This workshop explores the technology options, architectures, and implementations associated with instrumenting AR, VR, and simulated worlds. Using flight simulation as the primary use case, you learn to consume, process, store, and analyze high velocity telemetry as well as exploring control plane implementations using AWS IoT, AWS Lambda, Amazon Kinesis, and Amazon SNS. This is a hands-on workshop and you need a laptop (tablets are not suitable). You should have a solid understanding of AWS products and Node.js.
IOT313_AWS IoT and Machine Learning for Building Predictive Applications with...Amazon Web Services
In this session, we present AWS IoT and Amazon Machine Learning (Amazon ML) to demonstrate how you can use these services together to build smart applications. Customer SKF presents their use case around AWS IoT and Amazon ML in their wind turbines.
ABD202_Best Practices for Building Serverless Big Data ApplicationsAmazon Web Services
Serverless technologies let you build and scale applications and services rapidly without the need to provision or manage servers. In this session, we show you how to incorporate serverless concepts into your big data architectures. We explore the concepts behind and benefits of serverless architectures for big data, looking at design patterns to ingest, store, process, and visualize your data. Along the way, we explain when and how you can use serverless technologies to streamline data processing, minimize infrastructure management, and improve agility and robustness and share a reference architecture using a combination of cloud and open source technologies to solve your big data problems. Topics include: use cases and best practices for serverless big data applications; leveraging AWS technologies such as Amazon DynamoDB, Amazon S3, Amazon Kinesis, AWS Lambda, Amazon Athena, and Amazon EMR; and serverless ETL, event processing, ad hoc analysis, and real-time analytics.
"Do you want to learn more about building predictive IoT applications using AWS IoT and Amazon Machine Learning (Amazon ML)? In this workshop, we walk step by step through configuring AWS IoT “things”, training machine learning models using Amazon ML, and then using those models with AWS Lambda to predict device failures in the field and take corrective action. This is a hands-on workshop that provides participants with all of the code and machine learning training data needed to build a fully functional real-world IoT simulation. Participants should have a basic familiarity with AWS and with using the AWS Management Console.
This workshop is hands-on and provides the participants with all of the code and machine learning training data necessary to build a fully functional real-world IoT simulation.
Participants should have a basic familiarity with AWS and be familiar with using the console."
SRV304_Building High-Throughput Serverless Data Processing PipelinesAmazon Web Services
Have a lot of real-time data piling up? Need to analyze it, transform it, and store it somewhere else real quick? What if there were an easier way to perform streaming data processing, with less setup, instant scaling, and no servers to provision and manage? With serverless computing, you can build applications to meet your real-time needs for everything from IoT data to operational logs without needing to spin up servers or install software. Come learn how to leverage AWS Lambda with Amazon Kinesis, Kinesis Firehose, and Kinesis Analytics to architect highly scalable, high throughput pipelines that can cover all your real-time processing needs. We will cover different example architectures that handle use cases like in-line process or data manipulation, as well as discuss the advantages of using an AWS managed stream.
AMF305_Autonomous Driving Algorithm Development on Amazon AIAmazon Web Services
Over the next decade, accelerating autonomous driving technology—including advances in artificial intelligence, sensors, cameras, radar and data analytics—are set to transform how we commute. In this session, you learn how to use Amazon AI for a highly productive, on demand, and scalable autonomous driving development environment. We compare the most popular AI frameworks including TensorFlow and MXNet for use in autonomous driving workloads. You learn about the AWS optimizations on MXNet that yield near linear scalability for training deep neural networks and convolutional neural networks. We demonstrate the ease of getting started on AWS AI by using a sample training dataset for building an object detection model on AWS. This session is intended for audiences who have some exposure to the underlying concepts for AI-based autonomous driving development. After attending the session, you can get started with AI development on AWS by using a sample dataset for building an object detection model.
This workshop will give participants the opportunity to take a security focused journey across various AWS services and implement automated controls along the way. You will learn how to apply AWS security controls to services such as Amazon EC2, Amazon S3, AWS Lambda, and Amazon VPC. In short, you will learn how to use the cloud to protect the cloud.
We will talk about how to:
Adopt a workload-centric approach to your security strategy,
Address security issues in an cost-effective manner
Automate your security responses to promote maturity and auditability.
In order to complete this workshop, attendees will need a laptop with wireless access, an AWS account and an IAM user that has full administrative privileges within their account. AWS credits will be provided as attendees depart the session to cover the cost of running the workshop in their own account.
Also, please understand this is a 400-level workshop and assumes that you have basic understanding of core AWS services such as Amazon VPC, EC2, S3, Lambda, Security Groups, NACLs, etc. You should also understand basic networking and security constructs such as TCP/IP, DNS, monitoring and alerting, and be comfortable working on the AWS console and/or AWC CLI.
ENT227_IoT + Cloud enables Enterprise Digital TransformationAmazon Web Services
As a China-based global technology company that is helping some of the world's largest energy providers transition into renewable energy, Envision Energy is leading a digital disruption of the traditional energy system. In this session, Envision discusses how they used the AWS Cloud to create a technology infrastructure that connects and orchestrates millions of smart energy devices around the globe for their Energy IOT platform. They also review how AWS is used to host Envision's core systems, including SAP and Citrix.
IOT313_AWS IoT and Machine Learning for Building Predictive Applications with...Amazon Web Services
In this session, we present AWS IoT and Amazon Machine Learning (Amazon ML) to demonstrate how you can use these services together to build smart applications. Customer SKF presents their use case around AWS IoT and Amazon ML in their wind turbines.
ABD202_Best Practices for Building Serverless Big Data ApplicationsAmazon Web Services
Serverless technologies let you build and scale applications and services rapidly without the need to provision or manage servers. In this session, we show you how to incorporate serverless concepts into your big data architectures. We explore the concepts behind and benefits of serverless architectures for big data, looking at design patterns to ingest, store, process, and visualize your data. Along the way, we explain when and how you can use serverless technologies to streamline data processing, minimize infrastructure management, and improve agility and robustness and share a reference architecture using a combination of cloud and open source technologies to solve your big data problems. Topics include: use cases and best practices for serverless big data applications; leveraging AWS technologies such as Amazon DynamoDB, Amazon S3, Amazon Kinesis, AWS Lambda, Amazon Athena, and Amazon EMR; and serverless ETL, event processing, ad hoc analysis, and real-time analytics.
"Do you want to learn more about building predictive IoT applications using AWS IoT and Amazon Machine Learning (Amazon ML)? In this workshop, we walk step by step through configuring AWS IoT “things”, training machine learning models using Amazon ML, and then using those models with AWS Lambda to predict device failures in the field and take corrective action. This is a hands-on workshop that provides participants with all of the code and machine learning training data needed to build a fully functional real-world IoT simulation. Participants should have a basic familiarity with AWS and with using the AWS Management Console.
This workshop is hands-on and provides the participants with all of the code and machine learning training data necessary to build a fully functional real-world IoT simulation.
Participants should have a basic familiarity with AWS and be familiar with using the console."
SRV304_Building High-Throughput Serverless Data Processing PipelinesAmazon Web Services
Have a lot of real-time data piling up? Need to analyze it, transform it, and store it somewhere else real quick? What if there were an easier way to perform streaming data processing, with less setup, instant scaling, and no servers to provision and manage? With serverless computing, you can build applications to meet your real-time needs for everything from IoT data to operational logs without needing to spin up servers or install software. Come learn how to leverage AWS Lambda with Amazon Kinesis, Kinesis Firehose, and Kinesis Analytics to architect highly scalable, high throughput pipelines that can cover all your real-time processing needs. We will cover different example architectures that handle use cases like in-line process or data manipulation, as well as discuss the advantages of using an AWS managed stream.
