Building the ideal architecture
for remote and hybrid work

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100,000+ databases migrated to AWS 10,000+ data lakes and data warehouses deployed on AWS Hundreds of thousands of customers rely on AWS Databases

Why attend?

Increasing reliance on remote and hybrid work requires an evolution in the way we use technology to prevent risks while reducing costs.

Industry trends point to better ways to get work done and retain talent, with over 70% of the Global 2000 organizations deploying remote or hybrid-first work models by 2023.1 This puts pressure on IT, security, and human resources teams trying to build and manage infrastructure and onboard new hires based remotely all while providing secure access to propriety data without creating risk or exposure to bad actors.

At AWS End User Computing (EUC) Innovation Day 2022, you’ll learn how your organization can rearchitect its technology stack to strengthen security and reduce costs while enabling your employees to work from anywhere.

This event is ideal for anyone eager to learn more about:

  • How to securely modernize your desktop and application delivery solutions to support a hybrid workforce
  • How Amazon WorkSpaces, Amazon WorkSpaces Web, and Amazon AppStream 2.0 improve IT agility while keeping costs low
  • How AWS End User Computing and AWS Partners provide tools that encourage employee innovation and increase productivity

Event Agenda

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Event Agenda

  • To get the day started we take a quick look back at 20+ years of AI/ML innovation covering everything from predictive models used in fulfilment centers to Amazon SageMaker to autonomous vehicles delivering packages. We explain many of the world's firsts in AI/ML innovations delivered by Amazon.
  • Hear directly from customers innovating with AI/ML in the areas of sustainability and accessibility globally such as Mueller Water Products, Inspire, ResMed, and Siemens.
  • The decision making side of machine learning: computational, inferential, and economic perspectives
  • Much of the recent focus in machine learning has been on the pattern recognition side of the field. This talk will instead focus on the decision making side, where many fundamental challenges remain. Some are statistical in nature, including the challenges associated with multiple decision making. Others are economic, involving learning systems that must cope with scarcity, competition, and incentives, and some are algorithmic, including the challenge of coordinated decision making on distributed platforms and the need for algorithms to converge to equilibria rather than optima. How can next-generation machine learning platforms provide environments that support this kind of large scale, dynamic, data-aware, and market-aware decision making?
  • AWS leadership session
  • We explore the latest news from AWS services to see how we are helping more customers move from idea to production with machine learning.
  • Closing remarks from an AWS Evangelist

Event Agenda

  • Track2 Session 1
  • Track3 Session 1
  • Track4 Session 1
  • Track5 Session 1
  • Track6 Session 1
  • Track7 Session 1
  • Track8 Session 1
  • Track9 Session 1
  • Track10 Session 1

8:00 AM – 10:00 AM PT | 11:00 AM - 1:00 PM ET

Lab: Microservice Extractor for .NET

Level: 300

Description: AWS Microservice Extractor for .NET simplifies the process of refactoring applications into independent services. Modernize and transform your applications with an assistive tool that analyzes source code and runtime metrics to create a visual representation of your application and its dependencies. AWS Microservice Extractor for .NET delivers a holistic visualization of applications and assists in code refactoring and extraction of the codebase into separate code projects that teams can develop, build, and operate independently to improve agility, uptime, and scalability.

• This workshop will guide you through a step-by-step process of extracting an independent service from a monolithic ASP.NET application.
• You will use AWS Microservice Extractor to visualize, group and extract parts of the monolith as a separate service.
• The workshop expects that participants have an introductory knowledge of C# and Visual Studio.

Presenters:

• Craig Bossie, Senior Microsoft Specialist Solutions Architect, AWS
• Runeet Vashisht, Senior Solutions Architect, Microsoft Workloads, AWS



10:00 AM – 11:00 AM PT | 1:00 PM - 2:00 PM ET

Presentation: Plan, Migrate and Modernize your Microsoft Workloads on AWS

Level: 300

Description: Customers have been running their Microsoft workloads on AWS for over 12 years, longer than any other cloud provider. Today, over 300,000 customers trust AWS with their Microsoft workloads. Over the years, AWS programs have helped our customers achieve substantial business benefit by providing an approach and investments to accelerate, reduce risks, and offset costs when migrating workloads to AWS. In this session, we’ll overview the typical journey Windows workloads take when moving to AWS; including the planning, tooling, and guidance that AWS can provide.

