You’ve designed and built a well-architected data lake and ingested extreme amounts of structured and unstructured data. Now what? In this session, we explore real-world use cases where data scientists, developers, and researchers have discovered new and valuable ways to extract business insights using advanced analytics and machine learning. We review Amazon S3, Amazon Glacier, and Amazon EFS, the foundation for the analytics clusters and data engines. We also explore analytics tools and databases, including Amazon Redshift, Amazon Athena, Amazon EMR, Amazon QuickSight, Amazon Kinesis, Amazon RDS, and Amazon Aurora; and we review the AWS machine learning portfolio and AI services such as Amazon SageMaker, AWS Deep Learning AMIs, Amazon Rekognition, and Amazon Lex. We discuss how all of these pieces fit together to build intelligent applications.
Easy Rider: How ML, Serverless, and IoT Drive Mobility as a Service (AMT302) ...Amazon Web Services
Vehicle mobility is evolving, from traditional rental and fleet services, to car sharing, ride hailing, and future driverless services. Mobility providers need an agile, scalable, digital platform to manage all aspects of their fleet and its usage. In this session, Avis Budget Group (ABG) and Slalom walk through their serverless mobility platform using the AWS connected vehicle reference architecture, Amazon SageMaker, Amazon Kinesis Data Analytics, and AWS Lambda. Learn the practical application of using AWS IoT to connect vehicles and Amazon SageMaker to apply machine learning to uncover insights for use cases, including vehicle inventory, shuttling efficiency, driver behavior, and vehicle trajectory analysis to identify fraudulent vehicle usage. We dive deep into the overall solution and services mentioned above, as well as the operations dashboard ABG created with Uber's open source framework, deck.gl.
Best Practices for Securing an Amazon VPC (NET318) - AWS re:Invent 2018Amazon Web Services
In this interactive workshop, we provide practical advice and guidance for designing and building secure Amazon Virtual Private Clouds (Amazon VPCs). Using a hands-on approach, we take you through using Amazon VPC features such as subnets, security groups, AWS PrivateLink, network ACLs, routing, flow logs, and service endpoints. We also share best practices for VPC design and management based on our experience supporting customers running large-scale infrastructures. We recommend you bring your own laptop.
Security Observability: Democratizing Security in the Cloud (DEV206-S) - AWS ...Amazon Web Services
In the world of security monitoring and alerting, there is an increasing number of opportunities and advanced technologies. People look for better ways to gain insights from large datasets and are tasked with the responsibility of communicating that data throughout the entire organization. In this talk, we explore how to democratize the security of your next-gen infrastructure by building measurement directly into systems, factoring in security-related KPIs and OKRs. Attendees learn how everyone, from SMBs to enterprises, securely scale their infrastructure while continuing to enable innovation at the speed of business. This session is brought to you by AWS partner, Threat Stack.
Closing Loops and Opening Minds: How to Take Control of Systems, Big and Smal...Amazon Web Services
Whether it’s distributing configurations and customer settings, launching instances, or responding to surges in load, having a great control plane is key to the success of any system or service. Come hear about the techniques we use to build stable and scalable control planes at Amazon. We dive deep into the designs that power the most reliable systems at AWS. We share hard-earned operational lessons and explain academic control theory in easy-to-apply patterns and principles that are immediately useful in your own designs.
Ticketek Sells 1,000s of Tickets a Minute with AWS Service Catalog (MAE204-S)...Amazon Web Services
Learn how the world’s third-largest ticketing company uses AWS Service Catalog to automate its entire PCI-compliant platform to better manage peak demand during major concert ticket sales for some of the world's largest venues, including the 100,000-seat Melbourne Cricket Ground in Australia. In this session, Deloitte’s Zack Levy and Ticketek CTO Matt Cudworth discuss taking automation to another level—from manually managing ‘hot shows’ to using AWS Service Catalog to automate multiple AWS services (Amazon EC2, Amazon Route 53, Amazon VPC, Amazon ELB, and AWS CloudFormation), enabling Ticketek to scale and run multiple hot shows concurrently across multiple jurisdictions. This session is brought to you by AWS partner, Deloitte Consulting LLP.
Real-Time Web Analytics with Amazon Kinesis Data Analytics (ADT401) - AWS re:...Amazon Web Services
Knowing what users are doing on your websites in real time provides insights you can act on without waiting for delayed batch processing of clickstream data. Watching the immediate impact on user behavior after new releases, detecting and responding to anomalies, situational awareness, and evaluating trends are all benefits of real-time website analytics. In this workshop, we build a cost-optimized platform to capture web beacon traffic, analyze it for interesting metrics, and display it on a customized dashboard. We start by deploying the Web Analytics Solution Accelerator, then once the core is complete, we extend their solution to capture new and interesting metrics, process those with Amazon Kinesis Analytics, and display new graphs on their custom dashboard. Participants come away with a fully functional system for capturing, analyzing, and displaying valuable website metrics in real time.
In this session delivered by the VP of AWS IoT, we cover how AWS IoT is being deployed across consumer, commercial, and industrial applications. See how customers are securely connecting and managing devices and creating analytics and machine learning (ML) based on IoT data. AWS IoT applications run in the cloud to enable massive scalablity or at the edge to enable real-time local action. Come away with an understanding how IoT is transforming business and what's new from AWS IoT.
Serverless:It All Started in Vegas (DVC306) - AWS re:Invent 2018Amazon Web Services
This talk dives into Trustpilot's journey to serverless compute. The journey starts at re:Invent 2016 and follows how the company fast-tracked its adoption within its engineering organization using a "serverless first" engineering principle. A representative from Trustpilot shares lessons learned and insights gained from running over 200 AWS Lambda functions with 12M invocations/day in production. Also covered are fun stories of what helped the company adopt serverless, how to make those stories actionable, a review of architectural patterns, and a discussion of why they choose serverless over traditional compute every day.
