AWS Summit Online India

Join us for AWS Summit Online India on Wednesday, 13 May 2020

AWS Summit Online is designed for executives and IT professionals looking to leverage the AWS Cloud to build and innovate at scale. Hear the very latest in opening and closing keynotes, an array of insightful breakout sessions featuring customer stories, and engage with AWS experts to get your questions answered live. Enhance your skills with hands-on learning, learn from inspiring demos in the Builders’ Zone and discover what AWS and Partner ecosystem can do for your business.

This free online conference is designed to educate you about AWS services; and help you design, deploy, and operate infrastructure and applications.

What to Expect

40+ Sessions across 8 Tracks
40+ Sessions across 8 Tracks
Experiential Zone
Experiential Zone
Live Chat
Live Chat
Resource Center
Resource Center
AWS DeepRacer League
AWS DeepRacer League

Join us on 13 May to build your own agenda on the event platform, and gain insights from a full catalogue of sessions that are most relevant to your job role, topic interest, and industry. These in-depth discussions will be delivered by AWS subject matter experts who will share best practices and real-world customer stories with you.

Machine Learning
Machine Learning
Data & Analytics
Data & Analytics
Why Attend?

Why Attend?

Whether you are recently-introduced to the cloud or an experienced user, learn how cloud technology can help your business transform – lowering costs, improving efficiency, and innovating at scale – at this free digital Summit. Get your questions answered by our AWS business and technical experts, and engage in virtual activities such as the Builders’ Zone and Skills Zone.

Who Should Attend?

Who Should Attend?

If you are a business decision-maker, look forward to a day of learning from an array of Introductory (Level 100) and Intermediate (Level 200) content. If you are an IT professional, solution architect, developer, engineer or system administrator, gain new skills and a deeper understanding of the greatest tech stacks on AWS with Advanced (Level 300) and Expert (Level 400) content.

Dr. Werner Vogels
Dr. Werner Vogels, Chief Technology Officer,

Dr. Werner Vogels is Chief Technology Officer at, where he is responsible for driving the company's customer-centric technology vision.

As one of the forces behind Amazon's approach to cloud computing, he is passionate about helping young businesses reach global scale, and transforming enterprises into fast-moving digital organizations.

Vogels joined Amazon in 2004 from Cornell University, where he was a distributed systems researcher. He has held technology leadership positions in companies that handle the transition of academic technology into industry. Vogels holds a PhD from the Vrije Universiteit in Amsterdam and has authored many articles on distributed systems technologies for enterprise computing.

Andy Jassy
Andy Jassy, Chief Executive Officer, Amazon Web Services

Andy Jassy is CEO of Amazon Web Services (AWS), the world’s most comprehensive and broadly adopted cloud platform. Having led AWS since its inception, he’s managed an inventive and nimble team that has delivered more than 165 cloud infrastructure and application services that are used by millions of startup, enterprise, and government customers around the world. Jassy joined Amazon in 1997. Prior to founding AWS, he held various leadership roles across the company. He has an AB from Harvard University and an MBA from Harvard Business School. Jassy serves on the Board of Trustees for Rainier Scholars and as chair of Rainier Prep’s Board of Directors.

Matt Garman
Matt Garman, Vice President, AWS WW Sales and Marketing

Matt Garman joined Amazon in 2006, is currently the Vice President of the Worldwide Sales and Marketing organization in Amazon Web Services (AWS), and also sits on Amazon’s executive leadership S-Team. He has held several leadership positions in AWS over that time.

Matt previously served as Vice President of the Amazon EC2 and Compute Services businesses for AWS for over 10 years. Matt was responsible for P&L, product management, and engineering and operations for all compute and storage services in AWS. He started at Amazon when AWS first launched in 2006 and served as one of the first product managers, helping to launch the initial set of AWS services. Prior to Amazon, he spent time in product management roles at early stage Internet startups.

Matt earned a BS and MS in Industrial Engineering from Stanford University, and an MBA from the Kellogg School of Management at Northwestern University. 

