AWS re:Invent 2016

As more and more organizations strive to gain real-time insights into their business, streaming data has become ubiquitous. Typical streaming data analytics solutions require specific skills and complex infrastructure. However, with Amazon Kinesis Analytics, you can analyze streaming data in real-time with standard SQL—there is no need to learn new programming languages or processing frameworks.

CEO Andy Jassy discusses the latest AWS news and announcements.

CTO Werner Vogels discusses the latest AWS news and announcements.

Distinguished Engineer James Hamilton

As we add thousands of skills to Alexa, our developers have uncovered some basic and more complex tips for building better skills. Whether you are new to Alexa skill development or if you have created skills that are live today, this session helps you understand how to create better voice experiences. Last year, Capital One joined Alexa on stage at re:Invent to talk about their experience building an Alexa skill. Hear from them one year later to learn from the challenges that they had to overcome and the results they are seeing from their skill. In this session, you will learn the importance of flexible invocations, better VUI design, how OAuth and account linking can add value to your skill, and about Capital One's experience building an Alexa skill.

The experience in the auto industry is changing. For both the driver and the car manufacturer, a whole new frontier is on the near horizon. What do you do with your time while the car is driving itself? How do I have a consistent experience while driving shared or borrowed cars? How do I stay safer and more aware in the ever increasing complexity of traffic, schedules, calls, messages and tweets? In this session we will discuss how the auto industry is facing new challenges and how the use of Amazon Alexa, IoT, Logistics services and the AWS Cloud is transforming the Mobility experience of the (very near) future.

The Jet Propulsion Laboratory designs and creates some of the most advanced space robotics ever imagined. JPL IT is now innovating to help streamline how JPLers will work in the future in order to design, build, operate, and support these spacecraft. They hope to dramatically improve JPLers' workflows and make their work easier for them by enabling simple voice conversations with the room and the equipment across the entire enterprise.

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 zero 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.

Learn how to develop voice-based serverless back ends for Alexa Voice Service (AVS) and Alexa devices using the Alexa Skills Kit (ASK), which allows you to add new voice-based interactions to Alexa. We’ll code a new skill, implemented by a serverless backend leveraging AWS services such as Amazon Cognito, AWS Lambda, and Amazon DynamoDB. Often, your skill needs to authenticate your users and link them back to your backend systems and to persist state between user invocations. User authentication is performed by leveraging OAuth compatible identity systems. Running such a system on your back end requires undifferentiated heavy lifting or boilerplate code. We’ll leverage Login with Amazon as the identity provider instead, allowing you to focus on your application implementation and not on the low-level user management parts. At the end of this session, you’ll be able to develop your own Alexa skills and use Amazon and AWS services to minimize the required backend infrastructure. This session shows you how to deploy your Alexa skill code on a serverless infrastructure, leverage AWS Lambda, use Amazon Cognito and Login with Amazon to authenticate users, and leverage AWS DynamoDB as a fully managed NoSQL data store.

At Librato, a Solarwinds company, we run hundreds of Cassandra instances across multiple rings and use it as our primary data store. In the past year, we embarked on a process to upgrade our fleet of Cassandra Amazon EC2 instances from instance store to instances using Amazon EBS and attached elastic network interfaces (ENIs). We find running Cassandra on EBS gives us the flexibility to choose the best instances for the best performance of our workload while saving us significant costs on infrastructure. In this session, we discuss how Librato operates Cassandra on EBS. Topics include how we chose the right instance for our workload, use detached EBS volumes and ENI mobility to reduce MTTR, use mixed EBS storage types for the best cost/performance tradeoff, debug performance issues, and continuously monitor Cassandra to get the most from AWS. We also look at performance tradeoffs made in the implementation of storage engines of large data systems like Cassandra.