This session is part of re:Invent Developer Community Day, a series led by AWS enthusiasts who share firsthand technical insights on trending topics.
Easy Rider: How ML, Serverless, and IoT Drive Mobility as a Service (AMT302) ...Amazon Web Services
Vehicle mobility is evolving, from traditional rental and fleet services, to car sharing, ride hailing, and future driverless services. Mobility providers need an agile, scalable, digital platform to manage all aspects of their fleet and its usage. In this session, Avis Budget Group (ABG) and Slalom walk through their serverless mobility platform using the AWS connected vehicle reference architecture, Amazon SageMaker, Amazon Kinesis Data Analytics, and AWS Lambda. Learn the practical application of using AWS IoT to connect vehicles and Amazon SageMaker to apply machine learning to uncover insights for use cases, including vehicle inventory, shuttling efficiency, driver behavior, and vehicle trajectory analysis to identify fraudulent vehicle usage. We dive deep into the overall solution and services mentioned above, as well as the operations dashboard ABG created with Uber's open source framework, deck.gl.
Best Practices for Securing an Amazon VPC (NET318) - AWS re:Invent 2018Amazon Web Services
In this interactive workshop, we provide practical advice and guidance for designing and building secure Amazon Virtual Private Clouds (Amazon VPCs). Using a hands-on approach, we take you through using Amazon VPC features such as subnets, security groups, AWS PrivateLink, network ACLs, routing, flow logs, and service endpoints. We also share best practices for VPC design and management based on our experience supporting customers running large-scale infrastructures. We recommend you bring your own laptop.
Security Observability: Democratizing Security in the Cloud (DEV206-S) - AWS ...Amazon Web Services
In the world of security monitoring and alerting, there is an increasing number of opportunities and advanced technologies. People look for better ways to gain insights from large datasets and are tasked with the responsibility of communicating that data throughout the entire organization. In this talk, we explore how to democratize the security of your next-gen infrastructure by building measurement directly into systems, factoring in security-related KPIs and OKRs. Attendees learn how everyone, from SMBs to enterprises, securely scale their infrastructure while continuing to enable innovation at the speed of business. This session is brought to you by AWS partner, Threat Stack.
Closing Loops and Opening Minds: How to Take Control of Systems, Big and Smal...Amazon Web Services
Whether it’s distributing configurations and customer settings, launching instances, or responding to surges in load, having a great control plane is key to the success of any system or service. Come hear about the techniques we use to build stable and scalable control planes at Amazon. We dive deep into the designs that power the most reliable systems at AWS. We share hard-earned operational lessons and explain academic control theory in easy-to-apply patterns and principles that are immediately useful in your own designs.
Ticketek Sells 1,000s of Tickets a Minute with AWS Service Catalog (MAE204-S)...Amazon Web Services
Learn how the world’s third-largest ticketing company uses AWS Service Catalog to automate its entire PCI-compliant platform to better manage peak demand during major concert ticket sales for some of the world's largest venues, including the 100,000-seat Melbourne Cricket Ground in Australia. In this session, Deloitte’s Zack Levy and Ticketek CTO Matt Cudworth discuss taking automation to another level—from manually managing ‘hot shows’ to using AWS Service Catalog to automate multiple AWS services (Amazon EC2, Amazon Route 53, Amazon VPC, Amazon ELB, and AWS CloudFormation), enabling Ticketek to scale and run multiple hot shows concurrently across multiple jurisdictions. This session is brought to you by AWS partner, Deloitte Consulting LLP.
Real-Time Web Analytics with Amazon Kinesis Data Analytics (ADT401) - AWS re:...Amazon Web Services
Knowing what users are doing on your websites in real time provides insights you can act on without waiting for delayed batch processing of clickstream data. Watching the immediate impact on user behavior after new releases, detecting and responding to anomalies, situational awareness, and evaluating trends are all benefits of real-time website analytics. In this workshop, we build a cost-optimized platform to capture web beacon traffic, analyze it for interesting metrics, and display it on a customized dashboard. We start by deploying the Web Analytics Solution Accelerator, then once the core is complete, we extend their solution to capture new and interesting metrics, process those with Amazon Kinesis Analytics, and display new graphs on their custom dashboard. Participants come away with a fully functional system for capturing, analyzing, and displaying valuable website metrics in real time.
In this session delivered by the VP of AWS IoT, we cover how AWS IoT is being deployed across consumer, commercial, and industrial applications. See how customers are securely connecting and managing devices and creating analytics and machine learning (ML) based on IoT data. AWS IoT applications run in the cloud to enable massive scalablity or at the edge to enable real-time local action. Come away with an understanding how IoT is transforming business and what's new from AWS IoT.
Serverless:It All Started in Vegas (DVC306) - AWS re:Invent 2018Amazon Web Services
This talk dives into Trustpilot's journey to serverless compute. The journey starts at re:Invent 2016 and follows how the company fast-tracked its adoption within its engineering organization using a "serverless first" engineering principle. A representative from Trustpilot shares lessons learned and insights gained from running over 200 AWS Lambda functions with 12M invocations/day in production. Also covered are fun stories of what helped the company adopt serverless, how to make those stories actionable, a review of architectural patterns, and a discussion of why they choose serverless over traditional compute every day.
This session is part of re:Invent Developer Community Day, a series led by AWS enthusiasts who share firsthand technical insights on trending topics.
