[NEW LAUNCH!] [REPEAT 1] Amazon FSx for Lustre: How to build and deploy file systems for compute-intensive workloads, HPC, and machine learning applications (STG320-R1) - AWS re:Invent 2018
If you have compute-intensive workloads like high-performance computing, machine learning, and media processing then this is the workshop for you. Our new file storage service, Amazon FSx for Lustre, provides high-performance storage with fully managed Lustre file systems that can deliver hundreds of gigabytes of throughput and consistent low latencies. You will learn how to spin up an FSx for Lustre file system in minutes, feed data to it from an S3 data lake automatically, run analyses while periodically writing results back to S3, and then spin down the file system once the workload is finished.
AWS re:Invent è l’annuale conferenza globale di Amazon Web Services. Ogni anno presentiamo più di 1000 sessioni tecniche, workshops e hackathon che coprono argomenti chiave inerenti a AWS e che illustrano le tecnologie che AWS sviluppa e introduce. In questo webinar vedremo un riepilogo degli annunci e delle novità presentate a Las Vegas e diversi casi d’uso per i principali servizi introdotti.
Migrating Data to the Cloud: Exploring Your Options from AWS (STG205-R1) - AW...Amazon Web Services
The document discusses various options for migrating data to the AWS cloud, including AWS Direct Connect for private connectivity, AWS DataSync for online data transfer, the AWS Snowball and Snowball Edge devices for offline data transfer of large volumes, AWS Storage Gateway for hybrid storage, AWS Transfer for SFTP, and Amazon S3 Transfer Acceleration. It provides overviews and use cases for each service and how they can help with migrating and managing data in hybrid cloud environments.
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.
Alexa, Ask Jarvis to Create a Serverless App for Me (SRV315) - AWS re:Invent ...Amazon Web Services
Today, we can build and deploy a serverless application in minutes without having to write a line of code using pre-built AWS CloudFormation templates, or services such as the AWS Serverless Application Repository. But can we push the limits even more? In this workshop, we use the Serverless Application Repository combined with Amazon Alexa to create Iron Man's Jarvis look-a-like skill. You learn hands-on with Alexa, Amazon Lex, Amazon SageMaker, and the AWS Serverless Application Repository.
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.
[NEW LAUNCH!] Introducing Amazon EC2 A1 Instances Based on the Arm Architectu...Amazon Web Services
The document introduces Amazon EC2 A1 instances, which are powered by AWS Graviton processors featuring Arm architecture. These instances offer lower costs than other EC2 instances due to improved hardware efficiency. Customer SmugMug discussed migrating their workload to A1 instances, finding a 40% reduction in cost per core. The software ecosystem to support A1 instances is also expanding to include options like Amazon Linux 2, Ubuntu, and Red Hat.
Save up to 90% on Big Data and Machine Learning Workloads with Spot Instances...Amazon Web Services
The document discusses how to use Amazon EC2 Spot Instances to save up to 90% on big data and machine learning workloads. It explains that Spot Instances provide access to unused Amazon EC2 computing capacity at steep discounts compared to on-demand prices. It then provides guidance on how to best utilize Spot Instances for both training machine learning models and deploying trained models, including using checkpointing and Auto Scaling to handle potential interruptions of Spot Instance availability.
Build a Searchable Media Library & Moderate Content at Scale Using Machine Le...Amazon Web Services
Companies have to process, analyze, and extract meaning from ever-growing volumes of audio, image, and video data. Automating media workflows, such as image and video indexing or manual transcription for closed captions, can help you scale the growth of your media library and save time from manual, error-prone work. In this workshop, you learn how to automate workflows using the Media Analysis Solution, which includes Amazon Rekognition, Amazon Transcribe, and Amazon Comprehend. You learn how to extract metadata from media files and create a searchable library of metadata.
AWS re:Invent è l’annuale conferenza globale di Amazon Web Services. Ogni anno presentiamo più di 1000 sessioni tecniche, workshops e hackathon che coprono argomenti chiave inerenti a AWS e che illustrano le tecnologie che AWS sviluppa e introduce. In questo webinar vedremo un riepilogo degli annunci e delle novità presentate a Las Vegas e diversi casi d’uso per i principali servizi introdotti.
Migrating Data to the Cloud: Exploring Your Options from AWS (STG205-R1) - AW...Amazon Web Services
The document discusses various options for migrating data to the AWS cloud, including AWS Direct Connect for private connectivity, AWS DataSync for online data transfer, the AWS Snowball and Snowball Edge devices for offline data transfer of large volumes, AWS Storage Gateway for hybrid storage, AWS Transfer for SFTP, and Amazon S3 Transfer Acceleration. It provides overviews and use cases for each service and how they can help with migrating and managing data in hybrid cloud environments.
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.
Alexa, Ask Jarvis to Create a Serverless App for Me (SRV315) - AWS re:Invent ...Amazon Web Services
Today, we can build and deploy a serverless application in minutes without having to write a line of code using pre-built AWS CloudFormation templates, or services such as the AWS Serverless Application Repository. But can we push the limits even more? In this workshop, we use the Serverless Application Repository combined with Amazon Alexa to create Iron Man's Jarvis look-a-like skill. You learn hands-on with Alexa, Amazon Lex, Amazon SageMaker, and the AWS Serverless Application Repository.
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.
[NEW LAUNCH!] Introducing Amazon EC2 A1 Instances Based on the Arm Architectu...Amazon Web Services
The document introduces Amazon EC2 A1 instances, which are powered by AWS Graviton processors featuring Arm architecture. These instances offer lower costs than other EC2 instances due to improved hardware efficiency. Customer SmugMug discussed migrating their workload to A1 instances, finding a 40% reduction in cost per core. The software ecosystem to support A1 instances is also expanding to include options like Amazon Linux 2, Ubuntu, and Red Hat.