AMF305_Autonomous Driving Algorithm Development on Amazon AIAmazon Web Services
Over the next decade, accelerating autonomous driving technology—including advances in artificial intelligence, sensors, cameras, radar and data analytics—are set to transform how we commute. In this session, you learn how to use Amazon AI for a highly productive, on demand, and scalable autonomous driving development environment. We compare the most popular AI frameworks including TensorFlow and MXNet for use in autonomous driving workloads. You learn about the AWS optimizations on MXNet that yield near linear scalability for training deep neural networks and convolutional neural networks. We demonstrate the ease of getting started on AWS AI by using a sample training dataset for building an object detection model on AWS. This session is intended for audiences who have some exposure to the underlying concepts for AI-based autonomous driving development. After attending the session, you can get started with AI development on AWS by using a sample dataset for building an object detection model.
This workshop will give participants the opportunity to take a security focused journey across various AWS services and implement automated controls along the way. You will learn how to apply AWS security controls to services such as Amazon EC2, Amazon S3, AWS Lambda, and Amazon VPC. In short, you will learn how to use the cloud to protect the cloud.
We will talk about how to:
Adopt a workload-centric approach to your security strategy,
Address security issues in an cost-effective manner
Automate your security responses to promote maturity and auditability.
In order to complete this workshop, attendees will need a laptop with wireless access, an AWS account and an IAM user that has full administrative privileges within their account. AWS credits will be provided as attendees depart the session to cover the cost of running the workshop in their own account.
Also, please understand this is a 400-level workshop and assumes that you have basic understanding of core AWS services such as Amazon VPC, EC2, S3, Lambda, Security Groups, NACLs, etc. You should also understand basic networking and security constructs such as TCP/IP, DNS, monitoring and alerting, and be comfortable working on the AWS console and/or AWC CLI.
ENT227_IoT + Cloud enables Enterprise Digital TransformationAmazon Web Services
As a China-based global technology company that is helping some of the world's largest energy providers transition into renewable energy, Envision Energy is leading a digital disruption of the traditional energy system. In this session, Envision discusses how they used the AWS Cloud to create a technology infrastructure that connects and orchestrates millions of smart energy devices around the globe for their Energy IOT platform. They also review how AWS is used to host Envision's core systems, including SAP and Citrix.
How to Determine If You Are Well Architected for Resiliency (or How I Learned...Amazon Web Services
Are your critical applications well architected? Come join this workshop to find out. In this workshop, we perform destructive testing on a reference architecture that is designed to be available 99.99% of the time. This architecture spans availability zones and even regions. We dive deep into how to achieve high availability and in the rare case of disaster, how to fail over to a completely different region. We explain some concepts and implement code to test each layer’s resiliency for simulated loss of Availability Zones, regional service loss, and regional loss. We cover web applications, databases, and storage. Bring your laptop or tablet with your favorite IDE and your AWS account. This workshop requires basic hands-on programming skills. You should be familiar with a programming language like python, java, c#, ruby, powershell or bash.
In this session, you learn how to set up a crawler to automatically discover your data and build your AWS Glue Data Catalog. You then auto-generate an AWS Glue ETL script, download it, and interactively edit it using a Zeppelin notebook, connected to an AWS Glue development endpoint. After that, you upload this script to Amazon S3, reuse it across multiple jobs, and add trigger conditions to run the jobs. The resulting datasets automatically get registered in the AWS Glue Data Catalog and you can then query these new datasets from Amazon EMR and Amazon Athena. Prerequisites: Knowledge of Python and familiarity with big data applications is preferred but not required. Attendees must bring their own laptops.
EUT305_Delivering the Future of Energy with Connected Home Products Using AWS...Amazon Web Services
What if your utilities company could fix your hot water service before you knew it was broken, or introduced novel pricing models to improve global sustainability? Centrica, a global utility company with notable brands like British Gas, is a market leader in connected home products that help customers manage their energy use. With millions of customers and thousands of device installations a week, the business was outgrowing their on-premises data center despite ongoing investments, so they needed a reliable and elastic architecture that could quickly scale to meet demand. They also needed an agile and compliant IoT platform to manage the explosion of data resulting from more customers, more devices, and more sensors. With AWS IoT, they can focus on delivering better customer experiences while generating valuable business insights to optimize energy usage, reduce costs, and enable global sustainability. In this session, participants learn how Centrica seamlessly migrated to AWS IoT, and how they are modernizing their platform to deliver the future of energy.
As serverless architectures become more popular, customers need a framework of patterns to help them identify how they can leverage AWS to deploy their workloads without managing servers or operating systems. This session describes re-usable serverless patterns while considering costs. For each pattern, we provide operational and security best practices and discuss potential pitfalls and nuances. We also discuss the considerations for moving an existing server-based workload to a serverless architecture. The patterns use services like AWS Lambda, Amazon API Gateway, Amazon Kinesis Streams, Amazon Kinesis Analytics, Amazon DynamoDB, Amazon S3, AWS Step Functions, AWS Config, AWS X-Ray, and Amazon Athena. This session can help you recognize candidates for serverless architectures in your own organizations and understand areas of potential savings and increased agility. What’s new in 2017: using X-Ray in Lambda for tracing and operational insight; a pattern on high performance computing (HPC) using Lambda at scale; how a query can be achieved using Athena; Step Functions as a way to handle orchestration for both the Automation and Batch patterns; a pattern for Security Automation using AWS Config rules to detect and automatically remediate violations of security standards; how to validate API parameters in API Gateway to protect your API back-ends; and a solid focus on CI/CD development pipelines for serverless –that includes testing, deploying, and versioning (SAM tools).
DVC303-Technological Accelerants for Organizational TransformationAmazon Web Services
"Developers and management can seem at cross purposes when one group looks at technologies and the other looks at organizational issues. Both groups are looking for ways to deliver value faster, leaner, and at less cost. There are technological avenues for accomplishing these goals, including DevOps and serverless architectures. However, these approaches also have organizational implications, as they change the nature and content of communication between teams. In this session, we cover the technology benefits and organizational transformations involved in DevOps and serverless architectures.
This session is part of the re:Invent Developer Community Day, six community-led sessions where AWS enthusiasts share technical insights on trending topics based on first-hand experiences and knowledge shared within local AWS communities."
Reducing the time to get actionable insights from data is important to all businesses, and customers who employ batch data analytics tools are exploring the benefits of streaming analytics. Learn best practices to extend your architecture from data warehouses and databases to real-time solutions. Learn how to use Amazon Kinesis to get real-time data insights and integrate them with Amazon Aurora, Amazon RDS, Amazon Redshift, and Amazon S3. The Amazon Flex team describes how they used streaming analytics in their Amazon Flex mobile app, used by Amazon delivery drivers to deliver millions of packages each month on time. They discuss the architecture that enabled the move from a batch processing system to a real-time system, overcoming the challenges of migrating existing batch data to streaming data, and how to benefit from real-time analytics.
