The document discusses options for running Oracle and SQL Server databases on AWS. It describes the differences between using Amazon RDS, which provides a managed service, versus running the databases on EC2 instances, which provides more control. Key features of RDS like licensing models, versions supported, high availability and security options are summarized. Storage and networking best practices for optimizing database performance when using EC2 instances are also covered.
In part one you will learn about benefits of moving Oracle Database Workloads to AWS, licensing and key aspects to consider. Part two is about understanding how to execute migrations, key success factors, and demonstration.
Choosing the Right Database for the Job: Relational, Cache, or NoSQL?Amazon Web Services
Developers and DBAs from a traditional relational background are spoilt for choice when looking to integrate caching and NoSQL into an application architecture to solve scaling problems and reduce costs. Even when using relational databases there are 3 managed database services on AWS for the MySQL engine alone. Trying to evaluate all the options often creates analysis paralysis, resulting in a reluctance to try something new or different. This session will guide you through a series of use cases that use different databases to solve business problems that customers face today.
Best practices for optimizing your EC2 costs with Spot Instances | AWS Floor28Amazon Web Services
Join this session to learn how AWS customers are using Spot Instances to save up to 90% off On-Demand price when running frontend and web applications, big-data and analytics, Batch and HPC, dev/test, and containerized workloads
Building with AWS Databases: Match Your Workload to the Right Database (DAT30...Amazon Web Services
We have recently seen some convergence of different database technologies. Many customers are evaluating heterogeneous migrations as their database needs have evolved or changed. Evaluating the best database to use for a job isn't as clear as it was ten years ago. We'll discuss the ideal use cases for relational and nonrelational data services, including Amazon ElastiCache for Redis, Amazon DynamoDB, Amazon Aurora, Amazon Neptune, and Amazon Redshift. This session digs into how to evaluate a new workload for the best managed database option. Please join us for a speaker meet-and-greet following this session at the Speaker Lounge (ARIA East, Level 1, Willow Lounge). The meet-and-greet starts 15 minutes after the session and runs for half an hour.
by Rich Alberth, Solutions Architect, AWS
Modernizing your database environment can bring many benefits, from avoiding technical debt to reducing expenses. AWS Database Migration Service enables easy modernization, enabling you to easily change database versions (and even database engines) and schema topologies while avoiding downtimes. We’ll look at some models for modernization, then do a hands-on exercise to migrate and consolidate MySQL databases to Amazon Aurora. You’ll need a laptop with a Firefox or Chrome browser.
This document provides an agenda and overview for a workshop on building a data lake on AWS. The agenda includes reviewing data lakes, modernizing data warehouses with Amazon Redshift, data processing with Amazon EMR, and event-driven processing with AWS Lambda. It discusses how data lakes extend traditional data warehousing approaches and how services like Redshift, EMR, and Lambda can be used for analytics in a data lake on AWS.
The document discusses options for running Oracle and SQL Server databases on AWS. It describes the differences between using Amazon RDS, which provides a managed service, versus running the databases on EC2 instances, which provides more control. Key features of RDS like licensing models, versions supported, high availability and security options are summarized. Storage and networking best practices for optimizing database performance when using EC2 instances are also covered.
In part one you will learn about benefits of moving Oracle Database Workloads to AWS, licensing and key aspects to consider. Part two is about understanding how to execute migrations, key success factors, and demonstration.
Choosing the Right Database for the Job: Relational, Cache, or NoSQL?Amazon Web Services
Developers and DBAs from a traditional relational background are spoilt for choice when looking to integrate caching and NoSQL into an application architecture to solve scaling problems and reduce costs. Even when using relational databases there are 3 managed database services on AWS for the MySQL engine alone. Trying to evaluate all the options often creates analysis paralysis, resulting in a reluctance to try something new or different. This session will guide you through a series of use cases that use different databases to solve business problems that customers face today.
