"As a fully managed database service, Amazon DynamoDB is a natural fit for serverless architectures. In this session, we dive deep into why and how to use DynamoDB in serverless applications, followed by a real-world use case from CapitalOne.
First, we dive into the relevant DynamoDB features, and how you can use it effectively with AWS Lambda in solutions ranging from web applications to real-time data processing. We show how some of the new features in DynamoDB, such as Auto Scaling and Time to Live (TTL), are particularly useful in serverless architectures, and distill the best practices to help you create effective serverless applications. In the second part, we talk about how CapitalOne migrated billions of transactions to a completely serverless architecture and built a scalable, resilient and fast transaction platform by leveraging DynamoDB, AWS Lambda and other services within the serverless ecosystem."
Companies, from startups to enterprises across the globe, are looking to migrate data warehousing to the cloud to increase performance and lower costs. Data engineers, data analysts, and developers also need to access and consume this important data. The landscape is constantly evolving and there are many solutions available for enterprises of all sizes. In this workshop, we dive deep into architectural patterns, use cases, and best practices when designing an enterprise data warehouse in the cloud. We also address key issues such as data governance and democratization. At the end of this workshop, you’ll be equipped to design and implement a cloud enterprise data warehouse platform that provides the most benefit for your enterprise, data consumers, and customers.
GAM310_Build a Telemetry and Analytics Pipeline for Game BalancingAmazon Web Services
In this workshop, we will together build telemetry/analytics data processing pipelines to assist game developers/architects, designers and producers. We will use a fictitious RPG and ingest data from in-game events. We will then analyze the data to help with game balancing, troubleshooting and other relevant recommendations for game developers and designers. As a participant, you will use Amazon Kinesis, Amazon Kinesis Firehose, Amazon Analytics, Amazon EMR, Amazon Redshift, Amazon S3, Amazon Athena and Amazon QuickSight. Prerequisites include having your own laptop and an interest in big data services, game data processing & analytics.
In order to make your time in the workshop as productive as possible, please make sure to check out the additional information below.
AWS account: Fully functional AWS Account with administrative access. Participant should have the ability to create & destroy resources in the us-west-2 and eu-west-1 regions via API, CLI & AWS Console.
Device/OS: A laptop computer – running Mac OS X, a Linux flavor or Windows. The computer will need a functional ssh/Remote Desktop client.
AWS service familiarity/experience:Familiarity/Experience with EC2, S3 & the AWS Console will be good. For the rest of the services, we will introduce each during the workshop.
Audience: Game Developers (server programmers), Architects, Game Producers/Designers, Game Marketing/Analytics team – hands-on members
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."
BAP202_Amazon Connect Delivers Personalized Customer Experiences for Your Clo...Amazon Web Services
Join us for an overview and demonstration of Amazon Connect, a self-service, cloud-based contact center based on the same technology used by Amazon customer service associates worldwide to power millions of conversations. The self-service graphical interface in Amazon Connect makes it easy to design contact flows for self and assisted call-handling experiences, manage agents, and track performance metrics – no specialized skills required. In this session, you will hear from Capital One and T-Mobile on how they are using Amazon Connect to provide their customers with dynamic, natural, and personalized experiences. See how quickly you can get started with Amazon Connect and build your contact center.
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 Distributed Machine Learning and Predictive Analytics Usin...Amazon Web Services
This session, we focus on common use cases and design patterns for predictive analytics using Amazon EMR. We address accessing data from a data lake, extraction and preprocessing with Apache Spark, analytics and machine learning code development with notebooks (Jupyter, Zeppelin), and data visualization using Amazon QuickSight. We cover other operational topics, such as deployment patterns for ad hoc exploration and batch workloads using Spot and multi-user notebooks. The intended audience for this session includes technical users who are building statistical and data analytics models for the business using tools, such as Python, R, Spark, Presto, Amazon EMR, Notebooks.
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).
Companies, from startups to enterprises across the globe, are looking to migrate data warehousing to the cloud to increase performance and lower costs. Data engineers, data analysts, and developers also need to access and consume this important data. The landscape is constantly evolving and there are many solutions available for enterprises of all sizes. In this workshop, we dive deep into architectural patterns, use cases, and best practices when designing an enterprise data warehouse in the cloud. We also address key issues such as data governance and democratization. At the end of this workshop, you’ll be equipped to design and implement a cloud enterprise data warehouse platform that provides the most benefit for your enterprise, data consumers, and customers.