Save up to 90% on Big Data and Machine Learning Workloads with Spot Instances...Amazon Web Services
The document discusses how to use Amazon EC2 Spot Instances to save up to 90% on big data and machine learning workloads. It explains that Spot Instances provide access to unused Amazon EC2 computing capacity at steep discounts compared to on-demand prices. It then provides guidance on how to best utilize Spot Instances for both training machine learning models and deploying trained models, including using checkpointing and Auto Scaling to handle potential interruptions of Spot Instance availability.
Build a Searchable Media Library & Moderate Content at Scale Using Machine Le...Amazon Web Services
Companies have to process, analyze, and extract meaning from ever-growing volumes of audio, image, and video data. Automating media workflows, such as image and video indexing or manual transcription for closed captions, can help you scale the growth of your media library and save time from manual, error-prone work. In this workshop, you learn how to automate workflows using the Media Analysis Solution, which includes Amazon Rekognition, Amazon Transcribe, and Amazon Comprehend. You learn how to extract metadata from media files and create a searchable library of metadata.
Configuration Management and Service Discovery with AWS Lambda (SRV338-R1) - ...Amazon Web Services
Your system is composed of highly decoupled, independent, fast, and modular microservices. But how can they share common configurations, dynamic endpoints, database references, and properly rotate secrets? Based on the size and complexity of your serverless system, you may use AWS Lambda environment variables, AWS Systems Manager's Parameter Store, and the recently announced AWS Secrets Manager. In this session, we showcase the best use cases for each solution, as well as corresponding best practices to achieve the highest standards for security and performance.
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.
Using Containers and Serverless to Deploy Microservices (ARC214) - AWS re:Inv...Amazon Web Services
The document discusses options for architecting microservices using containers and serverless architectures on AWS. It explores the benefits and trade-offs of container platforms like ECS, EKS and Fargate versus serverless platforms like AWS Lambda. It provides considerations for selecting between containers and serverless based on needs like compute requirements, data handling, demand predictability, control and operational complexity. It also notes hybrid approaches using services like API Gateway, AppSync and X-Ray for distributed systems.
[NEW LAUNCH!] Amazon FSx for Lustre: Introducing a new fully managed high-per...Amazon Web Services
This document discusses Amazon FSx for Lustre, a fully managed parallel file system service on AWS. It provides massively scalable performance for compute-intensive workloads and seamlessly integrates with data stored in Amazon S3. FSx for Lustre simplifies running high performance file systems on AWS by making them fully managed, easy to set up and operate, and optimized for cost. The presentation includes demos of FSx for Lustre loading data from S3 and generating files at high throughput and speed.
[NEW LAUNCH!] Introducing Amazon SageMaker RL - Build and Train Reinforcement...Amazon Web Services
Reinforcement Learning is an exciting area within machine learning that enables development of many intelligent applications such as autonomous vehicles and robots. The applications with Reinforcement Learning can span across many areas including energy management, financial portfolio management, operations research, natural language processing, and many more. In this interactive workshop, you will learn the basics of Reinforcement Learning (RL) and how you can build and train RL models with the newly announced Amazon SageMaker RL. We will model a simulation environment to represent real-world problems. Further, we will train RL models in this environment and tune them to obtain the required results. By the end of this workshop, you will become familiar with Reinforcement Learning and be able to use SageMaker RL for your own business problems to build intelligent applications.
Overview of the New Amazon EC2 Instances with AMD EPYC (CMP385-R1) - AWS re:I...Amazon Web Services
Learn about new the Amazon EC2 instances that offer AMD EPYC CPUs. We provide a technical overview and discuss how the new M5a, R5a, and T3a instance types fit into the Amazon EC2 product family. We then deep dive into which workloads customers should use the new instances to better optimize their utilization and costs.
What Can Your Logs Tell You? (ANT215) - AWS re:Invent 2018Amazon Web Services
Everyone has logs. They’re not the most exciting data that your systems generate, but often, they are the most useful. Across the board, we see customers using Amazon Elasticsearch Service (Amazon ES) to ingest, analyze, and search their log data. In this chalk talk, we discuss how to get your data into Amazon ES, and how to use Kibana to best effect to pull the information you need from the logs you’re generating.
[NEW LAUNCH!] Introducing Amazon Managed Streaming for Kafka (Amazon MSK) (AN...Amazon Web Services
Discover the power of running Apache Kafka on a fully managed AWS service. In this session, we describe how Amazon Managed Streaming for Kafka (Amazon MSK) runs Apache Kafka clusters for you, demo Amazon MSK and a migration, show you how to get started, and walk through other important details about the new service.
Building Your Own ML Application with AWS Lambda and Amazon SageMaker (SRV404...Amazon Web Services
In this workshop, we step through the process of deploying and hosting machine learning (ML) models with AWS Lambda and get on-demand inferences. Given a demonstrative dataset, we build and train a simple ML classification model with Amazon SageMaker. Then, we host this model in an AWS Lambda function and expose an inference endpoint through Amazon API Gateway. Finally, we build a pipeline for automating model deployment to Lambda leveraging AWS CodeBuild, AWS CodeDeploy, and AWS CodePipeline.
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Take advantage of serverless technologies for artificial intelligence (AI) by making a prediction on the fly. There is no model hosting and no servers to maintain. In this session, we show how to train a model in scikit-learn, an open source machine learning library for Python. Then we load and call the trained model from an AWS Lambda function, and finally we demonstrate how to load the library and send the data for prediction.
