Amazon Aurora is a relational database engine that combines the speed and reliability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. It delivers up to five times the throughput of standard MySQL running on the same hardware. Amazon Aurora is designed to be compatible with MySQL 5.6, so that existing MySQL applications and tools can run without requiring modification.
Amazon Aurora is a MySQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. The service is now in preview. Come to our session for an overview of the service and learn how Aurora delivers up to five times the performance of MySQL yet is priced at a fraction of what you'd pay for a commercial database with similar performance and availability.
Amazon Aurora: The New Relational Database Engine from AmazonAmazon Web Services
Amazon Aurora is a MySQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. The service is now in preview. Come to our session for an overview of the service and learn how Aurora delivers up to five times the performance of MySQL yet is priced at a fraction of what you'd pay for a commercial database with similar performance and availability.
Relational databases are a cornerstone of the enterprise IT landscape, powering business-critical applications of many kinds. Though they have been around for a while, current commercial relational databases have lagged behind in innovation. Amazon Aurora, a managed database service built for the cloud, is intended to change that. It targets the high-performance needs of business-critical applications with an emphasis on cost-effectiveness. In this session, we will look into how Aurora fits the needs of applications built and bought by enterprises to power their business. You will learn about the overall architecture, capabilities, and cost-effectiveness of Aurora, comparing it to current commercial database offerings. We will explore best practices for enterprises adopting Aurora for existing and new workloads, as well as strategies, tools, and techniques for migrating existing databases to Aurora. You will also hear from Expedia, one of world’s leading travel companies on how they are using Amazon Aurora to power application with high performance database needs.
Deep Dive on Amazon Aurora - Covering New Feature AnnouncementsAmazon Web Services
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 a disruptive technology in the database space, bringing a new architectural model and distributed system techniques to provide far higher performance, availability and durability than previously available using conventional monolithic database techniques. In this session, we will do a deep-dive into some of the key innovations behind Amazon Aurora, discuss best practices and configurations, and share customer experiences from the field.
Learning Objectives:
• Learn about the capabilities and features of Amazon Aurora and its new features
• Learn about the benefits of Amazon Aurora and how it delivers 5x the performance and 1/10th the cost
• Learn about the different use cases
• Learn how to get started using Amazon Aurora
Amazon Aurora is a MySQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. The service is now in preview. Come to our session for an overview of the service and learn how Aurora delivers up to five times the performance of MySQL yet is priced at a fraction of what you'd pay for a commercial database with similar performance and availability.
Speakers:
Ronan Guilfoyle, AWS Solutions Architect
Brian Scanlan, Engineer, Intercom.io
It’s been an exciting year for Amazon Aurora, the 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. In this deep dive session, we’ll discuss best practices and explore new features, include high availability options and new integrations with AWS services. We’ll also discuss the recently-announced Aurora with PostgreSQL compatibility.
Announcing Amazon Aurora with PostgreSQL Compatibility - January 2017 AWS Onl...Amazon Web Services
Amazon Aurora is now PostgreSQL compatible. With Amazon Aurora’s new PostgreSQL support, customers can get several times better performance than the typical PostgreSQL database and take advantage of the scalability, durability, and security capabilities of Amazon Aurora – all for one-tenth the cost of commercial grade databases. Amazon Aurora is a fully managed 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 built on a cloud native architecture that is designed to offer greater than 99.99 percent availability and automatic failover with no loss of data.
Learning Objectives:
• Learn about the capabilities and features of Amazon Aurora with PostgreSQL Compatibility
• Learn about the benefits and different use cases
• Learn how to get started using Amazon Aurora with PostgreSQL Compatibility
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 previously available using conventional monolithic database techniques. In this session, we will do a deep-dive into some of the key innovations behind Amazon Aurora, discuss best practices and configurations, and share early customer experience from the field.
Amazon Aurora is a MySQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. The service is now in preview. Come to our session for an overview of the service and learn how Aurora delivers up to five times the performance of MySQL yet is priced at a fraction of what you'd pay for a commercial database with similar performance and availability.
