When indexing large amounts of media files, it can become difficult to search through them to find certain objects and individuals. In this session, we show you how creating a custom celebrity list enables you to index your media files by the people you train it to recognize. Come and see how this solution can serve as the foundation for creating automated sports highlight reels, building face-based user verification systems, and more.
Bridging Message Brokers to Cloud-Native Messaging Services (API210-R2) - AWS...Amazon Web Services
Learn how to connect your JMS-based applications to the cloud and integrate them with new cloud-native applications. In this session, we quickly refresh your knowledge about messaging enterprise integration patterns. We then discuss architectural examples to bridge the JMS-based and cloud-native worlds. We work through an example implementation based on Amazon MQ, Amazon SQS, and Amazon SNS. Leave this session with a solid understanding of how to connect existing applications to new cloud-native applications using messaging patterns.
Enhancing Media Workflows with Machine Learning (MAE303) - AWS re:Invent 2018Amazon Web Services
AI/ML is changing the way media companies produce and distribute content. In this workshop, we review many of the ways AI/ML can be applied throughout the entire media production and distribution process. We build an end-to-end metadata enrichment workflow that extracts meaningful metadata from content (audio, video, and images). We then build a solution that uses Amazon Rekognition, Amazon SageMaker, Amazon Transcribe, Amazon Comprehend, and Amazon Mechanical Turk to analyze content, and we use it to enrich a viewing experience and assist with compliance. We also build and train a custom object detection model, which will be used to augment the data that Amazon Rekognition provides. We cover all aspects of AI/ML-based metadata generation, from labeling a dataset, to training and hosting a model, all the way to validating the metadata prior to playout.
Capture Voice of Customer Insights with NLP & Analytics (AIM415-R1) - AWS re:...Amazon Web Services
Understanding your customers is easier today than ever before. Natural language capabilities can capture a wealth of information, such as user sentiment and conversational intent. This workshop teaches you how to build an analytics pipeline that includes natural language processing (NLP) to better understand how to improve the customer experience. Attendees learn how to use AWS services, including Amazon Comprehend and Amazon Transcribe, to process and perform analysis on customer data, such as contact center call recordings.
Democratize Data Preparation for Analytics & Machine Learning A Hands-On Lab ...Amazon Web Services
Machine learning (ML) outcomes are only as good as the data they are built upon. Preparing data for ML is time consuming and cumbersome; “data wrangling” for analytics can consume over 80% of project effort. ML Wrangling Assistant, based on Trifacta running on AWS, streamlines ML applications so teams can focus on the work that matters—creating accurate predictions that improve products, services, and organizational efficiency. In this lab, we cover one of two data preparation use cases. Marketing Analytics analyzes web ads by cleaning and transforming ecommerce transactions in a relational table combined to a clickstream semi-structured log file. Cross-Sell Analytics explores, structures, standardizes, and combines multiple file types (CSV, JSON, Excel) to create a single, consistent view of customers. Final outputs are the categorical features and attributes to train, test, and validate the data sets required by Amazon SageMaker to perform ML modeling.
Resolving NLP Problems Using Amazon SageMaker Algorithms (GPSCT305) - AWS re:...Amazon Web Services
Natural language or text is regularly voted as the most important data type after structured data. This is because text can carry an enormous amount of hidden insight. In this session, we show you how to get started with the natural language processing (NLP) techniques using Amazon SageMaker, a platform to easily build, train, and deploy models at scale. We review all of the NLP-related algorithms available on Amazon SageMaker, including Amazon algorithms (Latent Dirichlet Allocation (LDA), Neural Topic Model (NTM), and Sequence2Sequence (seq2seq), and BlazingText). We dive into the details, and we run through an example Jupyter Notebook that uses these algorithms.
Securing Data in Serverless Applications and Messaging Services (API317-R2) -...Amazon Web Services
This chalk talk walks you through the process of designing a serverless application that secures customer data sent to the cloud. The design uses features recently introduced by Amazon SNS and Amazon SQS, including AWS KMS keys for encrypting messages at rest, and Amazon VPC endpoints powered by AWS PrivateLink for sending messages without traversing the public internet. These techniques are security best practices for systems that deal with private data, such e-commerce orders, candidate resumes, and employee information.
Have Your Front End and Monitor It, Too (ANT303) - AWS re:Invent 2018Amazon Web Services
Amazon Elasticsearch Service (Amazon ES) is both a search solution and a log monitoring solution. In this session, we address both. We build a front-end, PHP web server that provides a search experience on movie data as well as backend monitoring to send Apache web logs, syslogs, and application logs to Amazon ES. We tune the relevance for the search experience and build Kibana visualizations for the log data. In addition, we use security best practices and deploy everything into a VPC.
