Amazon Aurora is a relational database built for the cloud and is compatible with MySQL and PostgreSQL. It combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open-source databases. We'll cover some of the key innovations in the Aurora database engine and storage layers, explain recently announced features, such as Aurora Serverless, Aurora Multi-Master, and Aurora Parallel Query, and discuss best practices and optimal configurations. See why Aurora is a great fit for new application development and for migrations from overpriced, restrictive commercial databases.
VMware Cloud on AWS enables you to migrate existing workloads to the AWS Cloud quickly by using tools you are already familiar with. VMware Cloud on AWS brings VMware’s enterprise class Software-Defined Data Center software to Amazon’s public cloud, delivered as an on-demand, elastically scalable, cloud-based solution. Sold and operated by VMware, the solution enables customers to use a common set of software and tools to manage both their AWS-based and on-premises vSphere resources consistently. This session uses practical, real-world customer deployment examples to dive deep on hybrid cloud network connectivity, data protection best practices, and AWS native service integrations.
Amazon RDS enables you to launch an optimally configured, secure, and highly available relational database with just a few clicks. It provides cost-efficient and resizable capacity while managing time-consuming administration tasks, freeing you to focus on your applications and business. In this session, we take a closer look at how Amazon RDS works, and we review best practices to achieve performance, flexibility, and cost saving for your MySQL, PostgreSQL, MariaDB, Oracle, and SQL Server databases on Amazon RDS. We also discuss AWS Database Migration Service, a quick and secure means for migrating your existing RDBMS investments to Amazon RDS.
Amazon EC2 provides resizable compute capacity in the cloud, making web scale computing easier. It offers a wide variety of compute instances and is well suited to every imaginable use case, from static websites to on-demand, high-performance supercomputing--all with flexible pricing options. In this session, learn about the latest Amazon EC2 features and capabilities, including Approved instance families, the differences among their hardware types and capabilities, and their optimal use cases. Also discover best practices for optimizing your expenditure and getting the most benefit from your EC2 instances while saving time and money.
Hands-On: Building a Migration Strategy for SQL Server on AWS (WIN310) - AWS ...Amazon Web Services
In this workshop, we discuss how to migrate SQL Server databases to AWS. Following a short presentation, attendees have the opportunity to choose a hands-on walkthrough to migrate a SQL Server database from an on-premises environment to SQL Server on Amazon EC2 or SQL Server on Amazon RDS. Bring a laptop for the hands-on exercises.
This session provides IT pros and application owners an overview of AWS options for building hybrid storage architectures or even entirely migrating datacenter storage to the AWS cloud. The AWS Storage Gateway connects existing on-premises block, file or tape storage systems to AWS cloud storage over the WAN in a hybrid model. The AWS Snow family of physical devices can capture, pre-process and migrate data into and out of AWS without any network connection at all. Join us to learn how you can close down datacenters, reduce storage footprints, and build solutions for tiering, data lakes, backup, disaster recovery, and migration.
Building Serverless Analytics Solutions with Amazon QuickSight (ANT391) - AWS...Amazon Web Services
Querying and analyzing big data can be complicated and expensive. It requires you to setup and manage databases, data warehouses, and business intelligence (BI) applications—all of which require time, effort, and resources. Using Amazon Athena and Amazon QuickSight, you can avoid the cost and complexity by creating a fast, scalable, and serverless cloud analytics solution without the need to invest in databases, data warehouses, complex ETL solutions, and BI applications. In this session, we demonstrate how you can build a serverless big data analytics solution using Amazon Athena and Amazon QuickSight.
Replicate and Manage Data Using Managed Databases and Serverless Technologies Amazon Web Services
If you have disparate datasets within your data center and on AWS, it can be challenging to manage all of them while you extract and analyze data. In this workshop, we use AWS managed database services, migration tools, and serverless technologies to replicate data and manage it in the cloud. We replicate an on-premises database to Amazon Aurora using AWS Database Migration Service, and we show you how Aurora Serverless can automatically scale your database and reduce your database costs. Ensure that you have an AWS account, and familiarize yourself with the AWS Management Console at least a day before the workshop. You don't need any credit on the account.
AWS DeepLens Workshop_Build Computer Vision Applications Amazon Web Services
In this workshop, developers have the opportunity to learn how to build and deploy computer vision models using the AWS DeepLens deep-learning-enabled video camera. By working hands on, developers of all skill levels can explore and build their own deep-learning-powered computer vision applications using Amazon SageMaker and AWS DeepLens devices. Attendees can experiment with different sample projects for face detection, object detection, artistic style transfer, and other machine learning use cases using Apache MXNet. Attendees also learn about use cases that integrate other AWS services that extend the functionality of AWS DeepLens, such as AWS Lambda, Amazon Polly, and Amazon Rekognition.
VMware Cloud on AWS enables you to migrate existing workloads to the AWS Cloud quickly by using tools you are already familiar with. VMware Cloud on AWS brings VMware’s enterprise class Software-Defined Data Center software to Amazon’s public cloud, delivered as an on-demand, elastically scalable, cloud-based solution. Sold and operated by VMware, the solution enables customers to use a common set of software and tools to manage both their AWS-based and on-premises vSphere resources consistently. This session uses practical, real-world customer deployment examples to dive deep on hybrid cloud network connectivity, data protection best practices, and AWS native service integrations.
