This on-demand course equips students to understand, configure, and maintain multi-cluster Kubernetes infrastructures using Anthos GKE and Istio-based service mesh, whether deployed with Anthos on Google Cloud or with Anthos deployed on VMware.

In this course we will introduce you to Google Sheets, Google’s cloud-based spreadsheet software, included with Google Workspace. With Google Sheets, you can create and edit spreadsheets directly in your web browser—no special software is required. Multiple people can work simultaneously, you can see people’s changes as they make them, and every change is saved automatically. You will learn how to open Google Sheets, create a blank spreadsheet, and create a spreadsheet from a template. You will add, import, sort, filter and format your data using Google Sheets and learn how to work across different file types. Formulas and functions allow you to make quick calculations and better use your data. We will look at creating a basic formula, using functions, and referencing data. You will also learn how to add a chart to your spreadsheet. Google Sheets spreadsheets are easy to share. We will look at the different ways you can share with others. We will also discuss how to track changes and manage versions of your Google Sheets spreadsheets. Google Workspace makes it easy to collaborate with your team, clients, and others wherever they are. We will look at some of the collaboration options available to you in Google Sheets. Examples include commenting, action items, and notifications.

In modern cloud native application development, it’s oftentimes the goal to build out serverless architectures that are scalable, are highly available, and are fully managed. This means less operational overhead for you and your business, and more focusing on the applications and business specific projects that differentiate you in your marketplace. In this course, we will be covering how to build a modern, greenfield serverless backend on AWS. Building brand new applications on AWS is a different task than lifting and shifting existing applications into AWS. When you have an existing application that you need to move to AWS, you might first look to using Amazon EC2 as your virtual machines, or maybe you might look into using docker containers and container hosting services like Amazon Elastic Container Service or Amazon Elastic Kubernetes Service. Those are all great application hosting options, but in most cases, they still require you to have some kind of pulse on the underlying infrastructure hosting your application. ` Building Modern Java Applications on AWS will explore how to build an API driven application using Amazon API Gateway for serverless API hosting, AWS Lambda for serverless computing, and Amazon Cognito for serverless authentication. We will follow an API driven development process and first mock up what the API will look like. We will cover all the ins and outs of the service Amazon API Gateway, and as you’ll learn- it does a lot more than just hosting an API. Then we will add authentication to the API using Amazon Cognito. You’ll learn about how the authorization flow works with Cognito, and how to build it into your APIs. From there, we will add a Lambda backend that will be triggered by API Gateway. The lambda functions will be using the AWS SDKs to perform various data processing tasks. You’ll learn about the different configurations that exist for Lambda, and we will show you how to create and manage lambda functions. Some of the features of our API will require multiple lambda functions to execute in a specific order, like a workflow, and we will use AWS Step Functions to create a serverless workflow. Finally, we will talk about how to optimize your APIs at every layer using AWS features. Note: There are four versions of this class, "Building Modern Node.js Applications on AWS" for Node.js developers, "Building Modern Python Applications on AWS" for Python developers, "Building Modern .NET Applications on AWS" for .NET developers, and this course, "Building Modern Java Applications on AWS" for Java developers. The courses do for a large part, overlap and in general, we recommend that you take the course that focuses on the SDK you plan to use to develop your AWS Cloud based applications. We expect that you have basic knowledge of AWS already. Some examples of concepts you should be familiar with are: you should know the basics of the AWS Global infrastructure, like what regions and availability zones are. You also should know the at a high-level AWS Identity and Access Management, or IAM, and how it is used to control access to AWS resources. You should also understand what an Amazon EC2 instance is, what Amazon S3 is, what a VPC is, as well as other basic AWS terminology.

This course will introduce you to Amazon Web Services (AWS) core services and infrastructure. Through demonstrations you'll learn how to use and configure AWS services to deploy and host a cloud-native application. Early in the course, your AWS instructors will discuss how the AWS cloud infrastructure is built, walk you through Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Lightsail compute services. They'll also introduce you to networking on AWS, including how to set up Amazon Virtual Public Cloud (VPC) and different cloud storage options, including Amazon Elastic Block Storage (EBS), Amazon Simple Storage Service (S3) and Amazon Elastic File Service (EFS). Later in the course you'll learn about AWS Database services, such as Amazon Relational Database Service (RDS) and Amazon DynomoDB. Your instructors will also walk you through how to monitor and scale you application on AWS using Amazon CloudWatch and Amazon EC2 Elastic Load Balancing (ELB) and Auto Scaling. Lastly, you'll learn about security on AWS, as well as how to manage costs when using the AWS cloud platform. In this course, you won't be required to complete hands-on exercises, but we strongly suggest you take advantage of the AWS Free Tier to follow along as the instructors demonstrate the AWS services. Class forums will also allow you to ask questions and interact with AWS training instructors. After completing this course, you'll have the basic fundamentals to get started on AWS. This course has been developed by AWS, and is delivered by AWS technical instructors who teach cloud computing courses around the globe.

