AWS Online Summit

Agenda & Session Description

60 mins

Opening Keynote

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

30 mins

Using data and ML to innovate for customers (Level 100)

Businesses today are recognizing the value of collecting real-time and historical data and using ML technology to innovate faster for customers, whether through helping online shoppers automate repeat purchases, creating advanced real-time recommendations for online gamers, or accelerating new product development. In this session, Glenn Gore, Worldwide Lead Solutions Architect, AWS, explores how businesses such as Amazon.com, Amazon Alexa, and Amazon Robotics use data and ML to innovate for customers.

30 mins

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.

30 mins

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.

30 mins

Transform with Microsoft on AWS (Level 200)

According to IDC, nearly 60 percent of Windows servers in the public cloud run on AWS. In this session, you learn how to run Microsoft solutions on AWS, hear about key innovations, learn how to optimise licensing, and reduce end-of-support risk for Windows Server 2008 and SQL Server 2008. Come hear how leveraging these services for Microsoft on AWS can help you free up time to focus on transforming your workloads.

10 mins

Break

30 mins

Cloud Operating Models for accelerated transformation

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.

45 mins

Enterprise cloud migration meets application containerisation
(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.

45 mins

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.

30 mins

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.

30 mins

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.

10 mins

Break

30 mins

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.

45 mins

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.

30 mins

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.

30 mins

Simplify and accelerate time-series forecasts & real-time personalization (Level 200)

Deploying custom machine learning (ML) models to solve complex business challenges does not have to be hard. Based on ML technology that was perfected through years of use on Amazon.com, Amazon Forecast and Amazon Personalize enable developers with no prior ML experience to easily build accurate forecasting and sophisticated personalization capabilities into their applications. In this session, we show you how these two services, using a new automating process called AutoML, create individualized recommendations for customers and deliver highly accurate forecasts. Learn how both services run on fully managed infrastructure and provide easy-to-use recipes that deliver high-quality models, which you can use even if you have little ML experience.

10 mins

Break

30 mins

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 dive deep into insights and best practices developed while implementing deep learning-powered applications. Discover how Amazon ML services, with a large number of complementary AWS technologies, provide a great platform to implement production-grade solutions, such as recommendation, forecast, and prediction engines.

45 mins

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.

30 mins

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.

30 mins

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.

10 mins

Break

30 mins

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.

45 mins

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.

30 mins

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.

30 mins

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.

10 mins

Break

30 mins

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.

45 mins

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.

30 mins

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.

30 mins

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.

30 mins

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.

10 mins

Break

30 mins

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.

45 mins

Building event-driven architectures with Amazon EventBridge
(Level 300)

Many companies are adopting event-driven architectures to drive efficiencies and agility in their business processes, reduce the cost of integration, and unlock value with SaaS partners. In this session, we review how Amazon EventBridge helps developers build serverless event-driven architectures, enables them to easily define, share, discover, and process events across organizations and SaaS providers, and helps them integrate them across service and process boundaries. We show you how to use Amazon EventBridge Schema Registry and AWS Lambda Destinations to build end-to-end event-driven applications and accelerate developer productivity.

30 mins

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.

30 mins

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

Event sourcing is an exciting pattern for thinking differently about how to process and store data. With Amazon Managed Streaming for Apache Kafka (Amazon MSK), it’s now even easier for development teams to run and operate applications that are built around event sourcing patterns. In this session, we demonstrate a Java-based personal banking website that uses Amazon MSK, AWS Fargate, and Amazon Elasticsearch Service (Amazon ES) to process data using event sourcing with eventual consistency. We explore the code and review some of the operational characteristics in the AWS Management Console.

30 mins

End-to-end IoT solution building (Level 200)

The best IoT solutions work backwards from a desired outcome, such as a customisable consumer experience in a home, near-real time reactivity in a car, or increased machine uptime in a factory. Effectively translating from the right data and device inputs, to the actions and outputs that facilitate those outcomes requires a holistic strategic approach to IoT deployment. In this session, discover how to build an outcomes-focused IoT solution from end-to-end. Learn best practices and discover how to use the broad and deep range of AWS IoT services to design and launch your solution. Hear how to connect devices, collect, store and analyse device data, make data-driven decision-making and actions, and more. The session will also address security considerations and how to integrate with AI and ML for continuous improvement. You can expect to walk away with a holistic understanding of the right steps to take in order to build a smart and outcome-achieving IoT solution to meet customer needs.

10 mins

Break

30 mins

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.

45 mins

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.”

30 mins

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.

20 mins

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.

25 mins

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.

10 mins

Break

25 mins

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.

30 mins

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.

30 mins

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.