Presenter:

• Eric Cyffka, EC2 Windows Migration & Modernization Programs Manager, AWS

8:00 AM – 10:00 AM PT | 11:00 AM - 1:00 PM ET

Lab: Microservice Extractor for .NET

Level: 300

Description: AWS Microservice Extractor for .NET simplifies the process of refactoring applications into independent services. Modernize and transform your applications with an assistive tool that analyzes source code and runtime metrics to create a visual representation of your application and its dependencies. AWS Microservice Extractor for .NET delivers a holistic visualization of applications and assists in code refactoring and extraction of the codebase into separate code projects that teams can develop, build, and operate independently to improve agility, uptime, and scalability.

• This workshop will guide you through a step-by-step process of extracting an independent service from a monolithic ASP.NET application.
• You will use AWS Microservice Extractor to visualize, group and extract parts of the monolith as a separate service.
• The workshop expects that participants have an introductory knowledge of C# and Visual Studio.

Presenters:

• Craig Bossie, Senior Microsoft Specialist Solutions Architect, AWS
• Runeet Vashisht, Senior Solutions Architect, Microsoft Workloads, AWS



10:00 AM – 11:00 AM PT | 1:00 PM - 2:00 PM ET

Presentation: Plan, Migrate and Modernize your Microsoft Workloads on AWS

Level: 300

Description: Customers have been running their Microsoft workloads on AWS for over 12 years, longer than any other cloud provider. Today, over 300,000 customers trust AWS with their Microsoft workloads. Over the years, AWS programs have helped our customers achieve substantial business benefit by providing an approach and investments to accelerate, reduce risks, and offset costs when migrating workloads to AWS. In this session, we’ll overview the typical journey Windows workloads take when moving to AWS; including the planning, tooling, and guidance that AWS can provide.

Presenter:

• Eric Cyffka, EC2 Windows Migration & Modernization Programs Manager, AWS

8:00 AM – 10:00 AM PT | 11:00 AM - 1:00 PM ET

Lab: Microservice Extractor for .NET

Level: 300

Description: AWS Microservice Extractor for .NET simplifies the process of refactoring applications into independent services. Modernize and transform your applications with an assistive tool that analyzes source code and runtime metrics to create a visual representation of your application and its dependencies. AWS Microservice Extractor for .NET delivers a holistic visualization of applications and assists in code refactoring and extraction of the codebase into separate code projects that teams can develop, build, and operate independently to improve agility, uptime, and scalability.

• This workshop will guide you through a step-by-step process of extracting an independent service from a monolithic ASP.NET application.
• You will use AWS Microservice Extractor to visualize, group and extract parts of the monolith as a separate service.
• The workshop expects that participants have an introductory knowledge of C# and Visual Studio.

Presenters:

• Craig Bossie, Senior Microsoft Specialist Solutions Architect, AWS
• Runeet Vashisht, Senior Solutions Architect, Microsoft Workloads, AWS



10:00 AM – 11:00 AM PT | 1:00 PM - 2:00 PM ET

Presentation: Plan, Migrate and Modernize your Microsoft Workloads on AWS

Level: 300

Description: Customers have been running their Microsoft workloads on AWS for over 12 years, longer than any other cloud provider. Today, over 300,000 customers trust AWS with their Microsoft workloads. Over the years, AWS programs have helped our customers achieve substantial business benefit by providing an approach and investments to accelerate, reduce risks, and offset costs when migrating workloads to AWS. In this session, we’ll overview the typical journey Windows workloads take when moving to AWS; including the planning, tooling, and guidance that AWS can provide.

Presenter:

• Eric Cyffka, EC2 Windows Migration & Modernization Programs Manager, AWS

Track2 Session 1

Migrate your Oracle and SQL Server databases to

Organizations today are looking to free themselves from the constraints of on-premises databases and leverage the power of fully managed databases in the cloud. Amazon RDS is a fully managed relational database service that you can use to run your choice of database engines including open source engines, Oracle, and SQL Server in the cloud. Amazon RDS automates time-consuming database administration tasks and adds capabilities such as replication and Multi-AZ failover to make your database deployments more scalable, available, reliable, manageable, and cost-effective. This session covers why you should consider moving your on-premises Oracle & SQL Server deployments to Amazon RDS and the tools to get started.

Track3 Session 1

Tab 3 content

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Track4 Session 1

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Track5 Session 1

Tab 5 content

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Track6 Session 1

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Track7 Session 1

Tab 7 content

Organizations today are looking to free themselves from the constraints of on-premises databases and leverage the power of fully managed databases in the cloud. Amazon RDS is a fully managed relational database service that you can use to run your choice of database engines including open source engines, Oracle, and SQL Server in the cloud. Amazon RDS automates time-consuming database administration tasks and adds capabilities such as replication and Multi-AZ failover to make your database deployments more scalable, available, reliable, manageable, and cost-effective. This session covers why you should consider moving your on-premises Oracle & SQL Server deployments to Amazon RDS and the tools to get started.