Deep Dive on Amazon S3 Storage Classes: Creating Cost Efficiencies across You...Amazon Web Services
"Amazon S3 supports a range of storage classes that can help you cost-effectively store data without impacting performance or availability. Each of our storage classes offer different data-access levels, retrieval times, and costs to support various use cases. In this session, Amazon S3 experts dive deep into the different Amazon S3 storage classes, their respective attributes, and when you should use them.
"
Bridging Message Brokers to Cloud-Native Messaging Services (API210-R2) - AWS...Amazon Web Services
Learn how to connect your JMS-based applications to the cloud and integrate them with new cloud-native applications. In this session, we quickly refresh your knowledge about messaging enterprise integration patterns. We then discuss architectural examples to bridge the JMS-based and cloud-native worlds. We work through an example implementation based on Amazon MQ, Amazon SQS, and Amazon SNS. Leave this session with a solid understanding of how to connect existing applications to new cloud-native applications using messaging patterns.
Enhancing Media Workflows with Machine Learning (MAE303) - AWS re:Invent 2018Amazon Web Services
AI/ML is changing the way media companies produce and distribute content. In this workshop, we review many of the ways AI/ML can be applied throughout the entire media production and distribution process. We build an end-to-end metadata enrichment workflow that extracts meaningful metadata from content (audio, video, and images). We then build a solution that uses Amazon Rekognition, Amazon SageMaker, Amazon Transcribe, Amazon Comprehend, and Amazon Mechanical Turk to analyze content, and we use it to enrich a viewing experience and assist with compliance. We also build and train a custom object detection model, which will be used to augment the data that Amazon Rekognition provides. We cover all aspects of AI/ML-based metadata generation, from labeling a dataset, to training and hosting a model, all the way to validating the metadata prior to playout.
Capture Voice of Customer Insights with NLP & Analytics (AIM415-R1) - AWS re:...Amazon Web Services
Understanding your customers is easier today than ever before. Natural language capabilities can capture a wealth of information, such as user sentiment and conversational intent. This workshop teaches you how to build an analytics pipeline that includes natural language processing (NLP) to better understand how to improve the customer experience. Attendees learn how to use AWS services, including Amazon Comprehend and Amazon Transcribe, to process and perform analysis on customer data, such as contact center call recordings.
Democratize Data Preparation for Analytics & Machine Learning A Hands-On Lab ...Amazon Web Services
Machine learning (ML) outcomes are only as good as the data they are built upon. Preparing data for ML is time consuming and cumbersome; “data wrangling” for analytics can consume over 80% of project effort. ML Wrangling Assistant, based on Trifacta running on AWS, streamlines ML applications so teams can focus on the work that matters—creating accurate predictions that improve products, services, and organizational efficiency. In this lab, we cover one of two data preparation use cases. Marketing Analytics analyzes web ads by cleaning and transforming ecommerce transactions in a relational table combined to a clickstream semi-structured log file. Cross-Sell Analytics explores, structures, standardizes, and combines multiple file types (CSV, JSON, Excel) to create a single, consistent view of customers. Final outputs are the categorical features and attributes to train, test, and validate the data sets required by Amazon SageMaker to perform ML modeling.
Resolving NLP Problems Using Amazon SageMaker Algorithms (GPSCT305) - AWS re:...Amazon Web Services
Natural language or text is regularly voted as the most important data type after structured data. This is because text can carry an enormous amount of hidden insight. In this session, we show you how to get started with the natural language processing (NLP) techniques using Amazon SageMaker, a platform to easily build, train, and deploy models at scale. We review all of the NLP-related algorithms available on Amazon SageMaker, including Amazon algorithms (Latent Dirichlet Allocation (LDA), Neural Topic Model (NTM), and Sequence2Sequence (seq2seq), and BlazingText). We dive into the details, and we run through an example Jupyter Notebook that uses these algorithms.
Securing Data in Serverless Applications and Messaging Services (API317-R2) -...Amazon Web Services
This chalk talk walks you through the process of designing a serverless application that secures customer data sent to the cloud. The design uses features recently introduced by Amazon SNS and Amazon SQS, including AWS KMS keys for encrypting messages at rest, and Amazon VPC endpoints powered by AWS PrivateLink for sending messages without traversing the public internet. These techniques are security best practices for systems that deal with private data, such e-commerce orders, candidate resumes, and employee information.
Have Your Front End and Monitor It, Too (ANT303) - AWS re:Invent 2018Amazon Web Services
Amazon Elasticsearch Service (Amazon ES) is both a search solution and a log monitoring solution. In this session, we address both. We build a front-end, PHP web server that provides a search experience on movie data as well as backend monitoring to send Apache web logs, syslogs, and application logs to Amazon ES. We tune the relevance for the search experience and build Kibana visualizations for the log data. In addition, we use security best practices and deploy everything into a VPC.
Deep Dive on Amazon S3 Storage Classes: Creating Cost Efficiencies across You...Amazon Web Services
"Amazon S3 supports a range of storage classes that can help you cost-effectively store data without impacting performance or availability. Each of our storage classes offer different data-access levels, retrieval times, and costs to support various use cases. In this session, Amazon S3 experts dive deep into the different Amazon S3 storage classes, their respective attributes, and when you should use them.
