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.
Cloud migration is more than simply a business efficiency or a cost-saving measure. It’s a critical step towards digital transformation, innovation and operational resilience that has opened up opportunities for those who’ve embraced cloud adoption.
Whether you are looking to embark on your cloud migration or scaling the number of applications you’re moving to the cloud, it does not need to be a daunting task or one that you go at alone. AWS offers 10 years of experience helping businesses to efficiently move their legacy on-premises systems to the cloud. We work closely alongside numerous local delivery partners to help you meet your business needs.
Our Cloud Migration insights forum helps you to learn how to simplify your cloud journey with AWS.
Amazon SageMaker is an end-to-end machine learning platform that allows users to build, train, and deploy machine learning models at scale. It provides pre-built machine learning algorithms, notebook instances to build models, one-click training for ML/DL models and custom algorithms, and deployment of trained models without additional engineering effort. SageMaker also manages and scales model inference clusters and APIs for production.
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.
How a Global Healthcare Company Built a Migration Factory to Quickly Move Tho...Amazon Web Services
Setting a goal for your teams to move a large number of workloads to AWS in a short period of time can be a great way to motivate teams to migrate quickly. Cardinal Health created a migration factory composed of teams, tools, and processes that streamlined the movement of workloads from on-premises to AWS. In this session, hear from Cardinal Health about how they used a migration factory to successfully move thousands of applications to the AWS Cloud. In addition, learn best practices for creating an effective migration platform and process in your organization.
The document discusses strategies for executing a large-scale migration to AWS. It outlines establishing a cloud enablement team and AWS landing zone to provide a secure, scalable multi-account environment. Application migration strategies discussed include discovery, determining the migration path, rehosting/lift and shift, and replatforming/lift and reshape. Specific migration tools and services mentioned include AWS Application Discovery Service, VMware HCX, AWS Server Migration Service, and AWS Database Migration Service.
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.
This document outlines an agenda for an AWS Cost Management workshop. The agenda includes introductions and sessions on AWS Cost Explorer, AWS Budgets, AWS Reservations, and AWS Cost & Usage Reports. It provides overviews of AWS cost management products and highlights recent features including budget redesigns, forecasting enhancements, and reserved instance management updates.
AWS reInvent 2022 reCap AI/ML and DataChris Fregly
This document discusses Amazon Web Services (AWS) products and services for building end-to-end machine learning and data strategies. It covers topics such as ML infrastructure, governance, data preparation, model training, deployment, and education. Specific services mentioned include Amazon SageMaker, AWS Lake Formation, Amazon Redshift, Amazon EMR, AWS Glue, and AWS services for hardware acceleration like AWS Trainium and AWS Graviton.
Cloud Operating Models for Accelerated Cloud Transformation - AWS Summit SydneyAmazon Web Services
In this session you will learn about how the adoption of a Cloud Operating Model can accelerate your cloud transformation. You will learn about some of the effective Cloud Operating models (centralised, decentralised and distributed), how they affect organisational structures, and the role they play in digital transformation. Learn the role training plays in your accelerated transformation. Learn how to build and bootstrap a Cloud Center of Excellence (CCOE) and how they evolve as you transform your business in the adoption of cloud.
The document outlines an agenda for an AWSome Day event discussing Amazon's partnership model. The agenda includes sessions on the Amazon partnership model, AWS value proposition for partners, AWS Partner Network overview, business opportunities with AWS, AWS partner programs, program details, how to make partnerships work, and going to market with AWS. It also includes graphics showing AWS's growth, customers, services, and security capabilities. The presentation aims to explain Amazon's partnership programs and how partners can leverage AWS to drive new business and revenue opportunities.
Cloud Migration, Application Modernization and Security for PartnersAmazon Web Services
As AWS continues to expand, enterprise customers are increasingly looking to our partner ecosystem to assist in migrating their workloads to the cloud. This session describes the challenges, lessons learned, and best practices for large-scale application migrations. We will use real examples from our consulting partners and AWS Professional Services to illustrate how to move workloads to the cloud while modernizing the associated applications to take advantage of the unique benefits of AWS. We will also dive into how to use an array of AWS services and features to improve customers' security posture as they migrate and once they are up and running in the cloud.