Querying Data in Place with AWS Object Storage Features and Analytics Tools (...Amazon Web Services
AWS offers tools and services that make analyzing and processing petabytes of data in the cloud faster, simpler, and more cost effective. In this chalk talk, AWS experts provide an overview of our querying data-in-place services, such as Amazon S3 Select, Amazon Glacier Select, Amazon Athena, and Amazon Redshift Spectrum. We explore best practices around using them with other analytics services (like Amazon EMR and AWS Glue) and third-party tools to build data lakes in Amazon S3 and Amazon Glacier and deploy other analytics solutions. Our AWS experts also provide sample use cases.
Accelerate Your Analytic Queries with Amazon Aurora Parallel Query (DAT362) -...Amazon Web Services
Amazon Aurora with MySQL compatibility includes several features to improve query performance, while still maintaining full MySQL compatibility. One such feature is Parallel Query, which provides faster analytic queries over current data by pushing query processing down to thousands of CPUs in the storage layer, achieving performance gains of up to two orders of magnitude. Learn how to take advantage of this and other recent Aurora features to implement high performance distributed queries for your MySQL-based applications.
Scaling Fantasy Sports Platform at 3M Requests/Minute with ElastiCache & Auro...Amazon Web Services
The document discusses Dream11, a fantasy sports platform that saw huge traffic spikes during cricket matches. To handle the traffic, which reached over 3 million requests per minute, Dream11 transitioned to a microservices architecture using Amazon ElastiCache, Aurora, and other AWS services. This helped improve performance and allowed Dream11 to successfully handle traffic for the 2018 Indian Premier League cricket season with high availability.
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.
In this workshop, learn how to create a serverless data lake architecture. Understand how to ingest data at scale from multiple data sources, how to transform the data, and how to catalog it to make it available for querying using a variety of tools. Also learn how to set up governance and data quality controls.
Speakers:
Rajanikanth Bhargava Chilakapati - Solutions Architect, AWS
Karl Hart - Solutions Architect, AWS
John Pignata - Startup Solutions Architect, AWS
Migrating Real-Time Sports Scores to the Cloud via Low-Latency Messaging (API...Amazon Web Services
In this session, learn how media company Turner Broadcasting delivers real-time sports scores to high-profile sites like the NCAA and PGA using Amazon MQ. Gain a deeper understanding of how Turner migrated from their on-premises message broker to Amazon MQ, and was able to preserve the low-latency messaging expected by their customers. Expect to leave with insights on the migration process, including the surprisingly fast timelines, and the benefits of a managed message broker service.
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.
Deep Dive on Amazon Elastic File System (Amazon EFS) (STG301-R1) - AWS re:Inv...Amazon Web Services
In this session, we explore the world's first cloud-scale file system and its targeted use cases. Learn about Amazon Elastic File System (Amazon EFS), its features and benefits, how to identify applications that are appropriate to use with Amazon EFS, and details about its performance and security models. The target audience is security administrators, application developers, and application owners who operate or build file-based applications.
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.
Introducing AWS DataSync - Simplify, automate, and accelerate online data tra...Amazon Web Services
SFTP is used for the exchange of data across many industries, including financial services, healthcare, and retail. In this session, we will introduce you to AWS Transfer for SFTP, a service that helps you easily migrate file transfer workflows to AWS, without needing to modify applications or manage SFTP servers. We will demonstrate the product and talk about how to migrate your users so they continue to use their existing SFTP clients and credentials, while the data they access is stored in S3. You will also learn how FINRA is using this new service in conjunction with their Data Lake on AWS.N/A
Got Files? We Got You Covered! Deploy Your File Workloads Quickly & Easily wi...Amazon Web Services
AWS offers fully managed file system services that enable you to quickly and simply lift and shift or build new applications that access file data in the AWS Cloud. In this session, join Wayne Duso, the leader of file storage, hybrid-edge storage, and data transport services, to learn about our full set of file services and latest launches. Learn all about file storage, and get firsthand input on how you can accelerate your journey to AWS as you move from on-premises or do-it-yourself implementations to fully managed file storage solutions. Hear how AWS file storage solutions enabled LoanLogics to migrate its applications to the cloud, enabling better scalability, performance, and availability. Also discover why customers choose AWS file systems for migrating their mission-critical enterprise applications and compute-intensive workloads to deliver the performance they need in a cost-effective way, saving time and money.
Optimizing Storage for Enterprise Workloads and Migrations (STG202) - AWS re:...Amazon Web Services
In this session, we focus on best practices for AWS block and file storage when supporting enterprise workloads (like SAP, Oracle, Microsoft applications, and home directories). We discuss migrating mission-critical workload data, selecting volumes or file systems, optimizing performance, and designing for durability and availability. We also review optimizing for cost to ensure that your lift-and-shift project is a success.
Configuration Management and Service Discovery with AWS Lambda (SRV338-R1) - ...Amazon Web Services
Your system is composed of highly decoupled, independent, fast, and modular microservices. But how can they share common configurations, dynamic endpoints, database references, and properly rotate secrets? Based on the size and complexity of your serverless system, you may use AWS Lambda environment variables, AWS Systems Manager's Parameter Store, and the recently announced AWS Secrets Manager. In this session, we showcase the best use cases for each solution, as well as corresponding best practices to achieve the highest standards for security and performance.
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.
Using Containers and Serverless to Deploy Microservices (ARC214) - AWS re:Inv...Amazon Web Services
The document discusses options for architecting microservices using containers and serverless architectures on AWS. It explores the benefits and trade-offs of container platforms like ECS, EKS and Fargate versus serverless platforms like AWS Lambda. It provides considerations for selecting between containers and serverless based on needs like compute requirements, data handling, demand predictability, control and operational complexity. It also notes hybrid approaches using services like API Gateway, AppSync and X-Ray for distributed systems.