ABD207 building a banking utility leveraging aws to fight financial crime and...Amazon Web Services
"Banks aren’t known to share data and collaborate with one another. But that is exactly what the Mid-Sized Bank Coalition of America (MBCA) is doing to fight digital financial crime—and protect national security. Using the AWS Cloud, the MBCA developed a shared data analytics utility that processes terabytes of non-competitive customer account, transaction, and government risk data. The intelligence produced from the data helps banks increase the efficiency of their operations, cut labor and operating costs, and reduce false positive volumes. The collective intelligence also allows greater enforcement of Anti-Money Laundering (AML) regulations by helping members detect internal risks—and identify the challenges to detecting these risks in the first place. This session demonstrates how the AWS Cloud supports the MBCA to deliver advanced data analytics, provide consistent operating models across financial institutions, reduce costs, and strengthen national security.
Session sponsored by Accenture"
ABD317_Building Your First Big Data Application on AWS - ABD317Amazon Web Services
Want to ramp up your knowledge of AWS big data web services and launch your first big data application on the cloud? We walk you through simplifying big data processing as a data bus comprising ingest, store, process, and visualize. You build a big data application using AWS managed services, including Amazon Athena, Amazon Kinesis, Amazon DynamoDB, and Amazon S3. Along the way, we review architecture design patterns for big data applications and give you access to a take-home lab so that you can rebuild and customize the application yourself. You should bring your own laptop and have some familiarity with AWS services to get the most from this session.
ALX202_Integrate Alexa voice technology into your product with the Alexa Voic...Amazon Web Services
In this session, we’ll teach you how to use the Alexa Voice Service (AVS) and its suite of development tools to bring your first Alexa-enabled product to market. You’ll learn how commercial device manufacturers are getting to market faster using the new AVS Device SDK. To ensure your customers have the best voice experience, we’ll teach you how to choose an Audio Front End and client-side hardware from a range of commercial-grade Development Kits. You’ll walk out of this session with the knowledge required to design products with optimized Alexa-enabled voice experiences around your unique design requirements.
CON318_Interstella 8888 Monolith to Microservices with Amazon ECSAmazon Web Services
Interstella 8888 is an intergalactic trading company that deals in rare resources, but their antiquated monolithic logistics systems are causing the business to lose money. Join this workshop to get hands-on experience deploying Docker containers as you break Intersella 8888’s aging monolithic application into containerized microservices. Using Amazon ECS and the Application Load Balancer, you will create API-based microservices and deploy them leveraging integrations with other AWS services.
AWS credits are provided. Bring a laptop, and have an active AWS account."
ABD206-Building Visualizations and Dashboards with Amazon QuickSightAmazon Web Services
Just as a picture is worth a thousand words, a visual is worth a thousand data points. A key aspect of our ability to gain insights from our data is to look for patterns, and these patterns are often not evident when we simply look at data in tables. The right visualization will help you gain a deeper understanding in a much quicker timeframe. In this session, we will show you how to quickly and easily visualize your data using Amazon QuickSight. We will show you how you can connect to data sources, generate custom metrics and calculations, create comprehensive business dashboards with various chart types, and setup filters and drill downs to slice and dice the data.
Create a Serverless Image Processing Platform - ARC326 - re:Invent 2017Amazon Web Services
Are you interested in processing images at scale without launching a single virtual machine? In this workshop, we show participants how to create an entirely serverless image processing platform using Amazon Cognito, AWS Lambda, Amazon Rekognition, and Amazon Elasticsearch Service (Amazon ES). Participants leave this workshop with a web portal where users can upload images that ultimately end up in a searchable index powered by Amazon ES and Kibana. Bring your laptop, and AWS account with Admin access. Your laptop should have either SSH capability or have Putty installed.
CMP323_AWS Batch Easy & Efficient Batch Computing on Amazon Web ServicesAmazon Web Services
AWS Batch is a fully managed service that enables developers to easily and efficiently run batch computing workloads of any scale on AWS. AWS Batch automatically provisions the right quantity and type of compute resources needed to run your jobs. With AWS Batch, you don't need to install or manage batch computing software, so you can focus on analyzing results and solving problems. In this session, the principal product manager for AWS Batch, Jamie Kinney, describes the core concepts behind AWS Batch and details of how the service functions. The presenter then demonstrates the latest features of AWS Batch with relevant use cases and sample code before describing some of the upcoming features for the service. Finally, hear from AWS Batch customers as they describe why and how they are using AWS Batch. This portion of the talk is delivered by representatives from the University of Utah, Autodesk, and AdRoll.
NEW LAUNCH! Building Alexa Skills for Businesses (ALX204) Amazon Web Services
Alexa for Business makes it possible for businesses to create Alexa skills designed specifically for employees or customers. With Alexa for Business, devices can be managed and provisioned to be used by employees in conference rooms, at employees’ desks, or around the workplace. You can also create skills that can be used by customers, in places like hotel rooms, restaurants, hospitality suites, or even stores. In this session, we’ll provide an overview of Alexa for Business, and show you how Alexa for Business creates business value for both customers and employees.
One of the biggest tradeoffs customers usually make when deploying BI solutions at scale is agility versus governance. Large-scale BI implementations with the right governance structure can take months to design and deploy. In this session, learn how you can avoid making this tradeoff using Amazon QuickSight. Learn how to easily deploy Amazon QuickSight to thousands of users using Active Directory and Federated SSO, while securely accessing your data sources in Amazon VPCs or on-premises. We also cover how to control access to your datasets, implement row-level security, create scheduled email reports, and audit access to your data.
Join us to see how Public-sector organizations and AWS Partners are combining Smart Devices and Artificial Intelligence to create flexible, secure and cost-effective solutions. Applying machine learning models to live video/audio, cameras can be transformed into flexible IoT devices that perform critical functions around public safety, security, property management, smart parking & environmental management. Learn how these solutions are architected using AWS services such as AWS IoT Core, AWS GreenGrass, AWS DeepLens, Amazon SageMaker and Amazon Alexa.
MSDN Events Presents – for the Developer & Architect from
In this session, we will discuss:
Cloud computing architectures in general and the Azure architecture in particular
Several aspects of Azure from the developer’s and architect’s perspective
Azure roles (web, web service and worker)
Azure storage options
Azure security and identity options
How Azure-based applications can be integrated with on-premise applications
Configuration, deployment and scaling Azure-based applications
How development teams can optimize their applications for better management and monitoring
How to Determine If You Are Well Architected for Resiliency (or How I Learned...Amazon Web Services
Are your critical applications well architected? Come join this workshop to find out. In this workshop, we perform destructive testing on a reference architecture that is designed to be available 99.99% of the time. This architecture spans availability zones and even regions. We dive deep into how to achieve high availability and in the rare case of disaster, how to fail over to a completely different region. We explain some concepts and implement code to test each layer’s resiliency for simulated loss of Availability Zones, regional service loss, and regional loss. We cover web applications, databases, and storage. Bring your laptop or tablet with your favorite IDE and your AWS account. This workshop requires basic hands-on programming skills. You should be familiar with a programming language like python, java, c#, ruby, powershell or bash.
In this session, you learn how to set up a crawler to automatically discover your data and build your AWS Glue Data Catalog. You then auto-generate an AWS Glue ETL script, download it, and interactively edit it using a Zeppelin notebook, connected to an AWS Glue development endpoint. After that, you upload this script to Amazon S3, reuse it across multiple jobs, and add trigger conditions to run the jobs. The resulting datasets automatically get registered in the AWS Glue Data Catalog and you can then query these new datasets from Amazon EMR and Amazon Athena. Prerequisites: Knowledge of Python and familiarity with big data applications is preferred but not required. Attendees must bring their own laptops.