Agenda & Session Description

09:30 - 10:30 Opening Keynote
Dr. Werner Vogels, Chief Technology Officer,
  • Enterprise Transformation
  • Data and Analytics
  • Machine Learning - Track 1
  • Machine Learning - Track 2
  • Modern Application Development
  • Developers
  • Building Applications at Scale
  • AWSome Day
  • Builders' Zone Demo
  • Hands-on Labs (Hot Topics)
  • Hands-on Labs (Introductory)
  • Enterprise Transformation
  • 10:30 - 11:00

    Realising the business value of modernising (Level 200)

    Most organisations know that they can achieve cost savings by moving to the cloud, but they often struggle to quantify benefits beyond cost. In this session, we introduce the AWS Cloud Adoption Framework (CAF) and explain how it can be used to quantify not only cost savings, but also the value of business agility, operational resilience, and staff productivity. By the end of this session, you should be able to describe the benefits of the cloud to different stakeholders across your organisation and present a comprehensive value-based business case.

    11:00 - 11:35

    SAP on AWS: Unlocking value from your investment (Level 200)

    More than 5,000 active AWS customers run SAP on AWS and over half of those customers deployed SAP HANA-based solutions on AWS.  Join this session to hear the latest regarding how AWS can unlock more value from your SAP investments, and gain insights about SAP modernisation options to determine which approach might be best for you.

    11:35 - 11:40
    11:40 - 12:10

    Cloud Operating Models for accelerated transformation (Level 200)

    In this session, learn how to adopt a Cloud Operating Model and accelerate your cloud transformation. Get insights on some of the effective Cloud Operating models (centralised, decentralised and distributed), how they affect organisational structures, and the role they play in digital transformation. Learn how training plays a role in your accelerated transformation. Uncover how to build and bootstrap a Cloud Center of Excellence (CCOE) including how it evolves as you transform your business in the adoption of cloud.

    12:10 - 12:40

    Enterprise cloud migration meets application containerisation on AWS (Level 300)

    In this session, learn how to build your application migration framework and pipelines centering on containerization. We show you how to assess and qualify your applications, build and refine your landing zones, create specific security baselines, and create migration pipelines leveraging Amazon ECR and Amazon EKS, two services that are part of the AWS container management portfolio.

    12:40 - 13:05

    Create an environment to accelerate transformation and unlock innovation (Level 200)

    Transformation is a common theme for enterprises adopting the cloud. But in order to realize the benefits that the cloud has to offer, your workforce needs the type of skills and experience that take time to build. In this session, learn what you can do to provide your workforce with an environment that enables transformation, and discover how other organizations have worked with the AWS Skills Guild to produce an agile and innovative community of builders to accelerate their journey to cloud.

  • Data and Analytics
  • 10:30 - 11:00
    Turn data into insights (Level 200)

    Data is incredibly valuable, but extracting it is getting harder as the volume, variety, and velocity of data continues to increase. AWS offers a comprehensive collection of services to store, organize, secure, and analyze your data. Come learn about modern data architectures and the variety of ways you can analyze your data to find the hidden insights that will help you succeed.

    11:00 - 11:35

    Best practices for implementing a data lake in Amazon S3 (Level 200)

    Flexibility is key when building and scaling a data lake, and by choosing the right storage architecture, you have the agility to quickly experiment and migrate with the latest analytics solutions. In this session, we explore the best practices for building a data lake on Amazon S3, which allow you to leverage an entire array of AWS, open-source, and third-party analytics tools, helping you remain at the cutting edge. We also explore use cases for analytics tools, including Amazon EMR and AWS Glue, and query-in-place tools like Amazon Athena, Amazon Redshift Spectrum, Amazon S3 Select, and Amazon Glacier Select.

    11:35 - 11:40
    11:40 - 12:10

    Modernize your data warehouse (Level 200)

    Migrating an on-premises data warehouse to the cloud is often perceived as complex, but it doesn't have to be. In this session, we go over the steps you should take to correctly collect your requirements. We also cover AWS services that can assist you in migrating your data to Amazon Redshift, such as AWS Database Migration Service (AWS DMS), AWS Snowball, and AWS Snowmobile. We then dive into targeted use cases.