Amazon RDS enables you to launch an optimally configured, secure, and highly available relational database with just a few clicks. It provides cost-efficient and resizable capacity while managing time-consuming administration tasks, freeing you to focus on your applications and business. In this session, we take a closer look at how Amazon RDS works, and we review best practices to achieve performance, flexibility, and cost saving for your MySQL, PostgreSQL, MariaDB, Oracle, and SQL Server databases on Amazon RDS. We also discuss AWS Database Migration Service, a quick and secure means for migrating your existing RDBMS investments to Amazon RDS.
Amazon EC2 provides resizable compute capacity in the cloud, making web scale computing easier. It offers a wide variety of compute instances and is well suited to every imaginable use case, from static websites to on-demand, high-performance supercomputing--all with flexible pricing options. In this session, learn about the latest Amazon EC2 features and capabilities, including Approved instance families, the differences among their hardware types and capabilities, and their optimal use cases. Also discover best practices for optimizing your expenditure and getting the most benefit from your EC2 instances while saving time and money.
Hands-On: Building a Migration Strategy for SQL Server on AWS (WIN310) - AWS ...Amazon Web Services
In this workshop, we discuss how to migrate SQL Server databases to AWS. Following a short presentation, attendees have the opportunity to choose a hands-on walkthrough to migrate a SQL Server database from an on-premises environment to SQL Server on Amazon EC2 or SQL Server on Amazon RDS. Bring a laptop for the hands-on exercises.
This session provides IT pros and application owners an overview of AWS options for building hybrid storage architectures or even entirely migrating datacenter storage to the AWS cloud. The AWS Storage Gateway connects existing on-premises block, file or tape storage systems to AWS cloud storage over the WAN in a hybrid model. The AWS Snow family of physical devices can capture, pre-process and migrate data into and out of AWS without any network connection at all. Join us to learn how you can close down datacenters, reduce storage footprints, and build solutions for tiering, data lakes, backup, disaster recovery, and migration.
Building Serverless Analytics Solutions with Amazon QuickSight (ANT391) - AWS...Amazon Web Services
Querying and analyzing big data can be complicated and expensive. It requires you to setup and manage databases, data warehouses, and business intelligence (BI) applications—all of which require time, effort, and resources. Using Amazon Athena and Amazon QuickSight, you can avoid the cost and complexity by creating a fast, scalable, and serverless cloud analytics solution without the need to invest in databases, data warehouses, complex ETL solutions, and BI applications. In this session, we demonstrate how you can build a serverless big data analytics solution using Amazon Athena and Amazon QuickSight.
Replicate and Manage Data Using Managed Databases and Serverless Technologies Amazon Web Services
If you have disparate datasets within your data center and on AWS, it can be challenging to manage all of them while you extract and analyze data. In this workshop, we use AWS managed database services, migration tools, and serverless technologies to replicate data and manage it in the cloud. We replicate an on-premises database to Amazon Aurora using AWS Database Migration Service, and we show you how Aurora Serverless can automatically scale your database and reduce your database costs. Ensure that you have an AWS account, and familiarize yourself with the AWS Management Console at least a day before the workshop. You don't need any credit on the account.
AWS DeepLens Workshop_Build Computer Vision Applications Amazon Web Services
In this workshop, developers have the opportunity to learn how to build and deploy computer vision models using the AWS DeepLens deep-learning-enabled video camera. By working hands on, developers of all skill levels can explore and build their own deep-learning-powered computer vision applications using Amazon SageMaker and AWS DeepLens devices. Attendees can experiment with different sample projects for face detection, object detection, artistic style transfer, and other machine learning use cases using Apache MXNet. Attendees also learn about use cases that integrate other AWS services that extend the functionality of AWS DeepLens, such as AWS Lambda, Amazon Polly, and Amazon Rekognition.
Amazon DynamoDB is a serverless database for applications that need a flexible data model with high performance at any scale. In this session, we cover newly announced features and provide an end-to-end view of recent innovations. We also share some of our successful customer stories and use cases. Come to this session to learn all about what’s new with DynamoDB!
Developing with .NET Core on AWS: What's New (DEV318-R1) - AWS re:Invent 2018Amazon Web Services
In this demonstration-heavy session, we illustrate our latest techniques, tools, and libraries for developing end-to-end applications with .NET Core. We focus on serverless applications, but the techniques are broadly relevant. We start by showing you some useful features and best practices for authoring your serverless application, including debugging locally from the IDE and in production. From there, we demonstrate some helpful tools that make it easy to set up your CI/CD workflow from the start. Finally, we deploy our application with AWS Lambda.
SRV205 Architectures and Strategies for Building Modern Applications on AWSAmazon Web Services
Rapid growth of technology and tooling in the cloud has enabled us to build modern applications that are more secure, scalable, and focused on our business. In this session, we cover the key compute primitives that enable us to accelerate towards building and running modern, cloud-native applications. We highlight what we’ve learned from customers running applications with AWS Lambda and AWS Fargate, two modern compute technologies for running applications in the cloud. In addition, we cover architecture patterns of modern application, key primitives required for building modern systems, steps you can take to start building and monitoring modern applications today, and secrets to fearlessly going faster and farther in the cloud.
