AWS re:Invent 2019

Andy Jassy, CEO of Amazon Web Services, delivers his AWS re:Invent 2019 keynote, featuring the latest news and announcements, including the launches of M6g, R6g, C6g instances, Inf1 instances, Amazon EKS for AWS Fargate , Amazon S3 Access Points, Amazon Redshift RA3 instances, AQUA (Advanced Query Accelerator) for Amazon Redshift, UltraWarm for Amazon Elasticsearch Service, Amazon Managed Apache Cassandra Service, Amazon SageMaker Studio, Amazon SageMaker Notebooks, Amazon SageMaker Experiments, Amazon SageMaker Debugger, Amazon SageMaker Model Monitor, Amazon SageMaker Autopilot, Amazon Fraud Detector, Amazon CodeGuru, Contact Lens for Amazon Connect, Amazon Kendra, the general availability of AWS Outposts, AWS Local Zones, and AWS Wavelength. Guest speakers include Dr. Matt Wood, of AWS; David Solomon, of Goldman Sachs; Brent Shafer, of Cerner, and Hans Vestberg, of Verizon. Launch Announcements:00:19:50 M6g, R6g, C6g EC2 instances00:23:00 Inf1 EC2 instances00:27:50 Amazon EKS on AWS Fargate00:56:50 Amazon S3 Access Points01:03:30 Amazon Redshift RA3 instances01:06:45 AQUA (Advanced Query Accelerator) for Amazon Redshift01:11:05 UltraWarm for Amazon Elasticsearch Service01:16:50 Amazon Managed Apache Cassandra Service01:36:00 Amazon SageMaker Studio01:37:20 Amazon SageMaker Notebooks01:38:30 Amazon SageMaker Experiments01:40:10 Amazon SageMaker Debugger01:42:55 Amazon SageMaker Model Monitor01:45:40 Amazon SageMaker Autopilot01:55:20 Amazon Fraud Detector01:58:40 Amazon CodeGuru02:05:55 Contact Lens for Amazon Connect02:09:15 Amazon Kendra02:16:30 General availability of AWS Outposts02:23:20 AWS Local Zones02:31:55 AWS Wavelength Guest speakers include:01:48:00 Dr. Matt Wood, of AWS00:30:40 David Solomon, of Goldman Sachs01:21:35 Brent Shafer, of Cerner02:26:20 Hans Vestberg, of VerizonLearn more about AWS at - https://amzn.to/2OPqk0FNote: Amazon EKS for AWS Fargate is the proper term @ 00:27:58Awaken Your DataPower your workloads on AWS with the latest 2nd Gen Intel Xeon Scalable processors featuring built-in AI acceleration. On-demand viewing of the Keynote sponsored by Intel. Visit: https://youtu.be/MIv32gcwOQM

Werner Vogels, CTO of Amazon.com, delivers his AWS re:Invent 2019 keynote. Watch as pulls back the covers to talk about the innovations behind AWS Nitro, Firecracker, AWS Fargate, Amazon EBS and more. This year's featured guests include Clare Liguori, Principal Software Engineer at AWS - who goes deep on AWS Fargate and how we've built this to give customers a truly unique customer experience – as well as Jeff Dowds, IT Executive at Vanguard, Sebastien de Halleux, COO of Saildrone and Dr. Martin Hofmann, Group CIO of Volkswagen automotive group.In this keynote you'll also hear more about the launch of the Amazon Builders' Library: https://aws.amazon.com/builders-library/And Werner's video series, 'Now Go Build': https://aws.amazon.com/startups/NowGoBuild/01:10:26 A special thanks for the satellite imagery provided by AWS customer Maxar: https://bit.ly/33VJG8i

Watch Peter DeSantis, VP, AWS Global Infrastructure and Customer Support, deliver the Monday Night Live keynote, featuring Cris Collinsworth from PFF, Rob Smedley with Formula 1 and Daphne Koller, from Insitro. Learn more about re:Invent at - https://amzn.to/2DJJHmz.00:00:53 Cris Collinsworth from PFF00:32:48 Rob Smedley with Formula 1 01:03:24 Daphne Koller, from Insitro

Watch the Global Partner Keynote with Doug Yeum, Head of Worldwide Channels & Alliances, AWS. Featured Guests: - Andy Jassy, CEO, AWS, Stewart Fry, Vice President, CIO Global Enterprise Systems, BP, Chris Cerruto, Vice President, Global Architecture and Analytics & BI, Avis Budget Group, Dave McCann, VP, Migration, Marketplace & Control Services, and Sandy Carter, Vice President, Worldwide Public Sector Partners & Programs, AWS.