[NEW LAUNCH!] Amazon FSx for Lustre: Introducing a new fully managed high-per...Amazon Web Services
This document discusses Amazon FSx for Lustre, a fully managed parallel file system service on AWS. It provides massively scalable performance for compute-intensive workloads and seamlessly integrates with data stored in Amazon S3. FSx for Lustre simplifies running high performance file systems on AWS by making them fully managed, easy to set up and operate, and optimized for cost. The presentation includes demos of FSx for Lustre loading data from S3 and generating files at high throughput and speed.
[NEW LAUNCH!] Introducing Amazon SageMaker RL - Build and Train Reinforcement...Amazon Web Services
Reinforcement Learning is an exciting area within machine learning that enables development of many intelligent applications such as autonomous vehicles and robots. The applications with Reinforcement Learning can span across many areas including energy management, financial portfolio management, operations research, natural language processing, and many more. In this interactive workshop, you will learn the basics of Reinforcement Learning (RL) and how you can build and train RL models with the newly announced Amazon SageMaker RL. We will model a simulation environment to represent real-world problems. Further, we will train RL models in this environment and tune them to obtain the required results. By the end of this workshop, you will become familiar with Reinforcement Learning and be able to use SageMaker RL for your own business problems to build intelligent applications.
Overview of the New Amazon EC2 Instances with AMD EPYC (CMP385-R1) - AWS re:I...Amazon Web Services
Learn about new the Amazon EC2 instances that offer AMD EPYC CPUs. We provide a technical overview and discuss how the new M5a, R5a, and T3a instance types fit into the Amazon EC2 product family. We then deep dive into which workloads customers should use the new instances to better optimize their utilization and costs.
What Can Your Logs Tell You? (ANT215) - AWS re:Invent 2018Amazon Web Services
Everyone has logs. They’re not the most exciting data that your systems generate, but often, they are the most useful. Across the board, we see customers using Amazon Elasticsearch Service (Amazon ES) to ingest, analyze, and search their log data. In this chalk talk, we discuss how to get your data into Amazon ES, and how to use Kibana to best effect to pull the information you need from the logs you’re generating.
[NEW LAUNCH!] Introducing Amazon Managed Streaming for Kafka (Amazon MSK) (AN...Amazon Web Services
Discover the power of running Apache Kafka on a fully managed AWS service. In this session, we describe how Amazon Managed Streaming for Kafka (Amazon MSK) runs Apache Kafka clusters for you, demo Amazon MSK and a migration, show you how to get started, and walk through other important details about the new service.
Building Your Own ML Application with AWS Lambda and Amazon SageMaker (SRV404...Amazon Web Services
In this workshop, we step through the process of deploying and hosting machine learning (ML) models with AWS Lambda and get on-demand inferences. Given a demonstrative dataset, we build and train a simple ML classification model with Amazon SageMaker. Then, we host this model in an AWS Lambda function and expose an inference endpoint through Amazon API Gateway. Finally, we build a pipeline for automating model deployment to Lambda leveraging AWS CodeBuild, AWS CodeDeploy, and AWS CodePipeline.
Serverless AI with Scikit-Learn (GPSWS405) - AWS re:Invent 2018Amazon Web Services
Take advantage of serverless technologies for artificial intelligence (AI) by making a prediction on the fly. There is no model hosting and no servers to maintain. In this session, we show how to train a model in scikit-learn, an open source machine learning library for Python. Then we load and call the trained model from an AWS Lambda function, and finally we demonstrate how to load the library and send the data for prediction.
Querying Data in Place with AWS Object Storage Features and Analytics Tools (...Amazon Web Services
AWS offers tools and services that make analyzing and processing petabytes of data in the cloud faster, simpler, and more cost effective. In this chalk talk, AWS experts provide an overview of our querying data-in-place services, such as Amazon S3 Select, Amazon Glacier Select, Amazon Athena, and Amazon Redshift Spectrum. We explore best practices around using them with other analytics services (like Amazon EMR and AWS Glue) and third-party tools to build data lakes in Amazon S3 and Amazon Glacier and deploy other analytics solutions. Our AWS experts also provide sample use cases.
Accelerate Your Analytic Queries with Amazon Aurora Parallel Query (DAT362) -...Amazon Web Services
Amazon Aurora with MySQL compatibility includes several features to improve query performance, while still maintaining full MySQL compatibility. One such feature is Parallel Query, which provides faster analytic queries over current data by pushing query processing down to thousands of CPUs in the storage layer, achieving performance gains of up to two orders of magnitude. Learn how to take advantage of this and other recent Aurora features to implement high performance distributed queries for your MySQL-based applications.
Scaling Fantasy Sports Platform at 3M Requests/Minute with ElastiCache & Auro...Amazon Web Services
The document discusses Dream11, a fantasy sports platform that saw huge traffic spikes during cricket matches. To handle the traffic, which reached over 3 million requests per minute, Dream11 transitioned to a microservices architecture using Amazon ElastiCache, Aurora, and other AWS services. This helped improve performance and allowed Dream11 to successfully handle traffic for the 2018 Indian Premier League cricket season with high availability.
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.
In this workshop, learn how to create a serverless data lake architecture. Understand how to ingest data at scale from multiple data sources, how to transform the data, and how to catalog it to make it available for querying using a variety of tools. Also learn how to set up governance and data quality controls.