SRV327 Replicate, Analyze, and Visualize Data Using Managed Database and Ser...Amazon Web Services
If you have disparate datasets within your data center and on AWS, it can be challenging to manage all of them while you extract and analyze data to drive positive business outcomes. In this workshop, we use AWS managed database services, migration tools, and serverless technologies to replicate, analyze, and visualize data. We replicate an on-premises database to Amazon RDS and Amazon S3 using AWS Database Migration Service and the AWS Schema Conversion Tool. We then use Amazon Athena to interactively analyze data using SQL, and finally, we use Amazon QuickSight to visualize the data to enable better business decisions. For this session, ensure that you have an AWS account set up, and familiarize yourself with the AWS Management Console at least a day before the workshop. You don't need any credit on the account.
Citrix Moves Data to Amazon Redshift Fast with Matillion ETLAmazon Web Services
Matillion ETL, easily deployable from Amazon Web Services (AWS) Marketplace, helps Citrix collate and summarize data and augment it with more traditional business data from Microsoft SQL Server for additional context. Join our webinar to learn how organizations of any size can move data to the cloud quickly, accurately, and affordably with Matillion ETL.
Join our webinar to learn:
How Citrix moved data to Amazon Redshift with speed and accuracy.
How to make informed, business-critical decisions by analyzing data with Amazon Redshift.
How to speed time-to-value for your analytics initiatives using Matillion’s push-down ELT architecture.
Analyze your Data Lake, Fast @ Any Scale - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
-Learn how to automatically discover, catalog, and prepare your data for analytics
-Understand how to query data in your data lake without having to transform or load the data into your data warehouse
-See how to analyze data in both your data lake and data warehouse
Scaling Up to Your First 10 Million Users (ARC205-R1) - AWS re:Invent 2018Amazon Web Services
Cloud computing provides a number of advantages, such as the ability to scale your web application or website on demand. If you have a new web application and want to use cloud computing, you might be asking yourself, "Where do I start?" Join us in this session for best practices on scaling your resources from one to millions of users. We show you how to best combine different AWS services, how to make smarter decisions for architecting your application, and how to scale your infrastructure in the cloud.
In this workshop, learn how to create a cloud-based business intelligence platform and deliver dynamic insights through a custom Alexa Skill. Together, we architect a data analytics platform using Amazon S3, Amazon Athena, Amazon QuickSight, Amazon DynamoDB, Amazon CloudWatch on the backend, and a voice-based user interface through a private Alexa Skill deployed via Alexa for Business on the front end.
This session will highlight the most impactful announcements made at AWS re:Invent 2017 while giving you ideas on key use cases for new services and features. We’ll cover major themes of the conference, the new services and features within those themes and how they work together to make it faster and easier to build functionality into your app.
BDA301 Working with Machine Learning in Amazon SageMaker: Algorithms, Models,...Amazon Web Services
Today, organizations are using machine learning (ML) to address a host of business challenges, from product recommendations and pricing predictions, to tracking disease progression and demand forecasting. Until recently, developing these ML models took a significant amount of time and effort, and it required expertise in this field. In this session, we introduce you to Amazon SageMaker, a fully managed ML service that enables developers and data scientists to develop and deploy deep learning models more quickly and easily. We walk through the features and benefits of Amazon SageMaker and discuss the uniquely designed ML algorithms that allow for optimized model training, to get you to production fast.
SRV310 Optimizing Relational Databases on AWS: Deep Dive on Amazon RDSAmazon Web Services
Amazon RDS enables you to launch an optimally configured, secure, and highly available relational database with just a few clicks. It provides cost-efficient and resizable capacity while managing time-consuming administration tasks, and freeing you to focus on your applications and business. In this session, we take a closer look at how Amazon RDS works, and we review best practices to achieve performance, flexibility, and cost saving for your MySQL, PostgreSQL, MariaDB, Oracle, and SQL Server databases on Amazon RDS. We also discuss AWS Database Migration Service, a quick and secure means for migrating your existing RDBMS investments to Amazon RDS.
Humans and Data Don't Mix- Best Practices to Secure Your CloudAmazon Web Services
When it comes to security, human error far outpaces other causes of failures. The risk of humans touching sensitive data is clear, so how do you get them away from your data while also speeding up time to detection and remediation? Stephen Schmidt, AWS CISO, will share hard-earned lessons around potential opportunities in your security program, along with practical steps to improve the agility of your organization.
The Future of Enterprise Applications is Serverless (ENT314-R1) - AWS re:Inve...Amazon Web Services
At re:Invent 2014, we announced AWS Lambda and ushered in a whole new world of application design, one without the need to manage or think about traditional server infrastructure. Since then, serverless has become one of the hottest topics in the industry. Customers like Capital One and Coca Cola talk about how serverless saved them time and money, helped them reduce their operational burden, and drove developer agility and innovation. What is serverless, and what are the key trends you should be aware of? Where does one start on the journey of building serverless applications? We cover all of this and more in this session.
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.
