The document discusses Amazon Web Services (AWS) Internet of Things (IoT) solutions for connecting, managing and gaining insights from IoT devices. It provides an overview of the AWS IoT platform and services, including AWS IoT Core for device connectivity, AWS IoT Device Management for device onboarding and updates, AWS IoT Device Defender for security, and using AWS services like analytics for extracting value from device data.
This session covers the most recent AWS IoT announcements at re:Invent. Learn about trends and use cases for the Internet of Things (IoT). Hear about how AWS customers are using AWS IoT to connect their devices to the cloud and solve business challenges with IoT.
ABD331_Log Analytics at Expedia Using Amazon Elasticsearch ServiceAmazon Web Services
Expedia uses Amazon Elasticsearch Service (Amazon ES) for a variety of mission-critical use cases, ranging from log aggregation to application monitoring and pricing optimization. In this session, the Expedia team reviews how they use Amazon ES and Kibana to analyze and visualize Docker startup logs, AWS CloudTrail data, and application metrics. They share best practices for architecting a scalable, secure log analytics solution using Amazon ES, so you can add new data sources almost effortlessly and get insights quickly.
ABD302_Real-Time Data Exploration and Analytics with Amazon Elasticsearch Ser...Amazon Web Services
In this session, we use Apache web logs as example and show you how to build an end-to-end analytics solution. First, we cover how to configure an Amazon ES cluster and ingest data using Amazon Kinesis Firehose. We look at best practices for choosing instance types, storage options, shard counts, and index rotations based on the throughput of incoming data. Then we demonstrate how to set up a Kibana dashboard and build custom dashboard widgets. Finally, we review approaches for generating custom, ad-hoc reports.
NEW LAUNCH! AWS IoT Analytics from Consumer IoT to Industrial IoT - IOT211 - ...Amazon Web Services
This session is an overview of IoT Analytics challenges and use cases with our customers. This session will cover analytics use cases from Consumer IoT to Industrial IoT. It will then show how AWS IoT Analytics helps customers solve these challenges in different IoT verticals.
Data speaks. Discover how Ivy Tech, the nation's largest singly accredited community college, uses AWS to gather, analyze, and take action on student behavioral data for the betterment of over 3,100 students. This session outlines the process from inception to implementation across the state of Indiana and highlights how Ivy Tech's model can be applied to your own complex business problems.
NEW LAUNCH! Realtime and Offline application development using GraphQL with A...Amazon Web Services
All application developers today need to be concerned with offline access, realtime communications and efficient data fetching. These techniques are no longer optional for great user experiences yet are difficult to engineer and scale from scratch. In this session you’ll get a deep dive on using AWS AppSync to enable your applications for offline access, including optimistic updates on lossy connections, with just a few lines of code. You’ll learn how application data synchronization takes place with the cloud, how you can control the process, programming interfaces for native applications such as iOS and JavaScript based applications across the web, React Native, and Ionic. Additionally you’ll see how using GraphQL enables your application to efficiently leverage the network for queries and mutations while still having a scalable and fast connection for realtime updates when using subscriptions to data changes.
NEW LAUNCH! Infinitely Scalable Machine Learning Algorithms with Amazon AI - ...Amazon Web Services
In machine learning, training large models on massive amount of data usually improved results. Our customers report, however, that training such models and deploying them is either operationally prohibitive or outright impossible for them. Amazon AI Algorithms is designed to solve this problem. It is a collection of distributed streaming ML algorithms that scale to any amount of data. They are fast and efficient because they distribute across CPU/GPU machines and share a collective distributed state via a highly-optimized parameter server. They scale to an infinite amount of data because they operate in the streaming model. This means they require only one pass over the data and never increase their resources consumption, allowing training to be paused, resumed, and snapshotted and even for algorithms to consume kinesis streams directly providing an “always on” training mechanism. They are production ready. Trained models are automatically containerized and useable in production using Amazon SageMaker hosting. Finally, we provide a convenient SDK which allows scientists to create new algorithms which operate in this model and enjoy all the benefits above.
This talk will discuss our design choices and some of the internal working of the system. It will also describe the distributed streaming model and its numerous benefits to machine learning practitioners. We will show how to invoke large scale learning from Amazon SageMaker, or Amazon EMR, and host the solution. Time permits, we will show how to develop a new Algorithm using the SDK.