Speakers:
Rajanikanth Bhargava Chilakapati - Solutions Architect, AWS
Karl Hart - Solutions Architect, AWS
John Pignata - Startup Solutions Architect, AWS
Migrating Real-Time Sports Scores to the Cloud via Low-Latency Messaging (API...Amazon Web Services
In this session, learn how media company Turner Broadcasting delivers real-time sports scores to high-profile sites like the NCAA and PGA using Amazon MQ. Gain a deeper understanding of how Turner migrated from their on-premises message broker to Amazon MQ, and was able to preserve the low-latency messaging expected by their customers. Expect to leave with insights on the migration process, including the surprisingly fast timelines, and the benefits of a managed message broker service.
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.
Deep Dive on Amazon Elastic File System (Amazon EFS) (STG301-R1) - AWS re:Inv...Amazon Web Services
In this session, we explore the world's first cloud-scale file system and its targeted use cases. Learn about Amazon Elastic File System (Amazon EFS), its features and benefits, how to identify applications that are appropriate to use with Amazon EFS, and details about its performance and security models. The target audience is security administrators, application developers, and application owners who operate or build file-based applications.
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.
Introducing AWS DataSync - Simplify, automate, and accelerate online data tra...Amazon Web Services
SFTP is used for the exchange of data across many industries, including financial services, healthcare, and retail. In this session, we will introduce you to AWS Transfer for SFTP, a service that helps you easily migrate file transfer workflows to AWS, without needing to modify applications or manage SFTP servers. We will demonstrate the product and talk about how to migrate your users so they continue to use their existing SFTP clients and credentials, while the data they access is stored in S3. You will also learn how FINRA is using this new service in conjunction with their Data Lake on AWS.N/A
Introducing AWS DataSync - Simplify, automate, and accelerate online data tra...
Similar to [NEW LAUNCH!] [REPEAT 1] Amazon FSx for Lustre: How to build and deploy file systems for compute-intensive workloads, HPC, and machine learning applications (STG320-R1) - AWS re:Invent 2018
Got Files? We Got You Covered! Deploy Your File Workloads Quickly & Easily wi...Amazon Web Services
AWS offers fully managed file system services that enable you to quickly and simply lift and shift or build new applications that access file data in the AWS Cloud. In this session, join Wayne Duso, the leader of file storage, hybrid-edge storage, and data transport services, to learn about our full set of file services and latest launches. Learn all about file storage, and get firsthand input on how you can accelerate your journey to AWS as you move from on-premises or do-it-yourself implementations to fully managed file storage solutions. Hear how AWS file storage solutions enabled LoanLogics to migrate its applications to the cloud, enabling better scalability, performance, and availability. Also discover why customers choose AWS file systems for migrating their mission-critical enterprise applications and compute-intensive workloads to deliver the performance they need in a cost-effective way, saving time and money.
Optimizing Storage for Enterprise Workloads and Migrations (STG202) - AWS re:...Amazon Web Services
In this session, we focus on best practices for AWS block and file storage when supporting enterprise workloads (like SAP, Oracle, Microsoft applications, and home directories). We discuss migrating mission-critical workload data, selecting volumes or file systems, optimizing performance, and designing for durability and availability. We also review optimizing for cost to ensure that your lift-and-shift project is a success.
Deep Dive on Cloud File System Offerings: What to Use, Where, and Why (STG392...Amazon Web Services
The document summarizes Amazon Web Services' portfolio of file storage and data transfer services. It introduces Amazon Elastic File System (EFS), Amazon FSx for Lustre and Windows File Server, AWS Storage Gateway, AWS DataSync, and AWS Transfer for SFTP. The panel of AWS product managers discuss the different services and when each one is best suited for different use cases and workloads. The presentation also highlights some new related sessions at re:Invent that provide more in-depth information on the various services.
[NEW LAUNCH!] How to build and deploy Windows file system in AWS using Amazon...Amazon Web Services
If you have compute-intensive workloads like high performance computing, machine learning, and media processing then this is the workshop for you! Our new file storage service, Amazon FSx for Lustre, provides compute-optimized storage with fully managed Lustre file systems that can deliver hundreds of gigabytes of throughput and sub-millisecond latencies. You will learn how to spin up an FSx for Lustre file system in minutes, feed data to it from an S3 data lake, run analyses while writing results back to S3, and then spin down the file system once the workload is finished.
[NEW LAUNCH!] Deep Dive on Amazon FSx for Windows File Server (STG322-R1) - A...Amazon Web Services
In this session, we explore the new fully managed service that makes it easy to launch and use shared file storage for Windows applications. FSx for Windows provides fully managed file storage built on Microsoft Windows Server, providing native support for Windows file system features and for the Server Message Block (SMB) protocol. Learn about Amazon FSx for Windows File Server features and benefits, and details about its performance and security models. The target audience is storage administrators, application developers, and applications owners and infrastructure operations personnel who build or operate file-based Windows applications or NAS.
[NEW LAUNCH!] Deep Dive on Amazon FSx for Windows File Server (STG322-R) - AW...Amazon Web Services
If you have compute-intensive workloads like high performance computing, machine learning, and media processing then this is the workshop for you! Our new file storage service, Amazon FSx for Lustre, provides compute-optimized storage with fully managed Lustre file systems that can deliver hundreds of gigabytes of throughput and sub-millisecond latencies. You will learn how to spin up an FSx for Lustre file system in minutes, feed data to it from an S3 data lake, run analyses while writing results back to S3, and then spin down the file system once the workload is finished.
Building Hybrid Cloud Storage Architectures with AWS @scaleAmazon Web Services
The document discusses building hybrid cloud storage architectures with AWS. It provides an overview of AWS storage services including Amazon S3, Glacier, EBS, and EFS. It also describes the AWS Storage Gateway family of on-premises appliances that enable hybrid storage between on-premises and AWS cloud storage. Specifically, it covers the File Gateway for accessing S3 storage as files, Volume Gateway for iSCSI volumes, and Tape Gateway for migrating tape backups to S3.
