gkcloudsolutions

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Anthos Hybrid Cloud | Anthos Google Cloud |GK Cloud Solutions

Course Description

This two-day instructor-led Anthos Hybrid Cloud course prepares students to modernize, manage, and observe their applications using Kubernetes whether the application is deployed on-premises or on Google Cloud Platform (GCP). Through presentations, and hands-on labs, participants explore and deploy using Kubernetes Engine (GKE), GKE Connect, Istio service mesh and Anthos Config Management capabilities that enable operators to work with modern applications even when split among multiple clusters hosted by multiple providers, or on-premises.

Objectives

Connect and     manage Anthos GKE clusters from GCP Console whether clusters are part of     Anthos on Google Cloud or Anthos deployed on VMware.

Understand how     service mesh proxies are installed, configured and managed.

Configure     centralized logging, monitoring, tracing, and service visualizations     wherever the Anthos GKE clusters are hosted.

Understand and     configure fine-grained traffic management.

Use service mesh     security features for service-service authentication, user authentication,     and policy-based service authorization.

Install a     multi-service application spanning multiple clusters in a hybrid     environment. Understand how services communicate across clusters.

Migrate services     between clusters.

Install Anthos     Config Management, use it to enforce policies, and explain how it can be     used across multiple clusters.

Audience

This class is primarily intended for the following participants:

Technical employees using GCP, including customer companies,     partners and system integrators: deployment engineers, cloud architects,     cloud administrators, system engineers, and SysOps / DevOps engineers.

Individuals using GCP to create, integrate, or modernize solutions     using secure, scalable microservices architectures in hybrid environments.

Prerequisites

To get the most out of this Anthos Google Cloud course, participants should have completed the Architecting with Google Kubernetes Engine course and its prerequisites, or have equivalent experience.

Content

The course includes presentations and hands-on labs.

Module 1: Anthos Overview

Module 2: Managing Hybrid Clusters using Kubernetes Engine

Module 3: Introduction to Service Mesh

Module 4: Observing Services using Service Mesh Adapters

Module 5: Managing Traffic Routing with Service Mesh

Module 6: Managing Policies and Security with Service Mesh

Module 7: Managing Policies using Anthos Config Management

Module 8: Configuring Anthos GKE for Multi-Cluster Operation

For more IT Training on Google Cloud Courses visit GK Cloud Solutions.

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GKE Getting Started | Google Kubernetes Engine | GKCS

Course Description

This GKE Getting Started course will teach you how to containerize workloads in Docker containers, deploy them to Kubernetes clusters provided by Google Kubernetes Engine, and scale those workloads to handle increased traffic. You'll also learn how to continuously deploy new code in a Kubernetes cluster to provide application updates.

Objectives

At the end of the course, you will be able to:

Understand how     software containers work.

Understand the     architecture of Kubernetes.

Understand the     architecture of Google Cloud.

Understand how pod     networking works in Google Kubernetes Engine.

Create and manage     Kubernetes Engine clusters using the Google Cloud Console and     gcloud/kubectl commands.

Audience

This class is intended for the following participants:

Application     developers, Cloud Solutions Architects, DevOps Engineers, IT managers

Individuals using     Google Cloud Platform to create new solutions or to integrate existing     systems, application environments, and infrastructure with the Google     Cloud Platform

Prerequisites

To get the most out of this course, participants should have:

Basic proficiency     with command-line tools and Linux operating system environments, as well     as Web server

Systems     Operations experience including deploying and managing applications,     either on-premises or in a public cloud environment

Content

Module 1: Introduction to Google Cloud

Module​ ​​2:​​ Containers and Kubernetes in Google Cloud

Module​ ​​3:​​ ​Kubernetes Architecture

Module​ ​​4:​​ ​Continuous​ ​Deployment with​ ​Jenkins

For more IT Training on Google Cloud Courses visit GK Cloud Solutions.