This document provides an overview of AWS Lake Formation and related services for building a secure data lake. It discusses how Lake Formation provides a centralized management layer for data ingestion, cleaning, security and access. It also describes how Lake Formation integrates with services like AWS Glue, Amazon S3 and ML transforms to simplify and automate many data lake tasks. Finally, it provides an example workflow for using Lake Formation to deduplicate data from various sources and grant secure access for analysis.
Cloud migrations are hardly one size fits all. It can be challenging to migrate from a large-scale data center to an optimized AWS environment without draining IT resources. By leveraging CSC, organizations are able to determine exactly what they need from their IT infrastructure and efficiently migrate to a customized cloud environment on AWS that meets those needs. With 400+ AWS certified architects and 30+ experts with AWS professional-level certification, CSC helps organizations experience seamless, results-oriented migrations. Register for the upcoming webinar to hear speakers from CSC and AWS discuss the ins and outs of a successful large-scale migration to AWS.
Join us to learn:
How CSC helped a large federal systems integration company migrate their workloads to the AWS Cloud in less than three months
How CSC has facilitated customers split from their shared IT environment in less than 3 months
The step-by-step process of an efficient data center migration
Who Should Attend:
IT Manager, IT Security Manager, Solution Architect, Cloud App Architect, System Administrator, IT Project Manager, Product Manager, Business Development
The document discusses strategies for optimizing the total cost of ownership (TCO) of cloud infrastructure on AWS compared to on-premises infrastructure. It notes that on-premises infrastructure is typically underutilized and built to support peak capacity rather than average usage. AWS offers several ways to reduce TCO through pay-as-you-go pricing, reserved instances, spot instances, and economies of scale. The document outlines five pillars of cost optimization on AWS: right-sizing instances, increasing elasticity, monitoring usage, choosing the right pricing model, and matching usage to appropriate storage classes.
Introduction to the Well-Architected Framework and Tool - SVC208 - Anaheim AW...Amazon Web Services
Most modern businesses depend on a portfolio of technology solutions to operate and be successful every day. How do you know whether your team is following best practices or what the risks are in your architectures? This session shows how the AWS Well-Architected Framework provides prescriptive advice on best practices and how the AWS Well-Architected Tool enables you to measure and improve your technology portfolio. We explain how other customers are using AWS Well-Architected in their businesses, and we share what we learned from reviewing tens of thousands of architectures across operational excellence, security, reliability, performance efficiency, and cost optimization.
Cloud Adoption Framework Define Your Cloud Strategy and Accelerate Results Amazon Web Services
The document discusses the AWS Cloud Adoption Framework (CAF) and how it can help organizations transform their business using cloud technologies. The CAF is a structured approach in four stages - Envision, Align, Launch, and Realize Value. It helps organizations define business outcomes, identify stakeholders, develop cloud strategies and workstreams, and continuously measure value. The document provides examples and objectives for each CAF stage and emphasizes aligning cloud initiatives to business goals and measuring incremental value.
Migrate Enterprise Applications Framework and Guiding Principles.pdfAmazon Web Services
This webinar will cover the framework to migrate enterprise applications to AWS. You will learn AWS Cloud Adoption Framework which provides you with practical guidance and comprehensive guidelines including roles, governance and efficiency for your cloud adoption journey. We will also discuss technical and non-technical aspects of successful application migrations leveraging best practices and real world examples.
This is a Level 200 webinar.
Speaker: Manav Prabhakar, Practice Manager, AWS Professional Services
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.
Next Gen Innovation: Enhancing your Contact Center with Amazon Connect for t...Amazon Web Services
The document discusses enhancing contact centers with Amazon Connect for the public sector. It describes challenges with traditional contact center experiences and solutions. Amazon Connect is presented as a cloud-based solution that allows for personalized, intuitive customer experiences through dynamic contact flows and open integrations. It can scale to support seasonal needs through its pay-as-you-go model without hardware or long-term commitments. Examples of use cases for government and non-profits are provided.
The document discusses the AWS Cloud Adoption Framework (CAF) which is used to help organizations accelerate their journey to cloud adoption. It outlines the 4 stages of cloud adoption: retire technical debt, project, foundation, and migration/optimization. The CAF focuses on 6 perspectives - business value, people roles and readiness, governance and control, applications and infrastructure, security and risk, and operations. For each perspective, it identifies key stakeholders and questions organizations should consider to develop cloud capabilities. The CAF provides a holistic approach to cloud adoption by addressing business, people, and technical factors.