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 ML services work together to build a successful data lake for various roles, including data scientists and business users.
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
Most technology professionals know that the AWS cloud reduces the cost of running and maintaining traditional server infrastructure, as well as providing scalability on demand. Fewer know, however, that our platform meets the requirements of even the most security-conscious organizations, from financial services institutes to government departments.
To protect our customers, and to maintain your trust and confidence, AWS has created the shared responsibility security model. With this approach, we provide a secure global infrastructure, including compute, storage, networking and database services, as well as a range of high-level services. We also provide a range of security services and features that you can use to secure your content and to meet your specific security requirements.
Tapping into Key Enterprise Workloads: SAP, VMware, & Microsoft on AWS (GPSBU...Amazon Web Services
Every day, more and more enterprise customers are moving their Microsoft, SAP, and VMware workloads to AWS. In this session, we explain how enterprise customers are operating these mission-critical workloads on AWS to increase agility, scale, and to realize business benefits faster. We also discuss the modernization roadmap choices that many of these enterprise customers are making to further embrace new cloud-native technologies and gain deeper benefits from cloud computing on AWS.
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 ML services work together to build a successful data lake for various roles, including data scientists and business users.
0 best practices for architecting for the cloud
1. Enable Scalability
2. Use Disposable Resources
3. Automate Your Environment
4. Loosely Couple Your Components
5. Design Services, Not Servers
6. Choose the Right Database Solutions
7. Avoid Single Points of Failure
8. Optimize for Cost
9. Use Caching
10. Secure Your Infrastructure Everywhere
Speaker: Anson Shen
Amazon Aurora is a MySQL- and PostgreSQL-compatible relational database built for the cloud. It combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. In this session, we cover some of the key innovations in the database engine and storage layers, explain recently announced features, such as Aurora Serverless, Aurora Multi-Master, and Aurora Parallel Query, and discuss best practices and optimal configurations. See why Aurora is a great fit for new application development and for migrations from overpriced, restrictive commercial databases.
A closer look at the MySQL and PostgreSQL compatible relational database built for the cloud that combines the performance and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. We’ll explore how Aurora uses the AWS cloud to provide high reliability, high durability, and high throughput.
Amazon DynamoDB is a serverless database for applications that need a flexible data model with high performance at any scale. In this session, we cover newly announced features and provide an end-to-end view of recent innovations. We also share some of our successful customer stories and use cases. Come to this session to learn all about what’s new with DynamoDB!
Developing with .NET Core on AWS: What's New (DEV318-R1) - AWS re:Invent 2018Amazon Web Services
In this demonstration-heavy session, we illustrate our latest techniques, tools, and libraries for developing end-to-end applications with .NET Core. We focus on serverless applications, but the techniques are broadly relevant. We start by showing you some useful features and best practices for authoring your serverless application, including debugging locally from the IDE and in production. From there, we demonstrate some helpful tools that make it easy to set up your CI/CD workflow from the start. Finally, we deploy our application with AWS Lambda.
SRV205 Architectures and Strategies for Building Modern Applications on AWSAmazon Web Services
Rapid growth of technology and tooling in the cloud has enabled us to build modern applications that are more secure, scalable, and focused on our business. In this session, we cover the key compute primitives that enable us to accelerate towards building and running modern, cloud-native applications. We highlight what we’ve learned from customers running applications with AWS Lambda and AWS Fargate, two modern compute technologies for running applications in the cloud. In addition, we cover architecture patterns of modern application, key primitives required for building modern systems, steps you can take to start building and monitoring modern applications today, and secrets to fearlessly going faster and farther in the cloud.
SRV327 Replicate, Analyze, and Visualize Data Using Managed Database and Ser...Amazon Web Services
If you have disparate datasets within your data center and on AWS, it can be challenging to manage all of them while you extract and analyze data to drive positive business outcomes. In this workshop, we use AWS managed database services, migration tools, and serverless technologies to replicate, analyze, and visualize data. We replicate an on-premises database to Amazon RDS and Amazon S3 using AWS Database Migration Service and the AWS Schema Conversion Tool. We then use Amazon Athena to interactively analyze data using SQL, and finally, we use Amazon QuickSight to visualize the data to enable better business decisions. For this session, ensure that you have an AWS account set up, and familiarize yourself with the AWS Management Console at least a day before the workshop. You don't need any credit on the account.
Citrix Moves Data to Amazon Redshift Fast with Matillion ETLAmazon Web Services
Matillion ETL, easily deployable from Amazon Web Services (AWS) Marketplace, helps Citrix collate and summarize data and augment it with more traditional business data from Microsoft SQL Server for additional context. Join our webinar to learn how organizations of any size can move data to the cloud quickly, accurately, and affordably with Matillion ETL.
Join our webinar to learn:
How Citrix moved data to Amazon Redshift with speed and accuracy.
How to make informed, business-critical decisions by analyzing data with Amazon Redshift.
How to speed time-to-value for your analytics initiatives using Matillion’s push-down ELT architecture.