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Getting Started with GKE | Google Kubernetes Engine | GKCS

Course Description

This Getting Started with GKE course will teach you how to containerize workloads in Docker containers, deploy them to Kubernetes clusters provided by Google Kubernetes Engine, and scale those workloads to handle increased traffic. You'll also learn how to continuously deploy new code in a Kubernetes cluster to provide application updates.

Objectives

At the end of the course, you will be able to:

Understand     how software containers work.

Understand     the architecture of Kubernetes.

Understand     the architecture of Google Cloud.

Understand     how pod networking works in Google Kubernetes Engine.

Create     and manage Kubernetes Engine clusters using the Google Cloud Console and     gcloud/kubectl commands.

Audience

This class is intended for the following participants:

Application     developers, Cloud Solutions Architects, DevOps Engineers, IT managers

Individuals using     Google Cloud Platform to create new solutions or to integrate existing     systems, application environments, and infrastructure with the Google     Cloud Platform

Prerequisites

To get the most out of this course, participants should have:

Basic proficiency     with command-line tools and Linux operating system environments, as well     as Web server

Systems     Operations experience including deploying and managing applications,     either on-premises or in a public cloud environment

Content

Module 1: Introduction to Google Cloud

Module​ ​​2:​​ Containers and Kubernetes in Google Cloud

Module​ ​​3:​​ ​Kubernetes Architecture

Module​ ​​4:​​ ​Continuous​ ​Deployment with​ ​Jenkins

For more IT Training on Google Cloud Courses visit GK Cloud Solutions.

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Architecting with Google Kubernetes Engine |GK Cloud Solutions

Course Description

Learn how to deploy and manage containerized applications on Google Kubernetes Engine (GKE). Learn how to use other tools on Google Cloud that interact with GKE deployments. This Architecting with Google Kubernetes Engine course features a combination of lectures, demos, and hands-on labs to help you explore and deploy solution elements—including infrastructure components like pods, containers, deployments, and services—along with networks and application services. You'll also learn how to deploy practical solutions, including security and access management, resource management, and resource monitoring.

Objectives

Understand how     software containers work.

Understand the     architecture of Kubernetes.

Understand the     architecture of Google Cloud.

Understand how     pod networking works in Google Kubernetes Engine.

Create and manage     Kubernetes Engine clusters using the Google Cloud Console and gcloud/kubectl     commands.

Launch, roll     back, and expose jobs in Kubernetes.

Manage access     control using Kubernetes RBAC and IAM.

Manage pod     security policies and network policies.

Use Secrets and     ConfigMaps to isolate security credentials and configuration artifacts.

Understand Google     Cloud choices for managed storage services.

Monitor     applications running in Google Kubernetes Engine.

Audience

This class is intended for the following:

Cloud architects,     administrators, and SysOps/DevOps personnel Individuals using Google Cloud     Platform to create new solutions or to integrate existing systems,     application environments, and infrastructure with the Google Cloud     Platform.

Prerequisites

To get the most out of this course, participants should have:

Completed Google Cloud Platform Fundamentals:     Core Infrastructure or have equivalent experience

Basic proficiency with command-line tools and     Linux operating system environments

Content

Module 1: Introducing Google Cloud Platform

Module 2: Containers and Kubernetes in GCP

Module 3: Kubernetes Architecture

Module 4: Kubernetes Operations

Module 5: Deployments, Jobs, and Scaling

Module 6: GKE Networking

Module 7: Persistent Data and Storage

Module 8: Access Control and Security in Kubernetes and Kubernetes Engine

Module 9: Logging and Monitoring

Module 10: Using GCP Managed Storage Services from Kubernetes Applications

Module 11: Logging and Monitoring

For more IT Training on Google Cloud Courses visit GK Cloud Solutions.