Amazon Aurora: The New Relational Database Engine from AmazonAmazon Web Services
Amazon Aurora is a MySQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. The service is now in preview. Come to our session for an overview of the service and learn how Aurora delivers up to five times the performance of MySQL yet is priced at a fraction of what you'd pay for a commercial database with similar performance and availability.
Relational databases are a cornerstone of the enterprise IT landscape, powering business-critical applications of many kinds. Though they have been around for a while, current commercial relational databases have lagged behind in innovation. Amazon Aurora, a managed database service built for the cloud, is intended to change that. It targets the high-performance needs of business-critical applications with an emphasis on cost-effectiveness. In this session, we will look into how Aurora fits the needs of applications built and bought by enterprises to power their business. You will learn about the overall architecture, capabilities, and cost-effectiveness of Aurora, comparing it to current commercial database offerings. We will explore best practices for enterprises adopting Aurora for existing and new workloads, as well as strategies, tools, and techniques for migrating existing databases to Aurora. You will also hear from Expedia, one of world’s leading travel companies on how they are using Amazon Aurora to power application with high performance database needs.
Deep Dive on Amazon Aurora - Covering New Feature AnnouncementsAmazon Web Services
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 a disruptive technology in the database space, bringing a new architectural model and distributed system techniques to provide far higher performance, availability and durability than previously available using conventional monolithic database techniques. In this session, we will do a deep-dive into some of the key innovations behind Amazon Aurora, discuss best practices and configurations, and share customer experiences from the field.
Learning Objectives:
• Learn about the capabilities and features of Amazon Aurora and its new features
• Learn about the benefits of Amazon Aurora and how it delivers 5x the performance and 1/10th the cost
• Learn about the different use cases
• Learn how to get started using Amazon Aurora
Amazon Aurora is a MySQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. The service is now in preview. Come to our session for an overview of the service and learn how Aurora delivers up to five times the performance of MySQL yet is priced at a fraction of what you'd pay for a commercial database with similar performance and availability.
Speakers:
Ronan Guilfoyle, AWS Solutions Architect
Brian Scanlan, Engineer, Intercom.io
It’s been an exciting year for Amazon Aurora, the 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. In this deep dive session, we’ll discuss best practices and explore new features, include high availability options and new integrations with AWS services. We’ll also discuss the recently-announced Aurora with PostgreSQL compatibility.
Announcing Amazon Aurora with PostgreSQL Compatibility - January 2017 AWS Onl...Amazon Web Services
Amazon Aurora is now PostgreSQL compatible. With Amazon Aurora’s new PostgreSQL support, customers can get several times better performance than the typical PostgreSQL database and take advantage of the scalability, durability, and security capabilities of Amazon Aurora – all for one-tenth the cost of commercial grade databases. Amazon Aurora is a fully managed 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 built on a cloud native architecture that is designed to offer greater than 99.99 percent availability and automatic failover with no loss of data.
Learning Objectives:
• Learn about the capabilities and features of Amazon Aurora with PostgreSQL Compatibility
• Learn about the benefits and different use cases
• Learn how to get started using Amazon Aurora with PostgreSQL Compatibility
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 previously available using conventional monolithic database techniques. In this session, we will do a deep-dive into some of the key innovations behind Amazon Aurora, discuss best practices and configurations, and share early customer experience from the field.
AWS June 2016 Webinar Series - Amazon Aurora Deep Dive - Optimizing Database ...Amazon Web Services
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 a disruptive technology in the database space, bringing a new architectural model and distributed system techniques to provide far higher performance, availability and durability than previously available using conventional monolithic database techniques. In this session, we will do a deep-dive into some of the key innovations behind Amazon Aurora, discuss best practices and configurations, and share customer experiences from the field.
Learning Objectives:
Learn how Amazon Aurora delivers 5x the performance and 1/10th the cost
Learn best practices for using Amazon Aurora
(DAT207) Amazon Aurora: The New Amazon Relational Database EngineAmazon Web Services
In July, AWS announced the launch of Amazon Aurora, a MySQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. This session introduces you to Amazon Aurora, explains common use cases for the service, and helps you get started with building your first Amazon Aurora–powered application.