    12:10 - 12:55

    Streaming and real-time analytics (Level 300)

    Learn how streaming technologies can help analyze data in real time, move data between systems in real time, or power data flows in next-generation applications and microservices architectures. This block covers both the Amazon Kinesis family of products and Amazon Managed Streaming for Apache Kafka (Amazon MSK), and it provides deep examples of how these streaming technologies can be used to easily build real-time and connected applications.

    12:55 - 13:25
    Trends with data lakes and analytics (Level 200)

    In this session, you discover the key trends in analytics and data lakes. You also learn how AWS customers are leveraging analytics platforms to drive innovation, build data-driven products, and transform their customers’ experiences.
  • Machine Learning - Track 1
  • 10:30 - 11:00 Streamlining machine learning operations (Level 200)

    Machine learning (ML) workflows are continuous and iterative processes that require adequate tools and practices in order for ML teams to be highly efficient. In this session, we discuss the common challenges faced when using ML systems in production, and we address these challenges by diving deep into the new features introduced for Amazon SageMaker, including Amazon SageMaker Debugger and Amazon SageMaker Model Monitor.

    11:00 - 11:30

    Best practices for building production-grade Deep Learning systems (Level 300)

    AWS offers different paths for building and deploying scalable ML solutions. In this session, we will dive deep into insights and best practices learned from implementing Deep Learning-powered applications. Discover how AWS ML services, in conjunction with a large number of complementary AWS technologies, provide a great platform to implement production-grade solutions such as Recommendation /Forecast/Prediction Engines.

    11:30 - 11:40 Break
    11:40 - 12:10

    Deep dive into AWS Lake Formation (Level 400)

    In this session, learn how to build a secure and automated data lake using AWS Lake Formation. Also learn how to set up periodic sales data and ingest into the data lake, build automated transformations, and generate sales forecasts from the transformed data using AI. If you're a developer, DBA, or a data engineer who works with data, this session is for you.

    12:10 - 12:55

    The effortless development of custom computer vision models (Level 300)

    Do you want to use computer vision in your projects, but find the idea of training a custom neural network model daunting? Have you used pre-trained computer vision models, but find that these models don’t cover every aspect of your use case? With Amazon Rekognition Custom Labels, you can easily customize existing computer vision models without needing an expert data scientist. Come learn how to prepare your dataset, customize Amazon Rekognition models with your data, and deploy these models in an application. We also discuss the difference between training computer vision models using Amazon Rekognition Custom Labels and doing so using Amazon SageMaker.

  • Machine Learning - Track 2
  • 10:30 - 11:00
    All things AI/ML: Tying them together (Level 300)

    AWS offers comprehensive services to assist the work of developers, data scientists, and expert ML practitioners. In this session, explore how developers can start building complex multi-functional AI solutions that use reinforcement learning on AWS. We demonstrate these capabilities with a next generation-targeted advertising use case.

    11:00 - 11:40

    Fraud detection: Using ML to identify and manage fraudulent activities (Level 200)

    Amazon Fraud Detector is a fully managed service that you can use to identify potentially fraudulent online activities, such as online payment fraud and fake accounts. The service uses ML and 20 years of fraud detection expertise to automatically identify potentially fraudulent activity and enable you to catch more fraud faster. In this session, learn how to use Amazon Fraud Detector to create a fraud detection model with just a few clicks and no prior ML experience. Learn how to implement a customized fraud detection solution for online activities using ML, identify use cases, and implement changes to protect your company and customers.

    11:40 - 12:20

    AWS DeepRacer: Train, evaluate, and tune your reinforcement learning model (Level 300)

    In this session, we introduce the basics of reinforcement learning and show you how to apply it to train your own autonomous vehicle models. You also learn how to test them in a virtual car racing scenario powered by AWS DeepRacer. Learn about the single-car time-trial format and the dual-car head-to-head racing challenges in the AWS DeepRacer 3D racing simulator. By the end of this session, you will be able to participate in the AWS DeepRacer League, where you can compete for prizes and meet other machine learning enthusiasts.