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Networking in Google Cloud | Google Cloud Networking | GKCS

Course Description

This two-day instructor-led class gives participants broad study of networking options on Google Cloud Platform. Through a combination of presentations, demonstrations, and hands-on labs, participants explore and deploy GCP networking technologies, such as Google Virtual Private Cloud (VPC) networks, subnets, firewalls; interconnection among networks; load balancing; Cloud DNS; Cloud CDN; Cloud NAT. The Networking in Google Cloud course will also cover common network design patterns and automated deployment using Deployment Manager or Terraform.

Objectives

This Google Cloud Networking course teaches participants the following skills:

Understand how     software containers work Understand the architecture of Kubernetes

Understand the     architecture of Google Cloud Platform Understand how pod networking works     in Kubernetes Engine

Create and manage     Kubernetes Engine clusters using the GCP Console and gcloud/ kubectl     commands Launch, roll back and expose jobs in Kubernetes

Manage access     control using Kubernetes RBAC and Google Cloud IAM Managing pod security     policies and network policies Using Secrets and ConfigMaps to isolate     security credentials and configuration artifacts

Choose among and     use Google Cloud Platform storage options: Google Cloud Storage, Google     Cloud SQL, Google Cloud Bigtable, and Google Cloud Datastore

Audience

This class is intended for network engineers and network admins that are either using Google Cloud Platform or are planning to do so. The class is also for individuals that want to be exposed to software-defined networking solutions in the cloud.

Prerequisites

Familiarity with the Linux command line, web servers, and text editors.

Content

This course teaches participants the following skills:

Module 1: Google Cloud VPC Networking Fundamentals

Module 2: Controlling Access to VPC Networks

Module 3: Sharing Networks across Projects

Module 4: Load Balancing

Module 5: Hybrid Connectivity

Module 6: Networking Pricing and Billing

Module 7: Network Design and Deployment

Module 8: Network Monitoring and Troubleshooting

For more IT Training on Google Cloud Courses visit GK Cloud Solutions.

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Developing Applications with Google Cloud Platform | GKCS

Course Description

In this Developing Applications with Google Cloud Platform course, application developers learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. Through a combination of presentations, demos, and hands-on labs, participants learn how to use GCP services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications.

Objectives

Application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform.

This course teaches participants the following skills:

Use best practices for application     development.

Choose the appropriate data storage option for     application data.

Implement federated identity management.

Develop loosely coupled application components     or microservices.

Integrate application components and data     sources.

Debug, trace, and monitor applications.

Perform repeatable deployments with containers     and deployment services.

Choose the appropriate application runtime     environment; use Google Container.

Engine as a runtime environment and later     switch to a no-ops solution with Google App Engine Flex.

Audience

This class is intended for the following:

Application     developers who want to build cloud-native applications or redesign     existing applications that will run on Google Cloud Platform

Prerequisites

To get the most benefit from this course, participants should have the following prerequisites:

Completed Google     Cloud Platform Fundamentals or have equivalent experience

Working knowledge     of Node.js

Basic proficiency     with command line tools and Linux operating system environments

Content

The course includes presentations, demonstrations, and hands-on labs.

1. Best Practices for Application Development

2. Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK

3. Overview of Data Storage Options

4. Best Practices for Using Cloud Datastore

5. Performing Operations on Buckets and Objects

6. Best Practices for Using Cloud Storage

7. Securing Your Application

8. Using Google Cloud Pub/Sub to Integrate Components of Your Application

9. Adding Intelligence to Your Application

10. Using Cloud Functions for Event-Driven Processing

11. Managing APIs with Google Cloud Endpoints

12. Cloud Deploying an Application by Using Google Cloud Container Builder, Google Cloud Container Registry, and Google Deployment Manager

13. Execution Environments for Your Application

14. Debugging, Monitoring, and Tuning Performance by Using Google Stackdriver

For more IT Training on Google Cloud Courses visit GK Cloud Solutions.

