GCP DevOps: CloudOps with Google Cloud Platform

Google Cloud 2020    |    Intermediate
  • 18 videos | 1h 51m 22s
  • Includes Assessment
  • Earns a Badge
Likes 68 Likes 68
In this 18-video course, learners explore features of Google Cloud Platform (GCP), Google Kubernetes Engine (GKE), best practices for operating containers, and how to build cloud-native applications with CloudOps methodology. First, compare Google Cloud Source Repository with GitHub, and see how automated deployment capabilities of Google Cloud Deployment Manager compare with Terraform. Then delve into GCP's machine learning (ML), artificial intelligence, and analytical capabilities and essential design patterns for connecting GCP with other cloud platforms. Discover how to create and configure GKE clusters; deploy applications across multiple Kubernetes clusters; create repositories and manage code with Google Cloud Source Repository; and deploy applications from Cloud Source Repository to App Engine. Next, learn how to automate the configuration of GCP resources and application deployment with Google Cloud Deployment Manager, create virtual machine (VM) instances on GCP; build applications with Terraform; and configure AutoML and BigQuery to manage large volumes of data and build ML models. Finally, learners discover how to set up fully-managed real-time messaging environments, and transfer data between GCP and other Cloud Service providers.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    recognize Google Cloud Platform features and why Google Cloud Platform is a secondary cloud provider
    describe the key features of Google Kubernetes Engine and how it can be used to set up CloudOps to manage operations that scale and manage workload
    list best practices for operating containers inspired by the Twelve-Factor App methodology and recognize how to build cloud-native applications using the CloudOps methodology
    create and configure Google Kubernetes Engine clusters in default VPC and enable alias IP addresses
    deploy applications across multiple Kubernetes clusters using an Istio multi-cluster service mesh
    describe the features of Google Cloud Source Repository and compare its capabilities with GitHub
    create repositories using the Cloud Source Repository and manage code using the checkin/checkout and merge strategies
    deploy applications from the Cloud Source Repository to App Engine
  • compare the automated deployment capabilities of Google Cloud Deployment Manager and Hashicorp Terraform
    use the Google Cloud Deployment Manager to automate the configuration of Google Cloud Platform resources to deploy applications on targeted environments
    use Terraform to create virtual machine instances on the Google Cloud Platform and build applications on the instances
    recognize the machine learning, artificial intelligence, and analytical capabilities of Google Cloud Platform, with focus on the toolsets that enable edge feature implementations like artificial intelligence, IoT, and business intelligence
    configure AutoML and BigQuery to manage large scale of data and provide high quality machine learning models following the CloudOps paradigm
    configure Cloud Pub/Sub to set up fully-managed real-time messaging environments to send and receive messages between independent applications
    recognize the concept of multi-cloud design along with the essential design patterns for connecting Google Cloud Platform with other cloud platforms
    establish connectivity and transfer data between Google Cloud Platform and other cloud service providers using external IP addresses
    summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 38s
  • 4m 53s
  • Locked
    3.  Features of GKE for Operations
    5m 59s
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    4.  Cloud Native with CloudOps
    8m 50s
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    5.  Creating and Configuring GKE
    5m 42s
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    6.  Deploying Apps across Multiple GKE Clusters
    8m 20s
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    7.  Google Cloud Source Repository
    5m 36s
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    8.  Creating the Repository and Managing Code
    8m 14s
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    9.  Deploying Apps from Cloud Source Repository
    4m 19s
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    10.  Cloud Deployment Manager vs. Terraform
    6m 34s
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    11.  Using Deployment Manager for Automation
    5m 14s
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    12.  Using Terraform for Automation
    8m 41s
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    13.  ML and AI with Google Cloud Platform
    6m 43s
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    14.  Using AutoML and BigQuery for ML Ops
    6m 51s
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    15.  Messaging in GCP
    5m 31s
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    16.  Multi-Cloud Design Pattern Powered by GCP
    5m 13s
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    17.  Transferring Data from GCP to Other Cloud Providers
    11m 23s
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    18.  Course Summary
    1m 41s

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