Analyze your Data Lake, Fast @ Any Scale - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
-Learn how to automatically discover, catalog, and prepare your data for analytics
-Understand how to query data in your data lake without having to transform or load the data into your data warehouse
-See how to analyze data in both your data lake and data warehouse
Scaling Up to Your First 10 Million Users (ARC205-R1) - AWS re:Invent 2018Amazon Web Services
Cloud computing provides a number of advantages, such as the ability to scale your web application or website on demand. If you have a new web application and want to use cloud computing, you might be asking yourself, "Where do I start?" Join us in this session for best practices on scaling your resources from one to millions of users. We show you how to best combine different AWS services, how to make smarter decisions for architecting your application, and how to scale your infrastructure in the cloud.
In this workshop, learn how to create a cloud-based business intelligence platform and deliver dynamic insights through a custom Alexa Skill. Together, we architect a data analytics platform using Amazon S3, Amazon Athena, Amazon QuickSight, Amazon DynamoDB, Amazon CloudWatch on the backend, and a voice-based user interface through a private Alexa Skill deployed via Alexa for Business on the front end.
This session will highlight the most impactful announcements made at AWS re:Invent 2017 while giving you ideas on key use cases for new services and features. We’ll cover major themes of the conference, the new services and features within those themes and how they work together to make it faster and easier to build functionality into your app.
BDA301 Working with Machine Learning in Amazon SageMaker: Algorithms, Models,...Amazon Web Services
Today, organizations are using machine learning (ML) to address a host of business challenges, from product recommendations and pricing predictions, to tracking disease progression and demand forecasting. Until recently, developing these ML models took a significant amount of time and effort, and it required expertise in this field. In this session, we introduce you to Amazon SageMaker, a fully managed ML service that enables developers and data scientists to develop and deploy deep learning models more quickly and easily. We walk through the features and benefits of Amazon SageMaker and discuss the uniquely designed ML algorithms that allow for optimized model training, to get you to production fast.
SRV310 Optimizing Relational Databases on AWS: Deep Dive on Amazon RDSAmazon Web Services
Amazon RDS enables you to launch an optimally configured, secure, and highly available relational database with just a few clicks. It provides cost-efficient and resizable capacity while managing time-consuming administration tasks, and freeing you to focus on your applications and business. In this session, we take a closer look at how Amazon RDS works, and we review best practices to achieve performance, flexibility, and cost saving for your MySQL, PostgreSQL, MariaDB, Oracle, and SQL Server databases on Amazon RDS. We also discuss AWS Database Migration Service, a quick and secure means for migrating your existing RDBMS investments to Amazon RDS.
Humans and Data Don't Mix- Best Practices to Secure Your CloudAmazon Web Services
When it comes to security, human error far outpaces other causes of failures. The risk of humans touching sensitive data is clear, so how do you get them away from your data while also speeding up time to detection and remediation? Stephen Schmidt, AWS CISO, will share hard-earned lessons around potential opportunities in your security program, along with practical steps to improve the agility of your organization.
The Future of Enterprise Applications is Serverless (ENT314-R1) - AWS re:Inve...Amazon Web Services
At re:Invent 2014, we announced AWS Lambda and ushered in a whole new world of application design, one without the need to manage or think about traditional server infrastructure. Since then, serverless has become one of the hottest topics in the industry. Customers like Capital One and Coca Cola talk about how serverless saved them time and money, helped them reduce their operational burden, and drove developer agility and innovation. What is serverless, and what are the key trends you should be aware of? Where does one start on the journey of building serverless applications? We cover all of this and more in this session.
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.
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 ML services work together to build a successful data lake for various roles, including data scientists and business users.
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
Most technology professionals know that the AWS cloud reduces the cost of running and maintaining traditional server infrastructure, as well as providing scalability on demand. Fewer know, however, that our platform meets the requirements of even the most security-conscious organizations, from financial services institutes to government departments.
To protect our customers, and to maintain your trust and confidence, AWS has created the shared responsibility security model. With this approach, we provide a secure global infrastructure, including compute, storage, networking and database services, as well as a range of high-level services. We also provide a range of security services and features that you can use to secure your content and to meet your specific security requirements.
Tapping into Key Enterprise Workloads: SAP, VMware, & Microsoft on AWS (GPSBU...Amazon Web Services
Every day, more and more enterprise customers are moving their Microsoft, SAP, and VMware workloads to AWS. In this session, we explain how enterprise customers are operating these mission-critical workloads on AWS to increase agility, scale, and to realize business benefits faster. We also discuss the modernization roadmap choices that many of these enterprise customers are making to further embrace new cloud-native technologies and gain deeper benefits from cloud computing on AWS.
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 ML services work together to build a successful data lake for various roles, including data scientists and business users.
0 best practices for architecting for the cloud
1. Enable Scalability
2. Use Disposable Resources
3. Automate Your Environment
4. Loosely Couple Your Components
5. Design Services, Not Servers
6. Choose the Right Database Solutions
7. Avoid Single Points of Failure
8. Optimize for Cost
9. Use Caching
10. Secure Your Infrastructure Everywhere
Speaker: Anson Shen
Amazon Aurora is a MySQL- and PostgreSQL-compatible relational database built for the cloud. It combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. In this session, we cover some of the key innovations in the database engine and storage layers, explain recently announced features, such as Aurora Serverless, Aurora Multi-Master, and Aurora Parallel Query, and discuss best practices and optimal configurations. See why Aurora is a great fit for new application development and for migrations from overpriced, restrictive commercial databases.