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Architecting with Google Compute Engine | GK Cloud Solutions

Course Description

This three-day instructor-led class introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud Platform, with a focus on Compute Engine. Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems, and application services. This Architecting with Google Compute Engine course also covers deploying practical solutions including securely interconnecting networks, customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring.

Objectives

Configure VPC networks and virtual machines

Administer, Identity and Access Management for     resources

Implement data storage services in GCP

Manage and examine billing of GCP resources

Monitor resources using Stackdriver services

Connect your infrastructure to GCP

Configure load balancers and autoscaling for     VM instances

Automate the deployment of GCP infrastructure     services

Leverage managed services in GCP

Audience

Cloud Solutions Architects, DevOps Engineers Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure, with a focus on Compute Engine.

Prerequisites

Completion of     Google Cloud Platform Fundamentals or equivalent experience

Basic proficiency     with command-line tools and Linux operating system environments

Systems     operations experience, including deploying and managing applications,     either on-premises or in a public cloud environment

Content

The course includes presentations, demonstrations, and hands-on labs.

Module 1: Introduction to Google Cloud Platform

Module 2: Virtual Networks

Module 3: Virtual Machines

Module 4: Cloud IAM

Module 5: Storage and Database Services

Module 6: Resource Management

Module 7: Resource Monitoring

Module 8: Interconnecting Networks

Module 9: Load Balancing and Autoscaling

Module 10: Infrastructure Automation

Module 11: Managed Services

For more IT Training on Google Cloud Courses visit GK Cloud Solutions.

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Data Engineering on GCP | Google Cloud Data Engineer | GKCS

Course Description

This four-day instructor-led class provides participants a hands-on introduction to designing and building data processing systems on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, participants will learn how to design data processing systems, build end-to-end data pipelines, analyze data and carry out machine learning. The Data Engineering on GCP course covers structured, unstructured, and streaming data.

Objectives

This Google Cloud Data Engineer course teaches participants the following skills:

Design and build     data processing systems on Google Cloud Platform

Process batch and     streaming data by implementing autoscaling data pipelines on Cloud     Dataflow

Derive business     insights from extremely large

datasets using     Google BigQuery

Train, evaluate     and predict using machine learning models using Tensorflow and Cloud ML

Leverage     unstructured data using Spark and ML APIs on Cloud Dataproc

Enable instant     insights from streaming data

Audience

This class is intended for the following:

Extracting, loading, transforming, cleaning,     and validating data

Designing pipelines and architectures for data     processing

Creating and maintaining machine learning and     statistical models

Querying datasets, visualizing query results     and creating reports

Prerequisites

To get the most of out of this course, participants should have:

Completed Google     Cloud Fundamentals- Big Data and Machine Learning course #8325 OR have     equivalent experience

Basic proficiency   �� with common query language such as SQL

Experience with     data modeling, extract, transform, load activities

Developing     applications using a common programming language such Python

Familiarity with    Machine Learning and/or statistics

Content

The course includes presentations,     demonstrations, and hands-on labs.

Leveraging Unstructured Data with Cloud     Dataproc on Google Cloud Platform

Module 1: Google Cloud Dataproc Overview

Module 2: Running Dataproc Jobs

Module 3: Integrating Dataproc with Google Cloud Platform

Module 4: Making Sense of Unstructured Data with Google’s Machine Learning APIs

Module 5: Serverless data analysis with BigQuery

Module 6: Serverless, autoscaling data pipelines with Dataflow

Module 7: Getting started with Machine Learning

Module 8: Building ML models with Tensorflow

Module 9: Scaling ML models with CloudML

Module 10: Feature Engineering

Module 11: Architecture of streaming analytics pipelines

Module 12: Ingesting Variable Volumes

Module 13: Implementing streaming pipelines

Module 14: Streaming analytics and dashboards

Module 15: High throughput and low-latency with Bigtable

For more IT Training on Google Cloud Courses visit GK Cloud Solutions.