"
Build an Intelligent Multi-Modal User Agent with Voice and NLU (AIM340) - AWS...Amazon Web Services
Sophisticated AI capabilities can help us manage the exploding number of information sources and tools required to perform our daily tasks. In this chalk talk, we describe how intelligent agents can be designed to quickly and efficiently complete tasks delegated by users. To build this intelligent agent, we combine a number of AWS services, such as Amazon Polly, Amazon Lex, Amazon Rekognition, Amazon Sumerian, and Amazon ElastiCache along with other technologies, such as CLIPS and Reinforcement Learning. Come hear us discuss the project’s architecture, implementation, and demo progress made to date.
Enterprise Data Protection with Veritas NetBackup on AWS (STG347) - AWS re:In...Amazon Web Services
Veritas Technologies is an AWS Partner Network (APN) Advanced Technology Partner that addresses information management challenges, including backup and recovery, business continuity, software-defined storage, and information governance to simplify backup and improve efficiency. In this chalk talk, we do a deep dive on Veritas NetBackup, an industry-leading backup software that protects on-premises and Amazon EC2 workloads and provides support for Amazon S3 Standard-Infrequent Access and Amazon Glacier. We also hear from Bell Media, who is utilizing Veritas NetBackup to retain backups long-term on Amazon S3.
Amazon S3 provides a number of different settings to help you secure your data, controls to ensure that those settings remain in place, and features to help you audit all of the above. In this workshop, we walk you through these different capabilities of Amazon S3, presenting scenarios to help you apply them for different security requirements.
Train Models on Amazon SageMaker Using Data Not from Amazon S3 (AIM419) - AWS...Amazon Web Services
Questions often arise about training machine learning models using Amazon SageMaker with data from sources other than Amazon S3. In this chalk talk, we dive deep into training models in real time using data from Amazon DynamoDB or a relational database. We demonstrate how training models with Amazon SageMaker is quick and easy, regardless of the data source.
Tailor Your Alexa Skill Responses to Deliver Truly Personal Experiences (ALX3...Amazon Web Services
Delivering truly personal responses to customers is one of the most engaging features of an Alexa skill. In this session, learn the different approaches and best practices in creating responses that are tailored to each one of your customers. By applying what you learn, you can keep them coming back to your voice experience.
Create Advanced Text Analytics Solutions with NLP - BDA310 - New York AWS Sum...Amazon Web Services
About 80% of data held by an organization is unstructured—such as emails, social media feeds, news articles, and customer feedback—which makes it difficult to analyze and use. NLP and ML can help. Amazon Comprehend is an NLP service that uses ML to find insights and relationships in text. In this session, learn how to easily process, analyze, and visualize data by pairing Amazon Comprehend with Amazon RDS, Amazon Elasticsearch Service, and Amazon Neptune. Also see real-world examples of how customers have built advanced text analytics solutions with Amazon Comprehend.
Best Practices for Building Multi-Region, Active-Active Serverless Applicatio...Amazon Web Services
In this session, we walk through building and deploying a global-scale, multi-region, active-active serverless backend using Amazon Route 53 to route the traffic among AWS Regions, Amazon API Gateway, and AWS Lambda for the backend, and Amazon DynamoDB global tables for handling data storage at a global scale. We provide a demo and a hands-on coding opportunity.
In this session, learn from market-leader Vonage how and why they re-architected their QoS-sensitive, highly available and highly performant legacy real-time communications systems to take advantage of Amazon EC2, Enhanced Networking, Amazon S3, ASG, Amazon RDS, Amazon ElastiCache, AWS Lambda, StepFunctions, Amazon SNS, Amazon SQS, Amazon Kinesis, Amazon EFS, and more. We also learn how Aspect, a multinational leader in call center solutions, used AWS Lambda, Amazon API Gateway, Amazon Kinesis, Amazon ElastiCache, Amazon Cognito, and Application Load Balancer with open-source API development tooling from Swagger, to build a comprehensive, microservices-based solution. Vonage and Aspect share their journey to TCO optimization, global outreach, and agility with best practices and insights.
Build an End-To-End IoT Example with AWS IoT Core (IOT211-R2) - AWS re:Invent...Amazon Web Services
In this session, participate in a hands-on exercise with AWS IoT Core. You begin by leveraging the AWS IoT Device SDKs to securely connect to AWS IoT, then you modify and send sample data over MQTT to AWS IoT Core. Lastly, you learn how to make that data actionable by leveraging the AWS IoT rules engine. By the end of the session, expect to have a solid understanding of how AWS IoT works and how to begin using AWS IoT in your applications.