The document discusses Amazon FSx for Windows File Server, a fully managed native Windows file system for AWS. It provides concise summaries of key features:
- FSx for Windows File Server allows users to lift and shift Windows file storage to AWS with fully managed Windows file servers that provide native Windows compatibility, fast performance, broad accessibility, and are enterprise-ready.
- Key capabilities include high throughput and IOPS, integration with Active Directory and DFS, automated backups to S3, encryption at rest and in transit, and support for a wide range of use cases.
- The service aims to simplify management of Windows file storage in AWS by automatically handling tasks like backups, software updates, and provisioning/man
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.
Public sector teams with on-prem applications face many problems managing storage arrays throughout their short lifecycle: guessing at capacity needs, waiting for procurement cycles, recruiting staff with specialized hardware skills, etc. AWS Storage Gateway helps reduce these pains by providing a way to start using Amazon S3, Amazon Glacier and Amazon EBS in hybrid architectures for traditional and cutting-edge workloads, from backup to big data analytics. Storage Gateway connects local applications to AWS storage with familiar block and file protocols, and local caching for performance. In this session, learn how you can use these AWS Storage services with Storage Gateway for backup, content storage, data lakes, disaster recovery, data migration and more.
Stevan Beara, Solutions Architect, Amazon Web Services
Matt Campbell, Engineering Director, D2L
The document discusses data lake architectures on AWS. It defines a data lake as a centralized storage platform capable of storing heterogeneous data sets at virtually limitless scale. It describes how AWS services like S3, Glue, Athena, EMR, Redshift, and Kinesis can be used to build data lakes for storing, cataloging, processing, analyzing and gaining insights from large volumes of diverse data. Examples of using these services for clickstream analytics, real-time analytics, machine learning, and reducing total cost of ownership are also provided.
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.
This session provides IT pros and application owners an overview of AWS options for building hybrid storage architectures or even entirely migrating datacenter storage to the AWS cloud. The AWS Storage Gateway connects existing on-premises block, file or tape storage systems to AWS cloud storage over the WAN in a hybrid model. The AWS Snow family of physical devices can capture, pre-process and migrate data into and out of AWS without any network connection at all. Join us to learn how you can close down datacenters, reduce storage footprints, and build solutions for tiering, data lakes, backup, disaster recovery, and migration.
Build Data Lakes and Analytics on AWS: Patterns & Best PracticesAmazon Web Services
With over 90% of today’s data generated in the last two years, the rate of data growth is showing no sign of slowing down. In this session, we step through the challenges and best practices for capturing data, understanding what data you own, driving insights, and predicting the future using AWS services. We frame the session and demonstrations around common pitfalls of building data lakes and how to successfully drive analytics and insights from data. We also discuss the architecture patterns brought together key AWS services, including Amazon S3, AWS Glue, Amazon Athena, Amazon Kinesis, and Amazon Machine Learning. Discover the real-world application of data lakes for roles including data scientists and business users.
Stephen Moon, Sr. Solutions Architect, Amazon Web Services
James Juniper, Solution Architect for the Geo-Community Cloud, Natural Resources Canada
Build Data Lakes & Analytics on AWS: Patterns & Best PracticesAmazon Web Services
This document discusses building data lakes and analytics on AWS. It covers challenges with big data like volume, velocity, and variety. An AWS data lake can quickly ingest and store any type of data. The data lake includes analytics, machine learning, real-time data movement, and traditional data movement. Metadata management is important for data lakes. AWS Glue crawlers can discover data in various formats and populate the data catalog. Different tools like Amazon Athena, Amazon EMR, and Amazon Redshift can be used for analytics depending on the user and use case. Machine learning benefits from big data, and a data lake supports agility in machine learning.
How Fannie Mae Processes over a Quarter Million Loans per Day with Amazon S3 ...Amazon Web Services
Fannie Mae processes over 250,000 loans per day with Amazon S3 by optimizing performance, availability, and durability. They implemented caching to improve GET and PUT latency, uncoupled writes from transactions with compensation, and encrypted data at rest. These changes reduced response times by over 100% and improved latency percentiles. Additional challenges involved retrying occasional slow GETs and rightsizing instances.
A data lake is an architectural approach that allows you to store massive amounts of data into a central location, so it's readily available to be categorized, processed, analyzed and consumed by diverse groups within an organization.In this session, we will introduce the Data Lake concept and its implementation on AWS.We will explain the different roles our services play and how they fit into the Data Lake picture.
AWS Floor 28 - Building Data lake on AWSAdir Sharabi
AWS makes it easy to build and operate a highly scalable and flexible data platforms to collect, process, and analyze data so you can get timely insights and react quickly to new information. In this session we will talk about how to improve over time using your data. How do you take your everyday data and build relevant business insights, to help and continuously improve your business processes, and keep your innovation going based on your data.
Cloud computing gives you a number of advantages, such as the ability to scale your web application or website on demand. If you have a new web application and want to use cloud computing, you might be asking yourself, "Where do I start?" Join us to understand best practices for scaling your resources from one to millions of users. We’ll show you how to best combine different AWS services, how to make smarter decisions for architecting your application, and how to scale your infrastructure in the cloud.
AWS Portfolio: highlight delle categorie di prodotti AWS con esempiAmazon Web Services
The document discusses Amazon Web Services (AWS) and its various cloud computing products and services. It provides information on AWS' global infrastructure including 21 regions, 64 availability zones, and 158 edge locations. It also describes compute services such as EC2 instances, containers, and serverless functions. Additional sections cover database services, storage options, data transfer mechanisms, analytics and machine learning tools, and specific AI services for image and text recognition.