EUT305_Delivering the Future of Energy with Connected Home Products Using AWS...Amazon Web Services
What if your utilities company could fix your hot water service before you knew it was broken, or introduced novel pricing models to improve global sustainability? Centrica, a global utility company with notable brands like British Gas, is a market leader in connected home products that help customers manage their energy use. With millions of customers and thousands of device installations a week, the business was outgrowing their on-premises data center despite ongoing investments, so they needed a reliable and elastic architecture that could quickly scale to meet demand. They also needed an agile and compliant IoT platform to manage the explosion of data resulting from more customers, more devices, and more sensors. With AWS IoT, they can focus on delivering better customer experiences while generating valuable business insights to optimize energy usage, reduce costs, and enable global sustainability. In this session, participants learn how Centrica seamlessly migrated to AWS IoT, and how they are modernizing their platform to deliver the future of energy.
As serverless architectures become more popular, customers need a framework of patterns to help them identify how they can leverage AWS to deploy their workloads without managing servers or operating systems. This session describes re-usable serverless patterns while considering costs. For each pattern, we provide operational and security best practices and discuss potential pitfalls and nuances. We also discuss the considerations for moving an existing server-based workload to a serverless architecture. The patterns use services like AWS Lambda, Amazon API Gateway, Amazon Kinesis Streams, Amazon Kinesis Analytics, Amazon DynamoDB, Amazon S3, AWS Step Functions, AWS Config, AWS X-Ray, and Amazon Athena. This session can help you recognize candidates for serverless architectures in your own organizations and understand areas of potential savings and increased agility. What’s new in 2017: using X-Ray in Lambda for tracing and operational insight; a pattern on high performance computing (HPC) using Lambda at scale; how a query can be achieved using Athena; Step Functions as a way to handle orchestration for both the Automation and Batch patterns; a pattern for Security Automation using AWS Config rules to detect and automatically remediate violations of security standards; how to validate API parameters in API Gateway to protect your API back-ends; and a solid focus on CI/CD development pipelines for serverless –that includes testing, deploying, and versioning (SAM tools).
DVC303-Technological Accelerants for Organizational TransformationAmazon Web Services
"Developers and management can seem at cross purposes when one group looks at technologies and the other looks at organizational issues. Both groups are looking for ways to deliver value faster, leaner, and at less cost. There are technological avenues for accomplishing these goals, including DevOps and serverless architectures. However, these approaches also have organizational implications, as they change the nature and content of communication between teams. In this session, we cover the technology benefits and organizational transformations involved in DevOps and serverless architectures.
This session is part of the re:Invent Developer Community Day, six community-led sessions where AWS enthusiasts share technical insights on trending topics based on first-hand experiences and knowledge shared within local AWS communities."
Reducing the time to get actionable insights from data is important to all businesses, and customers who employ batch data analytics tools are exploring the benefits of streaming analytics. Learn best practices to extend your architecture from data warehouses and databases to real-time solutions. Learn how to use Amazon Kinesis to get real-time data insights and integrate them with Amazon Aurora, Amazon RDS, Amazon Redshift, and Amazon S3. The Amazon Flex team describes how they used streaming analytics in their Amazon Flex mobile app, used by Amazon delivery drivers to deliver millions of packages each month on time. They discuss the architecture that enabled the move from a batch processing system to a real-time system, overcoming the challenges of migrating existing batch data to streaming data, and how to benefit from real-time analytics.
ABD207 building a banking utility leveraging aws to fight financial crime and...Amazon Web Services
"Banks aren’t known to share data and collaborate with one another. But that is exactly what the Mid-Sized Bank Coalition of America (MBCA) is doing to fight digital financial crime—and protect national security. Using the AWS Cloud, the MBCA developed a shared data analytics utility that processes terabytes of non-competitive customer account, transaction, and government risk data. The intelligence produced from the data helps banks increase the efficiency of their operations, cut labor and operating costs, and reduce false positive volumes. The collective intelligence also allows greater enforcement of Anti-Money Laundering (AML) regulations by helping members detect internal risks—and identify the challenges to detecting these risks in the first place. This session demonstrates how the AWS Cloud supports the MBCA to deliver advanced data analytics, provide consistent operating models across financial institutions, reduce costs, and strengthen national security.
Session sponsored by Accenture"
ABD317_Building Your First Big Data Application on AWS - ABD317Amazon Web Services
Want to ramp up your knowledge of AWS big data web services and launch your first big data application on the cloud? We walk you through simplifying big data processing as a data bus comprising ingest, store, process, and visualize. You build a big data application using AWS managed services, including Amazon Athena, Amazon Kinesis, Amazon DynamoDB, and Amazon S3. Along the way, we review architecture design patterns for big data applications and give you access to a take-home lab so that you can rebuild and customize the application yourself. You should bring your own laptop and have some familiarity with AWS services to get the most from this session.
ALX202_Integrate Alexa voice technology into your product with the Alexa Voic...Amazon Web Services
In this session, we’ll teach you how to use the Alexa Voice Service (AVS) and its suite of development tools to bring your first Alexa-enabled product to market. You’ll learn how commercial device manufacturers are getting to market faster using the new AVS Device SDK. To ensure your customers have the best voice experience, we’ll teach you how to choose an Audio Front End and client-side hardware from a range of commercial-grade Development Kits. You’ll walk out of this session with the knowledge required to design products with optimized Alexa-enabled voice experiences around your unique design requirements.
CON318_Interstella 8888 Monolith to Microservices with Amazon ECSAmazon Web Services
Interstella 8888 is an intergalactic trading company that deals in rare resources, but their antiquated monolithic logistics systems are causing the business to lose money. Join this workshop to get hands-on experience deploying Docker containers as you break Intersella 8888’s aging monolithic application into containerized microservices. Using Amazon ECS and the Application Load Balancer, you will create API-based microservices and deploy them leveraging integrations with other AWS services.
AWS credits are provided. Bring a laptop, and have an active AWS account."
ABD206-Building Visualizations and Dashboards with Amazon QuickSightAmazon Web Services
Just as a picture is worth a thousand words, a visual is worth a thousand data points. A key aspect of our ability to gain insights from our data is to look for patterns, and these patterns are often not evident when we simply look at data in tables. The right visualization will help you gain a deeper understanding in a much quicker timeframe. In this session, we will show you how to quickly and easily visualize your data using Amazon QuickSight. We will show you how you can connect to data sources, generate custom metrics and calculations, create comprehensive business dashboards with various chart types, and setup filters and drill downs to slice and dice the data.
Create a Serverless Image Processing Platform - ARC326 - re:Invent 2017Amazon Web Services
Are you interested in processing images at scale without launching a single virtual machine? In this workshop, we show participants how to create an entirely serverless image processing platform using Amazon Cognito, AWS Lambda, Amazon Rekognition, and Amazon Elasticsearch Service (Amazon ES). Participants leave this workshop with a web portal where users can upload images that ultimately end up in a searchable index powered by Amazon ES and Kibana. Bring your laptop, and AWS account with Admin access. Your laptop should have either SSH capability or have Putty installed.