Salesforce Commerce Cloud, formerly called Demandware, is a cloud-based service for unifying the way businesses engage with customers over any channel or device. Now a days E-Commerce is growing rapidly. Every merchant or seller wants to do online selling. Salesforce Commerce Cloud is a platform where a large E-Commerce business can be handled very easily. All the cloud services make this very easy for Merchants as well as for Customers. Create Multi regional Online Stores , Easy Product selling , Best order management & customer handling. This Course is dedicated to : - Spread Knowledge of this Cloud base Salesforce product. - Easy tutorials for Merchants so that they can handle Business Manager/ Admin very easily. - Tutorials for beginers as well as Advance developers. - Coding Standards for Backend as well as frontend developers. - Solutions to common issues in Sales force commerce cloud development. Lets spread the knowledge of Salesforce Commerce Cloud . Topics covered in the sessions are as following : Introduction to Salesforce Commerce Cloud Understand Business Manager Connect Salesforce Commerce Cloud Using UXStudio & Eclipse Catalog & Products Campaigns & Promotions Customers Groups Cartridge or File Structure of Salesforce Commerce Cloud Concept of Pipelines At the End of course you will be able to start Administration & Development in Salesforce Commerce Cloud.

Cloud Computing has really changed the way companies looking into their digital Infrastructure now a days. Cloud computing with its unique paradigms brings in new opportunities and challenges for developers and administrators worldwide. With our unique curriculum we have tried to create the content which will bring beginners up to speed with Cloud technologies. The Course will start with basic introduction to cloud concepts like SAAS, PAAS and IAAS. You will also learn how Linux systems is changing the Infrastructure landscape worldwide. You will then learn to use popular cloud technologies like Google Compute Engine , Amazon AWS and Redhat open shift. The last unit covers Virtualization Technologies to provide you a holistic understanding of cloud computing environment. This course is surely the fastest and smartest way to get started with Cloud computing technologies.

This course provides a holistic experience of optimally configuring SAP on Google Cloud. Participants will learn to configure SAP on Google Cloud, and what best practices are, leaving the course with actionable experience to configure SAP on Google Cloud and run SAP workloads on Google Cloud. >>> By enrolling in this course you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<

This course introduces participants to the strategies to migrate from a source environment to Google Cloud. Participants are introduced to Google Cloud's fundamental concepts and more in depth topics, like creating virtual machines, configuring networks and managing access and identities. The course then covers the installation and migration process of Migrate for Compute Engine, including special features like test clones and wave migrations.

This course provides an introduction to data center networking technologies, more specifically software-defined networking. It covers the history behind SDN, description of networks in data-centers, a concrete data-center network architecture (Microsoft VL2), and traffic engineering.

This course provides an overview of Computer Vision (CV), Machine Learning (ML) with Amazon Web Services (AWS), and how to build and train a CV model using the Apache MXNet and GluonCV toolkit. The course discusses artificial neural networks and other deep learning concepts, then walks through how to combine neural network building blocks into complete computer vision models and train them efficiently. This course covers AWS services and frameworks including Amazon Rekognition, Amazon SageMaker, Amazon SageMaker GroundTruth, and Amazon SageMaker Neo, AWS Deep Learning AMIs via Amazon EC2, AWS Deep Learning Containers, and Apache MXNet on AWS. The course is comprised of video lectures, hands-on exercise guides, demonstrations, and quizzes. Each week will focus on different aspects of computer vision with GluonCV. In week one, we will present some basic concepts in computer vision, discuss what tasks can be solved with GluonCV and go over the benefits of Apache MXNet. In the second week, we will focus on the AWS services most appropriate to your task. We will use services such as Amazon Rekognition and Amazon SageMaker. We’ll review the differences between AWS Deep Learning AMIs and Deep Learning containers. Finally, there are demonstrations on how to set up each of the services covered in this module. Week three will focus on setting up GluonCV and MXNet. We will look at using pre-trained models for classification, detection and segmentation. During week four and five, we will go over the fundamentals of Gluon, the easy-to-use high-level API for MXNet: understanding when to use different Gluon blocks, how to combine those blocks into complete models, constructing datasets, and writing a complete training loop. In the final week, there will be a final project where you will apply everything you’ve learned in the course so far: select the appropriate pre-trained GluonCV model, apply that model to your dataset and visualize the output of your GluonCV model.