The transition from on premises to the cloud, centralized to microservices-based architectures, and IT to DevOps has resulted in three trends: an exponential growth in machine-generated data, the increasing need for near real-time monitoring and interactive analytics of that data, and democratized access to that data to derive actionable insights by anyone, anywhere, and anytime in a secured manner. In this talk, we discuss how Amazon Elasticsearch Service provides a secure, scalable, and cost-effective log analytics solution.

Amazon Redshift continues to change the scale and economics of data warehousing. Learn more about announcements from the keynote and how they enable you to scale cost-effectively across diverse data warehouse workloads. We break down the benefits of the new Amazon Redshift RA3 instances and share real-world examples from the preview. You see how the new console and innovations like Amazon Redshift Federated Query and Data Lake Export enable you to bring together all your data, and you learn more about AQUA (Advanced Query Accelerator) for Amazon Redshift.

Artificial intelligence (AI) is reshaping the Healthcare industry. In this session, learn how automatic speech recognition and natural language processing services can be used to build powerful solutions that revolutionize the way medical information is collected, analyzed, and consumed by various stakeholders across the Healthcare ecosystem. From clinical documentation workflow and pharmacovigilance to telemedicine and revenue cycle management, AI services are driving changes that not only enhance Healthcare professionals' efficiencies, but also improve the overall quality of patient care.

Machine learning (ML) is a complex, iterative, often time-consuming process. One difficult aspect is the lack of integration between the workflow steps and the tools to accomplish them. Join us as we introduce Amazon SageMaker Studio, the first full integrated development environment (IDE) for ML that makes it easy to build, train, tune, debug, deploy, and monitor ML models at scale. It pulls together the ML workflow steps in a unified, visual interface-since they're performed and tracked within one environment, the non-linear and iterative nature of ML development is greatly simplified. You can quickly move between steps, compare results and adjust inputs and parameters, and iterate faster with Amazon SageMaker Studio.

Typical approaches to automatic ML don't provide insights into the data or logic used to create models, forcing you to compromise on accuracy. Join us as we introduce Amazon SageMaker Autopilot, an automated capability that generates ML models and provides complete control and visibility of them. Learn how Autopilot automatically inspects raw data, picks the best set of algorithms, trains multiple models, tunes them, and ranks them based on performance. The result is a recommendation for the best performing model and visibility into the logic and code for how the model was created and what's in it. Autopilot offers the best combination of automatic model creation with control and visibility.

During ML model training, it's challenging to ensure that models are progressively learning the correct values for different parameters and to analyze and debug model characteristics without building additional tools, making the process time-consuming and cumbersome. Come learn about Amazon SageMaker Debugger, a new capability that provides complete insights into the training process by automating data capture and analysis from training runs without code changes. Learn how you can analyze data using the Amazon SageMaker Studio visual interface and be alerted when anomalies and errors are detected, reducing the time needed to debug models from days to minutes. Amazon SageMaker Debugger helps you solve problems quickly, reduce troubleshooting time during training, and build high-quality models.

Typically, starting notebooks requires spinning up compute instances, and there was previously no easy way to share and collaborate without tracking dependencies and other restrictions. Join us as we introduce the new Amazon SageMaker notebooks experience, which allows you to access notebooks in seconds without spinning up compute instances. The elastic notebooks allow you to easily scale compute up or down, and the changes take place automatically without interrupting your work. You can share notebooks by automatically reproducing the environment and library dependencies without manually tracking them so others can reproduce the results with the same data. With this new experience, you can build models faster and collaborate at scale.

