AWS re:Invent 2017

Latest Episodes:

FSV307: Capital Markets Discovery: How FINRA Runs Trade Analytics and Surveillance on AWS Dec 01, 2017

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FINRA's analytics platform unlocks the value in capital markets data by accelerating trade analytics and providing a foundation for machine learning at scale. The platform enables FINRA's analysts to perform discovery on petabytes of trade data to identify instances of potential fraud, market manipulation, and insider trading. By centralizing all data in S3, FINRA's architecture offers improved agility, scalability, and cost effectiveness. Analytics services such as Amazon EMR and Amazon Redshift have freed FINRA's data scientists from the constraints of desktop tools, allowing them to apply machine learning techniques to develop and test new surveillance patterns. All of this is done while meeting FINRA's security and compliance responsibilities as a financial regulator. At the end of this session, you'll have an understanding of how to apply FINRA's architecture to trade analytics and other financial services use cases, including meeting regulatory requirements such as the Consolidated Audit Trail (CAT) reporting.

FSV308: Culture Shift: How to Move a Global Financial Services Organization to a DevOps Operating Model Dec 01, 2017

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Many enterprises that follow regulated, process-driven workflows would like to take advantage of the innate features and benefits of AWS to become more agile, achieve operational excellence, and accelerate time-to-market while leveraging a DevOps culture and development methodology. But building a mature DevOps capability doesn't happen overnight. Creating and implementing testing, compliance, and security automation frameworks requires time and organizational and process changes. Financial institutions are addressing this challenge by using AWS Service Catalog to help bridge the gap between traditional operations and true DevOps.

GAM301: Migrating the League of Legends Platform into the AWS Cloud Dec 01, 2017

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For years, Riot Games deployed to their own private data centers across the globe to meet the growing demands of their game, League of Legends. The last seven years saw explosive growth in new data centers worldwide, along with a great deal of technical debt. This is Riot Games' story of how they overcame their technical debt by taking the League of Legends platform into the AWS Cloud. AWS services gave Riot Games the infrastructure agility they were lacking within their data centers and empowered them to focus more on new player features and less on legacy infrastructure. In this session, you learn why and how Riot Games migrated their existing platform to the AWS Cloud and the advantages gained by the move using services such as Amazon EC2, Elastic Load Balancing (with Application Load Balancers), Amazon EBS, and Auto Scaling. Riot Games also shares how they created new automation toolsets to enable the existing tools and replace a few legacy ones.

GAM303: Migrating Battleborn and the Spark Platform to Amazon GameLift for Multiplayer Game Servers Dec 01, 2017

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Learn how Gearbox integrated Amazon GameLift into "Spark", the cloud-ready infrastructure that powers all of their games. In this session, Gearbox talks about the mental shifts they had to make when moving their games online, as well as the unexpected challenges. Gearbox also dives deep into their experience of integrating the Amazon GameLift Server SDK, running multiple processes with different parameters, asynchronous build deployment, global fleet management, load balancing, and scaling to meet unexpected player demand. You'll learn Amazon GameLift best practices that can help simplify game session management, reduce engineering overhead, and optimize for player experience.

GAM305: Automating Mother Nature: How Nexon Used AWS Services to Algorithmically Create and Manage an In-Game Ecosystem Dec 01, 2017

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Given the complexity and scale of contemporary games, it's been a dream of game creators to algorithmically generate game content. Nexon wanted to create a large-scale, open-world MMORPG called Durango, where algorithmic generation is desperately needed to minimize development costs and maintain game longevity. In-game objects such as trees and plants are placed based on complex rules, with the intention of mimicking the realistic ecosystem that evolves continuously. However, a large amount of computation and a careful orchestration of various computing resources are required due to the immense size of the in-game lands. Nexon achieved this goal by leveraging AWS services to take advantage of massive parallelism supported by the infrastructure. In this talk, Nexon discusses the architecture they settled on for algorithmic generation of game content in a large scale, and the AWS services involved such as Amazon SQS and Amazon ECS with automatic scaling and spot instances.

GAM306: Building a Lake of Wisdom Dec 01, 2017

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Learn how Rovio replaced functionalities in their analytics platform provided by a 3rd party vendor in seven weeks with Amazon Athena, Amazon EMR, and Amazon Redshift. In the ever changing world of games, you must stay ahead of trends and understand your customer base's actions. We describe how we built a data lake using AWS services such as Amazon S3, Amazon Athena, and Amazon EMR. We give a general overview on our analytics stack, business problems unique to the gaming industry we're trying to solve, data philosophy (one truth, open data), and challenges we had at the beginning of this year. We also dive deep into areas most gaming companies struggle with, like how we manage the schemas, convert data to efficient columnar format, partition the data, ultimately use the data, and handle some of the challenges we faced using services like Athena. Learn about our quest to perfect games and customer gaming experience!

GAM307: Ubisoft: How For Honor Runs Using Amazon ECS Dec 01, 2017

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This session covers how the team at Ubisoft evolved For Honor's infrastructure using Amazon ECS and supporting systems (Amazon CloudFront, Amazon ElastiCache, Amazon Elasticsearch Service, Amazon SQS, and AWS Lambda, with monitoring through DataDog) from a proof of concept to an infrastructure as code solution. The team shares war stories about supporting both internal and live environments, and the challenges of bridging cloud and on-premises systems.

GAM311: How Linden Lab Built a Virtual World on the AWS Cloud Dec 01, 2017

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Linden Lab has spent over a decade optimizing the production operations for Second Life, an online 3D virtual world created by its users. With our new social VR platform, Sansar, we wanted to take our vision of virtual experiences to a whole new level of innovation in which AWS played a vital role. We'll dive into Sansar's AWS tech stack, an infrastructure built not only for technical robustness but also extreme scalability. We will discuss what the different use cases were between EC2 and Containers and how Lambda worked as a positive enabler for customization. Lastly, we'll cover IAM, Security Groups and VPC, which we refer collectively as the "Great Wall of Preventing Unfortunate Design Decisions.”.

GAM401: Designing for the Future: Building a Flexible Event-based Analytics Architecture for Games Dec 01, 2017

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The pace of technology innovation is relentless, especially at AWS. Designing and building new system architectures is a balancing act between using established, production-ready technologies while maintaining the ability to evolve and take advantage of new features and innovations as they become available. In this session, learn how Amazon Game Studios built a flexible analytics pipeline on AWS for their team battle sport game, Breakaway, that provided value on day one, but was built with the future in mind. We will discuss the challenges we faced and the solution we built for ingesting, storing and analyzing gameplay telemetry and dive deep into the technical architecture using AWS many services including Amazon Kinesis, Amazon S3, and Amazon Redshift. This session will focus on game analytics as a specific use case, but will emphasize an overarching focus on designing an architectural flexibility that is relevant to any system.

GPSBUS201: GPS: Artificial Intelligence, Machine Learning, Deep Learning: Cutting through the Hype Dec 01, 2017

Show notes

In this session, we provide an overview of the artificial intelligence/machine learning landscape, discuss the current state of the industry, and identify new market opportunities. Partners will come away with a better understanding of the investment that AWS is making in this space, as well as our unique value proposition.

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