    12:20 - 13:05

    DevOps for data science: Operationalizing ML (Level 400)

    Organizations are recognizing the importance of cross-functional expertise and efficient tooling when bringing AI-driven products to market. In this session, learn how to build an end-to-end pipeline for continuous delivery of ML models. Also learn how to automate MLOps with Amazon SageMaker and serverless workflows to build, deploy, and monitor models at scale to maximize the business value to your organization.

  • Modern Application Development
  • 10:30 - 11:05 Applications and operations modernization (Level 200)

    Traditional operations are designed for long-lived infrastructure, low-to-medium velocity of changes, and predefined scale. However, serverless applications have diametrically opposite characteristics.  In this session, we outline the top challenges in operating serverless applications on AWS, and we demonstrate key operations-focused design patterns using a combination of AWS services.

    11:05 - 11:35

    Application integration patterns for microservices (Level 300)

    When you have a microservices architectural style, much of the communication between components is done over the network. In order to achieve what microservices promise, this communication must happen in a loosely coupled manner. In this session, we discuss some fundamental application integration patterns mostly based on messaging, and we connect them to real-world use cases in a microservices scenario. We also highlight the benefits that asynchronous messaging can have over REST APIs for communication between microservices.

    11:35 - 11:40 Break
    11:40 - 12:10

    Kubernetes GitOps on AWS (Level 300)

    GitOps is an approach where infrastructure as code lives alongside your application in the same Git repository, and any changes are automatically deployed when they’re merged there. This session demonstrates how to implement this approach for AWS-managed backend resources together with front-end services running on Kubernetes out of the same Git repository. You learn how AWS resources are deployed and managed in an automated way and deployed on Kubernetes via Flux. If you’re a developer or operational team member looking for ways to leverage AWS with Kubernetes and Amazon EKS to build and run applications in a simpler and cohesive Git-driven experience, this is the session for you.

    12:10 - 12:40

    The art of the state: Coordinating services using AWS Step Functions (Level 200)

    Microservice architectures give us increased agility and scale, but as they grow, they can become complicated to coordinate and debug. In this session, we review common service coordination patterns and how AWS Step Functions can help us quickly build fully managed and resilient workflows powered by easy-to-understand state machines.

    12:40 - 13:00 Delivering container-native applications without managing servers (Level 300)

    AWS Fargate is a completely serverless, container-native compute engine. It doesn’t require users to provision, scale, or manage servers, and it works with Amazon ECS and Amazon EKS. In this session, learn how to design and deliver a scalable and secure modern application on Fargate. Also learn how to use the AWS Cloud Development Kit (AWS CDK) to define reusable cloud components that compose the entire application architecture.
  • Developers
  • 10:30 - 11:05 Building serverless applications with AWS Amplify (Level 400)

    Since it was released in 2017 as a JavaScript library, AWS Amplify has become a great way to build, provision, and deploy web and mobile serverless applications on AWS. In this session, we explore what you can do with AWS Amplify. We provide examples of how to build application APIs, and we show you how to add advanced capabilities like AI/ML to your application. We also discuss best practices around developer tooling and workflow as well as CI/CD orchestration using the Amplify console.

    11:05 - 11:35

    Supersonic serverless Java on AWS Lambda (Level 300)

    Java has typically been associated with cold starts, making it less attractive for serverless technologies such as AWS Lambda. Discover the changes in AWS Lambda such as V2N, and Provisioned Capacity, and how that improves start up time. Learn about the significant changes with the Oracle GraalVM that now allow for native compilation of Java, opening up a new realm of opportunities for Java and JVM languages such as Kotlin and Scala, beyond AWS.

    11:35 - 11:40 Break
    11:40 - 12:10

    Database freedom: Break free to save, grow, and innovate (Level 200)

    Hundreds of thousands of customers have broken free from old-guard database providers to run on AWS databases, which provide commercial-grade features at one-tenth the cost. AWS databases merge the flexibility and low cost of open-source databases with the robust enterprise features of commercial databases, freeing teams from the heavy lifting of database administration. In this session, learn how AWS databases were designed to support the scale, performance, and availability demands of modern globally distributed applications with microservices architectures. Discover how AWS databases enable companies to break away from the constraints of legacy database providers and scale, grow, and innovate faster.