Best practices for optimizing your EC2 costs with Spot Instances | AWS Floor28Amazon Web Services
Join this session to learn how AWS customers are using Spot Instances to save up to 90% off On-Demand price when running frontend and web applications, big-data and analytics, Batch and HPC, dev/test, and containerized workloads
Building with AWS Databases: Match Your Workload to the Right Database (DAT30...Amazon Web Services
We have recently seen some convergence of different database technologies. Many customers are evaluating heterogeneous migrations as their database needs have evolved or changed. Evaluating the best database to use for a job isn't as clear as it was ten years ago. We'll discuss the ideal use cases for relational and nonrelational data services, including Amazon ElastiCache for Redis, Amazon DynamoDB, Amazon Aurora, Amazon Neptune, and Amazon Redshift. This session digs into how to evaluate a new workload for the best managed database option. Please join us for a speaker meet-and-greet following this session at the Speaker Lounge (ARIA East, Level 1, Willow Lounge). The meet-and-greet starts 15 minutes after the session and runs for half an hour.
by Rich Alberth, Solutions Architect, AWS
Modernizing your database environment can bring many benefits, from avoiding technical debt to reducing expenses. AWS Database Migration Service enables easy modernization, enabling you to easily change database versions (and even database engines) and schema topologies while avoiding downtimes. We’ll look at some models for modernization, then do a hands-on exercise to migrate and consolidate MySQL databases to Amazon Aurora. You’ll need a laptop with a Firefox or Chrome browser.
This document provides an agenda and overview for a workshop on building a data lake on AWS. The agenda includes reviewing data lakes, modernizing data warehouses with Amazon Redshift, data processing with Amazon EMR, and event-driven processing with AWS Lambda. It discusses how data lakes extend traditional data warehousing approaches and how services like Redshift, EMR, and Lambda can be used for analytics in a data lake on AWS.
What's New in Amazon Aurora (DAT204-R1) - AWS re:Invent 2018Amazon Web Services
Amazon Aurora is a MySQL- and PostgreSQL-compatible relational database with the speed, reliability, and availability of commercial databases at one-tenth the cost. This session provides an overview of Aurora, explores recently announced features, such as Serverless, Multi-Master, and Performance Insights, and helps you get started.
by Mikhail Prudnikov, Sr. Solutions Architect, AWS
In-memory data stores, such as ElastiCache for Redis, enable applications where response times are measured in microseconds. We’ll look at how to design and deploy high-performance applications using ElastiCache, Aurora, DynamoDB, DAX, and Lambda, then we’ll do a hands-on lab to do it ourselves. You’ll need a laptop with a Firefox or Chrome browser.
Deep Dive on PostgreSQL Databases on Amazon RDS (DAT324) - AWS re:Invent 2018Amazon Web Services
In this session, we provide an overview of the PostgreSQL options available on AWS, and do a deep dive on Amazon Relational Database Service (Amazon RDS) for PostgreSQL, a fully managed PostgreSQL service, and Amazon Aurora, a PostgreSQL-compatible database with up to 3x the performance of standard PostgreSQL. Learn about the features, functionality, and many innovations in Amazon RDS and Aurora, which give you the background to choose the right service to solve different technical challenges, and the knowledge to easily move between services as your requirements change over time.
Using data lakes to quench your analytics fire - AWS Summit Cape Town 2018Amazon Web Services
Speaker: Shafreen Sayyed, AWS
Level: 200
Traditional data storage and analytic tools no longer provide the agility and flexibility required to deliver relevant business insights. We are seeing more and more organisations shift to a data lake solution. This approach allows you to store massive amounts of data in a central location so its readily available to be categorized, processed, analyzed, and consumed by diverse organizational groups. In this session, we’ll assemble a data lake using services such as Amazon S3, Amazon Kinesis, Amazon Athena, Amazon EMR, AWS Glue and integration with Amazon Redshift Spectrum.
The Open Data Lake Platform Brief - Data Sheets | WhitepaperVasu S
An open data lake platform provides a robust and future-proof data management paradigm to support a wide range of data processing needs, including data exploration, ad-hoc analytics, streaming analytics, and machine learning.