CMP323_AWS Batch Easy & Efficient Batch Computing on Amazon Web ServicesAmazon Web Services
AWS Batch is a fully managed service that enables developers to easily and efficiently run batch computing workloads of any scale on AWS. AWS Batch automatically provisions the right quantity and type of compute resources needed to run your jobs. With AWS Batch, you don't need to install or manage batch computing software, so you can focus on analyzing results and solving problems. In this session, the principal product manager for AWS Batch, Jamie Kinney, describes the core concepts behind AWS Batch and details of how the service functions. The presenter then demonstrates the latest features of AWS Batch with relevant use cases and sample code before describing some of the upcoming features for the service. Finally, hear from AWS Batch customers as they describe why and how they are using AWS Batch. This portion of the talk is delivered by representatives from the University of Utah, Autodesk, and AdRoll.
NEW LAUNCH! Building Alexa Skills for Businesses (ALX204) Amazon Web Services
Alexa for Business makes it possible for businesses to create Alexa skills designed specifically for employees or customers. With Alexa for Business, devices can be managed and provisioned to be used by employees in conference rooms, at employees’ desks, or around the workplace. You can also create skills that can be used by customers, in places like hotel rooms, restaurants, hospitality suites, or even stores. In this session, we’ll provide an overview of Alexa for Business, and show you how Alexa for Business creates business value for both customers and employees.
One of the biggest tradeoffs customers usually make when deploying BI solutions at scale is agility versus governance. Large-scale BI implementations with the right governance structure can take months to design and deploy. In this session, learn how you can avoid making this tradeoff using Amazon QuickSight. Learn how to easily deploy Amazon QuickSight to thousands of users using Active Directory and Federated SSO, while securely accessing your data sources in Amazon VPCs or on-premises. We also cover how to control access to your datasets, implement row-level security, create scheduled email reports, and audit access to your data.
Join us to see how Public-sector organizations and AWS Partners are combining Smart Devices and Artificial Intelligence to create flexible, secure and cost-effective solutions. Applying machine learning models to live video/audio, cameras can be transformed into flexible IoT devices that perform critical functions around public safety, security, property management, smart parking & environmental management. Learn how these solutions are architected using AWS services such as AWS IoT Core, AWS GreenGrass, AWS DeepLens, Amazon SageMaker and Amazon Alexa.
MSDN Events Presents – for the Developer & Architect from
In this session, we will discuss:
Cloud computing architectures in general and the Azure architecture in particular
Several aspects of Azure from the developer’s and architect’s perspective
Azure roles (web, web service and worker)
Azure storage options
Azure security and identity options
How Azure-based applications can be integrated with on-premise applications
Configuration, deployment and scaling Azure-based applications
How development teams can optimize their applications for better management and monitoring
Before IoT was even a buzz word, our Heavy Industry customers have been running control systems for core parts of their business. Mining, Oil & Gas and Manufacturing have relied on PLCs and embedded systems, but are looking at liberating this data into modern, open platforms. Come and see how AWS tools and services can help accelerate this process with a focus on Edge and Time series data.
How to build a social network on Serverless (AWS Community Summit)Yan Cui
Many people are building different workloads using serverless technologies these days, but how would a non-trivial system such as a social network look like on serverless?
In this talk Yan will discuss his journey of migrating a social network startup to serverless, and how his team was able to improve performance, scalability and feature delivery using serverless technologies.
Yan will discuss how serverless technologies such as Lambda are used to implement each part of their system, including search, push notifications, timeline, user recommendations, and business intelligence. If you're wondering how serverless can be used to solve a wide variety of challenges in your business, this is the talk for you.
How to build a social network on serverless | Yan CuiAWSCOMSUM
Many people are building different workloads using serverless technologies these days, but how would a non-trivial system such as a social network look like on serverless?
In this talk Yan will discuss his journey of migrating a social network startup to serverless, and how his team was able to improve performance, scalability and feature delivery using serverless technologies.
Yan will discuss how serverless technologies such as Lambda are used to implement each part of their system, including search, push notifications, timeline, user recommendations, and business intelligence. If you're wondering how serverless can be used to solve a wide variety of challenges in your business, this is the talk for you.
TechNet Events Presents – for the IT Professional
In this session, we will discuss:
Azure architecture from the IT professional’s point of view
Why an IT operations team would want to pursue Azure as an extension to the data center
Configuration, deployment and scaling Azure-based applications
The Azure roles (web, web service and worker)
Azure storage options
Azure security and identity options
How Azure-based applications can be integrated with on-premises applications
How operations teams can manage and monitor Azure-based applications
How to build a social network on serverlessYan Cui
Many people are building different workloads using serverless technologies these days, but how would a non-trivial system such as a social network look like on serverless?
In this talk Yan will discuss his journey of migrating a social network startup to serverless, and how his team was able to improve performance, scalability and feature delivery using serverless technologies.
Yan will discuss how serverless technologies such as Lambda are used to implement each part of their system, including search, push notifications, timeline, user recommendations, and business intelligence. If you're wondering how serverless can be used to solve a wide variety of challenges in your business, this is the talk for you.
Battery Ventures: Simulating and Visualizing Large Scale Cassandra DeploymentsDataStax Academy
The SimianViz microservices simulator contains a model of Cassandra that allows large scale global deployments to be created and exercised by simulating failure modes and connecting the simulation to real monitoring tools to visualize the effects. The simulator is open source Go code at github.com/adrianco/spigo and is developing rapidly.
AWS re:Invent 2016: Internet of Things (IoT) Edge and Device Services (IOT202)Amazon Web Services
AWS IoT edge and device services make it easy to get started and scale quickly along with your business needs. Medical equipment, industrial machinery, building automation, and simple device to trigger services, are just a few physical-world use cases that are benefiting from elastic cloud computing while meeting the local execution requirements and real time responsiveness. This session covers the intersection between the device and cloud industries, and the way AWS and our customers will shape the future of those industries together. We will showcase how our customers are using AWS IoT Button, the IoT Device SDKs, and other AWS services to improve the existing business models, invent new way of working, and balance the benefits of the cloud services with the need for local execution.
The rise of the digital platforms is transforming the principles of economic growth, how businesses compete and organisations are formed; essentially reshaping the world we live, work, and play in. Scott will introduce the underpinning characteristics of a digital platform, explain why they both accelerate delivery within organisations as well as creating an ecosystem for positioning the organisation to compete and even shape the connected economy
From Zero to still Zero: The most beautiful mistakes going into the cloud. OPEN KNOWLEDGE GmbH
"Cloud is the new Normal”, so Andrew R. Jassy (CIO AWS). Was also liegt näher, als genau jetzt den Schritt in die Cloud zu wagen? Passende Blaupausen dazu gibt es mehr als genug. Aber ist dieser Schritt wirklich so einfach, wie uns die verschiedenen Cloud-Anbieter glauben machen wollen? Natürlich nicht. Diese Session zeigt anhand typischer Antipattern, wie der Weg in die Cloud garantiert im Desaster endet und wie man sich dagegen wappnen kann. Ähnlichkeiten zu existierenden Projekten sind rein zufällig – oder auch nicht.
How to build a social network on serverlessYan Cui
Many people are building different workloads using serverless technologies these days, but how would a non-trivial system such as a social network look like on serverless?
In this talk Yan will discuss his journey of migrating a social network startup to serverless, and how his team was able to improve performance, scalability and feature delivery using serverless technologies.
Yan will discuss how serverless technologies such as Lambda are used to implement each part of their system, including search, push notifications, timeline, user recommendations, and business intelligence. If you're wondering how serverless can be used to solve a wide variety of challenges in your business, this is the talk for you.