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.
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 previously available using conventional monolithic database techniques. In this session, we will do a deep-dive into some of the key innovations behind Amazon Aurora, discuss best practices and configurations, and share early customer experience from the field.
Amazon Aurora is a fully managed relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. It is purpose-built for the cloud using a new architectural model and distributed systems techniques to provide far higher performance, availability and durability than previously possible using conventional monolithic database architectures. Amazon Aurora packs a lot of innovations in the engine and storage layers. In this session, we will do a deep-dive into some of the key innovations behind Amazon Aurora, new improvements to Aurora's performance, availability and cost-effectiveness and discuss best practices and optimal configurations.
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 previously available using conventional monolithic database techniques. In this session, we will do a deep-dive into some of the key innovations behind Amazon Aurora, discuss best practices and configurations, and share early customer experience from the field.
AWS December 2015 Webinar Series - Amazon Aurora: Introduction and MigrationAmazon Web Services
Amazon Aurora is a MySQL-compatible 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 available through Amazon RDS as a fully managed database service.
This webinar introduces you to Amazon Aurora, explains common use cases for the service, and discusses methods to migrate your MySQL databases that are on Amazon RDS, Amazon EC2 or on-premises to Amazon Aurora.
Learning Objectives:
How Amazon Aurora is different and similar to traditional databases
Reliability and availability design in Aurora
How Amazon Aurora delivers up to 5x MySQL performance on similar hardware
Learn the scalability in Amazon Aurora: scaling instance size and database size, horizontal scaling with read replicas
Who Should Attend:
IT Managers, DBAs, Enterprise and Solution Architects , Devops Engineers and Developers
Deep Dive on the Amazon Aurora MySQL-compatible Edition - DAT301 - re:Invent ...Amazon Web Services
The Amazon Aurora MySQL-compatible Edition is a fully managed relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. It is purpose-built for the cloud using a new architectural model and distributed systems techniques. It provides far higher performance, availability, and durability than previously possible using conventional monolithic database architectures. Amazon Aurora packs a lot of innovations in the engine and storage layers. In this session, we do a deep-dive into some key innovations behind Amazon Aurora MySQL-compatible edition. We explore new improvements to the service and discuss best practices and optimal configurations.
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 provides up to five times better performance than MySQL at a price point one tenth that of a commercial database while delivering similar performance and availability.
In this webinar, learn how using Amazon Aurora allows you to: migrate existing MySQL databases for up to 5x increase in throughput performance, automatically grow database volumes up to 64TB, automatically replicate 6 copies of data across 3 Availability Zones, and transparently failover to ensure high-availability.
Learning Objectives:
• How to migrate existing MySQL databases to Amazon Aurora
• How Amazon Aurora delivers up to 5x MySQL performance on similar hardware
• How to automatically grow database volumes up to 64TB
• How Amazon Aurora protects you data through automated replication and transparent failover
Who Should Attend:
• Security Administrators, IT auditors, Devops Engineers and Developers
AWS provides a range of Compute Services – Amazon EC2, Amazon ECS and AWS Lambda. We will provide an intro level overview of these services and highlight suitable use cases. Amazon Elastic Compute Cloud (Amazon EC2) itself provides a broad selection of instance types to accommodate a diverse mix of workloads. Going a bit deeper on EC2 we will provide background on the Amazon EC2 instance platform, key platform features, and the concept of instance generations. We dive into the current-generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and GPU instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances, both from a performance and cost perspective.
RDS Postgres and Aurora Postgres | AWS Public Sector Summit 2017Amazon Web Services
Attend this session for a technical deep dive about RDS Postgres and Aurora Postgres. Come hear from Mark Porter, the General Manager of Aurora PostgreSQL and RDS at AWS, as he covers service specific use cases and applications within the AWS worldwide public sector community. Learn More: https://aws.amazon.com/government-education/
Amazon Elastic MapReduce (Amazon EMR) is a web service that allows you to easily and securely provision and manage your Hadoop clusters. In this talk, we will introduce you to Amazon EMR design patterns, such as using various data stores like Amazon S3, how to take advantage of both transient and active clusters, and how to work with other Amazon EMR architectural patterns. We will dive deep on how to dynamically scale your cluster and address the ways you can fine-tune your cluster. We will discuss bootstrapping Hadoop applications from our partner ecosystem that you can use natively with Amazon EMR. Lastly, we will share best practices on how to keep your Amazon EMR cluster cost-effective.