A closer look at the MySQL and PostgreSQL compatible relational database built for the cloud that combines the performance and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. We’ll explore how Aurora uses the AWS cloud to provide high reliability, high durability, and high throughput.
by Mahesh Pakala, Solutions Architect, AWS
Database Week at the AWS Loft is an opportunity to learn about Amazon’s broad and deep family of managed database services. These services provide easy, scalable, reliable, and cost-effective ways to manage your data in the cloud. We explain the fundamentals and take a technical deep dive into Amazon RDS and Amazon Aurora relational databases, Amazon DynamoDB non-relational databases, Amazon Neptune graph databases, and Amazon ElastiCache managed Redis, along with options for database migration, caching, search and more. You'll will learn how to get started, how to support applications, and how to scale.
Amazon Aurora is a relational database built for the cloud and is compatible with MySQL and PostgreSQL. It combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open-source databases. In this session, we cover some of the key innovations in the Aurora database engine and storage layers. We explain recently announced features, such as Aurora Serverless, Aurora Multi-Master, and Aurora Parallel Query, and we discuss best practices and optimal configurations. See why Aurora is a great fit for new application development and for migrations from overpriced, restrictive commercial databases.
Database Week at the San Francisco Loft
Amazon Aurora
A closer look at the MySQL and PostgreSQL compatible relational database built for the cloud that combines the performance and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. We’ll explore how Aurora uses the AWS cloud to provide high reliability, high durability, and high throughput.
Level: 200
Speakers:
Mahesh Pakala - Solutions Architect, AWS
Arabinda Pani - Partner Solutions Architect, Database Specialist, AWS
A closer look at the MySQL and PostgreSQL compatible relational database built for the cloud that combines the performance and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. We’ll explore how Aurora uses the AWS cloud to provide high reliability, high durability, and high throughput.
Speakers:
Steve Abraham - Principal Database Specialist Solutions Architect, AWS
Peter Dachnowicz - Sr. Technical Account Manager, AWS
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.
by Joe Idziorek & Mahesh Pakala
A closer look at the MySQL and PostgreSQL compatible relational database built for the cloud that combines the performance and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. We’ll explore how Aurora uses the AWS cloud to provide high reliability, high durability, and high throughput.
A closer look at the MySQL and PostgreSQL compatible relational database built for the cloud that combines the performance and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. We’ll explore how Amazon Aurora uses the AWS cloud to provide high reliability, high durability, and high throughput.
Introducing Amazon Aurora with PostgreSQL Compatibility - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- Learn about optimizing relational databases for the cloud
- Learn about Amazon Aurora scalability and high availability
- Learn about Amazon Aurora compatibility with PostgreSQL
[REPEAT 1] Deep Dive on Amazon Aurora with MySQL Compatibility (DAT304-R1) - ...Amazon Web Services
Amazon Aurora is a fully managed relational database service that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. With Aurora, we've completely reimagined how databases are built for the cloud, providing you higher performance, availability, and durability than previously possible. In this session, we dive deep into the architectural details of Aurora with MySQL compatibility, and we review recent innovations, such as parallel query, backtrack, serverless, and multi-master. We also share best practices for utilizing the power of relational databases at cloud scale.
Amazon Aurora is a MySQL and PostgreSQL compatible relational database built for the cloud, that combines the performance and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. AWS Database Migration Service helps you migrate databases to AWS quickly and securely. The source database remains fully operational during the migration, minimizing downtime to applications that rely on the database. In this session, we explore features of Amazon Aurora and demonstrate database migration using the AWS Database Migration Service.
What's new in Amazon Aurora - ADB207 - New York AWS SummitAmazon Web Services
Amazon Aurora is a fully managed relational database that runs on Amazon RDS and offers versions compatible with MySQL and PostgreSQL. Aurora provides the speed, reliability, and availability of commercial databases at a fraction of the cost and is faster than standard MySQL and PostgreSQL databases. In this session, we provide an overview of Aurora, exploring recently announced features, such as serverless, multi-master, and performance insights. We also discuss what you need to get your organization started with Aurora.
What's new in Amazon Aurora - ADB203 - Chicago AWS SummitAmazon Web Services
Amazon Aurora is a fully managed relational database that runs on Amazon Relational Database Service (Amazon RDS) and offers versions compatible with MySQL and PostgreSQL. Aurora provides the speed, reliability, and availability of commercial databases but at one-tenth the cost, and it is up to five times faster than standard MySQL databases, and three times faster than standard PostgreSQL databases. In this session, we give you an overview of Aurora; explore recently announced features such as serverless, multi-master, and performance insights; and go over what you need to get your organization started with Aurora.
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.
Migrating Your Oracle & SQL Server Databases to Amazon Aurora (DAT318) - AWS ...Amazon Web Services
Organizations today are looking to free themselves from the constraints of on-premises commercial databases and leverage the power of cloud-native and open-source systems. Amazon Aurora is a MySQL- and PostgreSQL-compatible relational database that is built for the cloud, with the speed, reliability, and availability of commercial databases at one-tenth the cost. In this session, we provide an overview of Aurora and its features. We talk about the latest advances in migration tooling and automation, and we explain how many of the common legacy features of Oracle and SQL Server map to modern cloud variants. We also hear from Dow Jones about its migration journey to the cloud.