NEW LAUNCH! Introducing Amazon SageMaker - MCL365 - re:Invent 2017Amazon Web Services
Amazon SageMaker is a fully-managed service that enables data scientists and developers to quickly and easily build, train, and deploy machine learning models, at scale. This session will introduce you the features of Amazon SageMaker, including a one-click training environment, highly-optimized machine learning algorithms with built-in model tuning, and deployment without engineering effort. With zero-setup required, Amazon SageMaker significantly decreases your training time and overall cost of building production machine learning systems. You'll also hear how and why Intuit is using Amazon SaeMaker on AWS for real-time fraud detection.
This session covers the most recent AWS IoT announcements at re:Invent. Learn about trends and use cases for the Internet of Things (IoT). Hear about how AWS customers are using AWS IoT to connect their devices to the cloud and solve business challenges with IoT.
ABD331_Log Analytics at Expedia Using Amazon Elasticsearch ServiceAmazon Web Services
Expedia uses Amazon Elasticsearch Service (Amazon ES) for a variety of mission-critical use cases, ranging from log aggregation to application monitoring and pricing optimization. In this session, the Expedia team reviews how they use Amazon ES and Kibana to analyze and visualize Docker startup logs, AWS CloudTrail data, and application metrics. They share best practices for architecting a scalable, secure log analytics solution using Amazon ES, so you can add new data sources almost effortlessly and get insights quickly.
ABD302_Real-Time Data Exploration and Analytics with Amazon Elasticsearch Ser...Amazon Web Services
In this session, we use Apache web logs as example and show you how to build an end-to-end analytics solution. First, we cover how to configure an Amazon ES cluster and ingest data using Amazon Kinesis Firehose. We look at best practices for choosing instance types, storage options, shard counts, and index rotations based on the throughput of incoming data. Then we demonstrate how to set up a Kibana dashboard and build custom dashboard widgets. Finally, we review approaches for generating custom, ad-hoc reports.
NEW LAUNCH! AWS IoT Analytics from Consumer IoT to Industrial IoT - IOT211 - ...Amazon Web Services
This session is an overview of IoT Analytics challenges and use cases with our customers. This session will cover analytics use cases from Consumer IoT to Industrial IoT. It will then show how AWS IoT Analytics helps customers solve these challenges in different IoT verticals.
Data speaks. Discover how Ivy Tech, the nation's largest singly accredited community college, uses AWS to gather, analyze, and take action on student behavioral data for the betterment of over 3,100 students. This session outlines the process from inception to implementation across the state of Indiana and highlights how Ivy Tech's model can be applied to your own complex business problems.
NEW LAUNCH! Realtime and Offline application development using GraphQL with A...Amazon Web Services
All application developers today need to be concerned with offline access, realtime communications and efficient data fetching. These techniques are no longer optional for great user experiences yet are difficult to engineer and scale from scratch. In this session you’ll get a deep dive on using AWS AppSync to enable your applications for offline access, including optimistic updates on lossy connections, with just a few lines of code. You’ll learn how application data synchronization takes place with the cloud, how you can control the process, programming interfaces for native applications such as iOS and JavaScript based applications across the web, React Native, and Ionic. Additionally you’ll see how using GraphQL enables your application to efficiently leverage the network for queries and mutations while still having a scalable and fast connection for realtime updates when using subscriptions to data changes.
NEW LAUNCH! Infinitely Scalable Machine Learning Algorithms with Amazon AI - ...Amazon Web Services
In machine learning, training large models on massive amount of data usually improved results. Our customers report, however, that training such models and deploying them is either operationally prohibitive or outright impossible for them. Amazon AI Algorithms is designed to solve this problem. It is a collection of distributed streaming ML algorithms that scale to any amount of data. They are fast and efficient because they distribute across CPU/GPU machines and share a collective distributed state via a highly-optimized parameter server. They scale to an infinite amount of data because they operate in the streaming model. This means they require only one pass over the data and never increase their resources consumption, allowing training to be paused, resumed, and snapshotted and even for algorithms to consume kinesis streams directly providing an “always on” training mechanism. They are production ready. Trained models are automatically containerized and useable in production using Amazon SageMaker hosting. Finally, we provide a convenient SDK which allows scientists to create new algorithms which operate in this model and enjoy all the benefits above.
This talk will discuss our design choices and some of the internal working of the system. It will also describe the distributed streaming model and its numerous benefits to machine learning practitioners. We will show how to invoke large scale learning from Amazon SageMaker, or Amazon EMR, and host the solution. Time permits, we will show how to develop a new Algorithm using the SDK.