    12:10 - 12:55

    A path to event sourcing with Amazon MSK (Level 200)

    Event sourcing is an exciting pattern for thinking differently about how you process and store your data. With Amazon Managed Streaming for Apache Kafka (MSK) it’s now even easier for development teams to run and operate applications that are built around event sourcing patterns. Join this session to find out more about an example Java based Personal Banking web site that uses MSK, AWS Fargate, and Amazon Elasticsearch Service to process data using event sourcing with eventual consistency. We will explore code and look at some of the operational characteristics in the AWS Console.

    12:55 - 13:25 Purpose-built databases for modern applications (Level 300)

    Seldom can one database fit the needs of multiple distinct use cases. The days of the one-size-fits-all monolithic database are behind us, and developers are building highly distributed applications using many purpose-built databases. The world is changing, and the categories of databases continue to grow. We are increasingly seeing customers wanting to build Internet-scale applications that require diverse data models. In response to these needs, developers now have the choice of relational, key-value, wide column, document, in-memory, graph, time-series, and ledger databases. Each solves a specific problem or group of problems. Come learn about AWS purpose-built databases that meet the scale, performance, and manageability requirements of modern applications.
  • Building Applications at Scale
  • 10:30 - 11:05 Move your desktops and applications to AWS end-user computing (Level 200)

    Designed for companies that have contingent workers, remote offices or frequent M&A, this session will help you understand how Amazon has taken on the challenge of providing virtual desktops to over 25K users around the world. Freed from the challenges of on-prem VDI solutions, Amazon IT uses Amazon WorkSpaces to quickly provision desktops in minutes supported by just two engineers - saving over $17M annually. This session will provide an overview of the WorkSpaces service, the Amazon IT use cases in production, and the architectural approach they chose to service 25K users. Learn why and how Amazon WorkSpaces has become “the de facto model for onboarding new remote employees, contract workers, and subsidiaries.”

    11:05 - 11:40

     Scaling Up to Your First 10 Million Users

    Cloud computing gives you a number of advantages, such as the ability to scale your web application or website on-demand. If you have a new web application and want to use cloud computing, you might be asking yourself, “Where do I start?” Join us in this session to understand the best practices for scaling your resources from one user to millions of users. Our guest speaker from Proptiger will show you how to best combine different AWS services, how to make smarter decisions for architecting your application, and how to scale your infrastructure and serverless components in the cloud.

    11:40 - 12:10

    Industrial machine performance insights with AWS IoT services (Level 400)

    In this session, we perform a demonstration showing how you can connect a device to a machine, read sensor data, and leverage AWS IoT Core and AWS IoT Greengrass to send the data to the cloud on AWS IoT SiteWise. After showing how to ingest the data, we then demonstrate how to create an overall equipment effectiveness (OEE) dashboard to monitor the performance of the machine.

    12:10 - 12:55  

    What's new in AWS file storage (300)

    In this session, we focus on innovations in the fast-growing AWS file-storage portfolio, including Amazon Elastic File System (Amazon EFS), Amazon FSx for Windows File Server, and Amazon FSx for Lustre.

    12:55 - 13:25 Tuning your cloud: Improve global network performance for applications (Level 300)

    Do you need to scale while also ensuring that you're getting the most out of your AWS services? This session provides you with the tools and techniques you need to analyze and understand your application’s network behavior, model and test different scenarios, and tune AWS services to meet your requirements. We focus on Amazon Linux, Amazon EC2 services, and AWS regional and backbone network infrastructure.
  • AWSome Day
  • Awsomeday-banner-agenda-2020-v3
    10:30 - 10:50

    Module 1: Introduction to the AWS Cloud

    In this session, you learn about the value of the cloud and the benefits of adopting the AWS Cloud.

    10:50 - 11:10

    Module 2: Getting started with the AWS Cloud

    This session covers several of the key AWS categories and services. Learn what the services do, and understand when and how to use them.

    11:10 - 11:35

    Module 3: Building in the cloud

    In this session, learn about the services that support building in the cloud and enable you to have scalable applications, monitor your resources, automate deployments, connect and share data, and streamline content delivery.

