Best Practices for Migrating Databases to the Cloud - AWS Summit SydneyAmazon Web Services
The document discusses best practices for migrating databases to AWS using AWS Database Migration Service (DMS) and AWS Schema Conversion Tool (SCT). It describes how the traditional approach to database migration involved complex steps like shutting down the database, replicating data, and long application downtimes. AWS DMS and SCT enable automated migration between on-premises and AWS databases with zero downtime and automated schema conversion. The document provides an overview of AWS database services, the database migration process, features of DMS and SCT, lessons learned, examples, and best practices for using DMS.
Let the data decide!
Amazon Relational Database Service (RDS)
Demo - Deploy Multi-AZ database in VPC
Amazon DynamoDB (NoSQL)
Intro to AWS Athena and Redshift
Using AWS Purpose-Built Databases to Modernize your ApplicationsAmazon Web Services
As you look to modernizing your applications, you will need to consider your database options to meet the new application requirements. AWS offers a series of purpose-built databases that include relational, key value, document, graph and cache use cases to help you deliver new and enhanced functionalities. In this webinar session, we share the different modern application architectures, and how to combine different database services to meet your requirements. Understand how to modernize your relational databases through easy upgrades with Amazon Relational Database Service and learn how to migrate from one database to another with AWS Database Migration Service and AWS Schema Conversion Tool.
Speaker:
Blair Layton, Business Development Manager, Amazon Web Services
Solutions for Storage and Data Migrations | AWS Summit Tel Aviv 2019AWS Summits
Objects? File Systems? Block? Hybrid? Let's talk about AWS' storage solutions, starting from ways to migrate your data into AWS, through the different storage services AWS has to offer, alongside AWS's storage parterships.
Best Practices for Migrating Databases to the Cloud - AWS Summit SydneyAmazon Web Services
The document discusses best practices for migrating databases to AWS using AWS Database Migration Service (DMS) and AWS Schema Conversion Tool (SCT). It describes how the traditional approach to database migration involved complex steps like shutting down the database, replicating data, and long application downtimes. AWS DMS and SCT enable automated migration between on-premises and AWS databases with zero downtime and automated schema conversion. The document provides an overview of AWS database services, the database migration process, features of DMS and SCT, lessons learned, examples, and best practices for using DMS.
Let the data decide!
Amazon Relational Database Service (RDS)
Demo - Deploy Multi-AZ database in VPC
Amazon DynamoDB (NoSQL)
Intro to AWS Athena and Redshift
Using AWS Purpose-Built Databases to Modernize your ApplicationsAmazon Web Services
As you look to modernizing your applications, you will need to consider your database options to meet the new application requirements. AWS offers a series of purpose-built databases that include relational, key value, document, graph and cache use cases to help you deliver new and enhanced functionalities. In this webinar session, we share the different modern application architectures, and how to combine different database services to meet your requirements. Understand how to modernize your relational databases through easy upgrades with Amazon Relational Database Service and learn how to migrate from one database to another with AWS Database Migration Service and AWS Schema Conversion Tool.
Speaker:
Blair Layton, Business Development Manager, Amazon Web Services
Solutions for Storage and Data Migrations | AWS Summit Tel Aviv 2019AWS Summits
Objects? File Systems? Block? Hybrid? Let's talk about AWS' storage solutions, starting from ways to migrate your data into AWS, through the different storage services AWS has to offer, alongside AWS's storage parterships.
對於投資現場部署技術的大多數組織而言,在混合式架構中運作是採用雲端的必要部分。遷移IT系統需要好一段時間。因此,選擇一個雲端廠商,能夠幫助您實行經過深思熟慮的混合策略,並不需要在本地硬件和軟件上進行昂貴的新投資,這對簡化運營及輕鬆實現業務目標非常重要。
在這場線上研討會中,我們將介紹 AWS 如何在存儲、網絡、安全、應用程序部署和管理工具中構建業界最廣泛的混合功能,以便您輕鬆及安全地擴展您現有的投資。
For most organizations with on-premises technology investments, operating in a hybrid architecture is a necessary part of cloud adoption. Migrating legacy IT systems takes time. Therefore, selecting a cloud provider who can help you implement a thoughtful hybrid strategy, without requiring costly new investments in on-premises hardware and software, is important to simplify operations and more easily achieve your business goals.