Automate & Audit Cloud Governance & Compliance in Your Landing Zone (ENT315-R...Amazon Web Services
In this session, we explore landing zone considerations as they apply to compliance and auditing. We include such topics as a repeatable approach to SCP and IAM policy creation, internal separation of duty & "need to know", compliance scope ringfencing, Region scoping, scope of impact limitation, and mandatory access control. We review approaches for log and event analytics and log record lifecycle management (including redaction where necessary) and alerting. We also discuss how compliance assessment tools can be deployed in multi-account environments and their output sensibly interpreted. We encourage you to attend the full AWS Landing Zone track, including SEC303. Search for #awslandingzone in the session catalog.
NFL and Forwood Safety Deploy Business Analytics at Scale with Amazon QuickSi...Amazon Web Services
Enabling interactive data and analytics for thousands of users can be expensive and challenging—from having to forecast usage, provisioning and managing servers, to securing data, governing access, and ensuring auditability. In this session, learn how Amazon QuickSight’s serverless architecture and pay-per-session pricing enabled the National Football League (NFL) and Forwood Safety to roll out interactive dashboards to hundreds and thousands of users. Understand how the NFL utilizes embedded Amazon QuickSight dashboards to provide clubs, broadcasters, and internal users with Next Gen Stats data collected from games. Also, learn about Forwood's journey to enabling dashboards for thousands of Rio Tinto users worldwide, utilizing Amazon QuickSight readers, federated single sign-on, dynamic defaults, email reports, and more.
Dissecting Media Asset Management Architecture and Media Archive TCO (MAE301)...Amazon Web Services
Every M&E migration strategy to AWS requires the customer and partners to design and implement a content ingest workflow. These services vary from simple file transfer to fairly complex workflows that do quality control, proxy creation, and metadata augmentation. In this session, we present a baseline process for moving content into a Media Asset Management system in AWS, leveraging common open-source tools for asset registry and using AWS ML services to augment the metadata associated with assets. We also talk about common considerations that M&E organizations should consider when moving their assets and workflows to the cloud. Topics include metadata input, modeling, storage services and policies, security considerations, and managing increased content demands. We also visit the different storage tiers for different archive use cases and offer a TCO model.
Breaking the Ice: Transform Cold Archival Data into Fresh Insights (STG355) -...Amazon Web Services
Broadridge Financial has a long history of providing solutions for regulatory archival content on behalf of its clients. Many archival solutions rely on legacy technology, requiring regular refresh and overhaul. With the advent of cloud technology, Broadridge has re-imagined archival systems as intelligent information management solutions. Broadridge's solution uses a wide array of AWS services, such as Amazon Glacier, Amazon S3, AWS Lambda, Amazon EC2, Amazon Aurora, Amazon EBS, AWS CloudTrail, Amazon SQS, AWS Direct Connect, Amazon Lex, and Amazon API Gateway. In this session, we explore the architecture behind Broadridge's solution. Attendees gain an understanding of how archival content can become a valuable repository of information that drives client services, data analytics, and business growth.
Shift-Left SRE: Self-Healing with AWS Lambda Functions (DEV313-S) - AWS re:In...Amazon Web Services
Even the best continuous delivery and DevOps practices cannot guarantee that there will be no issues in production. The rise of Site Reliability Engineering (SRE) has promoted new ways to automate resilience into your system and applications to circumvent potential problems, but it’s time to “shift-left” this effort into engineering. In this session, learn to leverage AWS Lambda functions as “remediation as code.” We show how to make it part of your continuous delivery process and orchestrate the invocation of Self-Healing Lambda functions in case of unexpected situations impacting the reliability of your system. Gone are the days of traditional operation teams—it’s the rise of “shift-lefters”! This session is brought to you by AWS partner, Dynatrace.
DevSecOps: Instituting Cultural Transformation for Public Sector Organization...Amazon Web Services
In this in-depth, interactive workshop, we examine how different public sector customers achieve this shift and analyze common success patterns. We address key points such as continuous compliance, integrating security, and removing people from the data to vastly improve the organization's security posture over traditional operating models. Takeaways include a blueprint for building a DevSecOps operating model in your organization; an understanding the security practitioners' point of view and embracing it to drive innovation; and ways to identify current operating characteristics in your organization and use them to drive a strategy for DevSecOps.
In this workshop, learn how to connect devices to AWS IoT and AWS Greengrass. Understand the architecture, and install and configure device communication using AWS Greengrass. In addition, take advantage of the opportunity to create various device communication scenarios with AWS Greengrass and simulate the data flow with sensor data. Attendees in workshop need an AWS account and are asked to bring their laptop.
Essere conformi al GDPR, il regolamento generale sulla protezione dei dati personali entrato in vigore il 25 maggio 2018, può risultare complicato ma AWS ha gli strumenti per guidarti attraverso tutto il processo. In questa sessione approfondiremo i meccanismi di automazione che AWS offre ai propri clienti per aiutarli nell'implementazione dei propri programmi di sicurezza e privacy e vedremo quali sono gli strumenti specifici messi a disposizione da AWS per indirizzare alcuni requisiti del GDPR.
Instrumenting Kubernetes for Observability Using AWS X-Ray and Amazon CloudWa...Amazon Web Services
In this hands-on workshop, we walk you through instrumenting container workloads running on the Amazon Elastic Container Service for Kubernetes (Amazon EKS). Learn how Amazon CloudWatch and the new AWS X-Ray capabilities enable you to quickly understand problem areas in your application and determine customer impact. To participate in this workshop, bring your laptop and have a nonproduction AWS account.
I container sono una tecnologia che permette di eseguire un'applicazione, con le relative dipendenze, in processi e risorse isolate all’interno di un sistema operativo condiviso. Consentono di creare con la massima semplicità un pacchetto contenente codice, configurazioni base e dipendenze di un'applicazione, da impiegare come elemento atomico per ottenere ambienti uniformi, efficienza operativa, produttività di sviluppo e controllo delle versioni. In questa sessione approfondiremo come usare i container sul cloud AWS per creare applicazioni a microservizi affidabili e scalabili sfruttando i vantaggi del cloud, ad esempio l'elasticità, la disponibilità, la sicurezza e le economie di scala.