Track8 Session 1

Tab 8 content

Organizations today are looking to free themselves from the constraints of on-premises databases and leverage the power of fully managed databases in the cloud. Amazon RDS is a fully managed relational database service that you can use to run your choice of database engines including open source engines, Oracle, and SQL Server in the cloud. Amazon RDS automates time-consuming database administration tasks and adds capabilities such as replication and Multi-AZ failover to make your database deployments more scalable, available, reliable, manageable, and cost-effective. This session covers why you should consider moving your on-premises Oracle & SQL Server deployments to Amazon RDS and the tools to get started.

Track9 Session 1

Tab 9 content

Organizations today are looking to free themselves from the constraints of on-premises databases and leverage the power of fully managed databases in the cloud. Amazon RDS is a fully managed relational database service that you can use to run your choice of database engines including open source engines, Oracle, and SQL Server in the cloud. Amazon RDS automates time-consuming database administration tasks and adds capabilities such as replication and Multi-AZ failover to make your database deployments more scalable, available, reliable, manageable, and cost-effective. This session covers why you should consider moving your on-premises Oracle & SQL Server deployments to Amazon RDS and the tools to get started.

Track10 Session 1

Tab 10 content

Organizations today are looking to free themselves from the constraints of on-premises databases and leverage the power of fully managed databases in the cloud. Amazon RDS is a fully managed relational database service that you can use to run your choice of database engines including open source engines, Oracle, and SQL Server in the cloud. Amazon RDS automates time-consuming database administration tasks and adds capabilities such as replication and Multi-AZ failover to make your database deployments more scalable, available, reliable, manageable, and cost-effective. This session covers why you should consider moving your on-premises Oracle & SQL Server deployments to Amazon RDS and the tools to get started.

Multiple City Registration

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Venue

The Meteropolitian
233 south wacker drive, 67th floor, Chicago, Illinois 60606

Sessions will focus on providing an overview of AWS services and features, with the assumption that attendees are new to the topic Sessions will focus on providing an overview of AWS services and features, with the assumption that attendees are new to the topic Sessions will focus on providing an overview of AWS services and features, with the assumption that attendees are new to the topic Sessions will focus on providing an overview of AWS services and features, with the assumption that attendees are new to the topic

Session Proficiency Levels Explained

  • Level 100

    Introductory

    Sessions will focus on providing an overview of AWS services and features, with the assumption that attendees are new to the topic

  • Level 200

    Intermediate

    Sessions will focus on providing best practices, details of service features and demos with the assumption that attendees have introductory knowledge of the topics

  • Level 300

    Advanced

    Sessions will dive deeper into the selected topic. Presenters assume that the audience has some familiarity with the topic, but may or may not have direct experience implementing a similar solution

  • Level 400

    Expert

    Sessions are for attendees who are deeply familiar with the topic, have implemented a solution on their own already, and are comfortable with how the technology works across multiple services, architectures, and implementations

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Over the past 20 years, Amazon has delivered many world firsts designed to break down barriers across each step of the machine learning (ML) lifecycle including the launch of Amazon SageMaker in 2017. Today, customers can prepare data and build, train, and deploy ML models for any use case using fully managed infrastructure, tools, workflows, AutoML, and no-code capabilities. They can also use AI services to improve business outcomes with ready-made intelligence for applications and workflows based on the same technology used to power Amazon’s own businesses. From startups to enterprise, customers are using AWS to harness the power of data with machine learning and, in many cases, changing the way we live for the better by launching ML applications to support sustainability and accessibility worldwide.


AWS is hosting a celebration on October 25, 2022 to toast key AI/ML milestones over the past 20 years. Hear stories from customers including Inspire, Mueller Water Products, ResMed, and Siemens Energy who show what’s possible using ML especially for sustainability and accessibility challenges.


Also hear from special guest, Professor Michael Jordan, who will talk about the decision-making side of machine learning spanning computational, inferential and economic perspectives.


Be among the first 1,500 people to sign up for the virtual celebration on October 25, 2022 <Tabatha to add link – do we advertise that it will be on all the streaming channels? > and received $25.00 of AWS credits.

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About the event

Be our guest as we celebrate 20 years of AI/ML innovation on October 25, 2022, 9:00 AM -10:30 AM PT. The first 1,500 people to register will receive $50 of AWS credits.