In this webinar, we will describe how we at AWS have built the industry’s broadest set of hybrid capabilities across storage, networking, security, application deployment, and management tools to make it easy for you to integrate the cloud as a seamless and secure extension of your existing investments.
Introduction to Hybrid Cloud on AWS - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- Understand Hybrid Cloud architecture options
- Understand AWS portfolio of capabilities to support Hybrid Cloud
- Understand AWS partnerships with VMWare, Microsoft and other key enterprise players help you execute your Hybrid Cloud strategy
Architect Your Legacy Microsoft Apps into Modern Cloud WorkloadsAmazon Web Services
Join our upcoming webinar with AWS, Six Nines, and NRC Health to learn how NRC Health migrated their 20-year-old Microsoft application to the cloud, reducing the risk of downtime and long change management windows.
by Everett Dolgner, Business Development Management, AWS
Do you have on-premises tape backups or expensive VTL hardware? Worried about moving cases of tapes off site? Not sure about the integrity of your data on tape? In this whiteboarding session, learn how to use AWS services, including AWS Storage Gateway, to replace existing traditional tape approaches to backup data.
Enterprises require that their mission critical business applications such as Microsoft, SAP and Oracle are up and running 24x7. Whatever it is, the requirements are the same: Availability, security and flexibility are key. In this session we will walk through practical examples of how AWS customers operate heavily mission critical applications in the cloud. Through real world customer examples, you will learn how Enterprise deploy mission critical workloads in highly redundant manner as well as apply security controls which will provide you with increased visibility and control of your applications.
This document discusses data migration solutions from on-premises storage to AWS using AWS DataSync and AWS Transfer for SFTP. It provides an overview of the services, how they work, examples of customers who use them and a call to action to try them out. Key points covered include how DataSync can automate and accelerate transferring data between on-premises and AWS storage, and how Transfer for SFTP provides a managed SFTP service to seamlessly migrate existing SFTP workflows to AWS.
This document provides guidance for organizations looking to migrate to the cloud. It discusses the typical benefits of cloud migration including cost savings, resource efficiency, and business agility. It then outlines a three phase methodology for cloud migration: foundation, migration, and optimization. Key aspects of preparing for migration are also examined like assessing organizational readiness, developing a business case, and planning the people and skills needed. Finally, AWS services that can help accelerate migrations like Server Migration Service and Database Migration Service are presented.
AWS controls over 50% of the cloud computing market and offers a broad range of services to help businesses innovate. The document discusses how AWS provides agility, economy, and elasticity to users, allowing them to focus on their business while AWS manages the infrastructure. It also highlights examples of large customers like NASA that have found AWS to be more secure than their own data centers.
There is a large number of legacy enterprise Microsoft applications (HR, Finance, CMS, BPM apps) still running on premises. This session will focus on retiring technical debt and bringing some of those applications into AWS. You will learn why it's important to go cloud, how easy it is to run & optimize Microsoft applications on AWS, the different approaches to maximize server utilization and save money.
AWS Outposts allows customers to run compute and storage on-premises while connecting to AWS's cloud services and managing it all through AWS's console. It provides the same APIs, tools, and infrastructure as the AWS cloud. Customers can use Outposts for applications that require low latency to on-premises systems or need to process data locally. Outposts addresses challenges like lack of cloud services on-premises and slower pace of innovation, providing a fully managed service running the same AWS-designed hardware on-site.
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.
This document appears to be a presentation on databases in the cloud using Amazon Web Services. The presentation covers Amazon RDS for relational databases, Amazon Aurora as a database option, Amazon Redshift for data warehousing, and data lakes. It discusses how these database services can provide scalability, high availability, automation of tasks, and pay-as-you-go pricing compared to managing databases on-premises.
The document discusses building data lakes and analytics on AWS. It provides an overview of challenges posed by big data including volume, velocity, variety and veracity of data. It then describes how AWS services like S3, Glue and Athena can help address these challenges by allowing quick ingestion and storage of raw data in its original format. The document also discusses best practices for preparing and analyzing data in the lake using services like EMR, Redshift and SageMaker to derive insights and drive machine learning models.
The document discusses AWS analytics services that can be used to build better data lakes. It describes how customers are moving to data lake architectures that bring together the benefits of data warehouses and data lakes. The document then summarizes various AWS analytics services like Amazon S3, AWS Glue, Lake Formation, Amazon Redshift, Amazon EMR, Amazon Athena, Amazon Elasticsearch Service, Amazon SageMaker, Amazon QuickSight, and AWS Data Exchange that can be used for different types of analytics on the data lake including data warehousing, big data processing, interactive querying, operational analytics, real-time analytics, predictive analytics, and visualizations.