New AI/ML Solutions with AWS DeepLens & Amazon SageMaker with ConocoPhillips ...Amazon Web Services
ConocoPhillips is exploring the combination of machine vision and machine learning. Four proof of concepts were developed using AWS DeepLens, Amazon SageMaker, Amazon S3, and more. These projects address the security, safety, and inventory associated with upstream field operations. In this session, we describe our successes, challenges, and lessons learned. We also share our ideas for future product improvements.
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.
Private Network Connectivity: Connecting AWS into Public Sector Networks (WPS...Amazon Web Services
Many countries operate separate, private networks for use purely by public sector organizations, which historically have hindered use of the public cloud. In this session, we examine the different architectures available to bridge this gap and answer questions that attendees might have, using examples from the UK and beyond.
Alexa for Device Makers: Create Products with Alexa Built-In Using AVS (ALX30...Amazon Web Services
In this hands-on workshop, learn how to use Alexa Built-In to create products that you can talk to and use to access music, information, control smart-home devices, and all of Alexa's skills. We use the C++-based AVS Device SDK and a Raspberry Pi to access the cloud-based Alexa Voice Service (AVS). Leave this session with your own working prototype and the knowledge to bring your products to market.
Build Deep Learning Applications Using PyTorch and Amazon SageMaker (AIM432-R...Amazon Web Services
In this workshop, learn how to get started with the PyTorch deep learning framework using Amazon SageMaker, a fully managed platform to build, train, and deploy machine learning (ML) models at scale quickly and easily. First, we create a computer vision model using deep neural networks that helps us discover analytical information from our image dataset. Then, we use Amazon Redshift, a fully managed data warehouse, to perform analytics and find business value using the output of our ML model.
Hollywood's Cloud-Based Content Lakes: Modernized Media Archives (MAE203) - A...Amazon Web Services
Content lake architecture can evolve the media workflow by providing efficiency from content security all the way to value-added services, such as machine learning and content monetization. In this session, technical leaders from 21st Century Fox, Warner Bros., and Astro Malaysia discuss the migration of their petabyte-scale video libraries (production and distribution archives) to the cloud in order to increase the customer reach and value of their media archives. Discover some of the lessons learned, the TCO analysis around various different storage tiers, the challenges and best practices from 10s of petabytes ingest, storage, and value-added compute at scale.
Protecting Amazon EC2 Instances, Relational Databases, and NoSQL Workloads (S...Amazon Web Services
For many IT professionals, cloud data protection can be challenging. In this session, we explore options for protecting and restoring your Amazon EC2 instances, relational databases, and NoSQL databases, such as MongoDB and Cassandra. We show you how solutions such as Rubrik Cloud Data Management and Rubrik Datos IO augment your Amazon EC2 backup strategy, including lifecycle management of Amazon EBS snapshots and Amazon Machine Images (AMI), automation and simplification of Amazon EBS volume and file-level restores from Amazon EBS snapshots, and application-consistent backup and recovery for Oracle, Microsoft SQL Server, MongoDB, and Cassandra databases on Amazon EC2. This session is brought to you by AWS partner, Rubrik.
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.
Unleash the Power of Temporary AWS Credentials (a.k.a. IAM roles) (SEC390-R1)...Amazon Web Services
In this chalk talk, we discuss why using temporary security credentials to manage access to your AWS resources is an AWS Identity and Access Management (AWS IAM) best practice. IAM roles help you follow this best practice by delivering and rotating temporary credentials automatically. We discuss the different types of IAM roles, the assume role functionality, and how to author fine-grained trust and access policies that limit the scope of IAM roles. We then show you how to attach IAM roles to your AWS resources, such as Amazon EC2 instances and AWS Lambda functions. We also discuss migrating applications that use long-term AWS access keys to temporary credentials managed by IAM roles.
Machine Learning for the Enterprise, ft. Sony Interactive Entertainment (ENT2...Amazon Web Services
Machine learning is powering innovation across industries, including media & entertainment, healthcare, finance, and many more. In this session, representatives from AWS and Sony Interactive Entertainment discuss building real-world scalable enterprise solutions with machine learning using Amazon SageMaker. Join us as we talk about managing large-scale systems and processes to get more value from data at any scale, with examples from Sony and AWS.
DevOps Concepts for Data Science (DEV347-R2) - AWS re:Invent 2018Amazon Web Services
DevOps and Data Science? How does that work? In software teams where innovation is a priority, DevOps can be an accelerator. In data science and machine learning, there are a number of factors that increase complexity of systems and thus the complexity of DevOps. This session will touch on fundamental concepts in data science such as data management, ETL, modeling, and model validation, and open discussion around some ways that common tools and processes can be used to decouple and stabilize workflows to accelerate research.