Bursting on-premise analytic workloads to Amazon EMR using AlluxioAlluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
Bursting on-premise analytic workloads to Amazon EMR using Alluxio
Roy Hasson, AWS
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
Migrate from Oracle to Aurora PostgreSQL: Best Practices, Design Patterns, & ...Amazon Web Services
In this session, we show you how to set the source Oracle database environment, the target PostgreSQL environment, and parameter group configuration. We also recommended database parameters to disable foreign keys and triggers. Finally, we discuss best practices for using AWS Database Migration Service (AWS DMS) and AWS Schema Conversion Tool (AWS SCT) and show you how to choose the instance type and configure AWS DMS.
What's New in Amazon Relational Database Service (DAT203) - AWS re:Invent 2018Amazon Web Services
Amazon Relational Database Service (Amazon RDS) is a fully managed relational database service that enables you to launch an optimally configured, secure, and highly available database with just a few clicks. It manages time-consuming database administration tasks, freeing you to focus on your applications and business. We review the capabilities of the service and review the latest available featurese.
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.
Ask Me Anything about Amazon Aurora (DAT369-R1) - AWS re:Invent 2018Amazon Web Services
Amazon Aurora is a MySQL- and PostgreSQL-compatible relational database with the speed, reliability, and availability of commercial databases at one-tenth the cost. We recently introduced several new features, such as Serverless, Multi-Master, Parallel Query, Backtrack, and Performance Insights. Bring your questions about these features or any other Aurora topic.
by Ben Willett, Solutions Architect, AWS
How do you get data from your sources into your Redshift data warehouse? We'll show how to use AWS Glue and Amazon Kinesis Firehose to make it easy to automate the work to get data loaded.
Migrating Databases to the Cloud with AWS Database Migration Service (DAT207)...Amazon Web Services
Learn how to convert and migrate your relational databases, nonrelational databases, and data warehouses to the cloud. AWS Database Migration Service (AWS DMS) and AWS Schema Conversion Tool (AWS SCT) can help with homogeneous migrations as well as migrations between different database engines, such as Oracle or SQL Server, to Amazon Aurora. Hear from Verizon about how they intend to migrate critical databases to Amazon Aurora with PostgreSQL compatibility from their current on-premises Oracle databases, and learn how they intend to deal with challenges such as conversion of legacy code and complex data types, supporting business resiliency, and maintaining data synchronization during the transition phase.
Data Warehousing with Amazon Redshift: Data Analytics Week at the SF LoftAmazon Web Services
Data Warehousing with Amazon Redshift: Data Analytics Week at the San Francisco Loft
A closer look at the fast, fully managed data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing Business Intelligence (BI) tools. We'll show how to run complex analytic queries against petabytes of structured data, using sophisticated query optimization, columnar storage on high-performance local disks, and massively parallel query execution.
Level: Beginner
Speakers:
Jay Formosa - Solutions Architect, AWS
Sudhir Gupta - Partner Solutions Architect, Redshift Specialist, AWS
Best Practices for Migrating Oracle Databases to the Cloud - AWS Online Tech ...Amazon Web Services
Learning Objectives:
- Learn how to migrate Oracle databases to the cloud
- Learn how to run additional components of the Oracle stack on AWS
- Get acquainted with other database options on AWS
Best Practices for Running Oracle Databases on Amazon RDS (DAT317) - AWS re:I...Amazon Web Services
Amazon Relational Database Service (Amazon RDS) continues to be a popular choice for Oracle DBAs moving new and legacy workloads to the cloud. In this session, we discuss how Amazon RDS for Oracle helps DBAs focus their time where it matters most. We cover recent RDS Oracle features, and we go deep on key functionality that enables license optimization, performance, and high availability for Oracle databases. We also hear directly from an AWS customer about their journey to Amazon RDS and the best practices that helped make their move successful.
Build on Amazon Aurora with MySQL Compatibility (DAT348-R4) - AWS re:Invent 2018Amazon Web Services
Amazon Aurora is a MySQL- and PostgreSQL-compatible relational database with the speed, reliability, and availability of commercial databases at one-tenth the cost. Join this session, and get started with the MySQL-compatible edition, discuss your existing application running on Aurora, or learn about recently announced features, such as Serverless or Parallel Query.
