AWS re:Invent 2017

Today's trends in auto technology are all about connecting cars and their occupants to the outside world in a seamless and safe manner. In this session, we discuss how automotive companies are leveraging AWS for a variety of connected vehicle use cases. You'll leave this session with source code, architecture diagrams, and an understanding of how to apply the AWS Connected Vehicle Reference Architecture to build your own prototypes. You'll also learn how car companies can leverage Amazon services such as Alexa and AWS services such as AWS IOT, AWS Greengrass, AWS Lambda and Amazon API Gateway to rapidly develop and deploy innovative connected vehicle services.

Manufacturing companies in all sectors—including automotive, aerospace, semiconductor, and industrial manufacturing—rely on design and engineering software in their product development processes. These computationally-intensive applications—such as computer-aided design and engineering (CAD and CAE), electronic design automation (EDA), other performance-critical applications—require immense scale and orchestration to meet the demands of today's manufacturing requirements. In this session, you learn how to achieve the maximum possible performance and throughput from design and engineering workloads running on Amazon EC2, elastic GPUs, and managed services such as AWS Batch and Amazon AppStream 2.0. We demonstrate specific optimization techniques and share samples on how to accelerate batch and interactive workloads on AWS. We also demonstrate how to extend and migrate on-premises, high performance compute workloads with AWS, and use a combination of On-Demand Instances, Reserved Instances, and Spot Instances to minimize costs.

Over the next decade, accelerating autonomous driving technology—including advances in artificial intelligence, sensors, cameras, radar and data analytics—are set to transform how we commute. In this session, you learn how to use Amazon AI for a highly productive, on demand, and scalable autonomous driving development environment. We compare the most popular AI frameworks including TensorFlow and MXNet for use in autonomous driving workloads. You learn about the AWS optimizations on MXNet that yield near linear scalability for training deep neural networks and convolutional neural networks. We demonstrate the ease of getting started on AWS AI by using a sample training dataset for building an object detection model on AWS. This session is intended for audiences who have some exposure to the underlying concepts for AI-based autonomous driving development. After attending the session, you can get started with AI development on AWS by using a sample dataset for building an object detection model.

Cloud computing gives you a number of advantages, such as the ability to scale your web application or website on demand. If you have a new web application and want to use cloud computing, you might be asking yourself, "Where do I start?" Join us in this session to understand best practices for scaling your resources from one to millions of users. We show you how to best combine different AWS services, how to make smarter decisions for architecting your application, and how to scale your infrastructure in the cloud.

This presentation compares three modern architecture patterns that startups are building their businesses around. It includes a realistic analysis of cost, team management, and security implications of each approach. It covers AWS Elastic Beanstalk, Amazon ECS, Amazon API Gateway, AWS Lambda, Amazon DynamoDB, and Amazon CloudFront. Attendees will also hear from venture capital investor Third Rock Ventures (TRV) who has launched 40+ biotech startups over the last 10 years. TRV will outline how it launches cloud native startups that turn bleeding edge science into new treatments across the spectrum of disease, with highlights drawn Relay Therapeutics and Tango Therapeutics.

Applications running in a typical data center are static entities. But applications aren't static in the cloud. Dynamic scaling and resource allocation is the norm on AWS. Technologies such as Amazon EC2, AWS Lambda, and Auto Scaling provide flexibility in building dynamic applications and with this flexibility comes an opportunity to learn how an enterprise application functions optimally.  New Relic helps manage these applications without sacrificing simplicity.  In this session, we discuss changes in monitoring dynamic cloud resources. We'll share best practices we've learned working with New Relic customers on managing applications running in this environment to understand and optimize how they are performing. Session sponsored by New Relic

At Netflix, we make explicit tradeoffs to balance our four key focus domains of innovation, reliability, security, and efficiency to ensure our customers, shareholders, and internal engineering stakeholders are happy. In this talk, learn the strategies behind each of our focus domains to optimize for one without detracting from another.

Netflix is a large, ever changing ecosystem system serving millions of customers across the globe through cloud-based systems and a globally distributed CDN. This entertaining romp through the tech stack serves as an introduction to how we think about and design systems, the Netflix approach to operational challenges, and how other organizations can apply our thought processes and technologies. In this session, we discuss the technologies used to run a global streaming company, scaling at scale, billions of metrics, benefits of chaos in production, and how culture affects your velocity and uptime.

Many companies use Amazon Simple Email Service (Amazon SES) to build applications that enable their users to send millions of emails every day. In this session, you learn how to build applications using the scalable, reliable Amazon SES infrastructure. You also learn how to monitor email sending and enforce compliance rules on individual accounts without impacting other accounts. Zendesk discusses the architecture of its multitenant email sending platform, the historical challenges it faced, its phased approach to platform migration, and the ways Amazon SES helped them meet their goals.

Startups and enterprises are increasingly using open source projects for architectures. AWS customers and partners also run their own open source programs and contribute key technologies to the industry (see DCS201). At AWS, we engage with open source projects in several ways. Through bug fixes and enhancements to popular projects, including work with the Hadoop ecosystem (see BDM401), Chromium (see BAP305) and Boto, and standalone projects like the security library s2n (see NET405) and machine learning project MXNet (see MAC401). We have services like Amazon ECS for Docker (see CON316) and Amazon RDS for MySQL and PostgreSQL (see DAT305) that make open source easier to use.  In this session, learn more about existing AWS open source work and our next steps.