Over the past 20 years, Amazon has delivered many world firsts designed to break down barriers across each step of the machine learning (ML) lifecycle including the launch of Amazon SageMaker in 2017. Today, customers can prepare data and build, train, and deploy ML models for any use case using fully managed infrastructure, tools, workflows, AutoML, and no-code capabilities. They can also use AI services to improve business outcomes with ready-made intelligence for applications and workflows based on the same technology used to power Amazon’s own businesses. From startups to enterprise, customers are using AWS to harness the power of data with machine learning and, in many cases, changing the way we live for the better by launching ML applications to support sustainability and accessibility worldwide.

AWS is hosting a celebration on October 25, 2022 to toast key AI/ML milestones over the past 20 years. Hear stories from customers including Mueller Water Products, Inspire, ResMed, and Siemens Energy who show what’s possible using ML especially for sustainability and accessibility challenges.

Also hear from special guest, Professor Michael Jordan, who will talk about the decision-making side of machine learning spanning computational, inferential and economic perspectives.

Where to watch

• AWS LinkedIn Live

• AWS Machine Learning LinkedIn

• AWSonAir Twitter

• AWS YouTube

• AWS Twitch

• AWSonAir Twitch


Who should attend

The event is ideal for anyone who is eager to learn more about:

• How AI/ML can help support sustainability and accessibility challenges

• The latest news on the AWS AI/ML services

• What's coming in the next 20 years for AI/ML from leading experts

Featured Speakers

  • Michael I. Jordan, Professor, University of California, Berkeley

    Michael Irwin Jordan is an American scientist, professor at the University of California, Berkeley and researcher in machine learning, statistics, and artificial intelligence. Jordan was elected a member of the National Academy of Engineering in 2010 for contributions to the foundations and applications of machine learning. He is one of the leading figures in machine learning, and in 2016 Science Magazine reported him as the World's Most Influential Computer Scientist.

  • Dr. Bratin Saha, Vice President of Machine Learning and AI Services, AWS

    Dr. Bratin Saha, a graduate of Harvard Business School and Yale University, has a proven track record of delivering innovative products and growing some of the world's largest technology companies including Intel, NVIDIA, and Amazon. He has developed product innovations, including those that have won CES Innovation Awards, been awarded over 100 patents, and published 30+ research papers in journals and international conferences.

  • Richard Boyd, Cloud Data Engineer, iRobot

    Richard Boyd is a cloud data engineer with the iRobot Corporation’s Cloud Data Platform where he builds tools and services to support the world’s most beloved vacuum cleaner. Before joining iRobot, Richard built discrete event simulators for Amazon’s automated fulfillment centers in Amazon Robotics. His previous roles include cyber warfare systems analyst at MIT and research for the Center for Army Analysis. He holds advanced degrees in Applied Mathematics & Statistics.

  • Raju Gulabani, VP of Databases, Analytics & AI, AWS

    Raju Gulabani is VP of Databases, Analytics & AI within AWS at Amazon.com. He is responsible for P&<, product management, engineering and operations for Database services such as Amazon Aurora and Amazon DynamoDB, and Analytics services such as Amazon Redshift and Amazon EMR, as well as AI services like Amazon Lex, Amazon Polly, and Amazon Rekognition. Prior to joining Amazon in his current position in 2010, Raju spent four years at Google and built the Google Apps business (now known as G Suite).Earlier in his career, Raju founded an Intel backed Wi-Fi Voice over IP company as well as held engineering management positions at Microsoft.

  • Ryan Kelly, Data Architect, Equinox

    Ryan Kelly is a data architect at Equinox, where he helps outline and implement frameworks for data initiatives. He also leads clickstream tracking which helps aid teams with insights on their digital initiatives. Ryan loves making it easier for people to reach and ingest their data for the purposes of business intelligence, analytics, and product/service enrichment. He also loves exploring and vetting new technologies to see how they can enhance what they do at Equinox

  • Richard Boyd, Cloud Data Engineer, iRobot

    Richard Boyd is a cloud data engineer with the iRobot Corporation’s Cloud Data Platform where he builds tools and services to support the world’s most beloved vacuum cleaner. Before joining iRobot, Richard built discrete event simulators for Amazon’s automated fulfillment centers in Amazon Robotics. His previous roles include cyber warfare systems analyst at MIT and research for the Center for Army Analysis. He holds advanced degrees in Applied Mathematics & Statistics.