Cost Optimization for Apache Hadoop/Spark Workloads with Amazon EMRProvectus
Considering new ways and options for reducing operational costs and scaling flexibility of your Apache Hadoop/Spark? Try migrating to Amazon EMR!
On-premises Apache Hadoop/Spark clusters are among the top sources of financial pressure for businesses. IT organizations want to reduce spend while still meeting demand, to keep their legacy data applications up and running. Come and learn from experts at Provectus & AWS how you can use Amazon EMR to start driving cost efficiencies in your organization!
Agenda
- Hadoop market and cost optimizations using Amazon EMR
- Cost related and other challenges of on-prem Hadoop clusters
- Cost optimizations by using Amazon EMR and migration best practices
Intended audience
Technology executives & decision makers, manager-level tech roles, data engineers & data scientists, and developers
Presenters
- Stepan Pushkarev, Chief Technology Officer, Provectus
- Pritpal Sahota, Technical Account Manager, Provectus
- Nirav Shah, Senior Solutions Architect, AWS
- Perry Peterson, Business Development Manager, AWS
Feel free to share this presentation with your colleagues and don't hesitate to reach out to us at info@provectus.com if you have any questions!
REQUEST WEBINAR: https://provectus.com/cost-optimization-for-apache-hadoop-spark-workloads-with-amazon-emr-june-2020/
Migrating Oracle to Aurora PostgreSQL Utilizing AWS Database Migration Servic...Amazon Web Services
Appriss creates actionable information and insights gained from their data and analytics solutions, their customers are able to more effectively save lives, mitigate fraud, and reduce risk. They call it “knowledge for good”. One of the many challenges facing Appriss was how to migrate a multi-terabyte Oracle database from one of their own data centers into AWS with minimal disruption to their applications and customers while reducing cost and not sacrificing security, availability, and reliability. This session provides an overview and demo of Aurora PostgreSQL and AWS Database Migration Service (DMS) as Appriss discusses their primary drivers for choosing the combination, preparation, challenges faced throughout the process, results, and future plans.
Building a Modern Data Warehouse: Deep Dive on Amazon Redshift - SRV337 - Chi...Amazon Web Services
In this chalk talk, 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 Amazon Redshift Spectrum, a feature of Amazon Redshift that enables you to analyze data across Amazon Redshift and your Amazon S3 data lake to deliver unique insights not possible by analyzing independent data silos.
AWS SSA Webinar 21 - Getting Started with Data lakes on AWSCobus Bernard
In this session, we will take you through getting started with a Data Lake by looking at how you can ingest data to Amazon S3, query it with Amazon Athena and perform ETL operations on it using AWS Glue. We will be using the Redshift cluster from the previous session to export data to S3 to query.
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.
What's New in Amazon Aurora (DAT204-R1) - AWS re:Invent 2018Amazon Web Services
Amazon Aurora is a MySQL- and PostgreSQL-compatible relational database with the speed, reliability, and availability of commercial databases at one-tenth the cost. This session provides an overview of Aurora, explores recently announced features, such as Serverless, Multi-Master, and Performance Insights, and helps you get started.
by Mikhail Prudnikov, Sr. Solutions Architect, AWS
In-memory data stores, such as ElastiCache for Redis, enable applications where response times are measured in microseconds. We’ll look at how to design and deploy high-performance applications using ElastiCache, Aurora, DynamoDB, DAX, and Lambda, then we’ll do a hands-on lab to do it ourselves. You’ll need a laptop with a Firefox or Chrome browser.
Deep Dive on PostgreSQL Databases on Amazon RDS (DAT324) - AWS re:Invent 2018Amazon Web Services
In this session, we provide an overview of the PostgreSQL options available on AWS, and do a deep dive on Amazon Relational Database Service (Amazon RDS) for PostgreSQL, a fully managed PostgreSQL service, and Amazon Aurora, a PostgreSQL-compatible database with up to 3x the performance of standard PostgreSQL. Learn about the features, functionality, and many innovations in Amazon RDS and Aurora, which give you the background to choose the right service to solve different technical challenges, and the knowledge to easily move between services as your requirements change over time.
