Google Cloud Practitioner Associates

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Google Cloud Practitioner Associates, An Associate Cloud Engineer would build the infrastructure on Google Cloud by using a compute engine, Kubernetes Engine, Cloud Functions, Monitoring tools like stack driver and so on.

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Course Details

Google Cloud Practitioner Associates, An Associate Cloud Engineer would build the infrastructure on Google Cloud by using a compute engine, Kubernetes Engine, Cloud Functions, Monitoring tools like stack driver and so on. He/She will learn how to use the G-cloud console to perform common platform-based tasks to maintain the deployed solutions.

 

Content:

  • Course Agenda Module 1 : Introducing Google Cloud Platform:
  •    Explain the advantages of Google Cloud Platform.
  •    Define the components of Google's network infrastructure, including: Points of presence, data centers, regions, and zones.
  •    Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS)
  •    Lab : Sign Up for the Free Trial and Create a Project.
  •    Register for the GCP free trial.
  •    Create a project using the Cloud Platform Console Module.
  • Getting Started with Google Cloud Platform
  •    Identify the purpose of projects on Google Cloud Platform.
  •    Understand the purpose of and use cases for Identity and Access Management.
  •    List the methods of interacting with Google Cloud Platform.
  •    Lab: Getting Started with Google Cloud Platform.
  •    Deploy a LAMP stack using Google Cloud Launcher Module .
  • Google App Engine and Google Cloud Datastore
  •    Learning Objectives.
  •    Understand the purpose of and use cases for Google App Engine and Google Cloud Datastore.
  •    Contrast the App Engine Standard environment with the App Engine Flexible environment.
  •    Understand the purpose of and use cases for Google Cloud Endpoints Lab: Deploying Applications Using App Engine and Cloud Datastore.
  •    Deploy a sample Python application called Bookshelf to the App Engine standard runtime environment.
  •    Test the Bookshelf application and inspect data saved to Cloud Datastore Module.
  • Google Cloud Platform Storage Options
  •    Understand the purpose of and use cases for: Google Cloud Storage, Google Cloud SQL, and Google Cloud Bigtable.
  •    Learn how to choose between the various storage options on Google Cloud Platform Lab: Integrating Applications with Google Cloud Storage.
  •    Create a Google Cloud Storage bucket to store images.
  •    Deploy an App Engine application that uses Cloud Storage.
  •    Use the Cloud Storage Browser to view objects.
  • Module 5 : Google Container Engine
  •    Define the concept of a container and identify uses for containers.
  •    Identify the purpose of and use cases for Google Container Engine and Kubernetes
  •    Lab : Deploying Applications Using Google Compute Engine.
  •    Create a Google Compute Engine instance.
  •    Deploy the Bookshelf application using a startup script.
  •    Add a firewall rule to allow HTTP traffic to the application.
  • Module 6 : Google Compute Engine and Networking
  •    Identify the purpose of and use cases for Google Compute Engine.
  •    Understand the various Google Cloud Platform networking and operational tools and services.
  •    Lab : Deploying Applications Using Google Container Engine.
  •    Create a container cluster using the Cloud SDK.
  •    Build and push a Bookshelf image to Container Registry.
  •    Use kubectl to deploy the Bookshelf container.
  • Module 7 : Big Data and Machine Learning
  •    Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms.
  •    Lab: Getting Started with Big Query.
  •    Load a CSV file into a BigQuery table using the web UI.
  •    Query the data using the BigQuery web UI.
  •    Query the data using the CLI and the BigQuery shell.
  • Mangalore Branch

    Balmatta Rd, opposite Hotel Roopa, below Hotel Sai Town House, Mangalore

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