Introduction to Kubernetes
Kubernetes allows you to deploy and manage containers at scale. Created by Google, and now supported by Azure, AWS, and Docker, Kubernetes is the container orchestration platform of choice for many deployments. For teams deploying containerized applications, this learning path will serve as an introduction to the Kubernetes ecosystem and a primer for preparing for production. You will work alongside us as we explore key features by deploying a sample application, and you will be able to practice deploying stateful and stateless applications in two hands-on labs.
Introduction to Azure Machine Learning Studio
Azure Machine Learning Studio is machine learning at its most accessible. With this web-based software, you can train and deploy machine learning models using a drag-and-drop interface, without any coding whatsoever. This course will help teams get started using Machine Learning Studio. You will learn how to prepare your data, train a machine learning model, and deploy it as a predictive web service across a series of hands-on demos.
Introduction to VMware Cloud on AWS
VMware Cloud on AWS allows you to seamlessly transition your VM workloads to the AWS cloud to take advantage of on-demand resourcing, scalability, flexibility, security and other benefits of the public cloud. With this course, business managers evaluating a hybrid cloud solution will be able to understand how VMware’s private on-premises architecture works with AWS and the benefits that this combination offers the enterprise.
Getting Started with Migrating to the Cloud
Now that you’ve decided to migrate to the cloud, it’s time to shift from theory to practice. This course features hands-on strategies, techniques, and best practices that teams can apply in migrating business applications to public cloud services. Your teams will get practical guidance for building your migration business case, moving up the maturity curve, creating your migration roadmap, and more.
An Overview of AWS Trusted Advisor
As your infrastructure grows, how can you make sure you’re deploying your resources in the best way while ensuring tight security and resiliency against failure? AWS Trusted Advisor recommends improvements across your account to help optimize and hone your environment based on AWS best practices. In this course, you’ll get the hands-on practice and actionable knowledge you need to start using AWS Trusted Advisor to improve your AWS infrastructure.
Azure Key Vault and Disk Encryption
Azure Key Vault is a service for managing and encrypting keys, secrets, and digital certificates that streamlines the key management process. With Key Vault, you can encrypt keys and secrets (authentication keys, .PFX files, passwords, and more) using keys protected by hardware security modules (HSMs). In this hands-on lab, you will use PowerShell to build the Azure Key Vault to store keys and secrets used to encrypt an Azure Virtual Machine.
Diagnose Cancer with an Amazon Machine Learning Classifier
Can a computer predict a diagnosis in a way that is faster and less expensive? Researchers and teams working with binary classification models will find an effective tool in Amazon Machine Learning Classifier. In this hands-on lab, you will use the service to train a model with medical data, evaluate the model’s performance, and use the model to make diagnoses for predictions in real time.
Using an MXNet Neural Network to Style Images
The AWS Deep Learning AMI has everything you need to start building an AI system. The MXNet deep learning framework on AWS supports training and deployment of neural networks on a variety of devices. In this hands-on lab, you will use the AWS Deep Learning AMI and a GPU instance to perform neural style transfers and examine performance and cost metrics in Amazon CloudWatch.
Serverless Web Development with Python for AWS
Cloud providers make it easy for software engineers to focus on writing their code without having to focus on the underlying server. For DevOps Engineers, Developers, or Site Reliability Engineers experimenting with serverless, AWS offers a variety of services for creating fully serverless applications. In this lab, you will practice serverless web development with Python by testing and deploying a multi-user to-do list application that uses the AWS Serverless Application Model, Amazon Cognito, and DynamoDB.
Manage Access to Azure with Role-Based Access Control
Limiting access to resources based on a user’s role is a simple way to ensure security within your environment. Microsoft Azure provides fine-grained role-based access control (RBAC) mechanisms to secure your resources. In this hands-on lab, you will follow the principle of least privilege for users as you manage access to Azure with RBAC. You will use Azure PowerShell to create a custom role, learn how to assign roles to users, and get tips on how to define your own custom roles.
AWS Machine Learning Services
The speed at which machine learning (ML) is evolving within the cloud industry is exponentially growing, and public cloud providers such as AWS are releasing more and more services and feature updates to run in parallel with the trend and demand of this technology within organizations t...
How to Develop Machine Learning Models in TensorFlow
Predictive analytics and automation—through AI and machine learning—are increasingly being integrated into enterprise applications to support decision making and address critical issues such as security and business intelligence. Public cloud platforms like AWS offer dedicated services ...
Analyze CPU vs. GPU Performance for AWS Machine Learning
For teams training complex machine learning models, time and cost are important considerations. In the cloud, different instance types can be employed to reduce the time required to process data and train models. Graphics Processing Units (GPUs) offer a lot of advantages over CPUs wh...
AWS Global Infrastructure: Availability Zones, Regions, Edge Locations, Regional Edge Caches
Amazon Web Services is a global public cloud provider, and as such, it has to have a global network of infrastructure to run and manage its many growing cloud services that support customers around the world. In this post, we'll take a look at the components that make up the AWS Global...
Introduction to Amazon Machine Learning
The goal of this post is to introduce you to machine learning - and specifically Amazon Machine Learning - and help you understand how the cloud can greatly simplify the implementation of a complex machine learning algorithm. What is Machine Learning? We humans learn a lot from everyt...
AWS re:Invent 2015: Real-World Smart Applications With Amazon Machine Learning
How to apply Machine Learning to social media to make your customers happy At his AWS re:Invent presentation, Alex Ingerman - technical product manager at AWS - went through the design and implementation of a real-world end-to-end application to transform a high-volume social stream in...