    11:35 - 11:40 Break
    11:40 - 12:05

    Module 4: Secure your cloud applications

    This session covers how AWS approaches securing the cloud. Additionally, we cover the AWS Shared Responsibility Model, AWS access control and management, AWS security compliance programs, and the resources that are available to help you better understand AWS Cloud security options.

    12:05 - 12:35 Module 5: AWS pricing, support, and architecting

    This session covers the fundamentals of AWS Support plans, elements of pricing for several key services, and AWS architecting. We also discuss the AWS Well-Architected Framework and reference architectures for fault tolerance, high availability, and web hosting.
  • Builders' Zone Demo
  • Quantum Computing

    Amazon Braket is a fully managed service that helps you get started with quantum computing by providing a development environment to explore and design quantum algorithms, test them on simulated quantum computers, and run them on your choice of different quantum hardware technologies. Join this session for an overview of Amazon Braket and find out how to get started with quantum computing today.


    Sign & Speak

    This demo showcases how the Sign & Speak program uses machine learning (ML) to build a tool that facilitates communication between users of sign language and users of spoken language. By combining artificial intelligence (AI) models trained to transcribe speech and interpret sign language with a camera and a microphone, the tool enables two-way conversation in situations where communication was previously challenging.


    Omni-Channel Contact Center

    The multichannel experience increasingly forms the core of the business strategy that organizations adopt to connect with their customers. While platforms such as web, mobile, and phone help companies engage and connect with their customers, in most cases, the customer still lacks a seamless experience and consistent messaging across these channels. This demo shows you how to build an omni-channel solution to serve customers in a way that creates an integrated and cohesive customer experience. Using the powerful conversational natural language capabilities of Amazon Lex, see how easily you can build voice-enabled chatbot experiences for customer service.


    Image Classification with AWS Deeplens

    Learn how to build a custom deep learning image classification model with AWS DeepLens, Amazon SageMaker, AWS IoT Greengrass, and other AWS services. The model can be used for a variety of purposes, including artistic style transfer, facial recognition, and license plate and other object detection.


    Underwater Garbage Detection

    With an estimated 8 million metric tons of trash deposited into oceans each year, there are now close to 500 dead zones, where most marine life cannot survive, globally covering more than 245,000 square kilometers, equivalent to the area of the UK. Clearing this trash is a massive job requiring first knowing exactly where the trash is located. This demo shows how to use machine learning to detect trash underwater, mapping it to its location. We use services like Amazon SageMaker, Amazon Elasticsearch Service, and AWS IoT to run this model at the edge with TensorFlow and an NVIDIA Jetson AGX Xavier Developer Kit.


    AI Worker Safety System

    Learn to use AWS DeepLens and Amazon Rekognition to build an application that helps identify if a person at a construction site is wearing the right safety gear, in this case, a hard hat. In this lab, we show how you can create and deploy an object detection project to AWS DeepLens, modify the AWS DeepLens object detection inference Lambda function to detect persons and upload the frame to Amazon S3, create a Lambda function to identify those who are not wearing safety hats and analyze the results using AWS IoT , Amazon CloudWatch and a web dashboard.


    Security Automation Toolkit

    Organizations that have automated their deployment, elasticized their workloads, and dynamically provisioned their fleet on AWS may wonder what to do next. In this demo, learn how to tackle automating your security needs using the latest capabilities in the cloud. While there’s no single path to building an automated and continuous security architecture that works for every organization, certain key principles and techniques can be used by all organizations to automate and use the event-driven security and remediation model on AWS. Learn how to put together a solution on AWS using services like Amazon CloudWatch, Amazon GuardDuty, AWS Config, AWS Lambda, and Amazon SNS to do this easily, cost-effectively, and at scale.


    Severless Healthcare Platform

    Learn how to build a serverless eHealth platform using AWS services like Amazon DynamoDB, Amazon S3, Amazon Lex, Amazon API Gateway, AWS Lambda, Amazon Connect, Amazon Pinpoint, Amazon Comprehend Medical, Amazon Personalize, Amazon SageMaker, and Amazon Rekognition. Also learn how these services are designed to work together to create a seamless and frictionless user experience for your customers.