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 previously available using conventional monolithic database techniques.
In this session, we will do a deep-dive into some of the key innovations behind Amazon Aurora, discuss best practices and configurations, and share early customer experience from the field.
Learning Objectives:
Learn how Amazon Aurora works under the hood and learn the best practices for using Aurora
Who Should Attend:
IT Managers, DBAs, Enterprise and Solution Architects and Developers
AWS re:Invent 2016: Case Study: Librato's Experience Running Cassandra Using ...Amazon Web Services
At Librato, a Solarwinds company, we run hundreds of Cassandra instances across multiple rings and use it as our primary data store. In the past year, we embarked on a process to upgrade our fleet of Cassandra Amazon EC2 instances from instance store to instances using Amazon EBS and attached elastic network interfaces (ENIs). We find running Cassandra on EBS gives us the flexibility to choose the best instances for the best performance of our workload while saving us significant costs on infrastructure. In this session, we discuss how Librato operates Cassandra on EBS. Topics include how we chose the right instance for our workload, use detached EBS volumes and ENI mobility to reduce MTTR, use mixed EBS storage types for the best cost/performance tradeoff, debug performance issues, and continuously monitor Cassandra to get the most from AWS. We also look at performance tradeoffs made in the implementation of storage engines of large data systems like Cassandra.
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.
Amazon API Gateway and AWS Lambda: Better TogetherDanilo Poccia
Amazon API Gateway is a fully managed service that makes it easy for developers to create, publish, maintain, monitor, and secure APIs at any scale. AWS Lambda is a compute service that runs your code in response to events and automatically manages the compute resources for you, making it easy to build applications that respond quickly to new information. Together they help you build a server-less event-driven backend that is easy to manage and scale.
AWS June 2016 Webinar Series - Amazon Aurora Deep Dive - Optimizing Database ...Amazon Web Services
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 a disruptive technology in the database space, bringing a new architectural model and distributed system techniques to provide far higher performance, availability and durability than previously available using conventional monolithic database techniques. In this session, we will do a deep-dive into some of the key innovations behind Amazon Aurora, discuss best practices and configurations, and share customer experiences from the field.
Learning Objectives:
Learn how Amazon Aurora delivers 5x the performance and 1/10th the cost
Learn best practices for using Amazon Aurora
(DAT207) Amazon Aurora: The New Amazon Relational Database EngineAmazon Web Services
In July, AWS announced the launch of Amazon Aurora, a MySQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. This session introduces you to Amazon Aurora, explains common use cases for the service, and helps you get started with building your first Amazon Aurora–powered application.
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.
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 previously available using conventional monolithic database techniques. In this session, we will do a deep-dive into some of the key innovations behind Amazon Aurora, discuss best practices and configurations, and share early customer experience from the field.
Amazon Aurora is a fully managed relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. It is purpose-built for the cloud using a new architectural model and distributed systems techniques to provide far higher performance, availability and durability than previously possible using conventional monolithic database architectures. Amazon Aurora packs a lot of innovations in the engine and storage layers. In this session, we will do a deep-dive into some of the key innovations behind Amazon Aurora, new improvements to Aurora's performance, availability and cost-effectiveness and discuss best practices and optimal configurations.
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 previously available using conventional monolithic database techniques. In this session, we will do a deep-dive into some of the key innovations behind Amazon Aurora, discuss best practices and configurations, and share early customer experience from the field.
AWS December 2015 Webinar Series - Amazon Aurora: Introduction and MigrationAmazon Web Services
Amazon Aurora is a MySQL-compatible 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 available through Amazon RDS as a fully managed database service.
This webinar introduces you to Amazon Aurora, explains common use cases for the service, and discusses methods to migrate your MySQL databases that are on Amazon RDS, Amazon EC2 or on-premises to Amazon Aurora.