GAM310_Build a Telemetry and Analytics Pipeline for Game BalancingAmazon Web Services
In this workshop, we will together build telemetry/analytics data processing pipelines to assist game developers/architects, designers and producers. We will use a fictitious RPG and ingest data from in-game events. We will then analyze the data to help with game balancing, troubleshooting and other relevant recommendations for game developers and designers. As a participant, you will use Amazon Kinesis, Amazon Kinesis Firehose, Amazon Analytics, Amazon EMR, Amazon Redshift, Amazon S3, Amazon Athena and Amazon QuickSight. Prerequisites include having your own laptop and an interest in big data services, game data processing & analytics.
In order to make your time in the workshop as productive as possible, please make sure to check out the additional information below.
AWS account: Fully functional AWS Account with administrative access. Participant should have the ability to create & destroy resources in the us-west-2 and eu-west-1 regions via API, CLI & AWS Console.
Device/OS: A laptop computer – running Mac OS X, a Linux flavor or Windows. The computer will need a functional ssh/Remote Desktop client.
AWS service familiarity/experience:Familiarity/Experience with EC2, S3 & the AWS Console will be good. For the rest of the services, we will introduce each during the workshop.
Audience: Game Developers (server programmers), Architects, Game Producers/Designers, Game Marketing/Analytics team – hands-on members
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."
BAP202_Amazon Connect Delivers Personalized Customer Experiences for Your Clo...Amazon Web Services
Join us for an overview and demonstration of Amazon Connect, a self-service, cloud-based contact center based on the same technology used by Amazon customer service associates worldwide to power millions of conversations. The self-service graphical interface in Amazon Connect makes it easy to design contact flows for self and assisted call-handling experiences, manage agents, and track performance metrics – no specialized skills required. In this session, you will hear from Capital One and T-Mobile on how they are using Amazon Connect to provide their customers with dynamic, natural, and personalized experiences. See how quickly you can get started with Amazon Connect and build your contact center.
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 Distributed Machine Learning and Predictive Analytics Usin...Amazon Web Services
This session, we focus on common use cases and design patterns for predictive analytics using Amazon EMR. We address accessing data from a data lake, extraction and preprocessing with Apache Spark, analytics and machine learning code development with notebooks (Jupyter, Zeppelin), and data visualization using Amazon QuickSight. We cover other operational topics, such as deployment patterns for ad hoc exploration and batch workloads using Spot and multi-user notebooks. The intended audience for this session includes technical users who are building statistical and data analytics models for the business using tools, such as Python, R, Spark, Presto, Amazon EMR, Notebooks.
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).
FSV307-Capital Markets Discovery How FINRA Runs Trade Analytics and Surveilla...Amazon Web Services
FINRA’s analytics platform unlocks the value in capital markets data by accelerating trade analytics and providing a foundation for machine learning at scale. The platform enables FINRA’s analysts to perform discovery on petabytes of trade data to identify instances of potential fraud, market manipulation, and insider trading. By centralizing all data in S3, FINRA’s architecture offers improved agility, scalability, and cost effectiveness. Analytics services such as Amazon EMR and Amazon Redshift have freed FINRA’s data scientists from the constraints of desktop tools, allowing them to apply machine learning techniques to develop and test new surveillance patterns. All of this is done while meeting FINRA’s security and compliance responsibilities as a financial regulator. At the end of this session, you’ll have an understanding of how to apply FINRA’s architecture to trade analytics and other financial services use cases, including meeting regulatory requirements such as the Consolidated Audit Trail (CAT) reporting.
STG314-Case Study Learn How HERE Uses JFrog Artifactory w Amazon EFS Support ...Amazon Web Services
HERE Technologies enables people, enterprises, and cities around the world to harness the power of location. In this session, you learn how HERE uses JFrog Artifactory with Amazon EFS to deliver close to a million downloads and uploads per day to its CI/CD environment. We walk you through HERE’s AWS process for handling development at scale, and we discuss lessons learned and best practices for success throughout.
