AWS re:Invent 2018

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STG324: NEW LAUNCH! AWS DataSync - Automate & accelerate online data transfer Dec 01, 2018

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AWS DataSync is a new online data transfer service that automates movement of data between on-premises storage and Amazon S3 or Amazon Elastic File System (Amazon EFS). In this session, we will introduce the service, showing how you can use DataSync to move active on-premises data to the cloud for one-time migration, timely in-cloud analysis, and replication for data protection and recovery. We'll demonstrate how to get started with DataSync, and you'll hear how it is helping Cox Automotive to move their archive of millions of images to AWS.

STG326: NEW LAUNCH! AWS Transfer for SFTP, a Fully Managed SFTP Service Dec 01, 2018

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SFTP is used for the exchange of data across many industries, including financial services, healthcare, and retail. In this session, we will introduce you to AWS Transfer for SFTP, a service that helps you easily migrate file transfer workflows to AWS, without needing to modify applications or manage SFTP servers. We will demonstrate the product and talk about how to migrate your users so they continue to use their existing SFTP clients and credentials, while the data they access is stored in S3. You will also learn how FINRA is using this new service in conjunction with their Data Lake on AWS.

STG391: Post-Production Media Delivery at Scale with AWS Dec 01, 2018

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Netflix is using AWS Snowball Edge to deliver post-production content to our asset management system, called Content Hub, in the AWS Cloud. Production companies have been historically using LTO tapes to move data around, and that has well-known complications. In order to accelerate and secure our media workflows Netflix has shifted to using Snowball Edge devices for data migration. Please join us to learn how Netflix is using the Snowball Edge service at scale.

STG398: Creating Cost Efficiencies across S3 Resources Dec 01, 2018

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Amazon S3 supports a range of storage classes that can help you cost-effectively store data without impacting performance or availability. Each of our storage classes offer different data-access levels, retrieval times, and costs to support various use cases. In this session, Amazon S3 experts dive deep into the different Amazon S3 storage classes, their respective attributes, and when you should use them. Complete Title: AWS re:Invent 2018: [REPEAT 1] Deep Dive on Amazon S3 Storage Classes: Creating Cost Efficiencies across Your S3 Resources (STG398-R1)

STP01: Data Teams: The Moral Compass of AI Dec 01, 2018

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Do we have a moral role as data scientists? How do you balance your responsibility to do what's best for the company with your moral responsibility as a member of society? As data becomes more accessible to everyone, and as AI and ML technologies become part of our everyday life, the data team takes on an important moral role as the conscience of the corporation. In this presentation, PeriscopeData CEO and cofounder Harry Glaser explores examples in which using ML and AI for classification, prediction, ranking, and more, runs a strong risk of delivering immoral outcomes if unchallenged.

STP02: Application Release Management at Deliveroo Dec 01, 2018

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From PR to production, the Deliveroo Application Platform needs to get developers' code into running containers as quickly and as safely as possible. This talk introduces Hopper, our release manager, and our process for safely shipping software with support for automatic rollbacks, service scaling, and configuration management.

STP03: Leveraging Amazon SageMaker to Drive Rapid Innovation Dec 01, 2018

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Too often, data scientists build potentially high-impact models that never see the light of day due to deployment obstacles. At Convoy, data science is at the core of its trucking network product, so building a robust, frictionless platform to deploy models is critical to the company's success. To minimize the code needed to transition from training a model locally to deploying the same model in production, the company adopted Amazon SageMaker to push various models to production-ready endpoints. In this talk, Convoy's data science director, David Tsai, reviews Convoy's Amazon SageMaker architecture and highlights how it has enabled them to drive meaningful impact.

STP04: Aetion's Journey to AWS CodePipeline, AWS CloudFormation, & Amazon ECS Dec 01, 2018

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In this talk, Junaid Kapadia, DevOps manager and staff software engineer for Aetion Systems, speaks about the company's journey from a Chef, Jenkins, and EC2-based architecture to a fault-tolerant, highly available, continuously provisioned, and deployed architecture via AWS CodePipeline, AWS CodeBuild, AWS CloudFormation, AWS Systems Manager Parameter Store, and Amazon Elastic Container Service (Amazon ECS). Kapadia also discusses the history of Aetion's original architecture, explains how it transitioned its movement to the new architecture, and shares specific caveats of the purpose of each service and why it was chosen. He also talks about future developments of the overall architecture.

STP05: #BUIDLing the Decentralized Future on Ethereum Dec 01, 2018

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Over the past few years, the number of companies exploring blockchain solutions has skyrocketed, but for most, it is unclear where to start and what the right use cases are for their business. At ConsenSys, we are building all layers of the Web 3.0 stack, from protocol to application, and we are working with companies across all industries to create new business models based on blockchain. In this session, we dive into blockchain, Ethereum, smart contracts, and more as we discuss real-world examples and where the space is heading.

STP06: Data Engineering the Startup Way Dec 01, 2018

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Join representatives from Uptake Technologies to learn about data engineering the startup way. They cover Uptake's evolution as a startup organization and its journey in building data systems that scale for data science and industrial IoT. Additionally, they discuss the challenges of building systems for data science on industrial data and how Uptake has overcome difficult data engineering problems in this space. Attendees will come away with lessons learned that apply to almost any startup that is learning to build and grow in the cloud.

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