AWS re:Invent 2016

Latest Episodes:

CMP316: Learn How FINRA Aligns Billions of Time Ordered Events with Spark on EC2 Dec 25, 2016

Show notes

FINRA is a leader in the Financial Services industry who sought to move toward real-time data insights of billions of time-ordered market events by migrating from SQL batch processes on-prem, to Apache Spark in the cloud. By using Apache Spark on Amazon EMR, FINRA can now test on realistic data from market downturns, enhancing their ability to provide investor protection and promote market integrity (FINRA enacts rules and provides guidance that securities exchanges & brokers must follow). By using AWS Spot instances, FINRA has saved up to 50% from its on premises solution, increased elasticity/scalability, and accelerated reprocessing requests (from months to days). Learn best practices on how FINRA moves toward real-time data analytics with Spark and AWS, while managing production workloads in parallel, increasing performance and IT efficiency, reducing cost, and modernizing and scaling their infrastructure to prepare for real-time processing in the future.

CMP317: Massively Parallel, Compute Intensive Workloads in the Cloud -- Choosing the right hardware accelerator and example use cases Dec 25, 2016

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Accelerated computing is on the rise because of massively parallel, compute-intensive workloads such as deep learning, 3D content rendering, financial computing, and engineering simulations. In this session, we provide an overview of our accelerated computing instances, including how to choose instances based on your application needs, best practices and tips to optimize performance, and specific examples of accelerated computing in real-world applications.

CMP318: Building HPC Clusters as Code in the (Almost) Infinite Cloud Dec 25, 2016

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Every day, the computing power of high-performance computing (HPC) clusters helps scientists make breakthroughs, such as proving the existence of gravitational waves and screening new compounds for new drugs. Yet building HPC clusters is out of reach for most organizations, due to the upfront hardware costs and ongoing operational expenses. Now the speed of innovation is only bound by your imagination, not your budget. Researchers can run one cluster for 10,000 hours or 10,000 clusters for one hour anytime, from anywhere, and both cost the same in the cloud. And with the availability of Public Data Sets in Amazon S3, petabyte scale data is instantly accessible in the cloud. Attend and learn how to build HPC clusters on the fly, leverage Amazon’s Spot market pricing to minimize the cost of HPC jobs, and scale HPC jobs on a small budget, using all the same tools you use today, and a few new ones too.

CMP319: NEW LAUNCH! Building Distributed Applications with AWS Step Functions Dec 25, 2016

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AWS Step Functions is a new, fully managed service that makes it easy to coordinate the components of distributed applications and microservices using visual workflows. Step Functions is a reliable way to coordinate components and step through the functions of your application. A graphical console helps you arrange and visualize the components of your application as a series of steps. Step Functions automatically triggers and tracks each step and retries when there are errors so that your application executes in order―and as expected―every time. This session shows how to use Step Functions to create, run, and debug multi-service applications in a matter of minutes. We also share how customers are using Step Functions to reliably build and scale multi-step applications such as order processing, report generation, and data transformation―and to innovate faster.

CON402: Securing Container-Based Applications Dec 25, 2016

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Containers have had an incredibly large adoption rate since Docker was launched, especially from the developer community, as it provides an easy way to package, ship, and run applications. Securing your container-based application is now becoming a critical issue as applications move from development into production. In this session, you learn ways to implement storing secrets, distributing AWS privileges using IAM roles, protecting your container-based applications with vulnerability scans of container images, and incorporating automated checks into your continuous delivery workflow.

CTD202: Deliver and Monetize Your Content with Video Center Operations on AWS Dec 25, 2016

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The flexibility of AWS provides many advantages in the processing and delivery of bursty video applications such as video on demand and live events. However, full channel playout and advanced monetization have been the domains of traditional on-premises workflows. Learn how Elemental and AWS are architecting media-centric playout, monetization, and delivery services on top of AWS with live and file playlist integration, static and motion graphic overlays, ad content transcoding, and personalized, server-side ad insertion to bring additional video center operations to the cloud.

DAT204: How Thermo Fisher Is Reducing Mass Spectrometry Experiment Times from Days to Minutes with MongoDB & AWS Dec 25, 2016

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Mass spectrometry is the gold standard for determining chemical compositions, with spectrometers often measuring the mass of a compound down to a single electron. This level of granularity produces an enormous amount of hierarchical data that doesn't fit well into rows and columns. In this talk, learn how Thermo Fisher is using MongoDB Atlas on AWS to allow their users to get near real-time insights from mass spectrometry experiments—a process that used to take days. We also share how the underlying database service used by Thermo Fisher was built on AWS.

DAT304: Deep Dive on Amazon DynamoDB Dec 25, 2016

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Explore Amazon DynamoDB capabilities and benefits in detail and learn how to get the most out of your DynamoDB database. We go over best practices for schema design with DynamoDB across multiple use cases, including gaming, AdTech, IoT, and others. We explore designing efficient indexes, scanning, and querying, and go into detail on a number of recently released features, including JSON document support, DynamoDB Streams, and more. We also provide lessons learned from operating DynamoDB at scale, including provisioning DynamoDB for IoT.

DAT305: Deep Dive on Amazon Relational Database Service Dec 25, 2016

Show notes

Amazon RDS allows customers to launch an optimally configured, secure and highly available database with just a few clicks. It provides cost-efficient and resizable capacity while managing time-consuming database administration tasks, freeing you up to focus on your applications and business. Amazon RDS provides you six database engines to choose from, including Amazon Aurora, Oracle, Microsoft SQL Server, PostgreSQL, MySQL and MariaDB. In this session, we take a closer look at the capabilities of RDS and all the different options available. We do a deep dive into how RDS works and the best practises to achive the optimal perfomance, flexibility, and cost saving for your databases.

DAT306: ElastiCache Deep Dive: Best Practices and Usage Patterns Dec 25, 2016

Show notes

In this session, we provide a peek behind the scenes to learn about Amazon ElastiCache's design and architecture. See common design patterns with our Redis and Memcached offerings and how customers have used them for in-memory operations to reduce latency and improve application throughput. During this session, we review ElastiCache best practices, design patterns, and anti-patterns.

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