Serverless Video Ingestion & Analytics with Amazon Kinesis Video Streams (ANT...Amazon Web Services
Amazon Kinesis Video Streams makes it easy to capture live video, play it back, and store it for real-time and batch-oriented ML-driven analytics. In this session, we first dive deep on the top five best practices for getting started and scaling with Amazon Kinesis Video Streams. Next, we demonstrate a streaming video from a standard USB camera connected to a laptop, and we perform a live playback on a standard browser within minutes. We also have on stage members of Amazon Go, who are building the next generation of physical retail store experiences powered by their "just walk out" technology. They walk through the technical details of their integration with Kinesis Video Streams and highlight their successes and difficulties along the way.
AWS IoT Analytics collects, processes, and analyzes IoT data quickly and easily so you can gain operational insights. To collect data and prepare it for analysis, you use Channels. Channels listen to devices and pull device messages into AWS IoT Analytics. Once messages are flowing, pipelines process messages and turn them into useful data using techniques like transforms and filters. Pipelines also enrich your IoT data with data from other AWS service and external data sources. After it's processed, data is stored in an IoT-optimized data store. Once data is ready to be analyzed, datasets are created by querying the data or by using built-in Jupyter notebook templates for sophisticated analytics, such as machine learning. AWS IoT Analytics integrates with Amazon SageMaker so you can build machine learning models, such as predictive analytics. Join us for a deep dive on these components.
Drive Customer Value with Data-Driven Decisions (GPSBUS206) - AWS re:Invent 2018Amazon Web Services
Organizations that use data as a competitive differentiator are more likely to lead and outperform their peers. Many organizations have transformed their data architectures and adopted the cloud to meet a variety of scalability and automation challenges. In this session, we develop a blueprint for data flows from data sources to data lakes, data warehousing, advanced analytics, and machine learning (ML). We look at the big picture, understand how to build data pipelines and repositories for different use cases, and enable data science at enterprise scale in a way that unleashes the value of corporate data, and embeds AI/ML in business processes.
Set Up a Communications Platform on AWS with AI-Enhanced Services (TLC302) - ...Amazon Web Services
Imagine being able to transcribe calls, translate them into multiple languages and then being able to identify key topics discussed in those calls. All of that is possible today with machine learning services offered by AWS. In AWS, you can easily integrate your real-time communication infrastructure with state-of-the-art AI services to enhance user experience. In this workshop, learn how to set up a secure and highly available WebRTC system on AWS and then integrate it with AWS AI services to provide services such as transcription (Amazon Transcribe), translation (Amazon Translate), and meta-data creation (Amazon Comprehend).
Serverless State Management & Orchestration for Modern Apps (API302) - AWS re...Amazon Web Services
Keeping track of state and orchestrating the components of a distributed application is complex. AWS Step Functions makes the job simpler, faster, and more intuitive. In this session, learn how to leverage AWS Step Functions to design and run workflows for your serverless, containerized, and instance-based architectures. We explore practical applications of orchestration spanning different industries and workloads. For each, we walk through the architecture, lessons learned, and business outcomes. Expect to leave this session with a practical understanding of how to use orchestration to express your application’s business logic more productively while improving its resilience.
[NEW LAUNCH!] Introducing Amazon Textract: Now in Preview (AIM363) - AWS re:I...Amazon Web Services
Amazon Textract enables you to easily extract text and data from virtually any document. Today, companies process millions of documents by manually entering the data or using customized optical character recognition solutions, which are prone to error and consume valuable resources. Join us to learn how Amazon Textract uses machine learning to simplify document processing by enabling fast and accurate text and data extraction so you can process millions of documents in hours.
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.
Operationalizing Your Analysis with AWS IoT Analytics (IOT358-R1) - AWS re:In...Amazon Web Services
AWS IoT Analytics makes it easy to run and operationalize sophisticated analytics on massive volumes of IoT data without having to worry about the cost and complexity required to build your own IoT analytics platform. It collects and prepares data for analysis and also lets you explore and visualize your IoT data so you can make better and more accurate business decisions. AWS IoT Analytics is a fully managed service that makes it easy to run and operationalize sophisticated analytics on massive volumes of IoT data without having to worry about the cost and complexity typically required to build an IoT analytics platform. It is the easiest way to run analytics on IoT data and get insights to make better and more accurate decisions for IoT applications and machine learning use cases. Models built and trained in AWS IoT Analytics can be run on connected devices. Join us for a deep dive and demo on how to operationalize your analytical workflows with AWS IoT Analytics.
Artificial Intelligence nella realtà di oggi: come utilizzarla al meglioAmazon Web Services
L'intelligenza Artificiale è qui questa volta, per restare. Per le aziende, l'intelligenza artificiale si concretizza in soluzioni che migliorano l'esperienza dei clienti ottimizzando, automatizzando e personalizzando attività ad alto volume e riducendo al contempo costi e tempi, accelerando notevolmente il ritmo di innovazione. In questa sessione, approfondiremo i servizi AI di AWS che promuovo l'innovazione in azienda mantenendo la conformità con diversi regimi come HIPAA, PCI e altro. Infine, presenteremo le architetture AWS necessarie per supportare i carichi di lavoro di apprendimento automatico e deep learning.