NEW LAUNCH! AWS PrivateLink: Bringing SaaS Solutions into Your VPCs and Your ...Amazon Web Services
Many customers are hesitant to adopt SaaS solutions due to the concerns on the safety of the network connectivity traversing internet. It is also difficult to manage the firewall rules, NAT Gateway or VPN connections. AWS PrivateLink provided solution that let our customers’ applications, whether in a VPC or in their own data center, to connect to SaaS solutions in a highly scalable and highly available manner, while keeping all the network traffic within the AWS network.
IoT-Daten: Mehr und schneller ist nicht automatisch besser.
Über optimale Sampling-Strategien, wie man rechnen kann, ob IoT sich rechnet, und warum es nicht immer Deep Learning und Real-Time-Analytics sein muss. (Folien Deutsch/Englisch)
Similar to ABD322_Implementing a Flight Simulator Interface Using AI, Virtual Reality, and Big Data on AWS (20)
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...Amazon Web Services
Il Forecasting è un processo importante per tantissime aziende e viene utilizzato in vari ambiti per cercare di prevedere in modo accurato la crescita e distribuzione di un prodotto, l’utilizzo delle risorse necessarie nelle linee produttive, presentazioni finanziarie e tanto altro. Amazon utilizza delle tecniche avanzate di forecasting, in parte questi servizi sono stati messi a disposizione di tutti i clienti AWS.
In questa sessione illustreremo come pre-processare i dati che contengono una componente temporale e successivamente utilizzare un algoritmo che a partire dal tipo di dato analizzato produce un forecasting accurato.
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...Amazon Web Services
La varietà e la quantità di dati che si crea ogni giorno accelera sempre più velocemente e rappresenta una opportunità irripetibile per innovare e creare nuove startup.
Tuttavia gestire grandi quantità di dati può apparire complesso: creare cluster Big Data su larga scala sembra essere un investimento accessibile solo ad aziende consolidate. Ma l’elasticità del Cloud e, in particolare, i servizi Serverless ci permettono di rompere questi limiti.
Vediamo quindi come è possibile sviluppare applicazioni Big Data rapidamente, senza preoccuparci dell’infrastruttura, ma dedicando tutte le risorse allo sviluppo delle nostre le nostre idee per creare prodotti innovativi.
Ora puoi utilizzare Amazon Elastic Kubernetes Service (EKS) per eseguire pod Kubernetes su AWS Fargate, il motore di elaborazione serverless creato per container su AWS. Questo rende più semplice che mai costruire ed eseguire le tue applicazioni Kubernetes nel cloud AWS.In questa sessione presenteremo le caratteristiche principali del servizio e come distribuire la tua applicazione in pochi passaggi
Vent'anni fa Amazon ha attraversato una trasformazione radicale con l'obiettivo di aumentare il ritmo dell'innovazione. In questo periodo abbiamo imparato come cambiare il nostro approccio allo sviluppo delle applicazioni ci ha permesso di aumentare notevolmente l'agilità, la velocità di rilascio e, in definitiva, ci ha consentito di creare applicazioni più affidabili e scalabili. In questa sessione illustreremo come definiamo le applicazioni moderne e come la creazione di app moderne influisce non solo sull'architettura dell'applicazione, ma sulla struttura organizzativa, sulle pipeline di rilascio dello sviluppo e persino sul modello operativo. Descriveremo anche approcci comuni alla modernizzazione, compreso l'approccio utilizzato dalla stessa Amazon.com.
Come spendere fino al 90% in meno con i container e le istanze spot Amazon Web Services
L’utilizzo dei container è in continua crescita.
Se correttamente disegnate, le applicazioni basate su Container sono molto spesso stateless e flessibili.
I servizi AWS ECS, EKS e Kubernetes su EC2 possono sfruttare le istanze Spot, portando ad un risparmio medio del 70% rispetto alle istanze On Demand. In questa sessione scopriremo insieme quali sono le caratteristiche delle istanze Spot e come possono essere utilizzate facilmente su AWS. Impareremo inoltre come Spreaker sfrutta le istanze spot per eseguire applicazioni di diverso tipo, in produzione, ad una frazione del costo on-demand!
In recent months, many customers have been asking us the question – how to monetise Open APIs, simplify Fintech integrations and accelerate adoption of various Open Banking business models. Therefore, AWS and FinConecta would like to invite you to Open Finance marketplace presentation on October 20th.
Event Agenda :
Open banking so far (short recap)
• PSD2, OB UK, OB Australia, OB LATAM, OB Israel
Intro to Open Finance marketplace
• Scope
• Features
• Tech overview and Demo
The role of the Cloud
The Future of APIs
• Complying with regulation
• Monetizing data / APIs
• Business models
• Time to market
One platform for all: a Strategic approach
Q&A
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...Amazon Web Services
Per creare valore e costruire una propria offerta differenziante e riconoscibile, le startup di successo sanno come combinare tecnologie consolidate con componenti innovativi creati ad hoc.
AWS fornisce servizi pronti all'utilizzo e, allo stesso tempo, permette di personalizzare e creare gli elementi differenzianti della propria offerta.
Concentrandoci sulle tecnologie di Machine Learning, vedremo come selezionare i servizi di intelligenza artificiale offerti da AWS e, anche attraverso una demo, come costruire modelli di Machine Learning personalizzati utilizzando SageMaker Studio.
OpsWorks Configuration Management: automatizza la gestione e i deployment del...Amazon Web Services
Con l'approccio tradizionale al mondo IT per molti anni è stato difficile implementare tecniche di DevOps, che finora spesso hanno previsto attività manuali portando di tanto in tanto a dei downtime degli applicativi interrompendo l'operatività dell'utente. Con l'avvento del cloud, le tecniche di DevOps sono ormai a portata di tutti a basso costo per qualsiasi genere di workload, garantendo maggiore affidabilità del sistema e risultando in dei significativi miglioramenti della business continuity.
AWS mette a disposizione AWS OpsWork come strumento di Configuration Management che mira ad automatizzare e semplificare la gestione e i deployment delle istanze EC2 per mezzo di workload Chef e Puppet.
Scopri come sfruttare AWS OpsWork a garanzia e affidabilità del tuo applicativo installato su Instanze EC2.
Microsoft Active Directory su AWS per supportare i tuoi Windows WorkloadsAmazon Web Services
Vuoi conoscere le opzioni per eseguire Microsoft Active Directory su AWS? Quando si spostano carichi di lavoro Microsoft in AWS, è importante considerare come distribuire Microsoft Active Directory per supportare la gestione, l'autenticazione e l'autorizzazione dei criteri di gruppo. In questa sessione, discuteremo le opzioni per la distribuzione di Microsoft Active Directory su AWS, incluso AWS Directory Service per Microsoft Active Directory e la distribuzione di Active Directory su Windows su Amazon Elastic Compute Cloud (Amazon EC2). Trattiamo argomenti quali l'integrazione del tuo ambiente Microsoft Active Directory locale nel cloud e l'utilizzo di applicazioni SaaS, come Office 365, con AWS Single Sign-On.
Dal riconoscimento facciale al riconoscimento di frodi o difetti di fabbricazione, l'analisi di immagini e video che sfruttano tecniche di intelligenza artificiale, si stanno evolvendo e raffinando a ritmi elevati. In questo webinar esploreremo le possibilità messe a disposizione dai servizi AWS per applicare lo stato dell'arte delle tecniche di computer vision a scenari reali.