    Virtual Rap Battles

    AI is quickly making inroads into the entertainment industry, helping create music loops, drum track samples, and even entire heavy metal albums. In this session, learn how to use Amazon SageMaker to build and train a lyrics-generation model and host the model as a real-time API. We show you how to create two virtual rappers using Amazon Sumerian and have them trade rhymes with each other. For a control panel, we use Amazon Comprehend, which detects the key phrase from the first rapper and passes it to the second one and enables replies that are specific to the topic of the first rapper’s rhyme.


    AI/ML blackjack challenge

    This AI/ML blackjack challenge demo showcases Amazon SageMaker, AWS IoT, and Serverless, using edge compute and cameras. Learn how these services in combination detect playing card rank and suit using computer vision, displaying results in real time, and provide player guidance recommendations and probabilities for the game of blackjack.


    AWS Smart Factory

    This demo highlights how AWS services can help customers build a next generation of smart factory which has five categories including Monitoring (Visualization), ERP, Industrial IOT, Analytics, and Machine Learning.  You can see how AWS services work in a real small factory equipment and get a good sense of how to start building one. Come and check the future of a smart factory.


    AWS Café Robotics

    Visit the cafe run by AWS Cafe Robotics to experience the latest AWS technology. The entire process of ordering and delivering beverages is automated with Robot, 3D characters, AR, and IoT technologies, and all the data generated in the process is transferred to the AWS Cloud and used to improve the beverage quality with Digital Twin technology. Robot Barista also offers free fresh drinks.

  • Hands-on Labs (Hot Topics)
  • Amazon ECS containerized web application

    In this lab, you learn how to build and run a containerized application. We also demonstrate how to use Amazon Elastic Container Service (Amazon ECS) to host and run your container in the cloud.


    Virtual contact center

    This lab explains how to build a contact center using Amazon Connect and Amazon Lex. Join us and learn how to match intent based on your input and provide greater flexibility for customers who interact with contact centers.


    Recommendation engine

    In this lab, you learn how to use Amazon Neptune to create a recommendation system using collaborative filtering.


    Sentiment analysis web application

    In this lab, we demonstrate how to add artificial intelligence (AI) and machine learning (ML) cloud service features to your web application with React and the AWS Amplify Framework.


    Lambda@Edge in A/B testing

    In this lab, you learn how to use Lambda@Edge functions to serve different variants of the same static resources from an Amazon CloudFront distribution.


    Customer churn prediction

    Come learn how identifying unhappy customers early provides you with the opportunity to incentivize them to stay and helps decrease customer churn. In this lab, we explain how you can use machine learning (ML) to predict this churn. Additionally, we discuss how to incorporate the costs associated with prediction mistakes to determine the financial outcome of using ML.


    Modern serverless web application

    AWS Amplify makes it easy for you to create, configure, and implement scalable mobile and web applications that are powered by AWS. In this workshop, you learn how to build the Vote Rocket voting web application with React and the AWS Amplify Framework.


    Health visibility dashboard

    In this lab, we showcase the AWS Health API Organizational View feature. We also show how Organizational View can aggregate AWS Health events displayed on the AWS Personal Health Dashboard at the payer account level within an organization.


    The 2048 game on Amazon EKS 

    In this lab, we demonstrate how to deploy the 2048 game on Amazon Elastic Kubernetes Service (Amazon EKS). 


    Movie batch recommendations

    In this lab, we walk you through how to train and create batch recommendations using Amazon Personalize. Learn how you can perform tasks such as generating recommendations for a large number of users that will be used later for batch-oriented workflows like sending emails or notifications.


    Amazon EKS on AWS Fargate

    AWS Fargate removes the need to provision and manage servers, lets you specify and pay for resources per application, and improves security through application isolation by design. In this lab, we demonstrate how to run Amazon Elastic Kubernetes Service (Amazon EKS) on AWS Fargate.


    Website authentication

    In this lab, you learn to use Application Load Balancer to build a website that requires that users be authenticated before accessing the content. Additionally, we cover how you can integrate this function with Amazon Cognito.