Learning Objectives:
How Amazon Aurora is different and similar to traditional databases
Reliability and availability design in Aurora
How Amazon Aurora delivers up to 5x MySQL performance on similar hardware
Learn the scalability in Amazon Aurora: scaling instance size and database size, horizontal scaling with read replicas
Who Should Attend:
IT Managers, DBAs, Enterprise and Solution Architects , Devops Engineers and Developers
Deep Dive on the Amazon Aurora MySQL-compatible Edition - DAT301 - re:Invent ...Amazon Web Services
The Amazon Aurora MySQL-compatible Edition is a fully managed relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. It is purpose-built for the cloud using a new architectural model and distributed systems techniques. It provides far higher performance, availability, and durability than previously possible using conventional monolithic database architectures. Amazon Aurora packs a lot of innovations in the engine and storage layers. In this session, we do a deep-dive into some key innovations behind Amazon Aurora MySQL-compatible edition. We explore new improvements to the service and discuss best practices and optimal configurations.
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 provides up to five times better performance than MySQL at a price point one tenth that of a commercial database while delivering similar performance and availability.
In this webinar, learn how using Amazon Aurora allows you to: migrate existing MySQL databases for up to 5x increase in throughput performance, automatically grow database volumes up to 64TB, automatically replicate 6 copies of data across 3 Availability Zones, and transparently failover to ensure high-availability.
Learning Objectives:
• How to migrate existing MySQL databases to Amazon Aurora
• How Amazon Aurora delivers up to 5x MySQL performance on similar hardware
• How to automatically grow database volumes up to 64TB
• How Amazon Aurora protects you data through automated replication and transparent failover
Who Should Attend:
• Security Administrators, IT auditors, Devops Engineers and Developers
AWS provides a range of Compute Services – Amazon EC2, Amazon ECS and AWS Lambda. We will provide an intro level overview of these services and highlight suitable use cases. Amazon Elastic Compute Cloud (Amazon EC2) itself provides a broad selection of instance types to accommodate a diverse mix of workloads. Going a bit deeper on EC2 we will provide background on the Amazon EC2 instance platform, key platform features, and the concept of instance generations. We dive into the current-generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and GPU instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances, both from a performance and cost perspective.
RDS Postgres and Aurora Postgres | AWS Public Sector Summit 2017Amazon Web Services
Attend this session for a technical deep dive about RDS Postgres and Aurora Postgres. Come hear from Mark Porter, the General Manager of Aurora PostgreSQL and RDS at AWS, as he covers service specific use cases and applications within the AWS worldwide public sector community. Learn More: https://aws.amazon.com/government-education/
Amazon Elastic MapReduce (Amazon EMR) is a web service that allows you to easily and securely provision and manage your Hadoop clusters. In this talk, we will introduce you to Amazon EMR design patterns, such as using various data stores like Amazon S3, how to take advantage of both transient and active clusters, and how to work with other Amazon EMR architectural patterns. We will dive deep on how to dynamically scale your cluster and address the ways you can fine-tune your cluster. We will discuss bootstrapping Hadoop applications from our partner ecosystem that you can use natively with Amazon EMR. Lastly, we will share best practices on how to keep your Amazon EMR cluster cost-effective.
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 previously available using conventional monolithic database techniques.
In this session, we will do a deep-dive into some of the key innovations behind Amazon Aurora, discuss best practices and configurations, and share early customer experience from the field.
Learning Objectives:
Learn how Amazon Aurora works under the hood and learn the best practices for using Aurora
Who Should Attend:
IT Managers, DBAs, Enterprise and Solution Architects and Developers
AWS re:Invent 2016: Case Study: Librato's Experience Running Cassandra Using ...Amazon Web Services
At Librato, a Solarwinds company, we run hundreds of Cassandra instances across multiple rings and use it as our primary data store. In the past year, we embarked on a process to upgrade our fleet of Cassandra Amazon EC2 instances from instance store to instances using Amazon EBS and attached elastic network interfaces (ENIs). We find running Cassandra on EBS gives us the flexibility to choose the best instances for the best performance of our workload while saving us significant costs on infrastructure. In this session, we discuss how Librato operates Cassandra on EBS. Topics include how we chose the right instance for our workload, use detached EBS volumes and ENI mobility to reduce MTTR, use mixed EBS storage types for the best cost/performance tradeoff, debug performance issues, and continuously monitor Cassandra to get the most from AWS. We also look at performance tradeoffs made in the implementation of storage engines of large data systems like Cassandra.