NEW LAUNCH! Introducing Amazon SageMaker - MCL365 - re:Invent 2017Amazon Web Services
Amazon SageMaker is a fully-managed service that enables data scientists and developers to quickly and easily build, train, and deploy machine learning models, at scale. This session will introduce you the features of Amazon SageMaker, including a one-click training environment, highly-optimized machine learning algorithms with built-in model tuning, and deployment without engineering effort. With zero-setup required, Amazon SageMaker significantly decreases your training time and overall cost of building production machine learning systems. You'll also hear how and why Intuit is using Amazon SaeMaker on AWS for real-time fraud detection.
NEW LAUNCH! AWS Serverless Application Repository - SRV215 - re:Invent 2017Amazon Web Services
In this session, we will discuss how the AWS Serverless Application Repository makes it easy to discover and deploy serverless applications published by fellow developers and companies like Datadog, Here, Splunk, and many others. We will cover how you can use the repository to find applications for a variety of use cases and then deploy them to your AWS account. In addition, we will discuss how you can publish your own applications to the repository. You will also hear from two contributors, Datadog and Here, who will describe their approach to building the serverless applications that they have published to the Serverless Application Repository.
Create an IoT Gateway and Establish a Data Pipeline to AWS IoT with Intel - I...Amazon Web Services
In this session, learn how to create a complete Gateway-based IoT framework – from the edge to the cloud and back. By using an IoT Gateway as a central data collection, processing, and communication hub, you can create IoT connectivity without having to replace legacy hardware. We show you how to use an Intel NUC gateway and Arduino 101 sensor hub to gather environmental data, and step you through establishing a data pipeline to AWS IoT. We use AWS Lambda to create a rules engine for your data, and then send a control signal back down the Intel Gateway. Bring your laptop and your AWS account for this workshop.
To win in the marketplace and provide differentiated customer experiences, businesses need to be able to use live data in real time to facilitate fast decision making. In this session, you learn common streaming data processing use cases and architectures. First, we give an overview of streaming data and AWS streaming data capabilities. Next, we look at a few customer examples and their real-time streaming applications. Finally, we walk through common architectures and design patterns of top streaming data use cases.
DynamoDB adaptive capacity: smooth performance for chaotic workloads - DAT327...Amazon Web Services
Database capacity planning is critical to running your business, but it’s also hard. In this session we’ll compare how scaling is usually performed for relational databases and NoSQL databases. We’ll look behind the scenes at how DynamoDB shards your data across multiple partitions and servers. Finally, we’ll talk about some of the recent enhancements to DynamoDB that make scaling even simpler, particularly a new feature called adaptive throughput that eliminates much of the throttling issues that you may have experienced.
Compute at the Edge with AWS Greengrass - IOT309 - re:Invent 2017Amazon Web Services
AWS Greengrass extends AWS onto your devices, so they can act locally on the data they generate while still taking advantage of the cloud. In this session, we discuss the features and development languages of AWS Greengrass that let you build powerful edge compute applications. You’ll also hear directly from Greengrass customers in multiple industries.
Cloud Adoption in Regulated Financial Services - SID328 - re:Invent 2017Amazon Web Services
Macquarie, a global provider of financial services, identified early on that it would require strong partnership between its business, technology and risk teams to enable the rapid adoption of AWS cloud technologies. As a result, Macquarie built a Cloud Governance Platform to enable its risk functions to move as quickly as its development teams. This platform has been the backbone of Macquarie’s adoption of AWS over the past two years and has enabled Macquarie to accelerate its use of cloud technologies for the benefit of clients across multiple global markets. This talk will outline the strategy that Macquarie embarked on, describe the platform they built, and provide examples for other organizations who are on a similar journey.
RET301-Build Single Customer View across Multiple Retail Channels using AWS S...Amazon Web Services
A challenge faced by many retailers is how to form an integrated single view of the customer across multiple retail channels to help you better understand purchasing behavior & patterns. In this session, we will present a solution that merges web analytics data with customer purchase history based on AWS API Gateway, Lambda and S3. Learn how to track customer purchase behaviors across different selling channels to better predict future needs and make relevant, intelligent recommendations.
NEW LAUNCH! Introduction to Amazon GuardDuty - SID218 - re:Invent 2017Amazon Web Services
Amazon GuardDuty is a managed threat detection service that continuously monitors for malicious or unauthorized behavior to help you protect your AWS accounts and workloads. It monitors for activity such as unusual API calls or potentially unauthorized deployments that indicate a possible account compromise. Enabled with a few clicks in the AWS Management Console, Amazon GuardDuty can immediately begin analyzing billions of events across your AWS accounts for signs of risk. It does not require you to deploy and maintain software or security infrastructure, meaning it can be enabled quickly with no risk of negatively impacting existing application workloads.