Using data lakes to quench your analytics fire - AWS Summit Cape Town 2018Amazon Web Services
Speaker: Shafreen Sayyed, AWS
Level: 200
Traditional data storage and analytic tools no longer provide the agility and flexibility required to deliver relevant business insights. We are seeing more and more organisations shift to a data lake solution. This approach allows you to store massive amounts of data in a central location so its readily available to be categorized, processed, analyzed, and consumed by diverse organizational groups. In this session, we’ll assemble a data lake using services such as Amazon S3, Amazon Kinesis, Amazon Athena, Amazon EMR, AWS Glue and integration with Amazon Redshift Spectrum.
The Open Data Lake Platform Brief - Data Sheets | WhitepaperVasu S
An open data lake platform provides a robust and future-proof data management paradigm to support a wide range of data processing needs, including data exploration, ad-hoc analytics, streaming analytics, and machine learning.
Bursting on-premise analytic workloads to Amazon EMR using AlluxioAlluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
Bursting on-premise analytic workloads to Amazon EMR using Alluxio
Roy Hasson, AWS
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
Migrate from Oracle to Aurora PostgreSQL: Best Practices, Design Patterns, & ...Amazon Web Services
In this session, we show you how to set the source Oracle database environment, the target PostgreSQL environment, and parameter group configuration. We also recommended database parameters to disable foreign keys and triggers. Finally, we discuss best practices for using AWS Database Migration Service (AWS DMS) and AWS Schema Conversion Tool (AWS SCT) and show you how to choose the instance type and configure AWS DMS.
What's New in Amazon Relational Database Service (DAT203) - AWS re:Invent 2018Amazon Web Services
Amazon Relational Database Service (Amazon RDS) is a fully managed relational database service that enables you to launch an optimally configured, secure, and highly available database with just a few clicks. It manages time-consuming database administration tasks, freeing you to focus on your applications and business. We review the capabilities of the service and review the latest available featurese.
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.
Ask Me Anything about Amazon Aurora (DAT369-R1) - AWS re:Invent 2018Amazon Web Services
Amazon Aurora is a MySQL- and PostgreSQL-compatible relational database with the speed, reliability, and availability of commercial databases at one-tenth the cost. We recently introduced several new features, such as Serverless, Multi-Master, Parallel Query, Backtrack, and Performance Insights. Bring your questions about these features or any other Aurora topic.
by Ben Willett, Solutions Architect, AWS
How do you get data from your sources into your Redshift data warehouse? We'll show how to use AWS Glue and Amazon Kinesis Firehose to make it easy to automate the work to get data loaded.
Migrating Databases to the Cloud with AWS Database Migration Service (DAT207)...Amazon Web Services
Learn how to convert and migrate your relational databases, nonrelational databases, and data warehouses to the cloud. AWS Database Migration Service (AWS DMS) and AWS Schema Conversion Tool (AWS SCT) can help with homogeneous migrations as well as migrations between different database engines, such as Oracle or SQL Server, to Amazon Aurora. Hear from Verizon about how they intend to migrate critical databases to Amazon Aurora with PostgreSQL compatibility from their current on-premises Oracle databases, and learn how they intend to deal with challenges such as conversion of legacy code and complex data types, supporting business resiliency, and maintaining data synchronization during the transition phase.
Data Warehousing with Amazon Redshift: Data Analytics Week at the SF LoftAmazon Web Services
Data Warehousing with Amazon Redshift: Data Analytics Week at the San Francisco Loft
A closer look at the fast, fully managed data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing Business Intelligence (BI) tools. We'll show how to run complex analytic queries against petabytes of structured data, using sophisticated query optimization, columnar storage on high-performance local disks, and massively parallel query execution.