Data Transformation Patterns in AWS - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- Learn how to accelerate common data transformations from a variety of data
- Learn how to efficiently orchestrate transformation jobs
- Learn best practices and methodologies in data preparation for analytics
Recomendaciones, predicciones y detección de fraude usando servicios de intel...javier ramirez
La implementación de modelos de aprendizaje automático para resolver desafíos de negocios complejos, como detección de fraude, recomendaciones o predicción de series de datos es difícil si se quiere partir desde cero. Sin embargo, utilizando herramientas de AWS, implementar esos modelos está al alcance de cualquier empresa que sea capaz de subir un fichero a la nube, y llamar a un API cuando quiera obtener resultados. Basados en la tecnología de aprendizaje automático que se perfeccionó gracias a años de uso en Amazon.com, Amazon Forecast, Amazon Personalize, y Amazon Fraud Detector permiten a cualquiera sin experiencia previa en aprendizaje automático integrar estas tecnologías en sus aplicaciones. En este video aprenderás cuáles son las dificultades de crear modelos de predicción para los casos ya mencionados, verás como AWS acelera el difícil trabajo que se necesita para diseñar, entrenar e implementar un modelo personalizado para tus datos, y te contaremos todo lo que necesitas para poder empezar a integrar estos modelos en tu aplicación. Por supuesto, veremos demos de cómo funcionan
AWS Summit Singapore 2019 | Accelerating ML Adoption with Our New AI servicesAmazon Web Services
Speaker: Ben Snively, Principal Solutions Architect - Data & Analytics, AWS
Note: This is part 2 of the deck.
Adding to the existing AI services, AWS continues to bridge the gap for developers to build ML solutions without the hurdle of having data science expertise. In this session learn about the new services announced at re: Invent (Forecast, Textract and Personalize) and get a preview of what to expect when building time series models, OCR and recommendation engines with little to no data science experience.
This presentation describes two major papers in multi-variate time-series using deep neural networks. The first paper, DeepAR was developed at Amazon to deal with forecasting of millions of items where the same model can be applied to millions of products. DeepAR is implemented as a built-in algorithm of Amazon SageMaker. Code example is provided.
The second paper, Long- and Short-Term Temporal Patterns with Deep Neural Networks is developed at CMU and introduces a novel way to detect both short term and long term seasonality in data through introduction of skip-rnn.
A Gluon implementation of the paper is provided in the presentation.
Speech deliverd on 20 June 2020 at TR.AI Meetup, Istanbul
TR.AI Türkiye Yapay Zeka İnisiyatifi
AI/ML PoweredPersonalized Recommendations in Gaming Industry
Amazon Web Services - AWS
The University of Maryland has created a robust analytics platform utilizing AWS and Tableau. This session will provide an overview of the Decision Support project at UMD, showcase the reports.umd.edu site built on an Amazon S3 server, and demonstrate how UMD has utilized Tableau to analyze and report AWS usage and billing data.
Best practices for Running Spark jobs on Amazon EMR with Spot Instances | AWS...Amazon Web Services
In this session we are going to focus on cost-optimizing and efficiently running Spark applications on EMR by using Spot Instances. There are several best practices you should follow, in order to increase the fault-tolerance of your Spark applications and make use of Spot Instances, without compromising availability or impacting performance/duration of your jobs.
Machine learning for developers & data scientists with Amazon SageMaker - AIM...Amazon Web Services
Machine learning (ML) offers innovation for every business. But until recently, developing ML models took time and effort, making it difficult for developers to get started. In this session, we demonstrate how Amazon SageMaker, a fully managed service that enables developers and data scientists to build, train, and deploy ML models at scale, overcomes those challenges. We review its capabilities, including data labeling, model building, model training, tuning, and production hosting.