Increase the Value of Video with ML & Media Services - SRV322 - Toronto AWS S...Amazon Web Services
Learn how to generate metadata from your media and make videos searchable by objects, people, activities, dialog, and more by using Amazon Machine Learning tools. Learn how to make videos more valuable and enable a wide range of use cases, including searching and indexing your video library. Learn how to use AWS Elemental MediaConvert to create video highlight clips from keywords, automatically or on demand, for content like sports videos and from sources like nature cameras or security feeds. Finally, learn how to use Amazon Transcribe and Amazon Translate with AWS Media Services to produce captions and translations to expand audience reach for corporate videos, marketing and sales material, and training videos.
Customizing Data Lakes to Work for Your Enterprise with Sysco (STG340) - AWS ...Amazon Web Services
Data lakes are helping enterprises of all sizes and industries make the most of their data. However, building a data lake requires consideration of your goals and an understanding of data lakes, including data ingestion, data consumption, and usability layers. In this chalk talk, AWS experts and representatives from Sysco, a Fortune 50 company and leader in food distribution and marketing, discuss parts of a data lake, design considerations, and the pros and cons of different architectural designs. They share guidance around data tracking, costs, user access, synchronization, and data integrity so that your data lake complies with governance requirements and works towards your data goals. Sysco representatives share their data lake experiences, best practices, and lessons learned. We highlight Amazon S3 and S3 Select, Amazon Athena, Amazon EMR, Amazon EC2, and Amazon Redshift Spectrum.
Build an Intelligent Multi-Modal User Agent with Voice and NLU (AIM340) - AWS...Amazon Web Services
Sophisticated AI capabilities can help us manage the exploding number of information sources and tools required to perform our daily tasks. In this chalk talk, we describe how intelligent agents can be designed to quickly and efficiently complete tasks delegated by users. To build this intelligent agent, we combine a number of AWS services, such as Amazon Polly, Amazon Lex, Amazon Rekognition, Amazon Sumerian, and Amazon ElastiCache along with other technologies, such as CLIPS and Reinforcement Learning. Come hear us discuss the project’s architecture, implementation, and demo progress made to date.
Enterprise Data Protection with Veritas NetBackup on AWS (STG347) - AWS re:In...Amazon Web Services
Veritas Technologies is an AWS Partner Network (APN) Advanced Technology Partner that addresses information management challenges, including backup and recovery, business continuity, software-defined storage, and information governance to simplify backup and improve efficiency. In this chalk talk, we do a deep dive on Veritas NetBackup, an industry-leading backup software that protects on-premises and Amazon EC2 workloads and provides support for Amazon S3 Standard-Infrequent Access and Amazon Glacier. We also hear from Bell Media, who is utilizing Veritas NetBackup to retain backups long-term on Amazon S3.
Amazon S3 provides a number of different settings to help you secure your data, controls to ensure that those settings remain in place, and features to help you audit all of the above. In this workshop, we walk you through these different capabilities of Amazon S3, presenting scenarios to help you apply them for different security requirements.
Train Models on Amazon SageMaker Using Data Not from Amazon S3 (AIM419) - AWS...Amazon Web Services
Questions often arise about training machine learning models using Amazon SageMaker with data from sources other than Amazon S3. In this chalk talk, we dive deep into training models in real time using data from Amazon DynamoDB or a relational database. We demonstrate how training models with Amazon SageMaker is quick and easy, regardless of the data source.
Tailor Your Alexa Skill Responses to Deliver Truly Personal Experiences (ALX3...Amazon Web Services
Delivering truly personal responses to customers is one of the most engaging features of an Alexa skill. In this session, learn the different approaches and best practices in creating responses that are tailored to each one of your customers. By applying what you learn, you can keep them coming back to your voice experience.
Create Advanced Text Analytics Solutions with NLP - BDA310 - New York AWS Sum...Amazon Web Services
About 80% of data held by an organization is unstructured—such as emails, social media feeds, news articles, and customer feedback—which makes it difficult to analyze and use. NLP and ML can help. Amazon Comprehend is an NLP service that uses ML to find insights and relationships in text. In this session, learn how to easily process, analyze, and visualize data by pairing Amazon Comprehend with Amazon RDS, Amazon Elasticsearch Service, and Amazon Neptune. Also see real-world examples of how customers have built advanced text analytics solutions with Amazon Comprehend.
Best Practices for Building Multi-Region, Active-Active Serverless Applicatio...Amazon Web Services
In this session, we walk through building and deploying a global-scale, multi-region, active-active serverless backend using Amazon Route 53 to route the traffic among AWS Regions, Amazon API Gateway, and AWS Lambda for the backend, and Amazon DynamoDB global tables for handling data storage at a global scale. We provide a demo and a hands-on coding opportunity.
In this session, learn from market-leader Vonage how and why they re-architected their QoS-sensitive, highly available and highly performant legacy real-time communications systems to take advantage of Amazon EC2, Enhanced Networking, Amazon S3, ASG, Amazon RDS, Amazon ElastiCache, AWS Lambda, StepFunctions, Amazon SNS, Amazon SQS, Amazon Kinesis, Amazon EFS, and more. We also learn how Aspect, a multinational leader in call center solutions, used AWS Lambda, Amazon API Gateway, Amazon Kinesis, Amazon ElastiCache, Amazon Cognito, and Application Load Balancer with open-source API development tooling from Swagger, to build a comprehensive, microservices-based solution. Vonage and Aspect share their journey to TCO optimization, global outreach, and agility with best practices and insights.