Introduction to Real-Time Streaming Analytics - Amazon Kinesis State Of Union...Amazon Web Services
Serverless streaming applications Lambda+Kinesis Data Analytics/Kinesis Data Firehose - how to solve common streaming problems using serverless architecture and learn how customers like GE, Comcast, Lyft and more are using Amazon Kinesis.
Analyzing Streaming Data in Real-time with Amazon KinesisAmazon Web Services
As more and more organizations strive to gain real-time insights into their business, streaming data has become ubiquitous. Typical streaming data analytics solutions require specific skills and complex infrastructure. However, with Amazon Kinesis Analytics, you can analyze streaming data in real-time with standard SQL—there is no need to learn new programming languages or processing frameworks.
In this session, we dive deep into the capabilities of Amazon Kinesis Analytics using real-world examples. We’ll present an end-to-end streaming data solution using Amazon Kinesis Streams for data ingestion, Amazon Kinesis Analytics for real-time processing, and Amazon Kinesis Firehose for persistence. We review in detail how to write SQL queries using streaming data and discuss best practices to optimize and monitor your Amazon Kinesis Analytics applications. Lastly, we discuss how to estimate the cost of the entire system.
WPS301-Navigating HIPAA and HITRUST_QuickStart Guide to Account Gov Strat.pdfAmazon Web Services
Join AWS in examining governance and compliance designs aimed at helping organizations meet HIPAA and HITRUST standards. Learn how to better validate and document your compliance, expedite access to AWS compliance accelerators, and discover new ways to use AWS native features to monitor and control your accounts. This session is for a technical audience seeking to dive deep into the AWS service offerings, console, and API.
Best Practices for AWS IoT Core (IOT347-R1) - AWS re:Invent 2018Amazon Web Services
There are many different components of AWS IoT Core, including Device gateway, Registry, Message broker, Rules engine, and Device shadow. In this session, we cover each component in depth, how to use them, and best practices. Come away with an understanding of how AWS IoT Core can help you securely connect and manage devices, process and act on device data, and read and set device state. In addition to best practices, we discuss common customer questions when using different features of AWS IoT Core.
HLC310-How Methodist Le Bonheur Healthcare's Focus on Standardizing Compliant...Amazon Web Services
The innovation team at Methodist Le Bonheur Healthcare (MLH), an integrated health care delivery system, saw AWS as an enabler to faster ideation on breakthrough patient care products over their existing internal private cloud options. In this session, you learn how they eliminated HIPAA compliance as a barrier to their speed-to-market goals by standardizing internal DevOps and DevSecOps duties across applications, as well as taking advantage of the containerization of enterprise technology. MLH partnered with Datica, an APN Healthcare Competency Partner, to address vulnerability scanning, intrusion detection, disaster recovery, backups, encryption, audit logging, and deployment orchestration. You hear how, with this partnership, they ensure that the configuration and orchestration of all AWS HIPAA Eligible Services meet the controls set by healthcare's most stringent accreditation body, HITRUST, with every workload deployment. You also learn how MLH's adoption of a standard compliance layer led to quickly achieving stronger data integration with electronic health records.
Get Started with Real-Time Streaming Data in Under 5 Minutes - AWS Online Tec...Amazon Web Services
Learning Objectives:
- Identify common problems that streaming data can help solve
- Understand the AWS services that are used to solve these problems, including Amazon Kinesis
- Try out one of 5+ different solutions powered by Amazon Kinesis through AWS CloudFormation templates
Connecting the dots - How Amazon Neptune and Graph Databases can transform yo...Amazon Web Services
Amazon Neptune is the fully-managed graph database service that makes it easy to build and run applications for highly connected datasets. Come learn how to transform your business with Amazon Neptune and hear diverse use cases such as recommendation engines, knowledge graphs, fraud detection, social networks, network management and life sciences. Learn about using Amazon Neptune with Apache TinkerPop Gremlin traversals and RDF/SPARQL query processing and watch live how we derive valuable business insights, customer satisfaction by region, in a simple query.
Training your engineers and developers the right way can increase the pace of adoption, cloud migration, and the delivery of business benefits. In this session, we discuss proven steps for training your technical teams so you can use the AWS Cloud securely, efficiently, and effectively. We also review structural mechanisms to help scale your organization's capacity to operate a cloud-based IT environment.