The document discusses strategies for migrating IT workloads to the cloud. It describes common drivers for cloud migration like cost reduction and agility. Potential barriers are also outlined, such as existing investments and lack of cloud expertise. The main sections of the document are on migration planning, common migration strategies ranging from rehosting to rearchitecting, examples of migration patterns, and modernizing applications on AWS.
Previously, ETL meant using proprietary products with commercial databases and users with specialist skills. Learn how to create ETL data pipelines that can securely consume data at scale while using open source technologies and languages to enable your organisation, team, and data.
Speaker: Paul Macey, Big Data Specialist, AWS
[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.
Big Data on AWS - To infinity and beyond! - Tel Aviv Summit 2018Amazon Web Services
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.
Connecting the dots - How Amazon Neptune and Graph Databases can transform yo...Amazon Web Services
This document discusses Amazon Neptune, a fully managed graph database service. It provides an overview of graph databases and their advantages over traditional databases for modeling connected data. It then describes Amazon Neptune's key features, like automatic scaling, high availability across Availability Zones, integration with open standards like Gremlin and SPARQL, and ease of use on AWS. Examples are given showing how to model and query graph data using Gremlin and SPARQL. Finally, it discusses Amazon Neptune's architecture and roadmap for general availability later in 2018.
SRV309 AWS Purpose-Built Database Strategy: The Right Tool for the Right JobAmazon Web Services
In this session, Shawn Bice, VP of NoSQL and QuickSight, covers the AWS purpose-built strategy for databases and explains why your application should drive the requirements of a database, not the other way around. We introduce AWS databases that are purpose-built for your application use cases. Learn why you should select different data services to solve different aspects of an application, and watch a demonstration on which application use cases lend themselves well to which data services. If you’re a developer building modern applications that require flexibility and consistent millisecond performance, and you’re trying to determine what relational and non-relational data services to use, this session is for you.
對於投資現場部署技術的大多數組織而言,在混合式架構中運作是採用雲端的必要部分。遷移IT系統需要好一段時間。因此,選擇一個雲端廠商,能夠幫助您實行經過深思熟慮的混合策略,並不需要在本地硬件和軟件上進行昂貴的新投資,這對簡化運營及輕鬆實現業務目標非常重要。
在這場線上研討會中,我們將介紹 AWS 如何在存儲、網絡、安全、應用程序部署和管理工具中構建業界最廣泛的混合功能,以便您輕鬆及安全地擴展您現有的投資。
For most organizations with on-premises technology investments, operating in a hybrid architecture is a necessary part of cloud adoption. Migrating legacy IT systems takes time. Therefore, selecting a cloud provider who can help you implement a thoughtful hybrid strategy, without requiring costly new investments in on-premises hardware and software, is important to simplify operations and more easily achieve your business goals.
In this webinar, we will describe how we at AWS have built the industry’s broadest set of hybrid capabilities across storage, networking, security, application deployment, and management tools to make it easy for you to integrate the cloud as a seamless and secure extension of your existing investments.
Introduction to Hybrid Cloud on AWS - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- Understand Hybrid Cloud architecture options
- Understand AWS portfolio of capabilities to support Hybrid Cloud
- Understand AWS partnerships with VMWare, Microsoft and other key enterprise players help you execute your Hybrid Cloud strategy
Architect Your Legacy Microsoft Apps into Modern Cloud WorkloadsAmazon Web Services
Join our upcoming webinar with AWS, Six Nines, and NRC Health to learn how NRC Health migrated their 20-year-old Microsoft application to the cloud, reducing the risk of downtime and long change management windows.
by Everett Dolgner, Business Development Management, AWS
Do you have on-premises tape backups or expensive VTL hardware? Worried about moving cases of tapes off site? Not sure about the integrity of your data on tape? In this whiteboarding session, learn how to use AWS services, including AWS Storage Gateway, to replace existing traditional tape approaches to backup data.
Enterprises require that their mission critical business applications such as Microsoft, SAP and Oracle are up and running 24x7. Whatever it is, the requirements are the same: Availability, security and flexibility are key. In this session we will walk through practical examples of how AWS customers operate heavily mission critical applications in the cloud. Through real world customer examples, you will learn how Enterprise deploy mission critical workloads in highly redundant manner as well as apply security controls which will provide you with increased visibility and control of your applications.