Come see first-hand how Amazon EC2 Systems Manager can help you manage your servers at scale with the agility and security you need in today's dynamic cloud-enabled world. To be truly agile, you need a way to define and track system configurations, prevent drift, and maintain software compliance. At the same time, you need to collect software inventory, apply OS patches, automate your system image maintenance, and configure anything in the OSs of your EC2 instances and on-premises servers. Amazon EC2 Systems Manager does all of that and more for both Linux and Windows systems. In this session, learn about the seven services that make up Amazon EC2 Systems Manager and see them in action. No matter if you are managing 10 or 10,000 instances, see how you can manage your systems, increasing your agility and security with EC2 Systems Manager.
GPSBUS221_Breaking Barriers Move Enterprise SAP Customers to SAP HANA on AWS ...Amazon Web Services
Migrating mission-critical SAP workloads to AWS allows enterprises to realize business benefits quickly and securely without a significant upfront investment. Today, customers are turning capital expense into operating expense at a record pace and are accelerating business processes and efficiency for less than the cost of a week at a beach resort. Learn how other SAP customers are removing risk and testing their SAP migrations and upgrades for low cost to jumpstart their SAP projects for low cost.
This session is especially tailored for technology and consulting partners, looking to learn more about big data and analytics on AWS. As individuals and commerce move online, companies have unprecedented access to data to improve customer experience and take advantage of new market opportunities. However, organizations often struggle with turning data into actionable insights to drive their business. Learn how AWS and big data APN partners are helping companies enable a broad range of analytic capabilities, to deliver better business results and better serve their customers. We discuss key big data and analytics use cases, and programs to enable partners to get to market with these solutions.
CMP216_Use Amazon EC2 Spot Instances to Deploy a Deep Learning Framework on A...Amazon Web Services
Deep learning, an implementation of machine learning, uses neural networks to solve complex problems like computer vision, natural language processing, and recommendations. Deep learning libraries and frameworks enable developers to enhance the capabilities of their applications and projects. In this workshop, learn how to build and deploy a powerful deep learning framework, Apache MXNet, on containers. The portability and resource management benefit of containers enables developers to focus less on infrastructure and more on building. The lab first demonstrates the automation capabilities of AWS CloudFormation to stand up core infrastructure. We also leverage Spot Fleet for the cost benefit of using Spot Instances, especially important for developer environments. Next we create an MXNet container in Docker and deploy it with Amazon ECS. Finally, we explore image classification with MXNet to validate that everything is working as expected.
LFS301-SAGE Bionetworks, Digital Mammography DREAM Challenge and How AWS Enab...Amazon Web Services
DREAM Challenges pose fundamental questions about systems biology and translational medicine. Designed and run by a community of researchers from a variety of organizations, the challenges invite participants to propose solutions, fostering collaboration and building communities in the process. The Sage Bionetworks Synapse platform, which powers many research consortiums including the DREAM Challenges, are starting to put into practice model cloud-initiatives that not only provide impactful discoveries in the areas of neuroscience, infectious disease, and cancer, but are also revolutionizing scientific research by enabling an interactive consortium science platform. In this session, you learn how to build a "consortium model" of research in order to connect research organizations with non-profit organizations, technology companies, biotechnology, and pharmaceutical companies. You can also learn about how to leverage machine learning, Amazon ECS, and R for consortium-based science initiatives.
AMF302-Alexa Wheres My Car A Test Drive of the AWS Connected Car Reference.pdfAmazon Web Services
Today's trends in auto technology are all about connecting cars and their occupants to the outside world in a seamless and safe manner. In this session, we discuss how automotive companies are leveraging AWS for a variety of connected vehicle use cases. You'll leave this session with source code, architecture diagrams, and an understanding of how to apply the AWS Connected Vehicle Reference Architecture to build your own prototypes. You'll also learn how car companies can leverage Amazon services such as Alexa and AWS services such as AWS IOT, AWS Greengrass, AWS Lambda and Amazon API Gateway to rapidly develop and deploy innovative connected vehicle services.
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.
AMF303-Deep Dive into the Connected Vehicle Reference Architecture.pdfAmazon Web Services
At this fast-paced, interactive workshop, get hands-on with live data streaming from an actual car driving the streets of Las Vegas. Explore AWS IoT, common patterns, and best practices for processing IoT data, and deploy a reference architecture to begin consuming and analyzing connected vehicle data in your own AWS account. Walk away from this workshop with the knowledge needed to connect your own vehicle to the cloud.