Extracting Insights from Industrial Data Using AWS IoT Services (IOT368) - AW...Amazon Web Services
IoT (IIoT) bridges the gap between legacy industrial equipment and infrastructure and new technologies, such as machine learning, cloud, mobile, and edge computing. In this session, we focus on how you can extract data from your industrial data sources and build operational insights using AWS IoT services. We cover how to bridge traditional on-premises applications and data stores with new cloud-based IoT applications.
IoT Building Blocks: From Edge Devices to Analytics in the Cloud - SRV204 - A...Amazon Web Services
In this session, we explore the features and functions of AWS IoT services. We first cover AWS IoT fundamentals and our AWS Partner Network (APN) ecosystem. Then we discuss AWS IoT services in greater detail, review best practices for IoT solutions, and examine common architectural patterns. With this foundation in place, we explore a use case for IoT applications. You gain an understanding of how to start building IoT applications with AWS IoT.
NEW LAUNCH! AWS Serverless Application Repository - SRV215 - re:Invent 2017Amazon Web Services
In this session, we will discuss how the AWS Serverless Application Repository makes it easy to discover and deploy serverless applications published by fellow developers and companies like Datadog, Here, Splunk, and many others. We will cover how you can use the repository to find applications for a variety of use cases and then deploy them to your AWS account. In addition, we will discuss how you can publish your own applications to the repository. You will also hear from two contributors, Datadog and Here, who will describe their approach to building the serverless applications that they have published to the Serverless Application Repository.
Create an IoT Gateway and Establish a Data Pipeline to AWS IoT with Intel - I...Amazon Web Services
In this session, learn how to create a complete Gateway-based IoT framework – from the edge to the cloud and back. By using an IoT Gateway as a central data collection, processing, and communication hub, you can create IoT connectivity without having to replace legacy hardware. We show you how to use an Intel NUC gateway and Arduino 101 sensor hub to gather environmental data, and step you through establishing a data pipeline to AWS IoT. We use AWS Lambda to create a rules engine for your data, and then send a control signal back down the Intel Gateway. Bring your laptop and your AWS account for this workshop.
To win in the marketplace and provide differentiated customer experiences, businesses need to be able to use live data in real time to facilitate fast decision making. In this session, you learn common streaming data processing use cases and architectures. First, we give an overview of streaming data and AWS streaming data capabilities. Next, we look at a few customer examples and their real-time streaming applications. Finally, we walk through common architectures and design patterns of top streaming data use cases.
DynamoDB adaptive capacity: smooth performance for chaotic workloads - DAT327...Amazon Web Services
Database capacity planning is critical to running your business, but it’s also hard. In this session we’ll compare how scaling is usually performed for relational databases and NoSQL databases. We’ll look behind the scenes at how DynamoDB shards your data across multiple partitions and servers. Finally, we’ll talk about some of the recent enhancements to DynamoDB that make scaling even simpler, particularly a new feature called adaptive throughput that eliminates much of the throttling issues that you may have experienced.
Compute at the Edge with AWS Greengrass - IOT309 - re:Invent 2017Amazon Web Services
AWS Greengrass extends AWS onto your devices, so they can act locally on the data they generate while still taking advantage of the cloud. In this session, we discuss the features and development languages of AWS Greengrass that let you build powerful edge compute applications. You’ll also hear directly from Greengrass customers in multiple industries.
Cloud Adoption in Regulated Financial Services - SID328 - re:Invent 2017Amazon Web Services
Macquarie, a global provider of financial services, identified early on that it would require strong partnership between its business, technology and risk teams to enable the rapid adoption of AWS cloud technologies. As a result, Macquarie built a Cloud Governance Platform to enable its risk functions to move as quickly as its development teams. This platform has been the backbone of Macquarie’s adoption of AWS over the past two years and has enabled Macquarie to accelerate its use of cloud technologies for the benefit of clients across multiple global markets. This talk will outline the strategy that Macquarie embarked on, describe the platform they built, and provide examples for other organizations who are on a similar journey.
RET301-Build Single Customer View across Multiple Retail Channels using AWS S...Amazon Web Services
A challenge faced by many retailers is how to form an integrated single view of the customer across multiple retail channels to help you better understand purchasing behavior & patterns. In this session, we will present a solution that merges web analytics data with customer purchase history based on AWS API Gateway, Lambda and S3. Learn how to track customer purchase behaviors across different selling channels to better predict future needs and make relevant, intelligent recommendations.
