node pools, pods, and services.
• 4.3 Deploying and Managing App Engine & Cloud Run Resources: Adjust traffic splitting parameters, configure autoscaling, and manage these resources.
• 4.4 Managing Storage and Database Solutions: Move objects between Cloud Storage