Welcome to Bootcamp AI

Introducción

Jobs in Cloud Computing

Cloud Computing

The cloud has become a key enabler for innovation with beneficial features like high availability, unlimited capacity, and on-demand scalability and elasticity. Learn the fundamentals of cloud computing while being introduced to compute power, security, storage, networking, messaging, and management services in the cloud. While learning the fundamentals, you will explore tools and services offered by Amazon Web Services (AWS) through interactive hands-on exercises. By the end of the course, you will have deployed your first website to AWS, and you will be prepared to continue your learning journey in the Cloud Developer Nanodegree program

Foundational & Compute Service

Storage & Content Delivery

Security

Networking & Elasticity

Messaging & Containers

AWS Management

Deploy Static Website on AWS

Getting Started with CloudFormation

With the advent of cloud computing, along came several tools that enabled us to deploy the underlying infrastructure components that provide security and services to our servers by writing scripts. In this course, you’ll learn how to deploy this infrastructure using CloudFormation, AWS’ tool for Infrastructure as Code. You will use CloudFormation to deploy Infrastructure patterns that are used broadly in the industry and can be readily used to deploy any cloud application. Like in the real world, you will begin with initial business requirements that you will turn into Cloud Architecture Diagrams. Then, you will deploy this architecture using CloudFormation

Infrastructure Diagrams

Networking Infrastructure

Servers and Security Groups

Storage and Databases

Monitoring & Logging

In this course, you’ll learn the process of taking software from source code to deployment and beyond. You’ll learn about automated testing, choosing the right deployment strategy for your business needs and deploying an appropriate CI/CD pipeline. You’ll also learn about monitoring and logging to ensure that your application is running at peak performance and stays that way. You’ll also learn to manage and make changes to your servers in an automated way, using Ansible, a leading Configuration Management tool.

Continuous Integration and Continuous Deployment—

Continuous Integration and Continuous Deployment Strategies —

Building a Continuous Integration Pipeline –

Enabling Continuous Delivery with Deployment Pipelines

Monitoring Environments

Deploy an Event-Driven Microservice

In this course, you will learn to create and deploy a Kubernetes cluster, configure Kubernetes autoscale, and load test a Kubernetes application. You’ll learn to operationalize both existing and new microservices, and apply containers best practices. You’ll learn to deploy Machine Learning microservices that are elastic and fault tolerant. You’ll learn to pick the appropriate abstraction for microservices: Serverless (AWS Lambda) or Container Orchestration (Kubernetes).

Using Docker Format Containers

Containerization of an Existing Application

Container Orchestration with Kubernetes

Operationalizing Microservices

Operationalize a Machine Learning Microservice API

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Install Kubernetes

Install Kubernetes

The simplest way to install Kubernetes is to use Docker Desktop for Windows or Docker Desktop for Mac. This comes with the kubectl kubernetes command line tool.

The next recommended way is to use a cloud shell environment like AWS Cloud9 or Google Cloud Shell. These cloud environments dramatically simplify issues that crop up on a laptop or workstation. You can follow the native packagement guide from the official documentation here.

A more advanced method for experts could be to directly download the latest binary. HINT: You probably don’t want to use this method shown in the video unless you are an expert and should use an easier method above. The expert commands are shown below.

Curl command

The curl command Noah uses in the video for Mac is as follows:

curl -LO https://storage.googleapis.com/kubernetes-release/release/$(curl -s https://storage.googleapis.com/kubernetes-release/release/stable.txt)/bin/darwin/amd64/kubectl

Note that the escape characters () in the above may need to be removed for the command to work on your system depending on your settings.

Checking for virtualization

The other command used is:

sysctl -a | grep machdep.cpu.features