AWS re:Invent 2017

Latest Episodes:

CMP301: Deep Dive on Amazon EC2 Instances, Featuring Performance Optimization Best Practices Dec 01, 2017

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Amazon EC2 provides a broad selection of instance types to accommodate a diverse mix of workloads. In this session, we provide an overview of the Amazon EC2 instance platform, key platform features, and the concept of instance generations. We dive into the current generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and GPU instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.

CMP303: Innovate Faster with Salesforce Heroku and AWS Dec 01, 2017

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Salesforce and AWS are leading the next revolution in building engaging customer experiences. Behind every great experience is an app, and the power of the Salesforce platform lets you build apps fast. Adding to that experience is the AWS platform that extends the ability to rapidly deliver apps by offering developers a collection of purpose-built and ready-to-consume set of services. Salesforce Heroku—built entirely on AWS—enables developers to focus on building business apps fast instead of spending cycles on the monotonous heavy-lifting. In this session, you learn how Salesforce Heroku and AWS accelerate developer productivity and lower operational complexity to deliver solutions around Salesforce data integration, media delivery, web security, big data analytics and warehousing. Session sponsored by Salesforce

CMP304: Deep Dive: Backing Up Amazon EC2 with Amazon EBS Snapshots Dec 01, 2017

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With Amazon EBS, you can easily make a simple point-in-time backup for your Amazon EC2 instances. In this deep dive session, you learn how to use Amazon EBS snapshots to back up your Amazon EC2 environment. We review the basics of how snapshots work as well as how to tag snapshots, track costs, and automate snapshots using AWS Lambda. We describe best practices and share tips for success throughout.

CMP306: Architectures for HPC/HTC Workloads on AWS Dec 01, 2017

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Researchers and IT professionals who use high-performance computing (HPC) and high-throughput computing (HTC) need a large scale infrastructure to move their research forward. This session provides reference architectures for running your workloads on AWS, which enable you to achieve scale on-demand and reduce your time to science. We debunk myths about HPC in the cloud and demonstrate techniques for running common on-premises workloads in the cloud.

CMP307: Save up to 90% and Run Production Workloads on Spot Dec 01, 2017

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In this session, you learn how to effectively harness Spot Instances for production workloads. Amazon EC2 Spot Instances enable you to use spare EC2 computing capacity, capacity that is often 90% less than on-demand prices. We explore application requirements to use Spot Instances, best practices learned from thousands of customers, and the services that make it easy. Finally, we run through practical examples of how to use Spot for the most common production workloads, the common pitfalls customers run into, and how to avoid them.

CMP308: FPGA Accelerated Computing Using Amazon EC2 F1 Instances Dec 01, 2017

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Amazon EC2 F1 instances with field programmable gate arrays (FPGAs), combined with improved cloud-based FPGA programming tools, provides researchers, application developers, and startups with a well-tested, standardized, and accessible platform for hardware-accelerated computing. This session introduces you to Amazon EC2 F1 instances with FPGAs, walks you through a typical development and deployment process, and highlights a number of use cases in different domains, including genomics, video processing, text search, and financial computing.

CMP309: How Netflix Encodes at Scale Dec 01, 2017

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The Netflix encoding team is responsible for transcoding different types of media sources to a large number of media formats to support all Netflix devices. Transcoding these media sources has compute needs ranging from running compute-intensive video encodes to low-latency, high-volume image and text processing. The encoding service may require hundreds of thousands of compute hours to be distributed at moment's notice where they are needed most. In this session, we explore the various strategies employed by the encoding service to automate management of a heterogenous collection of Amazon EC2 Reserved Instances, resolve compute contention, and distribute them based on priority and workload.

CMP311: Auto Scaling Prime Time: Target Tracking Hits the Bullseye at Netflix Dec 01, 2017

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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.

CMP314: Bringing Deep Learning to the Cloud with Amazon EC2 Dec 01, 2017

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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

CMP315: Optimizing Network Performance for Amazon EC2 Instances Dec 01, 2017

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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.

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