NEW LAUNCH! Introduction to Amazon GuardDuty - SID218 - re:Invent 2017Amazon Web Services
Amazon GuardDuty is a managed threat detection service that continuously monitors for malicious or unauthorized behavior to help you protect your AWS accounts and workloads. It monitors for activity such as unusual API calls or potentially unauthorized deployments that indicate a possible account compromise. Enabled with a few clicks in the AWS Management Console, Amazon GuardDuty can immediately begin analyzing billions of events across your AWS accounts for signs of risk. It does not require you to deploy and maintain software or security infrastructure, meaning it can be enabled quickly with no risk of negatively impacting existing application workloads.
Introduction to Real-Time Streaming Analytics - Amazon Kinesis State Of Union...Amazon Web Services
Serverless streaming applications Lambda+Kinesis Data Analytics/Kinesis Data Firehose - how to solve common streaming problems using serverless architecture and learn how customers like GE, Comcast, Lyft and more are using Amazon Kinesis.
Analyzing Streaming Data in Real-time with Amazon KinesisAmazon Web Services
As more and more organizations strive to gain real-time insights into their business, streaming data has become ubiquitous. Typical streaming data analytics solutions require specific skills and complex infrastructure. However, with Amazon Kinesis Analytics, you can analyze streaming data in real-time with standard SQL—there is no need to learn new programming languages or processing frameworks.
In this session, we dive deep into the capabilities of Amazon Kinesis Analytics using real-world examples. We’ll present an end-to-end streaming data solution using Amazon Kinesis Streams for data ingestion, Amazon Kinesis Analytics for real-time processing, and Amazon Kinesis Firehose for persistence. We review in detail how to write SQL queries using streaming data and discuss best practices to optimize and monitor your Amazon Kinesis Analytics applications. Lastly, we discuss how to estimate the cost of the entire system.
WPS301-Navigating HIPAA and HITRUST_QuickStart Guide to Account Gov Strat.pdfAmazon Web Services
Join AWS in examining governance and compliance designs aimed at helping organizations meet HIPAA and HITRUST standards. Learn how to better validate and document your compliance, expedite access to AWS compliance accelerators, and discover new ways to use AWS native features to monitor and control your accounts. This session is for a technical audience seeking to dive deep into the AWS service offerings, console, and API.
Best Practices for AWS IoT Core (IOT347-R1) - AWS re:Invent 2018Amazon Web Services
There are many different components of AWS IoT Core, including Device gateway, Registry, Message broker, Rules engine, and Device shadow. In this session, we cover each component in depth, how to use them, and best practices. Come away with an understanding of how AWS IoT Core can help you securely connect and manage devices, process and act on device data, and read and set device state. In addition to best practices, we discuss common customer questions when using different features of AWS IoT Core.
HLC310-How Methodist Le Bonheur Healthcare's Focus on Standardizing Compliant...Amazon Web Services
The innovation team at Methodist Le Bonheur Healthcare (MLH), an integrated health care delivery system, saw AWS as an enabler to faster ideation on breakthrough patient care products over their existing internal private cloud options. In this session, you learn how they eliminated HIPAA compliance as a barrier to their speed-to-market goals by standardizing internal DevOps and DevSecOps duties across applications, as well as taking advantage of the containerization of enterprise technology. MLH partnered with Datica, an APN Healthcare Competency Partner, to address vulnerability scanning, intrusion detection, disaster recovery, backups, encryption, audit logging, and deployment orchestration. You hear how, with this partnership, they ensure that the configuration and orchestration of all AWS HIPAA Eligible Services meet the controls set by healthcare's most stringent accreditation body, HITRUST, with every workload deployment. You also learn how MLH's adoption of a standard compliance layer led to quickly achieving stronger data integration with electronic health records.
Get Started with Real-Time Streaming Data in Under 5 Minutes - AWS Online Tec...Amazon Web Services
Learning Objectives:
- Identify common problems that streaming data can help solve
- Understand the AWS services that are used to solve these problems, including Amazon Kinesis
- Try out one of 5+ different solutions powered by Amazon Kinesis through AWS CloudFormation templates
Connecting the dots - How Amazon Neptune and Graph Databases can transform yo...Amazon Web Services
Amazon Neptune is the fully-managed graph database service that makes it easy to build and run applications for highly connected datasets. Come learn how to transform your business with Amazon Neptune and hear diverse use cases such as recommendation engines, knowledge graphs, fraud detection, social networks, network management and life sciences. Learn about using Amazon Neptune with Apache TinkerPop Gremlin traversals and RDF/SPARQL query processing and watch live how we derive valuable business insights, customer satisfaction by region, in a simple query.