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GCP Big Data and Machine Learning Fundamentals | GKCS

Course Description

This one-day instructor-led course introduces participants to the big data capabilities of Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, participants get an overview of the Google Cloud platform and a detailed view of the data processing and machine learning capabilities. This GCP Big Data and Machine Learning Fundamentals course showcases the ease, flexibility, and power of big data solutions on Google Cloud Platform.

Objectives

This course teaches participants the following skills:

Identify the     purpose and value of the key Big Data and Machine Learning products in the     Google Cloud Platform.

Use Cloud SQL and     Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive     workloads to Google Cloud Platform.

Employ     BigQuery and Cloud Datalab to carry out interactive data analysis.

Train and use a     neural network using TensorFlow.

Employ ML APIs.

Choose between     different data processing products on the Google Cloud Platform.

Interact with     Google Cloud Platform services

Audience

This class is intended for the following:

Data analysts,     Data scientists, Business analysts getting started with Google Cloud     Platform.

Individuals     responsible for designing pipelines and architectures for data processing,     creating and maintaining machine learning and statistical models, querying     datasets, visualizing query results and creating reports.

Executives and IT     decision makers evaluating Google Cloud Platform for use by data     scientists.

Prerequisites

To get the most of out of this course, participants should have:

Basic proficiency     with common query language such as SQL

Experience with     data modeling, extract, transform, load activities

Developing     applications using a common programming language such Python

Familiarity with     Machine Learning and/or statistic

Content

The course includes presentations, demonstrations, and hands-on labs.

Module 1: Introducing Google Cloud Platform

Module 2: Compute and Storage Fundamentals

Module 3: Data Analytics on the Cloud

Module 4: Scaling Data Analysis

Module 5: Machine Learning

Module 6: Data Processing Architectures

Module 7: Summary

For more IT Training on Google Cloud Courses visit GK Cloud Solutions.

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Google Cloud Fundamentals | GCP Core Infrastructure | GKCS

Course Description

This one-day instructor-led class provides an overview of Google Cloud Platform products and services. Through a combination of presentations, demos, and hands-on labs, participants learn the value of Google Cloud Platform and how to incorporate cloud-based solutions into business strategies.

Objectives

This Google Cloud Fundamentals course teaches participants the following skills:

Identify the     purpose and value of Google Cloud Platform products and services

Interact with     Google Cloud Platform services

Describe ways in     which customers have used Google Cloud Platform

Choose among and     use application deployment environments on Google Cloud Platform: Google     App Engine, Google Kubernetes Engine, and Google Compute Engine

Choose among and     use Google Cloud Platform storage options: Google Cloud Storage, Google     Cloud SQL, Google Cloud Bigtable, and Google Cloud Datastore

Make basic use of     BigQuery, Google’s managed data warehouse for analytics

Make basic use of     Cloud Deployment Manager, Google’s tool for creating and managing cloud     resources through templates

Make basic use of     Google Stackdriver, Google’s monitoring, logging, and diagnostics system

Audience

This class is intended for the following:

Individuals     planning to deploy applications and create application environments on     Google Cloud Platform.

Developers,     systems operations professionals, and solution architects getting started     with Google Cloud Platform.

Executives and     business decision makers evaluating the potential of Google Cloud Platform     to address their business needs.

Prerequisites

Familiarity with the Linux command line, web servers, and text editors.

Content

The GCP Core Infrastructure course includes presentations, demonstrations, and hands-on labs.

Module 1: Introducing Google Cloud Platform

Module 2: Getting Started with Google Cloud Platform

Module 3: Virtual Machines and Networks in the Cloud

Module 4: Storage in the Cloud

Module 5: Containers in the Cloud

Module 6: Applications in the Cloud

Module 7: Developing, Deploying, and Monitoring in the Cloud

Module 8: Big Data and Machine Learning in the Cloud

For more IT Training on Google Cloud Courses visit GK Cloud Solutions.

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