Deploying Microsoft products on AWS is fast, easy, and cost-effective. Before deploying these applications to production, it's helpful to have guidance on approaches for securing them. In this session, we outline the principles for protecting the environment of Microsoft applications hosted on AWS, with a focus on risk assessment, reducing attack surface, adhering to the principle of least privilege, and protecting data.

Join us for this advanced-level talk to learn about Pokemon's journey defending against DDoS attacks and bad bots with AWS WAF, AWS Shield, and other AWS services. We go through their initial challenges and the evolution of their bot mitigation solution, which includes offline log analysis and dynamic updates of badbot IPs along with rate-based rules. This is an advanced talk and assumes some knowledge of Amazon DynamoDB, Amazon Kinesis Data Firehose, Amazon Kinesis Data Analytics, AWS Firewall Manager, AWS Shield, and AWS WAF.

AWS offers fully managed file system services that enable you to quickly and simply lift and shift or build new applications that access file data in the AWS Cloud. In this session, join Wayne Duso, the leader of file storage, hybrid-edge storage, and data transport services, to learn about our full set of file services and latest launches. Learn all about file storage, and get firsthand input on how you can accelerate your journey to AWS as you move from on-premises or do-it-yourself implementations to fully managed file storage solutions. Hear how AWS file storage solutions enabled LoanLogics to migrate its applications to the cloud, enabling better scalability, performance, and availability. Also discover why customers choose AWS file systems for migrating their mission-critical enterprise applications and compute-intensive workloads to deliver the performance they need in a cost-effective way, saving time and money.

Do you wonder what AWS thinks about mobile development? In this session, learn the very latest about the many AWS services that web and mobile developers can leverage to make cloud-enabled development possible, and hear what might be in store for the future.

Discover how AWS IoT services, Amazon Alexa, and AWS services help businesses leverage the AWS Cloud to make millions of homes safer, more efficient, and healthier for their occupants. The initial pilots on low-income customer base saw over 6-20% reduction in electricity bills using the minimal customer configuration of just Alexa and very basic smart device control. Discover how companies are using Amazon Experts to deploy Alexa and AWS IoT into millions of smart homes across wide geographies. Learn how AWS IoT Core, digital twin, AWS Lambda, and data analytics are used to execute real-time coordination logic, implement scheduled actions, and execute event-based bidirectional control architected to manage millions customers simultaneously. Learn how coupling this in-home IoT capability with cloud-based big data/ML algorithms enables new customer-centric outcomes, including appliance performance detection, improving the value of solar assets, security monitoring, and better ways to schedule daily energy-intensive tasks, such EV charging and hot water heaters.

Understanding gamer behavior is critical in acquiring, retaining, and monetizing users effectively. The cycle requires constant fine-tuning through expensive and complex live operations to offer fresh, fun, and challenging experiences. In this session, learn how Rovio uses machine learning (ML) to make this process faster, more efficient, and more accurate. Learn how to leverage AWS compute, analytics, and database services, such as Amazon S3, Amazon EC2, Amazon EMR, Amazon Athena, Amazon DynamoDB, and Amazon Redshift, to build an ML workflow that predicts the future interests and behaviors of gamers to better serve your needs and theirs.

Edge computing is all about moving compute power to the source of the data instead of having to bring it to the cloud. The edge is a fundamental part of IoT, and it is not only about connecting things to the internet. In this sesssion, we discuss how AWS Greengrass, which is an IoT edge software, can power devices small and large, from a sensor all the way to a wind turbine. With AWS Greengrass, these IoT devices can securely gather data, keep device data in sync, and communicate with each other while still using the cloud for management, analytics, and durable storage. Join us to learn more about the edge of IoT.

Curious about how Amazon machine learning (ML) services can enable healthcare organizations to find the insights they need to survive and thrive? Join us to learn how Takeda researchers built and trained their own disease-specific ML models, including deep-learning models using Deloitte ConvergeHEALTH running on AWS to simulate and quantify the overall disease burden and identify potential risks. This session is brought to you by AWS partner, Deloitte Consulting LLP.

A single device can produce thousands of events every second. In traditional implementations, all data is transmitted back to a server or gateway for scoring by a machine learning (ML) model. This data is also stored in a data repository for later use by data scientists. In this session, we explore data science techniques for dealing with time series data leveraging Amazon SageMaker. We also look at modeling applications using deterministic rules with streaming pipelines for data prep, and model inferencing using deep learning frameworks directly onto edge devices or onto AWS Lambda using Project Flogo, an open-source event-driven framework. This session is brought to you by AWS partner, TIBCO Software Inc.

In this session, hear from an AWS customer about how they leveraged Amazon Rekognition deep learning-based image and video analysis to power a data-driven decision system for creative asset production. Learn how this customer was able to leverage the raw data provided by Amazon Rekognition combined with performance data to discover actionable insights. See a demonstration of the solution, and hear about media- and advertising-specific use cases. Learn from the customer's experiences implementing their architecture, the challenges, and the pleasant surprises along the way.

Amazon has a long history in AI, from personalization and recommendation engines to robotics in fulfillment centers. Amazon Go, Amazon Alexa, and Amazon Prime Air are also examples. In this session, learn more about the latest machine learning services from AWS, and hear from customers who are partnering with AWS for innovative AI.