Internet And Network Technologies
Google Cloud Platform Fundamentals
Container, Compute, and App Engine with Networking Services
Google Cloud
Google Cloud Big Data and Machine Learning

Container, Compute, and App Engine with Networking Services

Course Number:
cl_gcpf_a02_it_enus
Lesson Objectives

Container, Compute, and App Engine with Networking Services

  • start the course
  • describe Google's Container Engine and Kubernetes
  • define the concept of a container registry
  • deploy an application by creating a container and using the Google Cloud SDK
  • create an image and push it to the Container Registry
  • use kubectl to deploy an application to a container
  • identify characteristics and purpose of Google Compute Engine Networking Service
  • describe the relationship between networks, instances, and firewalls
  • create a network in the Web UI
  • create IP addresses in the Web UI
  • create firewall rules in the Web UI
  • describe networks and route collection
  • describe IP forwarding
  • describe Network Address Translation gateways
  • describe network load balancing and HTTP load balancing
  • identify the purpose and benefits of Google App Engine
  • compare traditional builds with Google App Engine builds
  • survey and define the various App Engine services
  • compare the App Engine Standard and App Engine Flexible environments
  • deploy a Python application to the App Engine environment
  • identify GCP attributes of Compute, Container, and App Engine as well as networking services

Overview/Description
Google Compute Engine offers virtual machines running in Google's innovative data centers and worldwide fiber network. In this course, you'll learn about the fundamental aspects of the Google Cloud Platform Container Engine, Compute Engine, and App Engine as well as Google's basic networking services.

Target Audience
IT professionals including managers, engineers, and developers evaluating or implementing application environments on Google Cloud Platform

Google Cloud

Course Number:
cl_gcpf_a01_it_enus
Lesson Objectives

Google Cloud

  • start the course
  • explain the value features of Google Cloud Platform products and services
  • identify the components of the Google Cloud Platform services components including Compute Engine, App Engine, Container Engine, container registry, and cloud function
  • identify the components of the Google Cloud Platform services components including Storage and Databases: Cloud Storage, Cloud SQL, Cloud Bigtable, Cloud Datastore, and Persistent Disk
  • identify the components of the Google Cloud Platform Big Data services including BigQuery, Cloud Dataflow, Cloud Dataproc, Cloud Datalab, Cloud Pub/Sub, and Genomics
  • identify the components of the Google Cloud Platform networking services components including: cloud virtual network, cloud load balancing, cloud CDN, cloud interconnect, and cloud DNS
  • define the concepts and components associated with the Google Cloud infrastructure and services
  • define Google Cloud regions with examples
  • define Google Cloud zones with examples
  • differentiate between Cloud Platform's platform as a service (PaaS), Software-as-a-Service (SaaS), and infrastructure as a service (IaaS)
  • identify the features of Google Cloud Platform's storage and database services
  • identify the features of Google Cloud Platform's networking services
  • identify the features of Google Cloud Platform's Big Data services
  • manage platform projects, permissions, and resources
  • register for a free trial with Google Cloud Platform using a Gmail account
  • create a project using the Google Cloud Platform Console
  • realize options for identity and access management
  • deploy a LAMP stack using Google Cloud Launcher
  • recognize different ways to interact with the Google Cloud Platform
  • recognize the basic components, terms, and features of Google Cloud Platform

Overview/Description
Google Cloud Platform offers a wide array of powerful IaaS and SaaS cloud solutions. In this course, the various service features and options are explored as well as the necessary steps for getting started with Google Cloud Platform with a Google e-mail account.

Target Audience
IT professionals including managers, engineers, and developers evaluating or implementing application environments on Google Cloud Platform

Google Cloud Big Data and Machine Learning

Course Number:
cl_gcpf_a03_it_enus
Lesson Objectives

Google Cloud Big Data and Machine Learning

  • start the course
  • identify the purpose and characteristics of Google Cloud Datastore
  • define various datastore terms including kind, entity, property, keys, and entity groups
  • define development libraries, queries, and indexes
  • deploy an App Engine application backed by Google Datastore
  • identify the features of Google Cloud Storage
  • identify the features of Google Cloud SQL
  • identify the features of Google Cloud Bigtable
  • create a Google Cloud Storage bucket and use it to store images
  • view objects using the Cloud Storage Browser
  • identify considerations for deployment of Cloud Storage required Applications
  • identify characteristics and purpose of Google Cloud Big Data and Machine Learning platforms
  • recognize loading a CSV File Into a BigQuery Table
  • recognize querying data using the CLI
  • recognize querying data using BigQuery Web UI
  • recognize querying data using BigQuery Shell
  • perform interactive queries using BigQuery
  • review the basic features of datastore, storage options, big data, and machine learning

Overview/Description
Google Cloud Storage is unified object storage for developers and enterprises, from live data serving to data analytics/ML to data archival. In this course, you'll learn about the fundamentals of the Google Cloud Datastore and other storage options along with the basics of Big Data and Machine Learning with Google Cloud Platform.

Target Audience
IT professionals including managers, engineers, and developers evaluating or implementing application environments on Google Cloud Platform

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