Migrating Your Databases to AWS – Tools and Services (Level 100)Amazon Web Services
In this webinar, you will learn how the AWS Database Migration Service (DMS) and AWS Schema Conversion Tool (SCT) can help migrate your databases to AWS for homogeneous and heterogeneous migrations. We will also discuss new sources and targets, together with new features that make DMS and SCT a powerful combination for both your database migration and data replication requirements.
Speaker: Blair Layton, APAC Business Development, Database, AWS APAC
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.
Build a Website & Mobile App for your first 10 million usersAmazon Web Services
Understand how businesses around the world are running the infrastructure that supports their websites to lower costs, improve time-to-market, and enable rapid scalability matching resource to demands of users.
And learn practical step-by-step solutions on how to deliver a website and mobile app for your first 10 million users. With the basics of AWS platform of availability zones, regions & edge locations.
We will be sharing the components of a web app such as web server, app server, database, components, application compute, database engine, storage and delivery.
Learn how customers like Netflix, DBS and Banyan Tree scale their business on AWS.
If you're in South East Asia join us for upcoming AWS Webinar Series https://aws.amazon.com/events/asean/webinars/
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.
by Rohan Dubal, Software Development Engineer, AWS
One of the biggest time sinks and challenges for mobile application developers is developing, accessing, and managing all of the disparate data sources that are involved in delivering delightful, collaborative, and real-time mobile experiences for users while also enabling offline capabilities for when a user is not connected, but still wants to use the app. In this session, you be introduced to the new AWS AppSync service that speed and simplifies these tasks for developers using GraphQL to provide a data abstraction layer and easy query and update statements without having to know the details of the underlying data sources.
Serverless Architectural Patterns and Best Practices - Madhu Shekar - AWSCodeOps Technologies LLP
This presentation was made by Madhusudan Shekar (Principal Evangelist) at AWS - on 9th June 2018 in Bridgei2i Analytics, Bangalore as part of Cloud Native meetup.
FSV307-Capital Markets Discovery How FINRA Runs Trade Analytics and Surveilla...Amazon Web Services
FINRA’s analytics platform unlocks the value in capital markets data by accelerating trade analytics and providing a foundation for machine learning at scale. The platform enables FINRA’s analysts to perform discovery on petabytes of trade data to identify instances of potential fraud, market manipulation, and insider trading. By centralizing all data in S3, FINRA’s architecture offers improved agility, scalability, and cost effectiveness. Analytics services such as Amazon EMR and Amazon Redshift have freed FINRA’s data scientists from the constraints of desktop tools, allowing them to apply machine learning techniques to develop and test new surveillance patterns. All of this is done while meeting FINRA’s security and compliance responsibilities as a financial regulator. At the end of this session, you’ll have an understanding of how to apply FINRA’s architecture to trade analytics and other financial services use cases, including meeting regulatory requirements such as the Consolidated Audit Trail (CAT) reporting.
STG314-Case Study Learn How HERE Uses JFrog Artifactory w Amazon EFS Support ...Amazon Web Services
HERE Technologies enables people, enterprises, and cities around the world to harness the power of location. In this session, you learn how HERE uses JFrog Artifactory with Amazon EFS to deliver close to a million downloads and uploads per day to its CI/CD environment. We walk you through HERE’s AWS process for handling development at scale, and we discuss lessons learned and best practices for success throughout.
Come see first-hand how Amazon EC2 Systems Manager can help you manage your servers at scale with the agility and security you need in today's dynamic cloud-enabled world. To be truly agile, you need a way to define and track system configurations, prevent drift, and maintain software compliance. At the same time, you need to collect software inventory, apply OS patches, automate your system image maintenance, and configure anything in the OSs of your EC2 instances and on-premises servers. Amazon EC2 Systems Manager does all of that and more for both Linux and Windows systems. In this session, learn about the seven services that make up Amazon EC2 Systems Manager and see them in action. No matter if you are managing 10 or 10,000 instances, see how you can manage your systems, increasing your agility and security with EC2 Systems Manager.
