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This week, we’ve got lots of new content to share with you on Cloud Academy! Explore our newest learning paths, video courses, and hands-on labs on AWS, Microsoft Azure, and Google Cloud Platform on security, cloud architecture, containers, and many more topics.
When implementing cloud services, ensuring that your data remains restricted, controlled, monitored, maintained, and secured at the proper level is essential.
AWS has developed a number of security services and management tools to help you protect your data and environment from unwanted exposure, vulnerabilities, and threats. In this learning path, we’ll introduce eight key AWS security services that you need to know about. Over a series of video courses, hands-on labs, and quizzes, you’ll learn how to implement AWS Identity & Access Management (IAM), AWS Key Management Service (KMS), AWS CloudHSM, AWS WAF, AWS CloudTrail, Amazon Inspector, AWS Trusted Advisor and AWS Config within your own AWS environment.
As your infrastructure grows within AWS and your environment scales over time, it’s important to have an understanding of the different AWS Cloud management tools available to operate your infrastructure efficiently and effectively.
You will learn about the following AWS services: CloudWatch, CloudFormation, CloudTrail, AWS Config, and AWS Trusted Advisor through video courses, hands-on labs, and quizzes. We’ll help you understand how each service works, how to configure them, and how to implement them in your own environment.
If you’re working with Azure, you’ll want to have a solid foundation in the platform’s fundamental services. In this learning path, we have courses and hands-on labs to help you get the most out of Azure. You’ll use our labs to start your first Azure virtual machine, and we’ll cover essentials such as Azure App Service, Azure Resource Manager Virtual Machines, Azure Functions, Virtual Networks, ARM Templates, and more.
If you’re interested in planning out complex cloud applications, this learning path provides a high-level introduction to Microsoft Azure services. We’ll cover topics like virtual networking, secure resources, storage and data access, app services, business continuity strategies, and more.
This learning path is also essential prep if you’re planning to take the 70-534 Architecting Microsoft Azure solutions exam. It includes video courses and seven quiz sessions to test your knowledge along the way.
Google Cloud Platform provides many services for building out highly available, highly scalable web applications and mobile back-ends, and it’s a great option for building modern software systems. This learning path covers the main platform concepts—how to deploy applications, storage options, database services, networking, and more—to help you get started. Then, we go into systems operations, where we’ll show you how to create virtual machines and networks, how to use the auto-scaler and load balancer, and more.
When you architect an infrastructure for mission-critical applications, you need to choose the appropriate compute, storage, and networking components while also designing for security, high availability, regulatory compliance, and disaster recovery. In this learning path, we’ll take you from Google Cloud Platform fundamentals, all the way to applying these principles to meet real-world requirements.
IPv4 is the fourth version of the internet protocol. This course is a deep dive into the IPv4 networking concepts and includes detailed explanations for key parts of the protocol, including IPv4 Addressing Notation, Classless Inter-Domain Routing, Reserved Addresses, Subnetting, and more. We will also spend some time formatting several IPv4 subnetting scenarios.
With the ever increasing threats of attacks against the integrity, confidentiality, and availability of your data, being able to ensure strict security procedures and processes is essential. Amazon Inspector helps you discover security vulnerabilities within your EC2 instances and any applications running on them, during any stage of development and deployment. In this course, we’ll take a close look at the service, show you how to configure it and work with findings, and you’ll learn how to integrate it with CloudWatch and CloudTrail.
Azure Container Service (ACS) is a cloud-based container deployment and management service that supports popular open source tools and technologies for container and container orchestration. In this course, you will learn how to use ACS to scale and orchestrate applications using DC/OS, Docker Swarm, or Kubernetes.
While Google’s documentation for Cloud Machine Learning Engine includes a Getting Started guide, it recommends that you should first have experience with machine learning and TensorFlow. In this course, we’ll give you the knowledge you need to be able to train and deploy machine learning models using Google Cloud Machine Learning Engine. You’ll learn how to run a simple TensorFlow program, how to deploy a trained model on ML Engine, and more.
Chef is a popular configuration management tool. It has built-in support for Windows and a thriving community that provides cookbooks for managing configurations.These labs will get you up and running with Chef Solo and help you configure a local host in Windows using Chef. Here’s what else you’ll learn:
The Chef configuration management tool is typically used in a client-server architecture where clients check a centralized server for configuration updates. Chef Solo brings most of the benefits of Chef to a single server. All of the concepts of Chef apply to Chef Solo: cookbooks, recipes, attributes, templates, roles, etc. In this lab, you will gain experience with each of those concepts as you configure a Linux virtual machine using Chef Solo.
Here’s what you will learn:
Amazon Elastic MapReduce (EMR) makes it easy to process vast amounts of data in a variety of applications, including log analysis, web indexing, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics. It uses Hadoop to distribute raw data and processing across a resizable cluster of Amazon EC2 instances.
In this hands-on lab, you will learn how to:
AWS CodeStar handles the source repository, builds, and deployments and allows you to focus on development. It is team-ready, with built-in roles for members to allow collaboration between owners, contributors, and viewers. This lab will help you start your project in AWS CodeStar.
You will learn how to:
Explore all of our newest content and see what’s coming up next on Cloud Academy in our content roadmap!
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Introduction to Machine Learning on AWSThis is your quick-start guide for building and deploying with Amazon Machine Learning. By the end of this learning path, you will be able to apply supervised and unsupervised learning, ML algorithms, deep learning, and deep neural networks on AW...
What is Amazon Machine Learning and how does it work"Amazon Machine Learning is a service that makes it easy for developers of all skill levels to use machine learning technology.”UPDATES: I've published a new hands-on lab on Cloud Academy! You can give it a try for free and st...
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How to use Mechanical Turk in combination with Amazon ML for dataset labellingWhether you build your own machine learning models in the Cloud or using complex mathematical tools, one of the most expensive and time consuming part of building your model is likely to be generating a high...
Welcome to our weekly review of some of what’s new, interesting, and upcoming at Cloud Academy.New courses:It's been an exciting week at Cloud Academy, with the content creation machine churning out three brand new courses!Amazon Machine LearningFirst out of the gate (and buildi...