Build an End-To-End IoT Example with AWS IoT Core (IOT211-R2) - AWS re:Invent...Amazon Web Services
In this session, participate in a hands-on exercise with AWS IoT Core. You begin by leveraging the AWS IoT Device SDKs to securely connect to AWS IoT, then you modify and send sample data over MQTT to AWS IoT Core. Lastly, you learn how to make that data actionable by leveraging the AWS IoT rules engine. By the end of the session, expect to have a solid understanding of how AWS IoT works and how to begin using AWS IoT in your applications.
New AI/ML Solutions with AWS DeepLens & Amazon SageMaker with ConocoPhillips ...Amazon Web Services
ConocoPhillips is exploring the combination of machine vision and machine learning. Four proof of concepts were developed using AWS DeepLens, Amazon SageMaker, Amazon S3, and more. These projects address the security, safety, and inventory associated with upstream field operations. In this session, we describe our successes, challenges, and lessons learned. We also share our ideas for future product improvements.
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.
Private Network Connectivity: Connecting AWS into Public Sector Networks (WPS...Amazon Web Services
Many countries operate separate, private networks for use purely by public sector organizations, which historically have hindered use of the public cloud. In this session, we examine the different architectures available to bridge this gap and answer questions that attendees might have, using examples from the UK and beyond.
Alexa for Device Makers: Create Products with Alexa Built-In Using AVS (ALX30...Amazon Web Services
In this hands-on workshop, learn how to use Alexa Built-In to create products that you can talk to and use to access music, information, control smart-home devices, and all of Alexa's skills. We use the C++-based AVS Device SDK and a Raspberry Pi to access the cloud-based Alexa Voice Service (AVS). Leave this session with your own working prototype and the knowledge to bring your products to market.
Build Deep Learning Applications Using PyTorch and Amazon SageMaker (AIM432-R...Amazon Web Services
In this workshop, learn how to get started with the PyTorch deep learning framework using Amazon SageMaker, a fully managed platform to build, train, and deploy machine learning (ML) models at scale quickly and easily. First, we create a computer vision model using deep neural networks that helps us discover analytical information from our image dataset. Then, we use Amazon Redshift, a fully managed data warehouse, to perform analytics and find business value using the output of our ML model.
Hollywood's Cloud-Based Content Lakes: Modernized Media Archives (MAE203) - A...Amazon Web Services
Content lake architecture can evolve the media workflow by providing efficiency from content security all the way to value-added services, such as machine learning and content monetization. In this session, technical leaders from 21st Century Fox, Warner Bros., and Astro Malaysia discuss the migration of their petabyte-scale video libraries (production and distribution archives) to the cloud in order to increase the customer reach and value of their media archives. Discover some of the lessons learned, the TCO analysis around various different storage tiers, the challenges and best practices from 10s of petabytes ingest, storage, and value-added compute at scale.
Protecting Amazon EC2 Instances, Relational Databases, and NoSQL Workloads (S...Amazon Web Services
For many IT professionals, cloud data protection can be challenging. In this session, we explore options for protecting and restoring your Amazon EC2 instances, relational databases, and NoSQL databases, such as MongoDB and Cassandra. We show you how solutions such as Rubrik Cloud Data Management and Rubrik Datos IO augment your Amazon EC2 backup strategy, including lifecycle management of Amazon EBS snapshots and Amazon Machine Images (AMI), automation and simplification of Amazon EBS volume and file-level restores from Amazon EBS snapshots, and application-consistent backup and recovery for Oracle, Microsoft SQL Server, MongoDB, and Cassandra databases on Amazon EC2. This session is brought to you by AWS partner, Rubrik.
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.
Unleash the Power of Temporary AWS Credentials (a.k.a. IAM roles) (SEC390-R1)...Amazon Web Services
In this chalk talk, we discuss why using temporary security credentials to manage access to your AWS resources is an AWS Identity and Access Management (AWS IAM) best practice. IAM roles help you follow this best practice by delivering and rotating temporary credentials automatically. We discuss the different types of IAM roles, the assume role functionality, and how to author fine-grained trust and access policies that limit the scope of IAM roles. We then show you how to attach IAM roles to your AWS resources, such as Amazon EC2 instances and AWS Lambda functions. We also discuss migrating applications that use long-term AWS access keys to temporary credentials managed by IAM roles.