Amazon Cloud Directory Deep Dive (DAT364) - AWS re:Invent 2018Amazon Web Services
Learn how companies like FocusCura and Clouden have on-boarded hierarchical data at scale using Amazon Cloud Directory, a highly available, fully managed, serverless, hierarchical datastore. It’s well-suited for such use cases as human resources applications, course catalogs, device registry, network topology, and any application that needs fine-grained permissions (authorization). We do a deep dive into the internals of Cloud Directory and discuss best practices.
The first step towards knowing your customer is to collect and extract insights and actionable information from your data. Learn how AWS enables you to cost efficiently store any amount of data and build an agile approach to data mining and visualization - helping you to make efficient business decisions and targeted offerings.
Automate & Audit Cloud Governance & Compliance in Your Landing Zone (ENT315-R...Amazon Web Services
In this session, we explore landing zone considerations as they apply to compliance and auditing. We include such topics as a repeatable approach to SCP and IAM policy creation, internal separation of duty & "need to know", compliance scope ringfencing, Region scoping, scope of impact limitation, and mandatory access control. We review approaches for log and event analytics and log record lifecycle management (including redaction where necessary) and alerting. We also discuss how compliance assessment tools can be deployed in multi-account environments and their output sensibly interpreted. We encourage you to attend the full AWS Landing Zone track, including SEC303. Search for #awslandingzone in the session catalog.
NFL and Forwood Safety Deploy Business Analytics at Scale with Amazon QuickSi...Amazon Web Services
Enabling interactive data and analytics for thousands of users can be expensive and challenging—from having to forecast usage, provisioning and managing servers, to securing data, governing access, and ensuring auditability. In this session, learn how Amazon QuickSight’s serverless architecture and pay-per-session pricing enabled the National Football League (NFL) and Forwood Safety to roll out interactive dashboards to hundreds and thousands of users. Understand how the NFL utilizes embedded Amazon QuickSight dashboards to provide clubs, broadcasters, and internal users with Next Gen Stats data collected from games. Also, learn about Forwood's journey to enabling dashboards for thousands of Rio Tinto users worldwide, utilizing Amazon QuickSight readers, federated single sign-on, dynamic defaults, email reports, and more.
Dissecting Media Asset Management Architecture and Media Archive TCO (MAE301)...Amazon Web Services
Every M&E migration strategy to AWS requires the customer and partners to design and implement a content ingest workflow. These services vary from simple file transfer to fairly complex workflows that do quality control, proxy creation, and metadata augmentation. In this session, we present a baseline process for moving content into a Media Asset Management system in AWS, leveraging common open-source tools for asset registry and using AWS ML services to augment the metadata associated with assets. We also talk about common considerations that M&E organizations should consider when moving their assets and workflows to the cloud. Topics include metadata input, modeling, storage services and policies, security considerations, and managing increased content demands. We also visit the different storage tiers for different archive use cases and offer a TCO model.
Breaking the Ice: Transform Cold Archival Data into Fresh Insights (STG355) -...Amazon Web Services
Broadridge Financial has a long history of providing solutions for regulatory archival content on behalf of its clients. Many archival solutions rely on legacy technology, requiring regular refresh and overhaul. With the advent of cloud technology, Broadridge has re-imagined archival systems as intelligent information management solutions. Broadridge's solution uses a wide array of AWS services, such as Amazon Glacier, Amazon S3, AWS Lambda, Amazon EC2, Amazon Aurora, Amazon EBS, AWS CloudTrail, Amazon SQS, AWS Direct Connect, Amazon Lex, and Amazon API Gateway. In this session, we explore the architecture behind Broadridge's solution. Attendees gain an understanding of how archival content can become a valuable repository of information that drives client services, data analytics, and business growth.
Shift-Left SRE: Self-Healing with AWS Lambda Functions (DEV313-S) - AWS re:In...Amazon Web Services
Even the best continuous delivery and DevOps practices cannot guarantee that there will be no issues in production. The rise of Site Reliability Engineering (SRE) has promoted new ways to automate resilience into your system and applications to circumvent potential problems, but it’s time to “shift-left” this effort into engineering. In this session, learn to leverage AWS Lambda functions as “remediation as code.” We show how to make it part of your continuous delivery process and orchestrate the invocation of Self-Healing Lambda functions in case of unexpected situations impacting the reliability of your system. Gone are the days of traditional operation teams—it’s the rise of “shift-lefters”! This session is brought to you by AWS partner, Dynatrace.
DevSecOps: Instituting Cultural Transformation for Public Sector Organization...Amazon Web Services
In this in-depth, interactive workshop, we examine how different public sector customers achieve this shift and analyze common success patterns. We address key points such as continuous compliance, integrating security, and removing people from the data to vastly improve the organization's security posture over traditional operating models. Takeaways include a blueprint for building a DevSecOps operating model in your organization; an understanding the security practitioners' point of view and embracing it to drive innovation; and ways to identify current operating characteristics in your organization and use them to drive a strategy for DevSecOps.
In this workshop, learn how to connect devices to AWS IoT and AWS Greengrass. Understand the architecture, and install and configure device communication using AWS Greengrass. In addition, take advantage of the opportunity to create various device communication scenarios with AWS Greengrass and simulate the data flow with sensor data. Attendees in workshop need an AWS account and are asked to bring their laptop.
Essere conformi al GDPR, il regolamento generale sulla protezione dei dati personali entrato in vigore il 25 maggio 2018, può risultare complicato ma AWS ha gli strumenti per guidarti attraverso tutto il processo. In questa sessione approfondiremo i meccanismi di automazione che AWS offre ai propri clienti per aiutarli nell'implementazione dei propri programmi di sicurezza e privacy e vedremo quali sono gli strumenti specifici messi a disposizione da AWS per indirizzare alcuni requisiti del GDPR.