Amazon Web Services e VMware organizzano un evento virtuale gratuito il prossimo mercoledì 14 Ottobre dalle 12:00 alle 13:00 dedicato a VMware Cloud ™ on AWS, il servizio on demand che consente di eseguire applicazioni in ambienti cloud basati su VMware vSphere® e di accedere ad una vasta gamma di servizi AWS, sfruttando a pieno le potenzialità del cloud AWS e tutelando gli investimenti VMware esistenti.
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
Crea la tua prima serverless ledger-based app con QLDB e NodeJSAmazon Web Services
Molte aziende oggi, costruiscono applicazioni con funzionalità di tipo ledger ad esempio per verificare lo storico di accrediti o addebiti nelle transazioni bancarie o ancora per tenere traccia del flusso supply chain dei propri prodotti.
Alla base di queste soluzioni ci sono i database ledger che permettono di avere un log delle transazioni trasparente, immutabile e crittograficamente verificabile, ma sono strumenti complessi e onerosi da gestire.
Amazon QLDB elimina la necessità di costruire sistemi personalizzati e complessi fornendo un database ledger serverless completamente gestito.
In questa sessione scopriremo come realizzare un'applicazione serverless completa che utilizzi le funzionalità di QLDB.
Con l’ascesa delle architetture di microservizi e delle ricche applicazioni mobili e Web, le API sono più importanti che mai per offrire agli utenti finali una user experience eccezionale. In questa sessione impareremo come affrontare le moderne sfide di progettazione delle API con GraphQL, un linguaggio di query API open source utilizzato da Facebook, Amazon e altro e come utilizzare AWS AppSync, un servizio GraphQL serverless gestito su AWS. Approfondiremo diversi scenari, comprendendo come AppSync può aiutare a risolvere questi casi d’uso creando API moderne con funzionalità di aggiornamento dati in tempo reale e offline.
Inoltre, impareremo come Sky Italia utilizza AWS AppSync per fornire aggiornamenti sportivi in tempo reale agli utenti del proprio portale web.
Database Oracle e VMware Cloud™ on AWS: i miti da sfatareAmazon Web Services
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
In queste slide, gli esperti AWS e VMware presentano semplici e pratici accorgimenti per facilitare e semplificare la migrazione dei carichi di lavoro Oracle accelerando la trasformazione verso il cloud, approfondiranno l’architettura e dimostreranno come sfruttare a pieno le potenzialità di VMware Cloud ™ on AWS.
Amazon Elastic Container Service (Amazon ECS) è un servizio di gestione dei container altamente scalabile, che semplifica la gestione dei contenitori Docker attraverso un layer di orchestrazione per il controllo del deployment e del relativo lifecycle. In questa sessione presenteremo le principali caratteristiche del servizio, le architetture di riferimento per i differenti carichi di lavoro e i semplici passi necessari per poter velocemente migrare uno o più dei tuo container.
2. Your Hosts for the Day
Marc Teichtahl
• Manager Solutions Architect, Melbourne Australia
3. Your Hosts for the Day
Marc Teichtahl
• Manager Solutions Architect, Melbourne Australia
Marten Payne
• Technical Account Manager , Melbourne Australia
4. Your Hosts for the Day
Marc Teichtahl
• Manager Solutions Architect, Melbourne Australia
Marten Payne
• Technical Account Manager , Melbourne Australia
Daniel O‘Brien
• Solutions Architect, Wellington, New Zealand
5. Your Hosts for the Day
Having trouble?
The proctors are here to help!
