AWS re:Invent 2017

Latest Episodes:

DAT318: NEW LAUNCH! Deep dive on Amazon Neptune Dec 01, 2017

Show notes

Amazon Neptune is a fully managed graph database service which has been built ground up for handling rich highly connected data. Graph databases have diverse use cases across multiple industries; examples include recommendation engines, knowledge graphs, fraud detection, social networks, network management and life sciences. Amazon Neptune is open and flexible with support for Apache TinkerPop and RDF/SPARQL standards. Under the hood Neptune uses the same foundational building blocks as Amazon Aurora which gives it high performance, availability and durability. In this session, we will do a deep dive into capabilities, performance and key innovations in Amazon Neptune.

DAT319: NEW LAUNCH! Amazon Neptune Overview and Customer Use Cases Dec 01, 2017

Show notes

In this session, we will provide an overview of Amazon Neptune, AWS's newest database service. Amazon Neptune is a fast, reliable graph database that makes it easy to build applications over highly connected data. We will then explore how Siemens is building a knowledge using Amazon Neptune.

DAT320: Moving a Galaxy into the Cloud: Best Practices from Samsung on Migrating to Amazon DynamoDB Dec 01, 2017

Show notes

In this session, we introduce you to the best practices for migrating databases, such as traditional RDBMS or other NoSQL databases to Amazon DynamoDB. We discuss DynamoDB key concepts, evaluation criteria, data modeling in DynamoDB, how to move data into DynamoDB, and data migration key considerations. We share a case study of Samsung Electronics, which migrated their Cassandra cluster to DynamoDB for their Samsung Cloud workload.

DAT321: From Minutes to Milliseconds: How Careem Used Amazon ElastiCache for Redis to Accelerate Their Ride Share Application Dec 01, 2017

Show notes

AWS architecture for Careem, a fast-growing car-booking service in the broader Middle East, has quickly evolved to support over six million users in eleven countries. Careem also operates in areas with weak GPS signals and unique traffic patterns, resulting in the poor user experience of long driver match times and rider wait times. Careem was storing driver location data in MySQL, but their high volume of concurrent calls and lack of geospatial support in MySQL 5.6 resulted in continuous deadlocks and performance issues. Amazon ElastiCache for Redis helped meet their need for in-memory storage service with advanced data structures. ElastiCache for Redis accelerated their car booking application and reduced ride matching times from several minutes to milliseconds. Learn how their big bottleneck of insert and update operations in MySQL became a quick lookup in ElastiCache for Redis by using Redis Sorted Sets, geohashes, and timestamps.

DAT322: The Nanoservices Architecture That Powers BBC Online Dec 01, 2017

Show notes

The BBC's website and apps are used around the world by an audience of millions who read, watch, and interact with a range of content. The BBC handles this scale with an innovative website platform, built on Amazon ElastiCache and Amazon EC2 and based on nanoservices. The BBC has over a thousand nanoservices, powering many of its biggest webpages. Explore its nanoservices platform and use of ElastiCache. Learn how Redis's ultra-fast queues and pub/sub allow thousands of nanoservices to interact efficiently with low latency. Discover intelligent caching strategies to optimize rendering costs and ensure lightning fast performance. Together, ElastiCache and nanoservices can make real-time systems that can handle thousands of requests per second.

DAT323: Dating and Data Science: How Coffee Meets Bagel Uses Amazon ElastiCache to Deliver High-Quality Match Recommendations Dec 01, 2017

Show notes

Coffee Meets Bagel is a top-tier dating app that focuses on delivering high-quality matches via our recommendation systems. We use Amazon ElastiCache as part of our recommendation pipeline to identify nearby users with geohashing, store feature vectors for on-demand user similarity calculations, and perform set intersections to find mutual friends between candidate matches. Coffee Meets Bagel also employs Redis for other novel use cases, such as a fault-tolerant priority queue mechanism for its asynchronous worker processes, and storing per-user recommendations in sorted sets. Join our top data scientist and CTO as we walk you through our use cases and architecture and highlight ways to take advantage of ElastiCache and Redis.

DAT324: Expedia flies with DynamoDB: lightning fast stream processing for travel analytics Dec 01, 2017

Show notes

Building rich, high-performance streaming data systems requires fast, on-demand access to reference data sets, to implement complex business logic. In this talk, Expedia will discuss the architectural challenges the company faced, and how DAX + DynamoDB fits into the overall architecture and met their design requirements. Additionally, you will hear how DAX that enabled Expedia to add caching to their existing applications in hours, which previously was taking much longer. Session attendees will walk away with three key outputs: 1) Expedia's overall architectural patterns for streaming data 2) how they uniquely leverage DynamoDB, DAX, Apache Spark, and Apache Kafka to solve these problems 3) the value that DAX provides and how it enabled them to improve our performance and throughput, reduce costs, and all without having to write any new code.

DAT325: Snapchat Stories on Amazon DynamoDB Dec 01, 2017

Show notes

The backend for the Snapchat Stories feature includes Snapchat's largest storage write workload. Learn how we rebuilt this workload for Amazon DynamoDB and executed the migration. Safely moving such a critical and high-scale piece of the Stories infrastructure to a new system, right before yearly peak usage, led to interesting challenges. In this session, we cover data model changes to leverage DynamoDB strengths and improve both performance and cost. We also cover challenges and risks in making remote calls across cloud providers, dealing with issues of scale, forecasting capacity requirements, and how to mitigate the risks of taking an unproven system through the dramatic traffic spikes that occur on New Year's Eve.

DAT326: How DynamoDB Powered Amazon Prime Day 2017 Dec 01, 2017

Show notes

Sales on Prime Day 2017 surpassed Black Friday and Cyber Monday, making it the biggest day ever in Amazon history. An event of this scale requires infrastructure that can easily scale to match the surge in traffic. In this session, learn how AWS and Amazon DynamoDB powered Prime Day 2017. DynamoDB requests from Amazon Alexa, the Amazon.com sites, and the Amazon fulfillment centers peaked at 12.9 million per second, a total of 3.34 trillion requests. Learn how the extreme scale, consistent performance, and high availability of DynamoDB let Amazon.com meet the needs of Prime Day without breaking a sweat.

DAT327: DynamoDB adaptive capacity: smooth performance for chaotic workloads Dec 01, 2017

Show notes

Database capacity planning is critical to running your business, but it's also hard. In this session we'll compare how scaling is usually performed for relational databases and NoSQL databases. We'll look behind the scenes at how DynamoDB shards your data across multiple partitions and servers. Finally, we'll talk about some of the recent enhancements to DynamoDB that make scaling even simpler, particularly a new feature called adaptive throughput that eliminates much of the throttling issues that you may have experienced.

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