Instrumenting Kubernetes for Observability Using AWS X-Ray and Amazon CloudWa...Amazon Web Services
In this hands-on workshop, we walk you through instrumenting container workloads running on the Amazon Elastic Container Service for Kubernetes (Amazon EKS). Learn how Amazon CloudWatch and the new AWS X-Ray capabilities enable you to quickly understand problem areas in your application and determine customer impact. To participate in this workshop, bring your laptop and have a nonproduction AWS account.
I container sono una tecnologia che permette di eseguire un'applicazione, con le relative dipendenze, in processi e risorse isolate all’interno di un sistema operativo condiviso. Consentono di creare con la massima semplicità un pacchetto contenente codice, configurazioni base e dipendenze di un'applicazione, da impiegare come elemento atomico per ottenere ambienti uniformi, efficienza operativa, produttività di sviluppo e controllo delle versioni. In questa sessione approfondiremo come usare i container sul cloud AWS per creare applicazioni a microservizi affidabili e scalabili sfruttando i vantaggi del cloud, ad esempio l'elasticità, la disponibilità, la sicurezza e le economie di scala.
Serverless Video Ingestion & Analytics with Amazon Kinesis Video Streams (ANT...Amazon Web Services
Amazon Kinesis Video Streams makes it easy to capture live video, play it back, and store it for real-time and batch-oriented ML-driven analytics. In this session, we first dive deep on the top five best practices for getting started and scaling with Amazon Kinesis Video Streams. Next, we demonstrate a streaming video from a standard USB camera connected to a laptop, and we perform a live playback on a standard browser within minutes. We also have on stage members of Amazon Go, who are building the next generation of physical retail store experiences powered by their "just walk out" technology. They walk through the technical details of their integration with Kinesis Video Streams and highlight their successes and difficulties along the way.
AWS IoT Analytics collects, processes, and analyzes IoT data quickly and easily so you can gain operational insights. To collect data and prepare it for analysis, you use Channels. Channels listen to devices and pull device messages into AWS IoT Analytics. Once messages are flowing, pipelines process messages and turn them into useful data using techniques like transforms and filters. Pipelines also enrich your IoT data with data from other AWS service and external data sources. After it's processed, data is stored in an IoT-optimized data store. Once data is ready to be analyzed, datasets are created by querying the data or by using built-in Jupyter notebook templates for sophisticated analytics, such as machine learning. AWS IoT Analytics integrates with Amazon SageMaker so you can build machine learning models, such as predictive analytics. Join us for a deep dive on these components.
Drive Customer Value with Data-Driven Decisions (GPSBUS206) - AWS re:Invent 2018Amazon Web Services
Organizations that use data as a competitive differentiator are more likely to lead and outperform their peers. Many organizations have transformed their data architectures and adopted the cloud to meet a variety of scalability and automation challenges. In this session, we develop a blueprint for data flows from data sources to data lakes, data warehousing, advanced analytics, and machine learning (ML). We look at the big picture, understand how to build data pipelines and repositories for different use cases, and enable data science at enterprise scale in a way that unleashes the value of corporate data, and embeds AI/ML in business processes.
Set Up a Communications Platform on AWS with AI-Enhanced Services (TLC302) - ...Amazon Web Services
Imagine being able to transcribe calls, translate them into multiple languages and then being able to identify key topics discussed in those calls. All of that is possible today with machine learning services offered by AWS. In AWS, you can easily integrate your real-time communication infrastructure with state-of-the-art AI services to enhance user experience. In this workshop, learn how to set up a secure and highly available WebRTC system on AWS and then integrate it with AWS AI services to provide services such as transcription (Amazon Transcribe), translation (Amazon Translate), and meta-data creation (Amazon Comprehend).
Serverless State Management & Orchestration for Modern Apps (API302) - AWS re...Amazon Web Services
Keeping track of state and orchestrating the components of a distributed application is complex. AWS Step Functions makes the job simpler, faster, and more intuitive. In this session, learn how to leverage AWS Step Functions to design and run workflows for your serverless, containerized, and instance-based architectures. We explore practical applications of orchestration spanning different industries and workloads. For each, we walk through the architecture, lessons learned, and business outcomes. Expect to leave this session with a practical understanding of how to use orchestration to express your application’s business logic more productively while improving its resilience.
[NEW LAUNCH!] Introducing Amazon Textract: Now in Preview (AIM363) - AWS re:I...Amazon Web Services
Amazon Textract enables you to easily extract text and data from virtually any document. Today, companies process millions of documents by manually entering the data or using customized optical character recognition solutions, which are prone to error and consume valuable resources. Join us to learn how Amazon Textract uses machine learning to simplify document processing by enabling fast and accurate text and data extraction so you can process millions of documents in hours.
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.
Operationalizing Your Analysis with AWS IoT Analytics (IOT358-R1) - AWS re:In...Amazon Web Services
AWS IoT Analytics makes it easy to run and operationalize sophisticated analytics on massive volumes of IoT data without having to worry about the cost and complexity required to build your own IoT analytics platform. It collects and prepares data for analysis and also lets you explore and visualize your IoT data so you can make better and more accurate business decisions. AWS IoT Analytics is a fully managed service that makes it easy to run and operationalize sophisticated analytics on massive volumes of IoT data without having to worry about the cost and complexity typically required to build an IoT analytics platform. It is the easiest way to run analytics on IoT data and get insights to make better and more accurate decisions for IoT applications and machine learning use cases. Models built and trained in AWS IoT Analytics can be run on connected devices. Join us for a deep dive and demo on how to operationalize your analytical workflows with AWS IoT Analytics.