Machine Learning for the Enterprise, ft. Sony Interactive Entertainment (ENT2...Amazon Web Services
Machine learning is powering innovation across industries, including media & entertainment, healthcare, finance, and many more. In this session, representatives from AWS and Sony Interactive Entertainment discuss building real-world scalable enterprise solutions with machine learning using Amazon SageMaker. Join us as we talk about managing large-scale systems and processes to get more value from data at any scale, with examples from Sony and AWS.
DevOps Concepts for Data Science (DEV347-R2) - AWS re:Invent 2018Amazon Web Services
DevOps and Data Science? How does that work? In software teams where innovation is a priority, DevOps can be an accelerator. In data science and machine learning, there are a number of factors that increase complexity of systems and thus the complexity of DevOps. This session will touch on fundamental concepts in data science such as data management, ETL, modeling, and model validation, and open discussion around some ways that common tools and processes can be used to decouple and stabilize workflows to accelerate research.
Increase the Value of Video with ML & Media Services - SRV322 - Toronto AWS S...Amazon Web Services
Learn how to generate metadata from your media and make videos searchable by objects, people, activities, dialog, and more by using Amazon Machine Learning tools. Learn how to make videos more valuable and enable a wide range of use cases, including searching and indexing your video library. Learn how to use AWS Elemental MediaConvert to create video highlight clips from keywords, automatically or on demand, for content like sports videos and from sources like nature cameras or security feeds. Finally, learn how to use Amazon Transcribe and Amazon Translate with AWS Media Services to produce captions and translations to expand audience reach for corporate videos, marketing and sales material, and training videos.
Customizing Data Lakes to Work for Your Enterprise with Sysco (STG340) - AWS ...Amazon Web Services
Data lakes are helping enterprises of all sizes and industries make the most of their data. However, building a data lake requires consideration of your goals and an understanding of data lakes, including data ingestion, data consumption, and usability layers. In this chalk talk, AWS experts and representatives from Sysco, a Fortune 50 company and leader in food distribution and marketing, discuss parts of a data lake, design considerations, and the pros and cons of different architectural designs. They share guidance around data tracking, costs, user access, synchronization, and data integrity so that your data lake complies with governance requirements and works towards your data goals. Sysco representatives share their data lake experiences, best practices, and lessons learned. We highlight Amazon S3 and S3 Select, Amazon Athena, Amazon EMR, Amazon EC2, and Amazon Redshift Spectrum.
Increase the Value of Video with ML & Media Services - SRV322 - Chicago AWS S...Amazon Web Services
Learn how to generate metadata from your media and make videos searchable by objects, people, activities, dialog, and more by using Amazon Machine Learning tools. Learn how to make videos more valuable and enable a wide range of use cases, including searching and indexing your video library. Learn how to use AWS Elemental MediaConvert to create video highlight clips from keywords, automatically or on demand, for content like sports videos and from sources like nature cameras or security feeds. Finally, learn how to use Amazon Transcribe and Amazon Translate with AWS Media Services to produce captions and translations to expand audience reach for corporate videos, marketing and sales material, and training videos.
Increase the Value of Video with ML & Media Services - SRV322 - Anaheim AWS S...Amazon Web Services
In this session, learn how to generate metadata from your media and make your videos searchable by objects, people, activities, dialog, and more by using Amazon Machine Learning tools. Also learn how to make videos more valuable and enable a wide range of use cases, including searching and indexing your video library. We show you how to use AWS Elemental MediaConvert to create video highlight clips from keywords, automatically or on demand, for content like sports videos and from sources like nature cameras or security feeds. Finally, we cover how to use Amazon Transcribe and Amazon Translate with AWS Media Services to produce captions and translations to expand audience reach for corporate videos, marketing and sales material, and training videos.
Increase the Value of Video with Machine Learning & Media Services - SRV322 -...Amazon Web Services
In this session, learn how to generate metadata from media, and make videos searchable by objects, people, activities, dialogs, and more by using Amazon Machine Learning (Amazon ML) tools. Learn how to make videos more valuable and enable a wide range of use cases, including searching and indexing video libraries. Learn how to use AWS Elemental MediaConvert to create video highlight clips from keywords, automatically or on demand, for content like sports videos and from sources like nature cameras or security feeds. Finally, use Amazon Transcribe and Amazon Translate with AWS Media Services to produce captions and translations to expand audience reach for corporate videos, marketing and sales material, and training videos.
AWS supports a robust suite of tools and services that makes analyzing and processing large amounts of data in the cloud faster and more efficient. In this builders session, AWS storage and data experts guide you through Amazon S3, Amazon Glacier, and our query-in-place services, such as Amazon S3 Select, Amazon Glacier Select, Amazon Athena, and Amazon Redshift Spectrum. We also provide best practices around using them with other analytics services, like Amazon EMR and AWS Glue to build data lakes and deploy other analytics solutions. Understanding of a data lake construct, AWS storage services, and AWS analytics tools is recommended.
