AWS re:Invent 2017

Auto Scaling allows cloud resources to scale automatically in reaction to the dynamic needs of customers, which helps to improve application availability and reduce costs. New target tracking scaling policies for Auto Scaling make it easy to set up dynamic scaling for your application in just a few steps. With target tracking, you simply select a load metric for your application, set the target value, and Auto Scaling adjusts resources as needed to maintain that target. In this session, you will learn how you can use target tracking to setup sound scaling policies “without the fuss”, and improve availability under fluctuating demand. Netflix is spending $6 billion on original content this year, with shows like The Crown, Narcos, and Stranger Things, and plenty more in the future. Hear how they're using target tracking scaling policies to improve performance, reliability and availability around the world at prime times, without over-provisioning - and without guesswork. They will share some best practices examples of how target tracking allows their infrastructure to automatically adapt to changing traffic patterns in order to keep their audience entertained and their costs on target.

Join us as we explore how SigOpt is using AWS to optimize machine learning and AI pipelines. SigOpt is an Optimization-as-a-Service platform that seamlessly tunes model configuration parameters through via an ensemble of optimization algorithms behind a simple API. This results in captured performance that may otherwise be left on the table by conventional techniques while also reducing the time and cost for developing and optimizing new models. In this session, you will learn how SigOpt has optimized ML and AI pipelines on Amazon EC2 instances for various algorithms (including the latest generation of GPU optimized instances), as well as how they internally leverage AWS to build their flexible and scalable platform and evaluation framework

Many customers are using Amazon EC2 instances to run applications with high performance networking requirements. In this session, we provide an overview of Amazon EC2 network performance features—such as enhanced networking, ENA, and placement groups—and discuss how we are innovating on behalf of our customers to improve networking performance in a scalable and cost-effective manner. We share best practices and performance tips for getting the best networking performance out of your Amazon EC2 instances.

Do you have daily, weekly, or monthly tasks that you would like to automate? Looking to link two or more AWS Lambda functions in long-running processes? Are you building applications using microservices or containers? AWS Step Functions makes it easy to coordinate the components of distributed applications using visual workflows. In this session, we will share how AWS customers like Yelp are using Step Functions to reliably build and scale multi-step applications such as order processing, report generation, and data transformation. You will learn how to reduce the time to deploy and change microservices and serverless applications, and automate IT infrastructure for improved resilience and security.

AWS Batch is a fully managed service that enables developers to easily and efficiently run batch computing workloads of any scale on AWS. AWS Batch automatically provisions the right quantity and type of compute resources needed to run your jobs. With AWS Batch, you don't need to install or manage batch computing software, so you can focus on analyzing results and solving problems. In this session, the principal product manager for AWS Batch, Jamie Kinney, describes the core concepts behind AWS Batch and details of how the service functions. The presenter then demonstrates the latest features of AWS Batch with relevant use cases and sample code before describing some of the upcoming features for the service. Finally, hear from AWS Batch customers as they describe why and how they are using AWS Batch. This portion of the talk is delivered by representatives from the University of Utah, Autodesk, and AdRoll.

When Amazon EC2 launched in 2006 there was a single instance size: m1.small. Over the past eleven years EC2 has evolved to provide an extensive selection of compute resources to customers including specialized resources such as NVMe SSDs, GPUs, and FPGAs. Under the hood, the servers used to host EC2 instances have transformed from off the shelf designs running virtualization software on the host CPUs to purpose built servers with AWS network and storage components implemented in hardware. Now we are happy to announce a new category of EC2 instances: Amazon EC2 Bare Metal Instances. These instances provide customers access to the physical compute resources of the host processors along with the security, scale, and services of EC2. This session will provide an overview of Bare Metal instances, how VMware used EC2 Bare Metal instances to build VMware Cloud on AWS, and other customer use cases for this new EC2 capability.

Over the last 11 years, the Amazon EC2 virtualization platform has quietly evolved to take advantage of unique hardware and silicon, an accelerated network and storage architecture, and with the launch of C5 instances, a bespoke hypervisor to deliver the maximum amount of resources and performance to instances. Come to this deep dive to get a behind-the-scenes look at how our virtualization stack has evolved, including a peak at how our latest generation platform works under the covers.

HPC Cloud services built on the latest Intel architecture, Skylake Xeon processor, are now powering the C5 compute intensive instance at AWS and can serve as your next-generation HPC platform. Hear how customers are starting to consider hybrid strategies to increase productivity and lower their capital expenditure and maintenance costs. Also learn how to adapt this model to meet the increasing HPC and data analytics needs for your applications with the new technologies incorporated into the platform. Also find out how high performance computing via Rescale's cloud platform using Intel's latest technology seamlessly brings these advantages to HPC management and users. To access team management and throughput, all can benefit from cloud platform adoption as demand increases. Learn how customers are already benefiting. Richard Childress Racing (RCR) discusses its use of AWS C5 via the Rescale platform and how the combination is giving it an edge in the highly competitive field of motorsport. Session sponsored by Intel

Just over four years after the first public release of Docker, and three years to the day after the launch of Amazon EC2 Container Service, the use of containers has surged to run a significant percentage of production workloads at startups and enterprise organizations. Join Deepak Singh, General Manager of Amazon Container Services, as we cover the state of containerized application development and deployment trends, new container capabilities on AWS that are available now, options for running containerized applications on AWS, and how AWS customers successfully run container workloads in production.

By packaging software into standardized units, Docker gives code everything it needs to run, ensuring consistency from your laptop all the way into production. But once you have your code ready to ship, how do you run and scale it in the cloud? In this session, you become comfortable running containerized services in production using Amazon EC2 Container Service. We cover container deployment, cluster management, service auto-scaling, service discovery, secrets management, logging, monitoring, security, and other core concepts. We also cover integrated AWS services and supplementary services that you can take advantage of to run and scale container-based services in the cloud.