Artificial Intelligence nella realtà di oggi: come utilizzarla al meglioAmazon Web Services
L'intelligenza Artificiale è qui questa volta, per restare. Per le aziende, l'intelligenza artificiale si concretizza in soluzioni che migliorano l'esperienza dei clienti ottimizzando, automatizzando e personalizzando attività ad alto volume e riducendo al contempo costi e tempi, accelerando notevolmente il ritmo di innovazione. In questa sessione, approfondiremo i servizi AI di AWS che promuovo l'innovazione in azienda mantenendo la conformità con diversi regimi come HIPAA, PCI e altro. Infine, presenteremo le architetture AWS necessarie per supportare i carichi di lavoro di apprendimento automatico e deep learning.
Amazon Cloud Directory Deep Dive (DAT364) - AWS re:Invent 2018Amazon Web Services
Learn how companies like FocusCura and Clouden have on-boarded hierarchical data at scale using Amazon Cloud Directory, a highly available, fully managed, serverless, hierarchical datastore. It’s well-suited for such use cases as human resources applications, course catalogs, device registry, network topology, and any application that needs fine-grained permissions (authorization). We do a deep dive into the internals of Cloud Directory and discuss best practices.
The first step towards knowing your customer is to collect and extract insights and actionable information from your data. Learn how AWS enables you to cost efficiently store any amount of data and build an agile approach to data mining and visualization - helping you to make efficient business decisions and targeted offerings.
The first step towards knowing your customer is to collect and extract insights and actionable information from your data. Learn how AWS enables you to cost efficiently store any amount of data and build an agile approach to data mining and visualization - helping you to make efficient business decisions and targeted offerings.
Modern Cloud Data Warehousing ft. Equinox Fitness Clubs: Optimize Analytics P...Amazon Web Services
Most companies are overrun with data, yet they lack critical insights to make timely and accurate business decisions. They are missing the opportunity to combine large amounts of new, unstructured big data that resides outside their data warehouse with trusted, structured data inside their data warehouse. In this session, we discuss the most common use cases with Amazon Redshift, and we take an in-depth look at how modern data warehousing blends and analyzes all your data to give you deeper insights to run your business. Equinox Fitness Clubs joins us to share their journey from static reports, redundant data, and inefficient data intergration to a modern and flexible data lake and data warehouse architecture that delivers dynamic reports based on trusted data.
Quickly and easily build, train, and deploy machine learning models at any scaleAWS Germany
The machine learning process often feels a lot harder than it should be to most developers because the process to build and train models, and then deploy them into production is too complicated and too slow.
This workshop starts with a brief review of the machine learning process, followed by an introduction and deep dive into the individual components of Amazon SageMaker. As part of the workshop we will train artificial neural networks, get insight into some of the built-in machine learning algorithms of SageMaker that you can use for a variety of problem types, and after successfully training a model, look at options on how to deploy and scale a model as a service.
This workshop is aimed at developers that are new to machine learning, as well as data scientists that continue to be challenged by the operational challenges of the machine learning process. Bring your own laptop with Python and Jupyter Notebook, and (ideally) your own activated AWS account to follow through the examples.
Building a Data Lake for Your Enterprise, ft. Sysco (STG309) - AWS re:Invent ...Amazon Web Services
Data lakes are transforming the way enterprises store, analyze, and learn insights from their data. While data lakes are a relatively new concept, many enterprises have already generated significant business value from the insights gleaned. In this session, AWS experts and technology leaders from Sysco, a Fortune 50 company and leader in food distribution and marketing, explain why Sysco decided to evolve its data management capabilities to include data lakes and how they customized them to support diverse querying capabilities and data science use cases. They also discuss how to architect different aspects of a data lake—ingestion from disparate sources, data consumption, and usability layers—and how to track data ingestion and consumption, monitor associated costs, enforce wanted levels of user access, manage data file formats, synchronize production and non-production environments, and maintain data integrity. Services to be discussed include Amazon S3 and S3 Select, Amazon Athena, Amazon EMR, Amazon EC2, and Amazon Redshift Spectrum.
Social Media Analytics with Amazon QuickSight (ANT370) - AWS re:Invent 2018Amazon Web Services
Realizing the value of social media analytics can bolster your business goals. This type of analysis has grown in recent years due to the large amount of available information and the speed at which it can be collected and analyzed. In this workshop, we build a serverless data processing and machine learning (ML) pipeline that provides a multi-lingual social media dashboard of tweets within Amazon QuickSight. We leverage API-driven ML services, AWS Glue, Amazon Athena and Amazon QuickSight. These building blocks are put together with very little code by leveraging serverless offerings within AWS.
Building a Data Lake in Amazon S3 & Amazon Glacier (STG401-R1) - AWS re:Inven...Amazon Web Services
Whether you are part of a startup or a global enterprise, using a data lake to store and analyze data can help your business glean insights to evolve service offerings and capitalize on emerging market opportunities. In this workshop, AWS engineers and experts provide hands-on guidance for IT professionals looking to build a data lake for their organization. We provide overviews of Amazon S3, Amazon Glacier, and AWS query-in-place features and services, such as Amazon S3 Select, Amazon Glacier Select, Amazon Athena, and Amazon Redshift Spectrum. Attendees also learn how to use these services with third-party tools to build data lakes and other analytics solutions. Familiarity of with AWS object storage and analytics services is helpful but not required.
Learning Objectives:
- Learn how Amazon SageMaker can be used for exploratory data analysis before training
- Learn how Amazon SageMaker provides managed distributed training with flexibility
- Learn how easy it is to deploy your models for hosting within Amazon SageMaker
Big Data Meets AI - Driving Insights and Adding Intelligence to Your SolutionsAmazon Web Services
Over 90% of today’s data has been generated in the last two years, and growth rates continue to climb. In this session, we’ll step through challenges and best practices with data capturing, how to derive meaningful insights to help predict the future, and common pitfalls in data analysis.