This document discusses data migration solutions from on-premises storage to AWS using AWS DataSync and AWS Transfer for SFTP. It provides an overview of the services, how they work, examples of customers who use them and a call to action to try them out. Key points covered include how DataSync can automate and accelerate transferring data between on-premises and AWS storage, and how Transfer for SFTP provides a managed SFTP service to seamlessly migrate existing SFTP workflows to AWS.
This document provides guidance for organizations looking to migrate to the cloud. It discusses the typical benefits of cloud migration including cost savings, resource efficiency, and business agility. It then outlines a three phase methodology for cloud migration: foundation, migration, and optimization. Key aspects of preparing for migration are also examined like assessing organizational readiness, developing a business case, and planning the people and skills needed. Finally, AWS services that can help accelerate migrations like Server Migration Service and Database Migration Service are presented.
AWS controls over 50% of the cloud computing market and offers a broad range of services to help businesses innovate. The document discusses how AWS provides agility, economy, and elasticity to users, allowing them to focus on their business while AWS manages the infrastructure. It also highlights examples of large customers like NASA that have found AWS to be more secure than their own data centers.
There is a large number of legacy enterprise Microsoft applications (HR, Finance, CMS, BPM apps) still running on premises. This session will focus on retiring technical debt and bringing some of those applications into AWS. You will learn why it's important to go cloud, how easy it is to run & optimize Microsoft applications on AWS, the different approaches to maximize server utilization and save money.
AWS Outposts allows customers to run compute and storage on-premises while connecting to AWS's cloud services and managing it all through AWS's console. It provides the same APIs, tools, and infrastructure as the AWS cloud. Customers can use Outposts for applications that require low latency to on-premises systems or need to process data locally. Outposts addresses challenges like lack of cloud services on-premises and slower pace of innovation, providing a fully managed service running the same AWS-designed hardware on-site.
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.
This document appears to be a presentation on databases in the cloud using Amazon Web Services. The presentation covers Amazon RDS for relational databases, Amazon Aurora as a database option, Amazon Redshift for data warehousing, and data lakes. It discusses how these database services can provide scalability, high availability, automation of tasks, and pay-as-you-go pricing compared to managing databases on-premises.
The document discusses building data lakes and analytics on AWS. It provides an overview of challenges posed by big data including volume, velocity, variety and veracity of data. It then describes how AWS services like S3, Glue and Athena can help address these challenges by allowing quick ingestion and storage of raw data in its original format. The document also discusses best practices for preparing and analyzing data in the lake using services like EMR, Redshift and SageMaker to derive insights and drive machine learning models.
The document discusses AWS analytics services that can be used to build better data lakes. It describes how customers are moving to data lake architectures that bring together the benefits of data warehouses and data lakes. The document then summarizes various AWS analytics services like Amazon S3, AWS Glue, Lake Formation, Amazon Redshift, Amazon EMR, Amazon Athena, Amazon Elasticsearch Service, Amazon SageMaker, Amazon QuickSight, and AWS Data Exchange that can be used for different types of analytics on the data lake including data warehousing, big data processing, interactive querying, operational analytics, real-time analytics, predictive analytics, and visualizations.
The document discusses strategies for migrating IT workloads to the cloud. It describes common drivers for cloud migration like cost reduction and agility. Potential barriers are also outlined, such as existing investments and lack of cloud expertise. The main sections of the document are on migration planning, common migration strategies ranging from rehosting to rearchitecting, examples of migration patterns, and modernizing applications on AWS.
Previously, ETL meant using proprietary products with commercial databases and users with specialist skills. Learn how to create ETL data pipelines that can securely consume data at scale while using open source technologies and languages to enable your organisation, team, and data.
Speaker: Paul Macey, Big Data Specialist, AWS
[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.
Big Data on AWS - To infinity and beyond! - Tel Aviv Summit 2018Amazon Web Services
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.
Connecting the dots - How Amazon Neptune and Graph Databases can transform yo...Amazon Web Services
This document discusses Amazon Neptune, a fully managed graph database service. It provides an overview of graph databases and their advantages over traditional databases for modeling connected data. It then describes Amazon Neptune's key features, like automatic scaling, high availability across Availability Zones, integration with open standards like Gremlin and SPARQL, and ease of use on AWS. Examples are given showing how to model and query graph data using Gremlin and SPARQL. Finally, it discusses Amazon Neptune's architecture and roadmap for general availability later in 2018.
