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Deploying & Implementing Cloud Solutions

  • Deploy an application infrastructure with Cloud Deployment Manager with a focus on the development and launch of Deployment Manager templates.
  • Deploy and implement App Engine, Cloud Functions, and Cloud Run resources: the learners will be required to demonstrate their skills in the deployment of applications, traffic splitting, updating scaling configuration, as well as deployment of applications that accept Google Cloud events;
  • Deploy solutions with Cloud Marketplace: the candidates must demonstrate the ability to browse the Cloud Marketplace catalog to check solution details; deploy Cloud Marketplace solutions;
  • Deploy and implement data solutions: the applicants should be able to initialize data systems with Google products and load data;
  • Deploy and implement networking resources: this will measure your ability to launch Compute Engine instances using custom network configuration; create egress and ingress firewall rule or VPC; create VPNs between the external network and Google VPC with Cloud VPN; create the load balancer to allocate the application network traffic for apps;
  • Deploy and implement Google Kubernetes Engine Resources: this domain includes skills in deploying Google Kubernetes Engine cluster, container application to Google Kubernetes Engine with pods, and configuring Google Kubernetes Engine Application logging and monitoring;
  • Deploy and implement compute engine resources: the skills required for this area include launching compute instances with Cloud SDK and Cloud Console; creating auto-scaled managed instance groups with instance templates; uploading/generating custom SSH keys for instances; configuring virtual machines or Stackdriver logging and monitoring. It also requires that the students can assess compute quotas and request for increases; install a Stackdriver Agent for logging and monitoring;

The Google Associate Cloud Engineer exam targets software engineers who would like to dabble into the Google Cloud. So, you need to be capable of using the command-line interfaces and Google Cloud Console to handle core platform-based tasks. These mostly include monitoring operations and managing enterprise solutions to maintain deployed applications. In addition, after successful writing of the test, candidates obtain the appropriate Google Cloud certification.

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Training

While the exam curriculum covers a lot of knowledge and skills, Google offers enough tools to help candidates systematize their preparation process. Self-paced and in-classroom courses as well we lab practice are also available.

So, you can take advantage of Architecting with Google Compute Engine, a three-day course that will introduce you to Google Cloud infrastructure and platform services by focusing on Compute Engine.

Alternatively, candidates can pose their questions to an expert instructor regarding Google Сloud products at a one-day Google Cloud Fundamentals: Core Infrastructure training session that includes lectures, presentations, and lab activities.

In addition, Google recommends that all applicants who want to know more about the format, structure, and topics of the certification exam finish the Preparing for the Associate Cloud Engineer Examination course. It helps applicants to assess their strengths and weaknesses and be fully prepared on the day of the final test.

If you are not confident in your readiness, you can also check your skills by answering sample questions alongside doing self-paced labs offered by the vendor.

Reference: https://cloud.google.com/certification/cloud-engineer

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Google Associate-Cloud-Engineer日本語 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Configuring Access and Security15-20%- Managing IAM resources
  • 1. Defining custom IAM roles
  • 2. Applying IAM policies to resources
  • 3. Creating and managing IAM roles
- Viewing audit logs
  • 1. Accessing and analyzing Cloud Audit Logs
  • 2. Configuring audit log policies
- Managing service accounts
  • 1. Assigning service accounts to resources
  • 2. Using service account keys
  • 3. Creating and managing service accounts
Topic 2: Planning and Configuring a Cloud Solution20-25%- Planning and configuring data storage options
  • 1. Selecting appropriate storage classes
  • 2. Choosing between Cloud Storage, Filestore, Persistent Disk
- Planning and configuring network resources
  • 1. Configuring load balancing and firewall rules
  • 2. Designing VPC networks
- Planning and configuring compute resources
  • 1. Selecting appropriate machine types and zones
  • 2. Configuring persistent disks and local SSDs
- Planning and estimating GCP product usage
  • 1. Using GCP Pricing Calculator
  • 2. Reading documentation for compute, storage, and network resources
Topic 3: Ensuring Successful Operation15-20%- Managing Cloud Run resources
  • 1. Managing revisions and traffic splitting
  • 2. Configuring resource limits
- Managing Compute Engine resources
  • 1. Resizing instances and persistent disks
  • 2. Managing instances, disks, and snapshots
  • 3. Attaching and detaching disks
- Managing Kubernetes Engine resources
  • 1. Upgrading clusters
  • 2. Scaling clusters and node pools
  • 3. Managing workloads (Deployments, Services, HPA)
- Managing logging and monitoring
  • 1. Viewing and analyzing logs
  • 2. Creating metrics and alerts
  • 3. Using Cloud Monitoring and Logging
- Managing storage and data solutions
  • 1. Configuring CORS and encryption
  • 2. Managing Cloud Storage buckets and objects
  • 3. Setting lifecycle policies
Topic 4: Deploying and Implementing a Cloud Solution20-25%- Deploying and managing Cloud Functions
  • 1. Configuring triggers and environment variables
  • 2. Creating and triggering Cloud Functions
- Deploying and managing Cloud Run resources
  • 1. Deploying containerized applications to Cloud Run
  • 2. Configuring memory limits and scaling settings
- Deploying applications with Cloud Deployment Manager
  • 1. Using templates for resource provisioning
  • 2. Creating deployment configurations
- Deploying and managing Kubernetes Engine resources
  • 1. Creating and managing GKE clusters
  • 2. Deploying workloads with Deployments and Services
  • 3. Configuring kubectl for cluster access
- Deploying and managing Compute Engine resources
  • 1. Creating and managing custom machine types
  • 2. Creating and managing managed instance groups
  • 3. Creating and managing instances with startup scripts
Topic 5: Setting Up a Cloud Solution Environment20-25%- Managing billing configuration
  • 1. Linking billing to projects
  • 2. Setting up budget alerts and notifications
  • 3. Creating billing accounts
- Setting up cloud projects and accounts
  • 1. Managing billing budgets and alerts
  • 2. Assigning IAM roles to users and groups
  • 3. Creating and managing projects

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