Construindo Aplicações Deep Learning com TensorFlow e Amazon SageMaker - MCL...Amazon Web Services
Deep Learning continua a impulsionar o estado da arte em domínios como visão computacional, linguagem natural e mecanismos de recomendação. Nesta sessão, você irá aprender como começar a usar o framework de Deep Learning TensorFlow usando o Amazon SageMaker, uma plataforma para criar, treinar e implantar facilmente modelos em escala. Você aprende como criar um modelo usando o TensorFlow configurando um Notebook Jupyter para começar a efetuar reconhecimento de imagem e objeto. Você também aprende como treinar e implantar rapidamente um modelo por meio do Amazon SageMaker.
This session highlights how Earth observation data shared in the cloud is accelerating research in machine learning that can have a dramatic impact on the effectiveness of future warfighting capability. Come learn about SpaceNet, a project sponsored by CosmiQ Works, DigitalGlobe, and Nvidia that makes commercial satellite imagery available for machine learning research on AWS. In this session, you will learn how AWS machine learning services like SageMaker, hyper-scale GPU compute capacity, and datasets shared in the cloud can ultimately produce machine learning models that could have a dramatic impact on the effectiveness of future warfighting capability. As the DoD strives to bring innovation directly to the warfighter, a combination of global open data sets coupled with easily built ML models can give warfighters access to critical information when the mission needs it most.
How Intuit TurboTax Ran Entirely on AWS for 2017 Taxes (ARC307) - AWS re:Inve...Amazon Web Services
In this session, Intuit presents how they prepared TurboTax to take the production load, and how they gained the confidence to run their 2017 peak activity entirely on AWS. They discuss resiliency testing, game days, operational run books, working with AWS Support, and how each of these activities impacted their confidence in their reliability and availability.
Air Passenger Prediction Using ARIMA Model AkarshAvinash
How has the Airline industry suffered during the pandemic? was a question that always stuck in my mind
when I saw articles on how travelling has been banned and movement of people not only from one country
to another country but also one state to another was being restricted. Hence as a statistics Student with a
curious mind I set out on a quest to find the effect of pandemic on the airline Industry. Tying statistics to
business problems that could benefit a business excites me. Hence I took up the initiative and called two
friends and decided to take their help in this task
we decided to get month wise domestic and international aviation data of the number of departures and
passengers in India during Jan 2010 to April 2022 from Airport Authorities of India website. We then took
this data cleaned, processed and transformed it to make it usable for our analysis. The analysis I suggested
to do for this objective was a familiar one which we had recently learnt in our fifth semester which was
Time series analysis under which we used the Auto Regressive Integrated Moving Average model which
creates a model that uses the past data to predict the future. As I am comfortable in coding I did the analysis
using R studio and python which has some excellent libraries to assist us in the analysis. We created the
model in such a way that the data could predict how the industry would behave if covid had not occurred.
We then compared the reality with the simulation which gave us some interesting interpretations. The results we found is that, international aviation industry on an average suffered five crores thirty three lakhs
per flight per month in losses and the domestic industry on an average suffered eighty two lakhs twenty
four thousand per flight per month in losses. But the key takeaway for the aviation industry from our
simulation vs reality analysis is that international travel is almost back on track after a major setback like
travel ban and it took 2 years and 3 months to do so whereas domestic travel is yet to recover.
I presented our findings and analysis to my statistics professor Mrs.Anwesha Roy also under whose
guidance we could come this far. She was thrilled with our work and encouraged us to get it published and
my team is currently working on it.
Getting started with streaming analytics: streaming basics (1 of 3)javier ramirez
In this webinar we explain which are some of the problems of streaming analytics, and why they are different to batch/big data analytics. Then we go into introducing some basic streaming concepts, like event queues, event processors, event vs processing time, and delivery guarantees. We end this first part of the series presenting a few of the most common open source components for streaming (Kafka, Spark, Flink, Cassandra, or ElasticSearch) and we mention the different options you have to run them on AWS.
In this webinar we explain which are some of the problems of streaming analytics, and why they are different to batch/big data analytics. Then we go into introducing some basic streaming concepts, like event queues, event processors, event vs processing time, and delivery guarantees. We end this first part of the series presenting a few of the most common open source components for streaming (Kafka, Spark, Flink, Cassandra, or ElasticSearch) and we mention the different options you have to run them on AWS.