GPSBUS221_Breaking Barriers Move Enterprise SAP Customers to SAP HANA on AWS ...Amazon Web Services
Migrating mission-critical SAP workloads to AWS allows enterprises to realize business benefits quickly and securely without a significant upfront investment. Today, customers are turning capital expense into operating expense at a record pace and are accelerating business processes and efficiency for less than the cost of a week at a beach resort. Learn how other SAP customers are removing risk and testing their SAP migrations and upgrades for low cost to jumpstart their SAP projects for low cost.
This session is especially tailored for technology and consulting partners, looking to learn more about big data and analytics on AWS. As individuals and commerce move online, companies have unprecedented access to data to improve customer experience and take advantage of new market opportunities. However, organizations often struggle with turning data into actionable insights to drive their business. Learn how AWS and big data APN partners are helping companies enable a broad range of analytic capabilities, to deliver better business results and better serve their customers. We discuss key big data and analytics use cases, and programs to enable partners to get to market with these solutions.
CMP216_Use Amazon EC2 Spot Instances to Deploy a Deep Learning Framework on A...Amazon Web Services
Deep learning, an implementation of machine learning, uses neural networks to solve complex problems like computer vision, natural language processing, and recommendations. Deep learning libraries and frameworks enable developers to enhance the capabilities of their applications and projects. In this workshop, learn how to build and deploy a powerful deep learning framework, Apache MXNet, on containers. The portability and resource management benefit of containers enables developers to focus less on infrastructure and more on building. The lab first demonstrates the automation capabilities of AWS CloudFormation to stand up core infrastructure. We also leverage Spot Fleet for the cost benefit of using Spot Instances, especially important for developer environments. Next we create an MXNet container in Docker and deploy it with Amazon ECS. Finally, we explore image classification with MXNet to validate that everything is working as expected.
LFS301-SAGE Bionetworks, Digital Mammography DREAM Challenge and How AWS Enab...Amazon Web Services
DREAM Challenges pose fundamental questions about systems biology and translational medicine. Designed and run by a community of researchers from a variety of organizations, the challenges invite participants to propose solutions, fostering collaboration and building communities in the process. The Sage Bionetworks Synapse platform, which powers many research consortiums including the DREAM Challenges, are starting to put into practice model cloud-initiatives that not only provide impactful discoveries in the areas of neuroscience, infectious disease, and cancer, but are also revolutionizing scientific research by enabling an interactive consortium science platform. In this session, you learn how to build a "consortium model" of research in order to connect research organizations with non-profit organizations, technology companies, biotechnology, and pharmaceutical companies. You can also learn about how to leverage machine learning, Amazon ECS, and R for consortium-based science initiatives.
AMF302-Alexa Wheres My Car A Test Drive of the AWS Connected Car Reference.pdfAmazon Web Services
Today's trends in auto technology are all about connecting cars and their occupants to the outside world in a seamless and safe manner. In this session, we discuss how automotive companies are leveraging AWS for a variety of connected vehicle use cases. You'll leave this session with source code, architecture diagrams, and an understanding of how to apply the AWS Connected Vehicle Reference Architecture to build your own prototypes. You'll also learn how car companies can leverage Amazon services such as Alexa and AWS services such as AWS IOT, AWS Greengrass, AWS Lambda and Amazon API Gateway to rapidly develop and deploy innovative connected vehicle services.
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.
AMF303-Deep Dive into the Connected Vehicle Reference Architecture.pdfAmazon Web Services
At this fast-paced, interactive workshop, get hands-on with live data streaming from an actual car driving the streets of Las Vegas. Explore AWS IoT, common patterns, and best practices for processing IoT data, and deploy a reference architecture to begin consuming and analyzing connected vehicle data in your own AWS account. Walk away from this workshop with the knowledge needed to connect your own vehicle to the cloud.
Migrating Your Databases to AWS – Tools and Services (Level 100)Amazon Web Services
In this webinar, you will learn how the AWS Database Migration Service (DMS) and AWS Schema Conversion Tool (SCT) can help migrate your databases to AWS for homogeneous and heterogeneous migrations. We will also discuss new sources and targets, together with new features that make DMS and SCT a powerful combination for both your database migration and data replication requirements.