SRV309 AWS Purpose-Built Database Strategy: The Right Tool for the Right JobAmazon Web Services
In this session, Shawn Bice, VP of NoSQL and QuickSight, covers the AWS purpose-built strategy for databases and explains why your application should drive the requirements of a database, not the other way around. We introduce AWS databases that are purpose-built for your application use cases. Learn why you should select different data services to solve different aspects of an application, and watch a demonstration on which application use cases lend themselves well to which data services. If you’re a developer building modern applications that require flexibility and consistent millisecond performance, and you’re trying to determine what relational and non-relational data services to use, this session is for you.
Migrate Your Hadoop/Spark Workload to Amazon EMR and Architect It for Securit...Amazon Web Services
"Customers are migrating their analytics, data processing (ETL), and data science workloads running on Apache Hadoop/Spark to AWS in order to save costs, increase availability, and improve performance. In this session, AWS customers Airbnb and Guardian Life discuss how they migrated their workload to Amazon EMR. This session focuses on key motivations to move to the cloud. It details key architectural changes and the benefits of migrating Hadoop/Spark workloads to the cloud.
"
Deriving Value with Next Gen Analytics and ML ArchitecturesAmazon Web Services
This presentation was delivered on March 19, 2019at Gartner's Data and Analytics Summit in Orlando, FL. Rahul Pathak, GM at AWS discusses Deriving Value with Next Gen Analytics and ML Architectures on AWS.
Building low latency apps with a serverless architecture and in-memory data I...AWS Germany
Memory data stores such as ElastiCache for Redis enables applications with response times in microseconds. By using Aurora, DynamoDB, DAX, Lambda, and ElastiCache, we explored how to design and deploy high-perfomance applications. Learn more here: https://aws.amazon.com/products/databases/
A decade ago, relational databases were used for nearly every use case. Today, new technologies are enabling a revolution in databases, creating new options for document, key: value, in-memory, search, and graph capabilities that do not use relational tables. We’ll discuss this revolution in database options and who is using them.
Building with Purpose-Built Databases: Match Your workload to the Right DatabaseAWS Summits
Learn how to evaluate a new workload for the best managed database option based on specific application needs related to data shape, data size at limit, computational requirements, programmability, throughput and latency needs, and more. This session explains the ideal use cases for relational and non-relational database services, including Amazon Aurora, Amazon DynamoDB, Amazon ElastiCache for Redis, Amazon Neptune, and Amazon Redshift.
Laura Caicedo, Solutions Architect, Amazon Web Services
In this session, we show you how to understand what data you have, how to drive insights, and how to make predictions using purpose-built AWS services. Learn about the common pitfalls of building data lakes and discover how to successfully drive analytics and insights from your data. Also learn how services such as Amazon S3, AWS Glue, Amazon Redshift, Amazon Athena, Amazon EMR, Amazon Kinesis, and Amazon Machine Learning (Amazon ML) services work together to build a successful data lake for various roles, including data scientists and business users.
The document discusses non-relational databases and how they enable new types of applications. It provides information on key-value, document, and graph databases and how they differ from traditional relational databases. It also describes Amazon DynamoDB, Amazon ElastiCache, Amazon Elasticsearch Service, and Amazon Neptune as examples of non-relational database services on AWS.
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.
The first step towards knowing your customer is to collect and extract insights and actionable information from your data. Learn how AWS enables you to cost efficiently store any amount of data and build an agile approach to data mining and visualization - helping you to make efficient business decisions and targeted offerings.
The document discusses building a global multi-region serverless architecture on AWS. It covers topics like system reliability and availability, why a multi-region multi-master architecture is needed, how to deploy one on AWS using services like DynamoDB Global Tables, Lambda, API Gateway and Route 53. It then provides an example of a serverless architecture with DynamoDB global tables replicated across regions and Lambda functions triggered from API endpoints in different regions for high availability.
The document discusses a virtual AWSome Day event. It provides an introduction to AWS by Stephan Hadinger, Head of Architecture at AWS. It highlights that AWS has millions of active customers including 80% of the CAC 40 companies and is positioned as a leader in Gartner's Magic Quadrant for Cloud Infrastructure as a Service. It also discusses how the cloud allows companies to build applications like startups by removing constraints and enabling agility.