Build Deep Learning Applications Using Apache MXNet - Featuring Chick-fil-A (...Amazon Web Services
The Apache MXNet deep learning framework is used for developing, training, and deploying diverse AI applications, including computer vision, speech recognition, natural language processing, and more at scale. In this session, learn how to get started with Apache MXNet on the Amazon SageMaker machine learning platform. Chick-fil-A share how they got started with MXNet on Amazon SageMaker to measure waffle fry freshness and how they leverage AWS services to improve the Chick-fil-A guest experience.
Build Deep Learning Applications Using Apache MXNet, Featuring Workday (AIM40...Amazon Web Services
The document discusses using machine learning for information extraction from enterprise documents. It describes using MXNet and Apache SageMaker for building and deploying models. It discusses various algorithms and techniques used for problems like document scanning, text recognition and understanding.
The document discusses Amazon SageMaker, a fully managed service that allows users to build, train, and deploy machine learning models at scale. It provides an overview of SageMaker's key features like notebooks for preprocessing data and building models, built-in algorithms for common tasks, one-click training of models, hyperparameter tuning, and deployment of trained models onto managed hosting infrastructure. SageMaker aims to make machine learning accessible to every developer by handling the complexities of training and deploying models.
[NEW LAUNCH!] Introducing Amazon Elastic Inference: Reduce Deep Learning Infe...Amazon Web Services
Deploying deep learning applications at scale can be cost prohibitive due to the need for hardware acceleration to meet latency and throughput requirements of inference. Amazon Elastic Inference helps you tackle this problem by reducing the cost of inference by up to 75% with GPU-powered acceleration that can be right-sized to your application’s inference needs. In this session, learn about how to deploy TensorFlow, Apache MXNet, and ONNX models with Amazon Elastic Inference on Amazon EC2 and Amazon SageMaker. Hear from Autodesk on the positive impact of AI on tools used to design and make a better world. Learn about how Autodesk and the Autodesk AI Lab are using Amazon Elastic Inference to make it cost efficient to run these tools at scale.
Analyze Amazon CloudFront and Lambda@Edge Logs to Improve Customer Experience...Amazon Web Services
Nowadays, web servers are often fronted by a global content delivery network, such as Amazon CloudFront, to accelerate delivery of websites, APIs, media content, and other web assets. In this hands-on-workshop, learn to improve website availability, optimize content based on devices, browser and user demographics, identify and analyze CDN usage patterns, and perform end-to-end debugging by correlating logs from various points in a request-response pipeline. Build an end-to-end serverless solution to analyze Amazon CloudFront logs using AWS Glue and Amazon Athena, generate visualization to derive deeper insights using Amazon QuickSight, and correlate with other logs such as CloudWatch logs to provide finer debugging experiences. Discuss how you can extend the pipeline you just built to generate deeper insights needed to improve the overall experience for your users.
Building a Modern Data Warehouse - Deep Dive on Amazon RedshiftAmazon Web Services
Osemeke Isibor, Solutions Architect, AWS
In this session, we take a deep dive on Amazon Redshift architecture and the latest performance enhancements that give you faster insights into your data. We also cover Redshift Spectrum, a feature of Redshift that enables you to analyze data across Redshift and your Amazon S3 data lake to deliver unique insights not possible by analyzing independent data silos.
Similar to Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learning. (20)
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
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.
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.
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.
AWS Serverless per startup: come innovare senza preoccuparsi dei serverAmazon Web Services
Serverless computing allows developers to build and run applications without having to manage infrastructure. With serverless, applications can automatically scale as usage increases and developers only pay for the resources consumed. Serverless services on AWS include AWS Lambda, API Gateway, DynamoDB, S3 and more which can be combined into serverless applications and architectures. AWS also provides training and certifications to help developers learn serverless concepts and services.
Amazon QuickSight è un servizio di business intelligence veloce e innovativo che consente di fornire informazioni dettagliate a tutti gli utenti dell'organizzazione. Come servizio completamente gestito, QuickSight consente di creare e pubblicare facilmente dashboard interattive che includono funzionalità uniche quali ML Insights, Ml Powered Forecasts and Anomaly Detection. Le dashboard sono quindi accessibili da qualsiasi dispositivo e possono essere integrate in applicazioni, portali e siti Web. Nell'ultimo anno QuickSight ha rilasciato oltre 200 nuove funzionalità. In questo webinar forniamo una panoramica dettagliata di QuickSight e una demo live per apprezzarne appieno il potenziale.