Training your engineers and developers the right way can increase the pace of adoption, cloud migration, and the delivery of business benefits. In this session, we discuss proven steps for training your technical teams so you can use the AWS Cloud securely, efficiently, and effectively. We also review structural mechanisms to help scale your organization's capacity to operate a cloud-based IT environment.
Extracting Insights from Industrial Data Using AWS IoT Services (IOT368) - AW...Amazon Web Services
IoT (IIoT) bridges the gap between legacy industrial equipment and infrastructure and new technologies, such as machine learning, cloud, mobile, and edge computing. In this session, we focus on how you can extract data from your industrial data sources and build operational insights using AWS IoT services. We cover how to bridge traditional on-premises applications and data stores with new cloud-based IoT applications.
IoT Building Blocks: From Edge Devices to Analytics in the Cloud - SRV204 - A...Amazon Web Services
In this session, we explore the features and functions of AWS IoT services. We first cover AWS IoT fundamentals and our AWS Partner Network (APN) ecosystem. Then we discuss AWS IoT services in greater detail, review best practices for IoT solutions, and examine common architectural patterns. With this foundation in place, we explore a use case for IoT applications. You gain an understanding of how to start building IoT applications with AWS IoT.
IoT Building Blocks: From Edge Devices to Analytics in the Cloud - SRV204 - A...Amazon Web Services
In this session, we explore features and functions of AWS IoT services. First we will cover AWS IoT fundamentals, review best practices for IoT solutions, and look at some common architectural patterns. Then we will dive deep into AWS IoT Analytics. We will explain how AWS IoT Analytics runs sophisticated analytics on massive volumes of IoT data and helps operationalize analyses without requiring you to build an IoT analytics platform from the ground up. You will hear from TensorIoT, an AWS IoT Analytics partner, about how they are using AWS IoT Analytics. Leave this session with an understanding of how to start building IoT applications with AWS IoT.
AWS IoT services provide a managed cloud platform that lets connected devices interact with cloud applications and other devices easily and securely. In this session, we will discuss how constrained devices can leverage AWS IoT Core to send data to the cloud and receive commands back to the device using the protocol of their choice. AWS Greengrass is software that lets you run local compute, messaging and data caching for connected devices in a secure way. AWS IoT Device Management is a service that makes it easy to securely onboard, organize, monitor, and remotely manage IoT devices at scale. With AWS IoT Analytics, you can run sophisticated analytics on massive volumes of IoT data without having to worry about the cost and complexity typically required to build your own IoT analytics platform.
How to use AWS IoT Analytics to unlock the value from IoT dataAmazon Web Services
Level: Intermediate
If you could solve real-world problems with IoT data, what would you tackle first?
To answer this question, we'll show you how to use AWS IoT Analytics to analyse massive volumes of IoT data without having to worry about the cost and complexity of building your own IoT analytics platform. The solution makes it easy to run analytics and derive insights from IoT data that will help you make better, more accurate decisions on IoT applications and machine learning use cases, for example, predictive maintenance.
Who Should Attend: Developers, Coders, Engineers, System Administrators, IT Managers, Solutions Architects and Product Heads.
In this workshop, you learn about the different components of AWS IoT Analytics. You have the opportunity to configure AWS IoT Analytics to ingest data from AWS IoT Core, enrich the data using AWS Lambda, visualize the data using Amazon QuickSight, and perform machine learning using Jupyter Notebooks. Join us, and build a solution that helps you perform analytics on appliance energy usage in a smart building and forecast energy utilization to optimize consumption.
본 실습은 AWS IoT Edge 구성 요소인 AWS IoT Greengrass를 이용하여 산업 현장에서 활용되는 표준 통신 프로토콜(OPC-UA)을 AWS IoT 호환 프로토콜로 변환 전처리하는 과정을 실습합니다. 이렇게 수집된 데이터는 AWS IoT Analytics 을 통해 분석 및 BI에 활용될 수 있으며, 본 실습에서는 Amazon Sage Maker를 활용하여 예지 정비 모델을 작성 및 배포하고, 추가적으로 Amazon QuickSight를 통한 시각화 구현을 목표로 합니다.
Understand the State of Your Connected Devices (IOT367) - AWS re:Invent 2018Amazon Web Services
In this session, we discuss the different ways to understand the state of your operations, how to use AWS IoT services, and how to take appropriate action using AWS IoT services, like the AWS IoT Rules Engine, to improve operational efficiency.