Deep Dive on Amazon Neptune (DAT403) - AWS re:Invent 2018Amazon Web Services
What can you do with Apache TinkerPop and Gremlin or RDF and SPARQL? How does Neptune provide multi-Availability Zone high availability? Learn about the features and details of Amazon's fully managed graph database service.
Amazon Aurora is a MySQL-compatible relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora is disruptive technology in the database space, bringing a new architectural model and distributed systems techniques to provide far higher performance, availability, and durability than was previously available using conventional monolithic database techniques. In this session, we dive deep into some of the key innovations behind Amazon Aurora, discuss best practices and migration from other databases to Amazon Aurora, and share early customer experiences from the field.
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...Amazon Web Services
Il Forecasting è un processo importante per tantissime aziende e viene utilizzato in vari ambiti per cercare di prevedere in modo accurato la crescita e distribuzione di un prodotto, l’utilizzo delle risorse necessarie nelle linee produttive, presentazioni finanziarie e tanto altro. Amazon utilizza delle tecniche avanzate di forecasting, in parte questi servizi sono stati messi a disposizione di tutti i clienti AWS.
In questa sessione illustreremo come pre-processare i dati che contengono una componente temporale e successivamente utilizzare un algoritmo che a partire dal tipo di dato analizzato produce un forecasting accurato.
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...Amazon Web Services
La varietà e la quantità di dati che si crea ogni giorno accelera sempre più velocemente e rappresenta una opportunità irripetibile per innovare e creare nuove startup.
Tuttavia gestire grandi quantità di dati può apparire complesso: creare cluster Big Data su larga scala sembra essere un investimento accessibile solo ad aziende consolidate. Ma l’elasticità del Cloud e, in particolare, i servizi Serverless ci permettono di rompere questi limiti.
Vediamo quindi come è possibile sviluppare applicazioni Big Data rapidamente, senza preoccuparci dell’infrastruttura, ma dedicando tutte le risorse allo sviluppo delle nostre le nostre idee per creare prodotti innovativi.
Ora puoi utilizzare Amazon Elastic Kubernetes Service (EKS) per eseguire pod Kubernetes su AWS Fargate, il motore di elaborazione serverless creato per container su AWS. Questo rende più semplice che mai costruire ed eseguire le tue applicazioni Kubernetes nel cloud AWS.In questa sessione presenteremo le caratteristiche principali del servizio e come distribuire la tua applicazione in pochi passaggi
Vent'anni fa Amazon ha attraversato una trasformazione radicale con l'obiettivo di aumentare il ritmo dell'innovazione. In questo periodo abbiamo imparato come cambiare il nostro approccio allo sviluppo delle applicazioni ci ha permesso di aumentare notevolmente l'agilità, la velocità di rilascio e, in definitiva, ci ha consentito di creare applicazioni più affidabili e scalabili. In questa sessione illustreremo come definiamo le applicazioni moderne e come la creazione di app moderne influisce non solo sull'architettura dell'applicazione, ma sulla struttura organizzativa, sulle pipeline di rilascio dello sviluppo e persino sul modello operativo. Descriveremo anche approcci comuni alla modernizzazione, compreso l'approccio utilizzato dalla stessa Amazon.com.
Come spendere fino al 90% in meno con i container e le istanze spot Amazon Web Services
L’utilizzo dei container è in continua crescita.
Se correttamente disegnate, le applicazioni basate su Container sono molto spesso stateless e flessibili.
I servizi AWS ECS, EKS e Kubernetes su EC2 possono sfruttare le istanze Spot, portando ad un risparmio medio del 70% rispetto alle istanze On Demand. In questa sessione scopriremo insieme quali sono le caratteristiche delle istanze Spot e come possono essere utilizzate facilmente su AWS. Impareremo inoltre come Spreaker sfrutta le istanze spot per eseguire applicazioni di diverso tipo, in produzione, ad una frazione del costo on-demand!
In recent months, many customers have been asking us the question – how to monetise Open APIs, simplify Fintech integrations and accelerate adoption of various Open Banking business models. Therefore, AWS and FinConecta would like to invite you to Open Finance marketplace presentation on October 20th.
Event Agenda :
Open banking so far (short recap)
• PSD2, OB UK, OB Australia, OB LATAM, OB Israel
Intro to Open Finance marketplace
• Scope
• Features
• Tech overview and Demo
The role of the Cloud
The Future of APIs
• Complying with regulation
• Monetizing data / APIs
• Business models
• Time to market
One platform for all: a Strategic approach
Q&A
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...Amazon Web Services
Per creare valore e costruire una propria offerta differenziante e riconoscibile, le startup di successo sanno come combinare tecnologie consolidate con componenti innovativi creati ad hoc.
AWS fornisce servizi pronti all'utilizzo e, allo stesso tempo, permette di personalizzare e creare gli elementi differenzianti della propria offerta.