Similar to [NEW LAUNCH!] [REPEAT 1] Amazon FSx for Lustre: How to build and deploy file systems for compute-intensive workloads, HPC, and machine learning applications (STG320-R1) - 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
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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.
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Crea la tua prima serverless ledger-based app con QLDB e NodeJSAmazon Web Services
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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
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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.
1) The document discusses building a minimum viable product (MVP) using Amazon Web Services (AWS).
2) It provides an example of an MVP for an omni-channel messenger platform that was built from 2017 to connect ecommerce stores to customers via web chat, Facebook Messenger, WhatsApp, and other channels.
3) The founder discusses how they started with an MVP in 2017 with 200 ecommerce stores in Hong Kong and Taiwan, and have since expanded to over 5000 clients across Southeast Asia using AWS for scaling.
This document discusses pitch decks and fundraising materials. It explains that venture capitalists will typically spend only 3 minutes and 44 seconds reviewing a pitch deck. Therefore, the deck needs to tell a compelling story to grab their attention. It also provides tips on tailoring different types of decks for different purposes, such as creating a concise 1-2 page teaser, a presentation deck for pitching in-person, and a more detailed read-only or fundraising deck. The document stresses the importance of including key information like the problem, solution, product, traction, market size, plans, team, and ask.
This document discusses building serverless web applications using AWS services like API Gateway, Lambda, DynamoDB, S3 and Amplify. It provides an overview of each service and how they can work together to create a scalable, secure and cost-effective serverless application stack without having to manage servers or infrastructure. Key services covered include API Gateway for hosting APIs, Lambda for backend logic, DynamoDB for database needs, S3 for static content, and Amplify for frontend hosting and continuous deployment.
This document provides tips for fundraising from startup founders Roland Yau and Sze Lok Chan. It discusses generating competition to create urgency for investors, fundraising in parallel rather than sequentially, having a clear fundraising narrative focused on what you do and why it's compelling, and prioritizing relationships with people over firms. It also notes how the pandemic has changed fundraising, with examples of deals done virtually during this time. The tips emphasize being fully prepared before fundraising and cultivating connections with investors in advance.
AWS_HK_StartupDay_Building Interactive websites while automating for efficien...Amazon Web Services
This document discusses Amazon's machine learning services for building conversational interfaces and extracting insights from unstructured text and audio. It describes Amazon Lex for creating chatbots, Amazon Comprehend for natural language processing tasks like entity extraction and sentiment analysis, and how they can be used together for applications like intelligent call centers and content analysis. Pre-trained APIs simplify adding machine learning to apps without requiring ML expertise.
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.
[NEW LAUNCH!] [REPEAT 1] Amazon FSx for Lustre: How to build and deploy file systems for compute-intensive workloads, HPC, and machine learning applications (STG320-R1) - AWS re:Invent 2018
With all this support it has allowed us to innovate at a rapid pace over the last decade. We are excited this has been recognized by Gartner and their clients in their annual Magic Quadrant as we have been in the furthest on both axis of any provider in the upper right since day 1.
One of many reasons that we’ve held this leadership position in the industry for so long is the breadth of our portfolio. No matter where you are in your cloud journey, we have a storage solution that will fit your applications. Whether you’re simply re-hosting, or lifting and shifting, an application with the same type of architecture you’ve been using on-prem; re-platforming using a hybrid architecture; or re-architecting to leverage all of the benefits of the cloud, we have a storage service that fits the bill. These are just a very small sample of the great customers that have migrated to the cloud.
But we talked with a lot of you, and you told us you needed more. You told us you needed an SMB file storage solution. You told us you needed a better solution to run Lustre for your HPC and Machine Learning workloads. You told us you wanted a solution to back up key AWS resources. Our roadmap is driven by your feedback.
So, as you’ve heard this week, we’re expanding our portfolio with 3 new storage classes and 2 new file storage services.
1/ Amazon S3 Intelligent-Tiering is a new S3 storage class that automatically optimizes customers’ storage costs for data with unknown or changing access patterns by moving data to the most cost-effective storage tier.
2/ Amazon S3 Glacier Deep Archive is a new storage class that delivers the lowest cost of any storage service, at less than 1/10th of one cent per gigabyte per month.
3/ Amazon FSx for Windows File Server provides fully managed Windows-based shared file storage designed to help customers lift-and-shift their applications to AWS.
4/ Amazon FSx for Lustre is a fully managed file system that is optimized for compute-intensive workloads, such as high-performance computing, machine learning, and media data processing workflows.
5/ Amazon EFS IA is a new storage class for Amazon EFS that is designed for files accessed less frequently, enabling customers to reduce storage costs by up to 85% compared to the EFS Standard storage class.
When we refer to file storage, we’re really talking about network file storage
Why is network file storage so useful?
Files and directories appear and work just like they would on local storage…
…while multiple users, computers, applications can access the same set of files…
…with strong data consistency even if multiple users or applications are editing the same file concurrently
These network file systems work natively with operating system APIs for working with files…
…so they work natively with existing applications and IT environments
And they generally provide high levels of throughput and IOPS…
…since many users/computers/apps accessing data at the same time…
…while providing near-local latencies so they really do appear like local file storage
And that’s why we built Amazon FSx for Lustre
On Wed we announced Amazon FSx, which provides fully managed third-party file systems that are optimized for a variety of workloads.
Amazon FSx provides you with the native compatibility of third-party file systems, with the feature sets for workloads such as Windows-based enterprise storage, high performance computing (HPC), and machine learning.
Simple: / fully managed You no longer need to manage file servers and storage for these file systems, as Amazon FSx automates the time-consuming administration tasks such as hardware provisioning, software configuration, patching, and backups.