AWS IoT Events is a new IoT-managed service that allows enterprises with large operations dependent on IoT devices to continuously monitor data from their equipment, applications, and fleets of devices for changes in operation and trigger the appropriate response when events occur. IoT Events monitors inputs from many IoT sensors and applications simultaneously; it can also combine sensor and application data with analytical results, including machine learning from AWS IoT Analytics. It helps customers reduce costs through efficiency gains, minimize downtime, and improve product quality. IoT Events is applicable to several industries, including device manufacturers, manufacturing plants, power and utilities, shipping, oil and gas, etc. Join us for this session to learn more about the customer benefits of IoT Events, and catch a demo of IoT Events in action.
AWS Simple Workflow: Distributed Out of the Box! - Morning@LohikaSerhiy Batyuk
Do you have a lot of complex jobs that you need to run as part of your application? Do they consist of multiple tasks and you wonder how to orchestrate them properly? Do you want to be able to easily scale their execution? Is availability of your workers important to you? If you answer “Yes” to these questions then AWS Simple Workflow is the right tool for you.
In this talk we will go through Amazon SWF and Java Flow Framework and you will see how to get a distributed job execution engine right out of the box. We will also compare SWF to alternative solutions, discuss real life experience, and of course enjoy a live demo.
The talk will be most useful to everyone who is interested in the design of distributed systems and is new to AWS SWF.
The IoT Offering Explained in Plain English - IOT201 - re:Invent 2017Amazon Web Services
This session can help you better understand how to leverage different AWS services to build an IoT application. Learn the value of each AWS service in the Internet of Things (IoT) category, as we go through different use cases that demonstrate how the services are better together. NASA/JPL illustrate those concepts by discussing the inner workings of a demonstration they’ve built. They also talk about how they use IoT to overcome their technical challenges.
ABD218_How Euroleague Basketball Uses IoT Analytics to Engage Fans- ABD218Amazon Web Services
IoT and big data have made their way out of industrial applications, general automation, and consumer goods, and are now a valuable tool for improving consumer engagement across a number of industries, including media, entertainment, and sports. The low cost and ease of implementation of AWS analytics services and AWS IoT have allowed AGT, a leader in IoT, to develop their IoTA analytics platform. Using IoTA, AGT brought a tailored solution to EuroLeague Basketball for real-time content production and fan engagement during the 2017-18 season. In this session, we take a deep dive into how this solution is architected for secure, scalable, and highly performant data collection from athletes, coaches, and fans. We also talk about how the data is transformed into insights and integrated into a content generation pipeline. Lastly, we demonstrate how this solution can be easily adapted for other industries and applications.
IoT Tutorial for Beginners | Internet of Things (IoT) | IoT Training | IoT Te...Edureka!
This "IoT Tutorial For Beginners" by Edureka will help you grasp the basic concepts of Internet of Things & explains, how IoT is trying to revolutionize the world. This IoT tutorial helps you learn following topics:
1. What is Internet of Things
2. Why do we need Internet of Things
3. Benefits of Internet of Things
4. IoT features
5. IoT Demo - Weather Station application using Raspberry Pi and Sense Hat
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#Whatisiot #iot #iottutorial #internetofthings #iotonlinetraining #iotforbeginners
For more information, please write back to us at sales@edureka.co
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Artificial Intelligence is the hot tech paradigm of the moment. It is the subject of a great deal of media hype, woes and mythologising. It seems worthwhile, therefore, to try to set the scene, look at some definitions, and see where it is currently being applied.
(APP203) How Sumo Logic and Anki Build Highly Resilient Services on AWS to Ma...Amazon Web Services
In just two years, Sumo Logic's multitenant log analytics service has scaled to query over 10 trillion more logs each day. Christian, Sumo Logic's cofounder and CTO shares the three most important lessons he has learned in building such a massive service on AWS. Ben Whaley is an AWS Community Hero who works for Anki as an AWS cloud architect. Ben uses hundreds of millions of logs to troubleshoot and improve Anki Drive, the coolest battle robot racing game on the planet. This is an ideal session for cloud architects constantly looking to improve scalability and application performance on AWS.
Sponsored by Sumo Logic.
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.
1. IoT State of Union
Ivan Cheng (鄭志帆) - AWS Solutions Architect
January 2018
2. If you knew the state of every thing and
could reason on top of that data…
what problems would you solve?
If you knew the state of every thing and
could reason on top of that data…
what problems would you solve?