    Deploy a Locust cluster using AWS CDK

    In this lab, we cover the AWS Cloud Development Kit (AWS CDK), which is a software development framework for defining cloud infrastructure as code and provisioning it through AWS CloudFormation. Join us as we walk you through how to deploy a Locust load tester using AWS CDK.


    Personalized recommendation

    Join us in this lab to learn how to use Amazon Personalize to create a recommendation system. Note that the data upload and training steps for this lab do take a long time to perform.

  • Hands-on Labs (Introductory)
  • Introduction to Amazon Simple Storage Service (Amazon S3)

    This lab demonstrates how to use an Amazon S3 bucket and manage files or objects that are stored in the bucket. Practice creating a bucket, adding an object, viewing an object, moving an object, and deleting an object and bucket in the AWS Management Console.


    Introduction to Amazon DynamoDB

    This lab provides an overview of Amazon DynamoDB and walks you through how to create, query, view, and delete a table in the AWS Management Console.


    Introduction to AWS Identity and Access Management (IAM)

    This lab shows you how to manage access and permissions to your AWS services using IAM. Practice the steps to add users to groups, manage passwords, and log in with IAM-created users, and see the effects of IAM policies on access to specific services.


    Introduction to AWS Lambda

    This lab provides a basic understanding of Lambda by demonstrating the steps required to create and deploy a Lambda function in an event-driven environment.


    Introduction to Amazon API Gateway

    In this lab, learn to create a simple FAQ microservice that returns a JavaScript Object Notation (JSON) object containing a random question and answer pair using an API Gateway endpoint that invokes an AWS Lambda function. Prerequisites: Students should take the lab “Introduction to AWS Lambda” before taking this lab.


    Introduction to AWS Device Farm

    This lab provides basic hands-on experience with AWS Device Farm, which provides a test harness for mobile app developers. It demonstrates the basic steps required to load an example Android app and run a series of tests using common mobile device platforms (Samsung, LG, Amazon, etc.).


    Introduction to Amazon CloudFront

    This lab introduces you to Amazon CloudFront, a content delivery web service. Learn to create an Amazon CloudFront distribution that uses a CloudFront domain name in the URL to distribute a publicly accessible image file stored in an Amazon S3 bucket.


    Introduction to AWS Key Management Service (AWS KMS)

    This lab provides a basic understanding of and hands-on experience with AWS KMS. It demonstrates the basic steps required to get started with AWS KMS, including creating keys, assigning management and usage permissions for the keys, encrypting data, and monitoring the access and usage of keys.


    Image insertion and input switching with AWS Elemental MediaLive

    In this lab, learn to insert static images (also referred to as graphic or video overlays) over a video stream, create multiple inputs and attach them to a MediaLive channel, and switch between multiple inputs.


    Amazon S3: Multi-Region storage backup with Cross-Region Replication

    This lab walks you through the process of enabling Cross-Region Replication on an Amazon S3 bucket. Learn to create source and destination buckets, enable versioning, and then create various replication policies to demonstrate different methods of replicating objects.

Level 100
Sessions are focused on providing an overview of AWS services and features, with the assumption that attendees are new to the topic.
Level 200
Sessions are focused on providing best practices, details of service features and demos with the assumption that attendees have introductory knowledge of the topics.
Level 300
Sessions 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
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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40+ Sessions across 8 Tracks
Learn from AWS experts to accelerate your cloud journey and deep dive into architecture and code. Based on your business needs and technical expertise, build your own agenda from a broad range of topics: machine learning, migration, data and analytics, enterprise, DevOps and more.

Experiential Zone
Dive deep into architectures and technical stacks, and learn how AWS experts have helped solve real-world problems for organizations in industries and walk away with the ability to implement these or similar solutions in your own organization.

Live Chat
Q&A with AWS experts during sessions and live chat whilst you explore our zones

Resource Center
Learn more by downloading resources around AWS Marketplace, AWS Partner Network and more. Gain access to short tutorials, whitepapers, reference architectures, and customer case studies to expand your knowledge of AWS.

AWS DeepRacer League Summit Race
Compete for prizes and meet fellow machine learning enthusiasts, online. Racers will have the opportunity to join the DeepRacer online workshop and have a 1-to-1 chat with our machine-learning experts.