Native compatibility, features, performance
Rich integrations with other cloud-native AWS services, making these file systems even more useful for a broader set of workloads.
Cost-optimized for particular workloads, like short-term compute-intensive workloads that don’t require replicated storage.
FSx for Lustre is one file system that’s part of our overall FSx service. Amazon FSx also provides Amazon FSx for Windows File Server, for Windows-based storage.
Amazon FSx for Lustre is a fully managed, high performance parallel file system on AWS
[Read through the three points]
Lustre is one of the most popular parallel file systems, and it’s open source. OpenSFS
It’s highly scalable and can be accessed from tens of thousands of compute instances, and is designed to store petabytes of data and deliver hundreds of GBs of data per second. Since it’s a parallel file system, with direct communication between clients and servers, it provides low, consistent latencies.
It was started in 1999 at CMU, and has matured into a file system that’s heavily used by businesses, research institutions, and government agencies for a wide variety of use cases including [read icons on the bottom.
And in fact 60% of the top 100 fastest supercomputers leverage Lustre for data storage
Variety of HPC workloads, including seismic processing and geospatial analysis
Financial modeling
…
With Amazon FSx for Lustre, you get a fully managed Lustre parallel file system.
Because it’s a Lustre file system, it’s performance is ideal for compute-intensive workloads with high-throughput and low-latency needs, like high performance computing, machine learning workloads, and media processing/rendering workflows.
[Read through icons]
Data repositories: S3 + on-premises data stores
I’ll now talk about each of these in turn.
Fitting in with the typical model of S3 data moving to a shared file system accessed by a compute cluster
You can link your file system to an S3 bucket
When that happens, all of your objects appear as directories and files on your Lustre file system.
However, the data itself is not moved until it’s needed. As your compute workload requests a file, it gets pulled automatically from S3 onto the file system.
This lazy load approach is really useful, because your bucket may have petabytes of data in it, but you need only a portion of that data for a given compute job.
You can then write results back at any point with a simple command from your compute instances.
Only incremental changes are written back.
So it’s really designed for the common compute-intensive workload, where you’re running your analysis for hours, days, or weeks, against a larger data set that’s in S3.
[Walk through file1.txt access, how it’s lazy loaded]
Each Amazon FSx for Lustre is built on a cluster of file servers, each with one or more disks
Data movement to/from S3 is done in parallel across each of the file servers hosting your data
Use multi-part upload/download to move large files quickly
Lots of folks want to burst to the cloud. Meaning they want to run spin up large compute clusters to run compute-heavy jobs, and then spin down the compute when needed.
For lots of these scenarios, the data is on-premises, need it on AWS while the job is running so the compute cluster has local access to it
Mount your Lustre file system from a computer or computers on-premises over DX or VPN. Then you can move data from your on-premises data store to Lustre.
[For first two icons] We really are putting the power of Lustre in-reach for anybody, but fully managing it.
The Lustre file system is POSIX-compliant, so your applications can work with files and directories just as they do with a local file system.
Included as part of that is a read after write/close consistency model – super-important as you’ll commonly have many compute instances accessing the same file, need to provide consistency guarantees
Also important for workloads with lots of compute instances accessing the same files – supports file locking
Your data is automatically encrypted at-rest
[Walk through other icons]
[Icon needs to say S3 or on-premises]
[Change “pay only for the resources you use” to “billed per second”, and remove “billed per second” from below]
[Put in parentheses after FSx for Lustre pricing that it’s (high-performance SSD)”]
Amazon FSx for Lustre is cost-optimized for short-term compute-intensive workloads by providing nonreplicated storage.
That’s because it’s designed to work with your long-term, durable data stores – and serve as the storage for when you need to run compute
You can spin up and spin down file systems as needed, and store long term data in S3 or in your on-premises data store.
You’re billed per second.
The price for the high-performance SSD is $0.14/GB-mo.
The more relevant way to think about it, since it’s for short-term processing workloads, is $0.20/TB-hour.
In addition to FSx for Lustre, we announced today FSx for Windows File Server.
EFS is our cloud-native Linux file system that we launched in 2016
FSx for Windows File Server joins that as our two file systems for supporting business applications: One for Linux workloads, the other for Windows
[TODO: Provide a better short description of Windows File Server]
EFS is our cloud-native Linux file system that we launched in 2016
FSx for Windows File Server joins that as our two file systems for supporting business applications: One for Linux workloads, the other for Windows
Lustre is a highly popular open-source parallel file system that’s used heavily in the high-performance computing space. We’re offering that as a fully managed file system that’s fully integrated with S3. You can use it to process data at hundreds of GB of throughput per second, millions of IOPs, and sub-millisecond latencies
[TODO: Add better short description of Lustre that makes compute-intensive/S3/redundancy points]
EFS:
Easily shared between multiple applications, instances, and on-premises servers simultaneously
Achieve petabyte scale from a distributed design that avoids the constraints imposed by traditional file servers
FSx for Windows:
Built on Windows Server with native support for Windows file system features you use today
SSD storage for high throughput, IOPS, and sub-millisecond latencies
FSx for Lustre:
Built on the highly popular, open source parallel file system Lustre
Process data at hundreds of GB of throughput per second, millions of IOPs, and sub-millisecond latencies
Revise this slide to focus on use cases instead of just a list of services.
Amazon EFS – show enterprise with files for large applications
Amazon EBS
Portfolio slide….show enterprise….
Need object, file, gateway…
Revise this slide to focus on use cases instead of just a list of services.
Amazon EFS – show enterprise with files for large applications
Amazon EBS
Portfolio slide….show enterprise….
Need object, file, gateway…