Level: Beginner
Speakers:
Jay Formosa - Solutions Architect, AWS
Sudhir Gupta - Partner Solutions Architect, Redshift Specialist, AWS
Best Practices for Migrating Oracle Databases to the Cloud - AWS Online Tech ...Amazon Web Services
Learning Objectives:
- Learn how to migrate Oracle databases to the cloud
- Learn how to run additional components of the Oracle stack on AWS
- Get acquainted with other database options on AWS
Best Practices for Running Oracle Databases on Amazon RDS (DAT317) - AWS re:I...Amazon Web Services
Amazon Relational Database Service (Amazon RDS) continues to be a popular choice for Oracle DBAs moving new and legacy workloads to the cloud. In this session, we discuss how Amazon RDS for Oracle helps DBAs focus their time where it matters most. We cover recent RDS Oracle features, and we go deep on key functionality that enables license optimization, performance, and high availability for Oracle databases. We also hear directly from an AWS customer about their journey to Amazon RDS and the best practices that helped make their move successful.
Build on Amazon Aurora with MySQL Compatibility (DAT348-R4) - AWS re:Invent 2018Amazon Web Services
Amazon Aurora is a MySQL- and PostgreSQL-compatible relational database with the speed, reliability, and availability of commercial databases at one-tenth the cost. Join this session, and get started with the MySQL-compatible edition, discuss your existing application running on Aurora, or learn about recently announced features, such as Serverless or Parallel Query.
Cost Optimization for Apache Hadoop/Spark Workloads with Amazon EMRProvectus
Considering new ways and options for reducing operational costs and scaling flexibility of your Apache Hadoop/Spark? Try migrating to Amazon EMR!
On-premises Apache Hadoop/Spark clusters are among the top sources of financial pressure for businesses. IT organizations want to reduce spend while still meeting demand, to keep their legacy data applications up and running. Come and learn from experts at Provectus & AWS how you can use Amazon EMR to start driving cost efficiencies in your organization!
Agenda
- Hadoop market and cost optimizations using Amazon EMR
- Cost related and other challenges of on-prem Hadoop clusters
- Cost optimizations by using Amazon EMR and migration best practices
Intended audience
Technology executives & decision makers, manager-level tech roles, data engineers & data scientists, and developers
Presenters
- Stepan Pushkarev, Chief Technology Officer, Provectus
- Pritpal Sahota, Technical Account Manager, Provectus
- Nirav Shah, Senior Solutions Architect, AWS
- Perry Peterson, Business Development Manager, AWS
Feel free to share this presentation with your colleagues and don't hesitate to reach out to us at info@provectus.com if you have any questions!
REQUEST WEBINAR: https://provectus.com/cost-optimization-for-apache-hadoop-spark-workloads-with-amazon-emr-june-2020/
Migrating Oracle to Aurora PostgreSQL Utilizing AWS Database Migration Servic...Amazon Web Services
Appriss creates actionable information and insights gained from their data and analytics solutions, their customers are able to more effectively save lives, mitigate fraud, and reduce risk. They call it “knowledge for good”. One of the many challenges facing Appriss was how to migrate a multi-terabyte Oracle database from one of their own data centers into AWS with minimal disruption to their applications and customers while reducing cost and not sacrificing security, availability, and reliability. This session provides an overview and demo of Aurora PostgreSQL and AWS Database Migration Service (DMS) as Appriss discusses their primary drivers for choosing the combination, preparation, challenges faced throughout the process, results, and future plans.
Building a Modern Data Warehouse: Deep Dive on Amazon Redshift - SRV337 - Chi...Amazon Web Services
In this chalk talk, 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 Amazon Redshift Spectrum, a feature of Amazon Redshift that enables you to analyze data across Amazon Redshift and your Amazon S3 data lake to deliver unique insights not possible by analyzing independent data silos.
AWS SSA Webinar 21 - Getting Started with Data lakes on AWSCobus Bernard
In this session, we will take you through getting started with a Data Lake by looking at how you can ingest data to Amazon S3, query it with Amazon Athena and perform ETL operations on it using AWS Glue. We will be using the Redshift cluster from the previous session to export data to S3 to query.
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.
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.