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Massive Scale Anomaly Detection Framework

PayPal analyzes billions of events every day in real-time across a wide range of services, devices and locations. In a collaboration between their Platform engineering team and data science teams, they have built a generic framework for developing robust and scalable anomaly detection streaming applications, focusing on flexibility to support different types of statistical and machine learning models. Inspired by the design of scikit-learn and Spark MLlib, the data team has designed a simple pipeline-based API on top of Spark Structured Streaming, that captures common patterns of the anomaly detection domain. 


Fannie Mae Processes over a Quarter Million Loans per Day w/ Amazon S3

Fannie Mae discusses how they completely re-architected a mission-critical application using AWS native services that process hundreds of thousands of mortgage loans every day in a highly scalable and reliable manner. The transaction-heavy workload uses over 20+ million Amazon S3 transactions a day, each within 150-millisecond response times, thus providing increased uptime and faster response. 


Moody’s: Deploying Cloud-Native Architectures with Automation

Moody’s has chosen Terraform as their tool of choice to define and deploy their application and security infrastructure for a range of different use cases on AWS. In this session, you will learn about Moody's range of automation use cases, including: AWS infrastructure creation; deployment of a shared service environment; onboarding of new/existing lines-of-business; and Integration with threat intelligence services such as Amazon GuardDuty. 


Policy Verification and Enforcement at Scale with AWS

Learn how Goldman Sachs uses  AWS Config, AWS Lambda, Amazon DynamoDB, and Amazon Simple Notification Service (Amazon SNS) as distributed infrastructure that help catch security issues early and remediate those that happen unexpectedly. You will also learn how they use distributed serverless logging pipelines and leverages AWS formal verification tools to help enforce access policy in the process.


How Uses Amazon SageMaker & AWS Glue to Enable Machine Learning processes over 40 million documents a year that customers upload into their system. These documents arrive unstructured, random, and in multiple formats. This talk describes how uses AWS for their Secure Data Platform infrastructure in order to enable machine learning. Kyle Guichard, Sr. Director Systems Engineering at, highlights how they leverage Amazon S3, Amazon SageMaker, and AWS Glue to enable the next generation of their Intelligent Virtual Assistant for zero data entry, which results in increased accuracy and efficiency for digital business payments for their customers.