Speaker: Blair Layton, APAC Business Development, Database, AWS APAC
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.
Build a Website & Mobile App for your first 10 million usersAmazon Web Services
Understand how businesses around the world are running the infrastructure that supports their websites to lower costs, improve time-to-market, and enable rapid scalability matching resource to demands of users.
And learn practical step-by-step solutions on how to deliver a website and mobile app for your first 10 million users. With the basics of AWS platform of availability zones, regions & edge locations.
We will be sharing the components of a web app such as web server, app server, database, components, application compute, database engine, storage and delivery.
Learn how customers like Netflix, DBS and Banyan Tree scale their business on AWS.
If you're in South East Asia join us for upcoming AWS Webinar Series https://aws.amazon.com/events/asean/webinars/
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.
by Rohan Dubal, Software Development Engineer, AWS
One of the biggest time sinks and challenges for mobile application developers is developing, accessing, and managing all of the disparate data sources that are involved in delivering delightful, collaborative, and real-time mobile experiences for users while also enabling offline capabilities for when a user is not connected, but still wants to use the app. In this session, you be introduced to the new AWS AppSync service that speed and simplifies these tasks for developers using GraphQL to provide a data abstraction layer and easy query and update statements without having to know the details of the underlying data sources.
Serverless Architectural Patterns and Best Practices - Madhu Shekar - AWSCodeOps Technologies LLP
This presentation was made by Madhusudan Shekar (Principal Evangelist) at AWS - on 9th June 2018 in Bridgei2i Analytics, Bangalore as part of Cloud Native meetup.
by Brent Rabowsky, Solutions Architect & Itzik Paz, Solutions Architect, AWS
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).
AWS Application Service Workshop - Serverless ArchitectureJohn Yeung
Demonstrate how severless architecture can benefits enterprise to build API platforms, using Lambda, DynamoDB and API Gateway etc. Real-life use cases are also included.
Leadership Session: Using DevOps, Microservices, and Serverless to Accelerate...Amazon Web Services
In this session, learn how AWS can help you innovate faster with DevOps, microservices, and serverless. Join us for a rare and intimate discussion with AWS senior leaders: David Richardson, VP of Serverless, Ken Exner, director of AWS Developer Tools, and Deepak Singh, director of Compute Services, Containers, and Linux. Hear them share development best practices and discuss key learnings from building modern applications at Amazon.com. Also, learn how developers can leverage containers, AWS Lambda, and developer tools to build and run production applications in the cloud.
Building Serverless Microservices with AWSDonnie Prakoso
Microservices architectures make applications easier to scale and faster to develop, enabling innovation and accelerating time-to-market for new features.
For those who are building microservices, this deck provides you a guideline on what AWS services you can use to build microservices, starting from development, deployment tools to coordination.
Getting Started with Serverless Computing Using AWS Lambda - ENT332 - re:Inve...Amazon Web Services
With serverless computing, you can build and run applications without the need for provisioning or managing servers. Serverless computing means that you can build web, mobile, and IoT backends, run stream processing or big data workloads, run chatbots, and more. In this session, learn how to get started with serverless computing with AWS Lambda, which lets you run code without provisioning or managing servers. We introduce you to the basics of building with Lambda. As part of that, we show how you can benefit from features such as continuous scaling, built-in high availability, integrations with AWS and third-party apps, and subsecond metering pricing. We also introduce you to the broader portfolio of AWS services that help you build serverless applications with Lambda, including Amazon API Gateway, Amazon DynamoDB, AWS Step Functions, and more.
Building Serverless Enterprise Applications - SRV315 - Anaheim AWS SummitAmazon Web Services
In this session, learn how to design, develop, deliver, and monitor enterprise applications as they take advantage of the AWS serverless platform and developer toolset. We discuss the common serverless patterns that enterprises use, and we explain how to implement the operational and security features that are used by large and mature organizations.
