AWS re:Invent 2017

Latest Episodes:

CTD406: Measuring the Internet in Real Time Dec 01, 2017

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Join this session for an in-depth look into how the Amazon CloudFront team measures the internet in real time to give our customers the best possible experience using AWS technologies, such as Amazon Kinesis and Amazon EMR. AWS customers should expect to leave this whiteboarding session with sample design patterns that they can use when they build their own distributed applications that need a feedback control system.

CTD408: I Want to Analyze and Visualize Website Access Logs, but Why Do I Need Servers to Do That? Dec 01, 2017

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Nowadays, it's common for a web server to be fronted by a global content delivery service, such as Amazon CloudFront, to accelerate delivery of websites, APIs, media content, and other web assets. Website administrators and developers want to generate insights in order to improve website availability through bot detection and mitigation, by optimizing web content based on the devices and browser used, by reducing perceived latency by caching a popular object closer to its viewer, and so on. In this session, we dive deep into building an end-to-end serverless analytics solution to analyze Amazon CloudFront access logs, both at rest and in transit, using Amazon Athena and Amazon Kinesis Analytics, respectively, and we generate visualization insights using Amazon QuickSight. Join a discussion with AWS solution architects to learn more about the various ways to generate insights to improve the overall perceived experience for your website users.

DAT202: Getting Started with Amazon Aurora Dec 01, 2017

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Amazon Aurora services are MySQL and PostgreSQL -compatible relational database engines with the speed, reliability, and availability of high-end commercial databases at one-tenth the cost. This session introduces you to Amazon Aurora, explores the capabilities and features of Aurora, explains common use cases, and helps you get started with Aurora.

DAT203: Running MySQL Databases on AWS Dec 01, 2017

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MySQL is the world's most popular open source relational database and is used by dozens of popular open source applications. AWS provides several ways to run a MySQL application in the cloud, including Amazon EC2, Amazon RDS for MySQL, Amazon RDS for MariaDB, and Amazon Aurora. This session presents the different options for running MySQL in the AWS Cloud, discusses the different ways to migrate your MySQL database to AWS, and provide tips and tricks for optimizing your MySQL workloads in AWS. Also, a customer presents lessons learned while migrating their MySQL databases to AWS.

DAT204: What's New for AWS Purpose Built, Non-relational Databases Dec 01, 2017

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In this session, Shawn Bice, VP of NoSQL and QuickSight, will cover what's new in AWS non-relational data services, such as Amazon DynamoDB, Amazon ElastiCache, and Amazon Elastisearch. We will discuss how developers might select different data services to solve different aspects of an application and demo scenarios on which application use cases lend themselves well to which data services. If you're a developer building massively scaled applications, requiring flexibility, consistent millisecond performance, and trying to understand what non-relational data service you might use, this is a great introductory session.

DAT301: Deep Dive on the Amazon Aurora MySQL-compatible Edition Dec 01, 2017

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The Amazon Aurora MySQL-compatible Edition is a fully managed relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. It is purpose-built for the cloud using a new architectural model and distributed systems techniques. It provides far higher performance, availability, and durability than previously possible using conventional monolithic database architectures. Amazon Aurora packs a lot of innovations in the engine and storage layers. In this session, we do a deep-dive into some key innovations behind Amazon Aurora MySQL-compatible edition. We explore new improvements to the service and discuss best practices and optimal configurations.

DAT302: Deep Dive on Amazon Relational Database Service (RDS) Dec 01, 2017

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Amazon RDS enables 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 Oracle, Microsoft SQL Server, PostgreSQL, MySQL and MariaDB. In this session, we take a closer look at the capabilities of the RDS service and review the latest features available. We do a deep dive into how RDS works and the best practices to achieve the optimal performance, flexibility, and cost saving for your databases.

DAT304: DynamoDB - What's new Dec 01, 2017

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This is the general session for Amazon DynamoDB and will cover newly announced features, as well as provide an end to end view of recent innovations. We will also share some of our successful customer stories and use cases. Come to this session to learn all about what's new for DynamoDB!

DAT305: ElastiCache Deep Dive: Best Practices and Usage Patterns Dec 01, 2017

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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.

DAT307: Modern Cloud Data Warehousing: Blending Structured and Semi-Structured Data in Real Time Dec 01, 2017

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We're still in the midst of a data explosion. With data, we want to do things smarter, quicker, and more accurately, and working with a company like Snowflake enables us to do so. In this session, Kelly Mungary, Lionsgate director of enterprise data and analytics, details how Lionsgate achieved the “Holy Grail” of data analytics – easily storing, blending, and analyzing structured and semi-structured data for agile reporting and data science. With modern data warehousing built for the cloud, Lionsgate achieves faster time to market and continues to migrate investment away from traditional, fading platforms. Lionsgate is a leading global entertainment company that generates vast stores of varied data types from sales, research, social media, exit polls, box office activity, and many other channels to better serve its business customers and its fans. Session sponsored by Snowflake

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