This document discusses running critical mission applications on AWS, specifically SAP workloads. It defines critical mission applications as secure, highly available, resilient, and having a major business impact if unavailable. AWS provides benefits for running these applications due to its global infrastructure, security features, experience hosting over a million customers, and ecosystem of partners and services. The document outlines how customers can migrate SAP systems to AWS through various options like backup/restore, system replication, and third-party tools. It also discusses how AWS services like EC2 instances, VPC, storage, and security tools help provide flexibility, speed, agility, and security for critical SAP workloads.
Building a Data Lake for Your Enterprise, ft. Sysco (STG309) - AWS re:Invent ...Amazon Web Services
Data lakes are transforming the way enterprises store, analyze, and learn insights from their data. While data lakes are a relatively new concept, many enterprises have already generated significant business value from the insights gleaned. In this session, AWS experts and technology leaders from Sysco, a Fortune 50 company and leader in food distribution and marketing, explain why Sysco decided to evolve its data management capabilities to include data lakes and how they customized them to support diverse querying capabilities and data science use cases. They also discuss how to architect different aspects of a data lake—ingestion from disparate sources, data consumption, and usability layers—and how to track data ingestion and consumption, monitor associated costs, enforce wanted levels of user access, manage data file formats, synchronize production and non-production environments, and maintain data integrity. Services to be discussed include Amazon S3 and S3 Select, Amazon Athena, Amazon EMR, Amazon EC2, and Amazon Redshift Spectrum.
Value of Data Beyond Analytics by Darin BriskmanSameer Kenkare
The document discusses analytics capabilities provided by Amazon Web Services (AWS). It describes how AWS offers a variety of services for building data lakes, loading and querying data, and performing analytics. These services include Amazon S3, Amazon Redshift, Amazon Athena, Amazon EMR, and Amazon QuickSight. It also provides examples of how customers like Epic Games and a large media company use these AWS analytics services.
The New Normal Getting Started with AWSTom Laszewski
As Administrators, we have become accustom to managing our VMware environments. Today we are being tasked with building a cloud strategy and moving our business to the cloud. How do you get started? What do you need to do to put your first VM in the cloud? How will your existing environment talk to this brave new world? How will you protect it and back it up? Join me in this session to learn how to get started and understand why you want to.
This document discusses big data processing at scale using AWS services. It begins with an overview of the increasing volume of data being generated. Common architectures for collecting, storing, processing, analyzing and consuming big data on AWS are then presented. Specific AWS services for each step of the big data workflow like Kinesis, S3, EMR, Redshift and Glue are described. Common architectural patterns for building event-driven batch analytics and combining real-time and batch analytics on AWS are shown. The document concludes with success stories of customers like Netflix, FINRA and Nasdaq using AWS for big data and analytics workloads.
Leadership Session: AWS Database and Analytics (DAT206-L) - AWS re:Invent 2018Amazon Web Services
Raju Gulabani, Vice President of Databases, Analytics, Machine Learning, and Blockchain at AWS, presented on AWS databases and analytics services. He discussed AWS's strategy of having a broad and deep portfolio of purpose-built analytics services including Redshift, Athena, EMR, QuickSight, and SageMaker. He also provided examples of customers like Epic Games and Anthropic using these services to build analytics solutions at large scale.
Get to Know Your Customers - Build and Innovate with a Modern Data ArchitectureAmazon Web Services
Your customers probably want a better experience with your brand. Your different business teams want and need better insights in their decision making. Almost certainly, your finance and operations teams require this to happen at a fraction of the cost of traditional on-premises options. Modern data architectures on AWS help many of our best customers realise all of those goals. Your business data contains critical information about customer behaviours, operational decisions, and many factors that have financial impact on your organisation. Increasingly, this data sits beyond your transactional systems, and is too big, too fast, and too complex for existing systems to handle. AWS Data and Analytics services are designed from our customers' requirements to ingest, store, analyse, and consume information at record-breaking scale. In this session you will learn how these services work together to deliver business automation, enhance customer engagement and intelligence.
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.
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.
Durante i laboratori pratici, gli esperti AWS ti mostrano quali strumenti aiutano a sviluppare le applicazioni Serverless in locale e nel cloud AWS e ti aiuteranno a programmare i prossimi passi per iniziare ad utilizzare questa tecnologia nella tua azienda.