RET304_Rapidly Respond to Demanding Retail Customers with the Same Serverless...Amazon Web Services
Today’s retail customers want to set the rules on how and when they buy, receive, and return their product. But many retailers are struggling to unify their sales channels using existing legacy e-commerce software stacks. To consistently serve customers across retail channels, retailers must adopt a modern architecture that is elastic, cost effective, and based on loosely coupled application services. In this session, we dive deep into how retailers can leverage serverless architectures using Amazon API Gateway, AWS Lambda, and Amazon DynamoDB. Learn how Amazon Fresh quickly responded to customer feedback on the Totes Pickup feature, developing a cost-effective and scalable self-service serverless application to deliver a 1-click experience for the customer, while providing faster insights back to the business.
Build Enterprise-Grade Serverless Apps - SRV315 - Atlanta AWS SummitAmazon Web Services
In this session, we explore how developers can design, develop, deliver, and monitor cloud applications as they take advantage of the AWS serverless platform and developer toolset. We discuss common serverless patterns used by enterprises, and we dive into the operational and security features used by large and mature organizations.
Streaming data ingestion and near real-time analysis gives you immediate insights into your data. By using AWS Lambda with Amazon Kinesis, you can obtain these insights without the need to manage servers. But are you doing this in the most optimal way? In this interactive session, we review the best practices for using Lambda with Kinesis, and how to avoid common pitfalls.
Similar to SRV301-Optimizing Serverless Application Data Tiers with Amazon DynamoDB (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.
27. Time Series Data Example
sensor_data
SensorId: 123
Timestamp: 1492641900
Temp: 172
AWS Lambda
Amazon Kinesis
Stream
• Sensor data (temp) from 1000’s of
sensors
• Store for fast access (<10 ms)
• Access by sensor ID + time range
• Store for 30 days
DynamoDB
SensorId: 123
Timestamp: 1492641900
MyTTL: 1492736400
Expiry
Kinesis, DynamoDB partition key: Sensor ID
DynamoDB sort key: Timestamp
29. Cost Considerations
Data rate: 100,000 data points per second
Data storage: 1 month’s worth = ~2.5 TB
Estimated cost:
Lambda: $2K – $5K per month
Kinesis: 100,000 records -> 100 shards -> ~$5K per month
DynamoDB: 100,000 WCU’s -> $50K per month
Where is the problem?
• DynamoDB Write Capacity Unit (WCU) is 1 KB
• Our scenario:
• Storing data points ~50 B in size
• Write capacity utilization per write: 50/1024 * 100% = 4.88%
30. Solution: DeviceId: 123
Timestamp: 1492641900
Temp: 172
MyTTL: 1492736400
AWS Lambda
Kinesis Stream
Group multiple data points into a single
item – save on writes to DynamoDB
Use Lambda batch size to control
DynamoDB item size
Batch-write to DynamoDB
Use DynamoDB TTL to manage data
lifetime
Optional: use compression
sensor_data
DynamoDB
Queue-based load leveling
using AWS Lambda
id: 123
dt: 1492641900
MyTTL: 1492736400 TTL Expiry
32. Cost, Revised
Data rate: 100,000 data points per second
Data storage: 1 month’s worth = ~2.5 TB
Lambda: $2K – $5K per month
Kinesis: 100,000 records -> 100 shards -> ~$5K per month
DynamoDB: 100,000 WCU’s -> $50K per month
• Bin data points: 10 per item saves 10x in cost
• 10,000 WCU’s -> $5K per month (10x less…)
• Diff. over 1 year: $600K vs. $60K
We can save a lot by storing multiple data points in a single record
(DynamoDB item)
33. Scaling Considerations
Adding more sensors:
- Kinesis: you need to add more shards
- Lambda: scales automatically based on Kinesis shards
- DynamoDB: scales automatically for space and throughput
- Auto Scaling increases and decreases provisioned capacity as needed
- For large spikes, provision capacity explicitly
- Time-to-live (TTL) automatically deletes expired data without consuming
provisioned capacity
Adding more events per sensor:
- Lambda function creates “denser” DynamoDB items
- More data points stored in each DynamoDB item
35. Time Series Data: Takeaways
DynamoDB:
- Know your data
- Structure
- Access patterns
- Know the cost model
- Writes are the most expensive resource
- Attribute names are counted in the item size
- Optimization:
- Binning—store multiple data points in a single item
- Compression
- TTL to delete cold data
- Queue-based load leveling for uneven workload patterns
Lambda:
- Reuse database connections
- Test for optimal batch size, memory/CPU, and execution time
Monitor!
Optimize