Concentrandoci sulle tecnologie di Machine Learning, vedremo come selezionare i servizi di intelligenza artificiale offerti da AWS e, anche attraverso una demo, come costruire modelli di Machine Learning personalizzati utilizzando SageMaker Studio.
OpsWorks Configuration Management: automatizza la gestione e i deployment del...Amazon Web Services
Con l'approccio tradizionale al mondo IT per molti anni è stato difficile implementare tecniche di DevOps, che finora spesso hanno previsto attività manuali portando di tanto in tanto a dei downtime degli applicativi interrompendo l'operatività dell'utente. Con l'avvento del cloud, le tecniche di DevOps sono ormai a portata di tutti a basso costo per qualsiasi genere di workload, garantendo maggiore affidabilità del sistema e risultando in dei significativi miglioramenti della business continuity.
AWS mette a disposizione AWS OpsWork come strumento di Configuration Management che mira ad automatizzare e semplificare la gestione e i deployment delle istanze EC2 per mezzo di workload Chef e Puppet.
Scopri come sfruttare AWS OpsWork a garanzia e affidabilità del tuo applicativo installato su Instanze EC2.
Microsoft Active Directory su AWS per supportare i tuoi Windows WorkloadsAmazon Web Services
Vuoi conoscere le opzioni per eseguire Microsoft Active Directory su AWS? Quando si spostano carichi di lavoro Microsoft in AWS, è importante considerare come distribuire Microsoft Active Directory per supportare la gestione, l'autenticazione e l'autorizzazione dei criteri di gruppo. In questa sessione, discuteremo le opzioni per la distribuzione di Microsoft Active Directory su AWS, incluso AWS Directory Service per Microsoft Active Directory e la distribuzione di Active Directory su Windows su Amazon Elastic Compute Cloud (Amazon EC2). Trattiamo argomenti quali l'integrazione del tuo ambiente Microsoft Active Directory locale nel cloud e l'utilizzo di applicazioni SaaS, come Office 365, con AWS Single Sign-On.
Dal riconoscimento facciale al riconoscimento di frodi o difetti di fabbricazione, l'analisi di immagini e video che sfruttano tecniche di intelligenza artificiale, si stanno evolvendo e raffinando a ritmi elevati. In questo webinar esploreremo le possibilità messe a disposizione dai servizi AWS per applicare lo stato dell'arte delle tecniche di computer vision a scenari reali.
Amazon Web Services e VMware organizzano un evento virtuale gratuito il prossimo mercoledì 14 Ottobre dalle 12:00 alle 13:00 dedicato a VMware Cloud ™ on AWS, il servizio on demand che consente di eseguire applicazioni in ambienti cloud basati su VMware vSphere® e di accedere ad una vasta gamma di servizi AWS, sfruttando a pieno le potenzialità del cloud AWS e tutelando gli investimenti VMware esistenti.
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
Crea la tua prima serverless ledger-based app con QLDB e NodeJSAmazon Web Services
Molte aziende oggi, costruiscono applicazioni con funzionalità di tipo ledger ad esempio per verificare lo storico di accrediti o addebiti nelle transazioni bancarie o ancora per tenere traccia del flusso supply chain dei propri prodotti.
Alla base di queste soluzioni ci sono i database ledger che permettono di avere un log delle transazioni trasparente, immutabile e crittograficamente verificabile, ma sono strumenti complessi e onerosi da gestire.
Amazon QLDB elimina la necessità di costruire sistemi personalizzati e complessi fornendo un database ledger serverless completamente gestito.
In questa sessione scopriremo come realizzare un'applicazione serverless completa che utilizzi le funzionalità di QLDB.
Con l’ascesa delle architetture di microservizi e delle ricche applicazioni mobili e Web, le API sono più importanti che mai per offrire agli utenti finali una user experience eccezionale. In questa sessione impareremo come affrontare le moderne sfide di progettazione delle API con GraphQL, un linguaggio di query API open source utilizzato da Facebook, Amazon e altro e come utilizzare AWS AppSync, un servizio GraphQL serverless gestito su AWS. Approfondiremo diversi scenari, comprendendo come AppSync può aiutare a risolvere questi casi d’uso creando API moderne con funzionalità di aggiornamento dati in tempo reale e offline.
Inoltre, impareremo come Sky Italia utilizza AWS AppSync per fornire aggiornamenti sportivi in tempo reale agli utenti del proprio portale web.
Database Oracle e VMware Cloud™ on AWS: i miti da sfatareAmazon Web Services
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
In queste slide, gli esperti AWS e VMware presentano semplici e pratici accorgimenti per facilitare e semplificare la migrazione dei carichi di lavoro Oracle accelerando la trasformazione verso il cloud, approfondiranno l’architettura e dimostreranno come sfruttare a pieno le potenzialità di VMware Cloud ™ on AWS.
Amazon Elastic Container Service (Amazon ECS) è un servizio di gestione dei container altamente scalabile, che semplifica la gestione dei contenitori Docker attraverso un layer di orchestrazione per il controllo del deployment e del relativo lifecycle. In questa sessione presenteremo le principali caratteristiche del servizio, le architetture di riferimento per i differenti carichi di lavoro e i semplici passi necessari per poter velocemente migrare uno o più dei tuo container.