  • Raju Gulabani, VP of Databases, Analytics & AI, AWS

    Raju Gulabani is VP of Databases, Analytics & AI within AWS at Amazon.com. He is responsible for P&<, product management, engineering and operations for Database services such as Amazon Aurora and Amazon DynamoDB, and Analytics services such as Amazon Redshift and Amazon EMR, as well as AI services like Amazon Lex, Amazon Polly, and Amazon Rekognition. Prior to joining Amazon in his current position in 2010, Raju spent four years at Google and built the Google Apps business (now known as G Suite).Earlier in his career, Raju founded an Intel backed Wi-Fi Voice over IP company as well as held engineering management positions at Microsoft.

  • Ryan Kelly, Data Architect, Equinox

    Ryan Kelly is a data architect at Equinox, where he helps outline and implement frameworks for data initiatives. He also leads clickstream tracking which helps aid teams with insights on their digital initiatives. Ryan loves making it easier for people to reach and ingest their data for the purposes of business intelligence, analytics, and product/service enrichment. He also loves exploring and vetting new technologies to see how they can enhance what they do at Equinox

  • Richard Boyd, Cloud Data Engineer, iRobot

    Richard Boyd is a cloud data engineer with the iRobot Corporation’s Cloud Data Platform where he builds tools and services to support the world’s most beloved vacuum cleaner. Before joining iRobot, Richard built discrete event simulators for Amazon’s automated fulfillment centers in Amazon Robotics. His previous roles include cyber warfare systems analyst at MIT and research for the Center for Army Analysis. He holds advanced degrees in Applied Mathematics & Statistics.

  • Raju Gulabani, VP of Databases, Analytics & AI, AWS

    Raju Gulabani is VP of Databases, Analytics & AI within AWS at Amazon.com. He is responsible for P&<, product management, engineering and operations for Database services such as Amazon Aurora and Amazon DynamoDB, and Analytics services such as Amazon Redshift and Amazon EMR, as well as AI services like Amazon Lex, Amazon Polly, and Amazon Rekognition. Prior to joining Amazon in his current position in 2010, Raju spent four years at Google and built the Google Apps business (now known as G Suite).Earlier in his career, Raju founded an Intel backed Wi-Fi Voice over IP company as well as held engineering management positions at Microsoft.

  • Ryan Kelly, Data Architect, Equinox

    Ryan Kelly is a data architect at Equinox, where he helps outline and implement frameworks for data initiatives. He also leads clickstream tracking which helps aid teams with insights on their digital initiatives. Ryan loves making it easier for people to reach and ingest their data for the purposes of business intelligence, analytics, and product/service enrichment. He also loves exploring and vetting new technologies to see how they can enhance what they do at Equinox

  • Richard Boyd, Cloud Data Engineer, iRobot

    Richard Boyd is a cloud data engineer with the iRobot Corporation’s Cloud Data Platform where he builds tools and services to support the world’s most beloved vacuum cleaner. Before joining iRobot, Richard built discrete event simulators for Amazon’s automated fulfillment centers in Amazon Robotics. His previous roles include cyber warfare systems analyst at MIT and research for the Center for Army Analysis. He holds advanced degrees in Applied Mathematics & Statistics.

Customer Highlights

Epic Logo Image

Epics Games’ entire analytics platform runs on AWS. Billions of game events, like player interactions on the map, their accuracy, damage taken and dealt, and what resources they are using are all sent to AWS.

Epics Games

Yelp Logo Image

Epics Games’ entire analytics platform runs on AWS. Billions of game events, like player interactions on the map, their accuracy, damage taken and dealt, and what resources they are using are all sent to AWS.

Yelp

Airbnb Logo Image

Epics Games’ entire analytics platform runs on AWS. Billions of game events, like player interactions on the map, their accuracy, damage taken and dealt, and what resources they are using are all sent to AWS.

Airbnb

Lyft Image

Epics Games’ entire analytics platform runs on AWS. Billions of game events, like player interactions on the map, their accuracy, damage taken and dealt, and what resources they are using are all sent to AWS.

Lyft

FAQS


Q: Where is this event?

A: This event is an online event, hosted by AWS on AWS LinkedIn Live, AWS Machine Learning LinkedIn Live, AWSonAir Twitter, AWS YouTube, AWS Twitch, and AWSonAir Twitch.

Q: Who should attend this event?

A: Anyone who is eager to learn more about how AI/ML is helping to transform the world, the current state of AI/ML and AWS innovations, and how AI/ML will evolve in years to come.

Q: How much does this event cost?

A: There is no cost to attend this event.

Q: What are the prerequisites before attending the event?

A: There are no prerequisites for attending the event. We encourage attendees to browse the AI/ML pages on the AWS website to get a brief overview of the available AI/ML services.

Q: How can I get AWS Cloud Credits?

A: Be among the first 1,500 people to register and get $50.00 of AWS Cloud Credits.