https://pixabay.com/en/balloon-talk-language-german-males-2557031/
6. Today
Section 1: Introduction to AR, VR, and Synthetic Worlds
Section 2: Architectures and Technology
Break
Section 3: Hands-On Workshop
7. Today
Section 1: Introduction to AR, VR, and Synthetic Worlds
Section 2: Architectures and Technology
Break
Section 3: Hands-On Workshop
8. Today
Section 1: Introduction to AR, VR, and Synthetic Worlds
Section 2: Architectures and Technology
Break
Section 3: Hands-On Workshop
9. Today
Section 1: Introduction to AR, VR, and Synthetic Worlds
Section 2: Architectures and Technology
Break
Section 3: Hands-On Workshop
10. Today
Section 1: Introduction to AR, VR, and Synthetic Worlds
Section 2: Architectures and Technology
Break
Section 3: Hands-On Workshop
20. These Worlds Are Similar but Different
Virtual
reality
Virtual “things” in
a virtual world
21. These Worlds Are Similar but Different
Virtual
reality
Virtual “things” in
a virtual world
22. These Worlds Are Similar but Different
Virtual
reality
Augmented
reality
Virtual “things” in
a virtual world
Virtual “things” in
the real world
23. These Worlds Are Similar but Different
Virtual
reality
Augmented
reality
Virtual “things” in
a virtual world
Virtual “things” in
the real world
24. These Worlds Are Similar but Different
Virtual
reality
Augmented
reality
Simulators
Virtual “things” in
a virtual world
Virtual “things” in
the real world
Real “things” in
a virtual world
25. These Worlds Are Similar but Different
Virtual
reality
Augmented
reality
Simulators
Virtual “things” in
a virtual world
Virtual “things” in
the real world
Real “things” in
a virtual world
26. These Worlds Are Similar but Different
Virtual
reality
Augmented
reality
Simulators
Virtual “things” in
a virtual world
Virtual “things” in
the real world
Real “things” in
a virtual world
Synthetic
worlds
31. However, They Have Similar Attributes
Many commonalities
Visual Tactile Audible
32. How do we think about these worlds?
https://pixabay.com/en/steelwork-engineering-structure-1031611/
33. A Framework for Synthetic Worlds
Simulate
• Models
• Systems
• Coordinates
• Inputs
• Outputs
34. A Framework for Synthetic Worlds
Simulate Visualize
• Views and cameras
• Landscapes
• Objects
• AI
35. A Framework for Synthetic Worlds
Simulate Visualize Interface
• Human
• Tactile
• Switches, dials
• Buttons
• Motors
• Lights
36. A Framework for Synthetic Worlds
Simulate Visualize Interface Process
• Mediate
• Normalize
• Transform
• Log and record
37. A Framework for Synthetic Worlds
Simulate Visualize Interface Process Interact
• Influence
• Impact
• Human factors
38. A Framework for Synthetic Worlds
Simulate Visualize Interface Process Interact
Learn
Machine learning Predictive analytics Feedback Reporting
39. A Reference Architecture
Sim hub
toCloudWatch toDynamo
CloudWatch Dynamo
DB
Redshift
toRedshift
kinesisAnalytics
Aggregatedata
raw data
AML
S3
Lex
CloudWatch
Dashboard
kinesis
raw data
raw data
Simulator
Visuals
Simulate
Interface/interact
Interact
Visualize
Learn
Process
40. A Reference Architecture
Sim hub
toCloudWatch toDynamo
CloudWatch Dynamo
DB
Redshift
toRedshift
kinesisAnalytics
Aggregatedata
raw data
AML
S3
Lex
CloudWatch
Dashboard
kinesis
raw data
raw data
Simulator
Visuals
Interface/interact
Interact
Visualize
Learn
Process
41. A Reference Architecture
Bus
toCloudWatch toDynamo
CloudWatch Dynamo
DB
Redshift
toRedshift
kinesisAnalytics
Aggregatedata
raw data
AML
S3
Lex
CloudWatch
Dashboard
kinesis
raw data
raw data
Simulator
Visuals
Interact
Visualize
Learn
Process
Switches, inputs, outputs
42. A Reference Architecture
Bus
toCloudWatch toDynamo
CloudWatch Dynamo
DB
Redshift
toRedshift
Aggregatedata
raw data
AML
S3
Lex
CloudWatch
Dashboard
Kinesis
raw data
raw data
Simulator
Visuals
Interact
Visualize
Learn
Switches, inputs, outputs
Kinesis Analytics
46. A Reference Architecture
Bus
Kinesis Analytics
Aggregatedata
raw data
AML
S3
Lex
CloudWatch
Dashboard
Kinesis
raw data
raw data
Simulator
Visuals
Switches, inputs, outputs
toCloudWatch toDynamotoRedshift
+Greengrass
IoT
GG
DynamoDBAmazon
CloudWatch
Amazon
Redshift
47. But When We Develop
https://pixabay.com/en/entrepreneur-start-start-up-career-696976/
48. But When We Develop
We care about a number
https://pixabay.com/en/entrepreneur-start-start-up-career-696976/
of important considerations
49. What must we consider?
Volume, velocity, frequency
50. What must we consider?
Volume, velocity, frequency
• The amount of data
• The rate at which data is
produced/consumed
• Frequency of data generated
51. What must we consider?
Volume, velocity, frequency
• Kinesis or IoT
• Control plane and data plane
• Sharding, costs
• Threads, concurrency, and
locking (mutexes/semaphores)
53. What must we consider?
Latency
• Network
• Application
• Processing
• Human factors
54. What must we consider?
Latency
• Network partitions—IoT and
AWS Greengrass
• Application design and
efficiencies
• AWS Lambda (warm-up time,
and so on)
• Motion sickness
55. What must we consider?
Cost, deployment, security
56. What must we consider?
Cost, deployment, security
• Choice of technology
• Ease of deployment
• Continuous deployment
• Lambda
57. You Can Choose Your Own Adventure
Visualize Interface Process InteractSimulate
58. You Can Choose Your Own Adventure
Simulate
Visualize Interface Process Interact
59. You Can Choose Your Own Adventure
Simulate
Visualize Interface Process Interact
SurgerySim
TouchSurgery
NurseSim
60. You Can Choose Your Own Adventure
Simulate Visualize
Interface Process Interact
61. You Can Choose Your Own Adventure
Simulate Visualize
Interface Process Interact
Lumberyard
Unity
CryEngine
UnrealEngine
62. You Can Choose Your Own Adventure
Simulate Visualize Interface
Process Interact
Bus
63. You Can Choose Your Own Adventure
Simulate Visualize Interface
Process Interact
RSLogix
SOIC
Step7
Bus
64. You Can Choose Your Own Adventure
Simulate Visualize Interface Process
Interact
Bus
65. You Can Choose Your Own Adventure
Simulate Visualize Interface Process
Interact
Bus
66. You Can Choose Your Own Adventure
Simulate Visualize Interface Process
Interact
AWS IoT
Amazon Kinesis Analytics
AWS Lambda
Amazon Athena
AWS CloudWatch
Bus
67. You Can Choose Your Own Adventure
Simulate Visualize Interface Process Interact
Bus
68. You Can Choose Your Own Adventure
Simulate Visualize Interface Process Interact
Bus
69. You Can Choose Your Own Adventure
Simulate Visualize Interface Process Interact
RaspberryPi
Intel Edison
Arduino
Bus
70. You Can Choose Your Own Adventure
Simulate Visualize Interface Process Interact
Bus
71. You Can Choose Your Own Adventure
Simulate Visualize Interface Process Interact
Amazon Lex
Amazon Polly
Bus
73. Introduction—The Problem Statement
Traditionally, it has been complex and expensive to:
Securely acquire “near” real-time data from
simulator engines
Process and store large volumes of data to enable
the extraction of meaningful insights
Deliver a user experience that intuitively exposes
near real-time information
74. Introduction—What You Will Do Today
• Uses AWS Kinesis, AWS Lambda, AWS CloudFormation and
AWS API Gateway to securely acquire, process, and publish
near real-time flight data from a simulator data source
• Implements AWS Lambda and Amazon Kinesis to process
flight data using serverless architectures
• Stores the flight data for real-time using Amazon
DynamoDB
• Deploys a user interface to visualize the flight data
You will build a system that:
75. How the Pieces Fit Together
https://pixabay.com/en/airplane-plane-aircraft-sign-99047/
Icons made by Freepik from www.flaticon.com
Data sources
76. How the Pieces Fit Together
https://pixabay.com/en/airplane-plane-aircraft-sign-99047/
Icons made by Freepik from www.flaticon.com
Data sources
Time
Flight
Environment
77. How the Pieces Fit Together
https://pixabay.com/en/airplane-plane-aircraft-sign-99047/
Icons made by Freepik from www.flaticon.com
Data sources
Time
Flight
Environment
Preprocessing
78. How the Pieces Fit Together
https://pixabay.com/en/airplane-plane-aircraft-sign-99047/
Icons made by Freepik from www.flaticon.com
Data sources
Time
Flight
Environment
Preprocessing Serverless processing
79. How the Pieces Fit Together
https://pixabay.com/en/airplane-plane-aircraft-sign-99047/
Icons made by Freepik from www.flaticon.com
Data sources
Time
Flight
Environment
Preprocessing User interfaceServerless processing
80. How the Pieces Fit Together
https://pixabay.com/en/airplane-plane-aircraft-sign-99047/
Icons made by Freepik from www.flaticon.com
Data sources
Time
Flight
Environment
Preprocessing User interface
Acquire
Serverless processing
81. How the Pieces Fit Together
https://pixabay.com/en/airplane-plane-aircraft-sign-99047/
Icons made by Freepik from www.flaticon.com
Data sources
Time
Flight
Environment
Preprocessing Serverless processing User interface
Acquire
Process
82. How the Pieces Fit Together
https://pixabay.com/en/airplane-plane-aircraft-sign-99047/
Icons made by Freepik from www.flaticon.com
Data sources
Time
Flight
Environment
Preprocessing Serverless processing User interface
Acquire
Process Present
83. How the Pieces Fit Together
https://pixabay.com/en/airplane-plane-aircraft-sign-99047/
Icons made by Freepik from www.flaticon.com
Time
Flight
Environment
• Various types of data from sensors and systems
• Send raw data from the simulator
• Real time and simulator time
• Pitch, roll, yaw, airspeed, heading, and so on
• Wind speed and direction, turbulence
• Aggregation of raw data
Acquire
84. How the Pieces Fit Together
https://pixabay.com/en/airplane-plane-aircraft-sign-99047/
Icons made by Freepik from www.flaticon.com
Time
Flight
Environment
• Processing
• Storage
• Publishing
Amazon
Aurora
Amazon
S3
Amazon
Redshift
AWS
Lambda
Amazon
Kinesis
Streams
Amazon
Kinesis
Analytics
Amazon
Kinesis
Firehose
Amazon
SNS
ProcessAcquire
85. How the Pieces Fit Together
https://pixabay.com/en/airplane-plane-aircraft-sign-99047/
Icons made by Freepik from www.flaticon.com
Time
Flight
Environment
Final UI
image here
Acquire Process Present
86. Data Lifecycle
Process Present
• A powerful user interface to view
flight data
• A map, location, and flight info UI
to visualize the simulated world
Acquire
Processing of raw data into final
simulation dataset
• Smoothed data
• Aggregates
• Averages
Acquisition of data from remote
simulator data sources
• Flight
• Environmental/weather
• Time