Many machine learning (ML) applications require humans to review for labeling or moderation of nuanced content, which can result in low confidence predictions to ensure the correct results. But building human review systems can be time-consuming and expensive. Amazon Augmented AI (A2I) makes it easy to build and manage human reviews for ML applications through built-in workflows for common ML use cases, such as content moderation (with Amazon Rekognition) and text extraction (with Amazon Textract). You can create workflows for custom ML models or those built on Amazon SageMaker. In this session, learn about Amazon A2I and how to use it. Then hear from VidMob about how they plan to use Amazon A2I to quickly optimize and fine-tune video analytics models.

In this session, come see how AWS Wavelength brings services such as Amazon EC2 and Amazon ECS to the edge of 5G mobile networks. This enables developers to build applications that reach 5G connected devices with single-digit millisecond latencies using familiar AWS APIs and development processes. This session provides an overview of typical application architectures that benefit from low-latency compute. We also dive deep into how Bethesda Softworks, a video game publisher best known for iconic franchises like The Elder Scrolls, Fallout, and DOOM, is using AWS Wavelength to greatly enhance the experience of streaming video games. You learn how to use AWS in the 5G network edge to build applications that require ultra low-latency such as game streaming, AR/VR, IoT, and analytics.

Quantum computing has the potential to solve computational problems that are beyond the reach of classical computers. Amazon Braket and the Amazon Quantum Solutions Lab help customers explore quantum computing, evaluate its potential, and develop expertise. Amazon Braket is a managed service that provides customers access to quantum computing resources and makes it easy to build, simulate, and test quantum computing applications. The Quantum Solutions Lab connects customers with quantum experts for education and collaboration. In this session, learn about the potential of quantum computing and how you can get started with the Amazon Braket service and the Quantum Solutions Lab.

In this session, learn about EC2 Image Builder, a new capability that makes it easier and faster to build and maintain secure images. Keeping server images up-to-date can be time-consuming, resource-intensive, and error-prone. Currently, customers either manually update and snapshot VMs or have teams that build automation scripts to maintain images. Learn how EC2 Image Builder simplifies the creation, patching, testing, distribution, and sharing of Linux or Windows Server images.

Containerized applications, especially those using modern micro-service architectural patterns, are often robust to interruption and unexpected termination of individual containers. For this reason, containerized applications are a good fit for EC2 Spot and Fargate Spot. With minimal modifications, many containerized applications can run some or even all of their containers as-is on Spot at substantially lower cost. In this session we discuss the design decisions and best practices for utilizing EC2 Spot and Fargate Spot with modern containerized applications.

Fargate is a serverless compute engine for containers that supports multiple orchestrators. Come to this session to learn how the new integration between EKS and Fargate allows developers to deploy containers on a kubernetes cluster without thinking about infrastructure.

Learn how you can use Amazon RDS to create and manage databases running on-premises on AWS Outposts or VMware vSphere environments. AWS Outposts bring native AWS services, infrastructure, and operating models to virtually any data center, co-location space, or on-premises facility. We cover how you can use the same RDS capabilities that you use today on the cloud to easily set up, operate, scale, and manage databases running on AWS Outposts and VMware vSphere environments in your data centers. Amazon RDS automates time-consuming administrative tasks such as database setup, patching, backups, and restore in your on-premises environments. See how Amazon RDS makes it seamless to create, monitor, and manage databases running across your data centers and the cloud.

Even for the most seasoned engineers, it can be difficult to detect some types of code issues and challenging to identify the most expensive lines of code without performance engineering expertise. Amazon CodeGuru is a new machine learning service that helps you catch code issues faster and improve application performance. In this session, you get the details and a demo on how CodeGuru works. CodeGuru reviews Java code in your GitHub and AWS CodeCommit source code repositories, and it profiles your applications and searches for optimizations even in production. It also provides intelligent recommendations so that you can take action immediately to fix and improve code issues and inefficiencies.

AWS Network Manager is a new service that enables customers to centrally manage and monitor their global networks across AWS and their on-premises environments. Network Manager reduces the operational cost and complexity involved with visualizing and troubleshooting connectivity across remote locations, third-party network appliances, and cloud resources. Come to this session to learn more about this new service and how it integrates with AWS Transit Gateway, AWS Direct Connect, and AWS Site-to-Site VPNs.