Come discover how integrated solutions involving Amazon S3, AWS Glue, Amazon Redshift, Amazon Athena, Amazon EMR, Amazon Kinesis, and Amazon Machine Learning, and Deep Learning on AWS result in effective data systems for data scientists and business users, alike.
Ben Snively, Principal Solutions Architect, AWS; Kate Werling, Solutions Architect, AWS
SaaS Analytics and Metrics: Capturing and Surfacing the Data That's Fundament...Amazon Web Services
Metrics are fundamental to succeeding with SaaS. As you pour tenants into a shared infrastructure environment, you need to rely on a rich collection of data that can drive insights into the architectural, operational, and business dimensions of your SaaS solution. In this session, learn to identify the different types of metrics commonly collected by SaaS providers and connect these with the design and architecture strategies that are employed to surface and analyze this data on AWS. We look at how SaaS organizations instrument, aggregate, publish and build actionable views of this data with specific emphasis on how a robust metrics architecture can fundamentally impact the operational, architectural, and business decision-making process for SaaS organizations.
How to Build HR Lakes on AWS to Unlock New Business Insights (DAT367) - AWS r...Amazon Web Services
In this session, learn how to create an HR data lake on AWS to develop a more wholistic view of people data to enable secure, self-service reporting for HR business partners and managers, and to use more advanced data science tools to unlock new insights to reduce retention, enhance hiring practices, and improve employee productivity. We provide examples of HR insights and the business value they can drive, walk through a reference architecture example for an HR data lake, and outline key steps and best practices as you design and launch your HR data lake project. AWS services addressed in this session include AWS Lambda, Amazon S3, AWS Glue, and Amazon Athena.
AI/ML with Data Lakes: Counterintuitive Consumer Insights in Retail (RET206) ...Amazon Web Services
In this session, learn how data scientists in the retail industry, from companies like Tapestry, Coach, and Kate Spade, are finding new, counterintuitive consumer insights using AWS artificial intelligence services in a data lake. By leveraging data from various retail systems, including CRM, marketing, e-commerce, point of sale, order management, merchandising, and customer care, we show you how these consumer insights might influence new and interesting retail use cases while establishing a data-driven culture within the organization. Services referenced include Amazon S3, Amazon Machine Learning, Amazon QuickSight, Amazon SageMaker, among others.
Automate Business Insights on AWS - Simple, Fast, and Secure Analytics PlatformsAmazon Web Services
Business analysts require easy access to data from across different parts of the business. In this session, learn why more customers have adopted Amazon Redshift than any other cloud-native Data Warehouse, and how they are building a broader analytics capability with data lakes on AWS.
Understand how AWS built machine learning (ML) into the services, taking away many of the time-intensive tasks of building an analytics platform. We cover why these customers choose Amazon Redshift for the accessibility to analysts, business reporting, deep security, ability to scale from GB to PB, and integration with the broader platform.
Learn about these customers who are increasingly opening insights to data analysts for data discovery and data scientists for machine learning. We also share how the AWS services such as AWS Glue and the coming ML-enabled AWS Lake Formation take away most of the heavy lifting,
Choosing the Right Database for My Workload: Purpose-Built Databases AWS Germany
AWS offers a broad range of databases purpose-built for your specific application use cases. Our fully managed database services include relational databases for transactional applications, non-relational databases for internet-scale applications, a data warehouse for analytics, an in-memory data store for caching and real-time workloads, and a graph database for building applications with highly connected data. If you are looking to migrate your existing databases to AWS, the AWS Database Migration Service makes it easy and cost-effective to do so. The session will cover various SQL engines, “cloud-native SQL” (Aurora), SQL DWH + Spectrum, NoSQL, GraphDB.
What are the different options for a developer to run his DB in the Cloud? This session will look into the different options and how to choose the right DB for your workload.
M&E Leadership Session: The State of the Industry, What's New from AWS for M&...Amazon Web Services
In this wide-ranging keynote session, first hear from AWS VP Carla Stratfold on the major forces affecting the industry, then learn from AWS Global M&E Tech Lead Usman Shakeel about the latest and most exciting releases coming out of re:Invent relevant to the M&E industry. And finally, hear how technical leaders at the forefront of the industry are responding to accelerating changes in the media landscape.
CI/CD for Your Machine Learning Pipeline with Amazon SageMaker (DVC303) - AWS...Amazon Web Services
Amazon SageMaker is a powerful tool that enables us to build, train, and deploy at scale our machine learning-based workloads. With help from AWS CI/CD tools, we can speed up this pipeline process. In this talk, we discuss how to integrate Amazon SageMaker into a CI/CD pipeline as well as how to orchestrate with other serverless components.
This session is part of re:Invent Developer Community Day, a series led by AWS enthusiasts who share first-hand, technical insights on trending topics.
Get to Know Your Customers - Build and Innovate with a Modern Data ArchitectureAmazon Web Services
Your customers probably want a better experience with your brand. Your different business teams want and need better insights in their decision making. Almost certainly, your finance and operations teams require this to happen at a fraction of the cost of traditional on-premises options. Modern data architectures on AWS help many of our best customers realise all of those goals. Your business data contains critical information about customer behaviours, operational decisions, and many factors that have financial impact on your organisation. Increasingly, this data sits beyond your transactional systems, and is too big, too fast, and too complex for existing systems to handle. AWS Data and Analytics services are designed from our customers' requirements to ingest, store, analyse, and consume information at record-breaking scale. In this session you will learn how these services work together to deliver business automation, enhance customer engagement and intelligence.
Similar to Driving Machine Learning and Analytics Use Cases with AWS Storage (STG302) - AWS re:Invent 2018 (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. … Can we create services that change the
perception of what it means to store and
archive information, in an effort to make it a
value driver to an enterprise?