AWS Immersion Day - Image Data Insights & Analytics Specialist Session - June...Amazon Web Services
Learn how to incorporate video data and analytics into your data management and business decision process. Discover how industry leaders are using AWS to do the heavy lifting with image data and innovating quickly. Our specialists will cover common issues and provide best practices from using IoT devices to collect data to training a ML model to using these models on the edge without network connectivity.
Voice-Powered Serverless Analytics (SRV240-R1) - AWS re:Invent 2018Amazon Web Services
As a business manager, imagine asking Alexa within a skill that was specifically built for your organization for key insights into your business, such as “Who is our largest customer in Northern California?” or “How has our sales volume grown between Q1 and Q2 in our Asian markets?” In this workshop, you build an Alexa skill that queries metrics from a data lake that you define. The goal is for you to understand how to uncover key performance indicators (KPIs) from a dataset, build and automate queries with AWS Lambda, and access them via Alexa voice-enabled devices. Startups can make available voice-powered analytics to query at any time, and enterprises can deliver these types of solutions to stakeholders so they can have easy access to the business KPIs that are top of mind.
AWS Storage Leadership Session: What's New in Amazon S3, Amazon EFS, Amazon E...Amazon Web Services
Mai-Lan Tomsen Bukovec, VP of Amazon S3, introduces the latest innovations across all AWS storage services. In this keynote address, we announce new storage capabilities, and we talk about features and services that make AWS storage unique. We focus on new innovations in object storage, file storage, block storage, and data transfer services. You also hear from executives from companies that are major AWS storage customers, Sony and Expedia, about how they're using AWS storage to create a competitive advantage in their businesses.
Bridge the Storage Gap: Hybrid Media Workflows with AWS Storage Gateway (STG3...Amazon Web Services
Media and entertainment companies are navigating their own digital transformation strategies, and they want to make their editors, artists, and VFX compositing teams comfortable with using the cloud for their production workflows. Companies such as Disney and Netflix are on track to spend over $20B in original content this year and they need ways to get their content in front of audiences as fast as possible. In this chalk talk, learn how AWS Storage Gateway can help studios and other media and entertainment firms bridge the storage gap between the cloud and their on-premises editorial environments.
Building an end to end image recognition service - Tel Aviv Summit 2018Amazon Web Services
In this session, we’ll learn how to build and deploy end to end solutions for ingesting and processing computer vision solutions, using machine learning models connected to live video streams, and getting insights such as face detection and object analysis. At the end of the session developers of all skill levels will be able to build their own deep learning powered, computer-vision applications. Attendees will learn how to experiment with different projects for face detection, object recognition and other video-based AWS Machine Learning services.
As your use of the AWS platform matures and evolves you need to be continuously looking at ways to streamline IT operations to maximise your business innovation, outcomes and maintaining that competitive edge.
In this advanced technical session we will provide insights on server-less IT ops designs, building end-to-end automation systems, implementing robust security controls, and automated response to IT behavioural analysis to ensure that your operations and management of the AWS Platform is designed to deliver scale, resiliency, security, and is cost optimised. Be prepared for a technically deep session on AWS technology.
Speaker: Dean Samuels, Black Belt Ninja Master, Amazon Web Services
Build Machine Learning Solutions on Data Lakes (ARC321) - AWS re:Invent 2018Amazon Web Services
As customers move from building data lakes and analytics on AWS to building machine learning solutions, one of their biggest challenges is getting visibility into their data for feature engineering and data format conversions for using Amazon SageMaker. In this workshop, we demonstrate best practices and build data pipelines for training data using Amazon Kinesis Data Firehose, AWS Glue, and Amazon SageMaker, and then we use Amazon SageMaker for inference. Important: This is a hands-on session where you need to already have an AWS account that can run AWS CloudFormation, AWS Lambda, Amazon DynamoDB, Amazon Kinesis, AWS Glue, AWS Database Migration Service (AWS DMS), Amazon S3, and Amazon SageMaker.
Evolution of media workflows aided by Machine Learning- AWS Summit Cape Town ...Amazon Web Services
Speaker: Usman Shakeel, AWS
Level: 200
This session looks at the evolving M&E workloads from Content creation workflows, to smart Supply Chains and Archives and personalization around content delivery. With this evolution we also discuss AWS machine learning tool set and its application towards this evolution of M&E workloads. Learn some of the cool use cases and architecture patterns using AWS ML tool set on how studios, networks and creative service companies as well as broadcasters are using them from boosting creative productivity, efficiencies and creativity in production planning, animation, visual effects, editorial, post and localization. We’ll see what AI and ML apps are capable of doing right now and glimpse their long-term potential to alter workflows.
In this workshop, learn how to create a cloud-based business intelligence platform and deliver dynamic insights through a custom Alexa Skill. Together, we architect a data analytics platform using Amazon S3, Amazon Athena, Amazon QuickSight, Amazon DynamoDB, Amazon CloudWatch on the backend, and a voice-based user interface through a private Alexa Skill deployed via Alexa for Business on the front end.
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.