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.
Amazon API Gateway and AWS Lambda: Better TogetherDanilo Poccia
Amazon API Gateway is a fully managed service that makes it easy for developers to create, publish, maintain, monitor, and secure APIs at any scale. AWS Lambda is a compute service that runs your code in response to events and automatically manages the compute resources for you, making it easy to build applications that respond quickly to new information. Together they help you build a server-less event-driven backend that is easy to manage and scale.
Amazon Aurora is a MySQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. This session introduces you to Amazon Aurora, explains common use cases for the service, and helps you get started with building your first Amazon Aurora–powered application.
AWS offers you the ability to add additional layers of security to your data at rest in the cloud, providing access control as well scalable and efficient encryption features. Flexible key management options allow you to choose whether to have AWS manage the encryption keys or to keep complete control over the keys yourself. In this session, you will learn how to secure data when using AWS services. We will discuss data encryption using Key Management Service, S3 access controls, edge and host access security, and database platform security features.
Data Replication Options in AWS (ARC302) | AWS re:Invent 2013Amazon Web Services
One of the most critical roles of an IT department is to protect and serve its corporate data. As a result, IT departments spend tremendous amounts of resources developing, designing, testing, and optimizing data recovery and replication options in order to improve data availability and service response time. This session outlines replication challenges, key design patterns, and methods commonly used in today’s IT environment. Furthermore, the session provides different data replication solutions available in the AWS cloud. Finally, the session outlines several key factors to be considered when implementing data replication architectures in the AWS cloud.
AWS re:Invent 2016: Workshop: Stretching Scalability: Doing more with Amazon ...Amazon Web Services
Easy scalability is a powerful feature of Amazon Aurora. Scalability in its actual definition refers to being able to get larger or smaller depending on the need. Amazon Aurora allows you to easily achieve this by scaling the database instance up or down and adding or removing read replicas. Scaling across regions brings additional resilience to your architectures and could boost your application performance due to geographic proximity. You can perform all of these scaling operations through the Aurora console. You can also automate instance and read scaling using lambda function or scripts based on the usage pattern you define. You can extend the automation by feeding your database usage data from Aurora enhanced monitoring into Machine Learning to provide more sophisticated predictive patterns to drive your automation. In this session we will do a deep dive into how scalability works in Aurora and how to make the best use of it to reduce your cost, increase application performance and architect resilient applications.
You should have good database knowledge and at least some experience with Amazon RDS or Amazon Aurora and should bring your own laptop.
Building Event-Driven Serverless Applications - AWS - Danilo PocciaIT Talent College
On the 18th of May Danilo Poccia, Technical Evangelist at Amazon Web Services, gave a lecture on Cloud Computing at IT Talent College. Watch the slides of his presentation here.
Building a Scalable and Highly Available Web Service with AWS: A Live DemoDanilo Poccia
We’ll build together a web service in a live environment, starting from a prototype on a single node, and ending up with an highly available and scalable architecture, distributed across multiple facilities (multi-AZ) and using auto scaling to dynamically adjust to the actual workload.
Slides from the Cloudyna event in Katowice, Poland on November 14th, 2015. Data analysis is being used to transform businesses, increase efficiency, and drive innovation. The AWS Cloud has a comprehensive portfolio of analytics services to help you process data of any volume and automate how you put that data to work for your organization. In this session we'll see how to put those services at work on structured, unstructured and real-time data.
In this talk from the Dublin Websummit 2014 AWS Technical Evangelist Danilo Poccia discusses NoSQL technology.
Includes an introduction to NoSQL DB and a discussion of when it is time to consider NoSQL.
Danilo also introduces Amazon DynamoDB as a NoSQL solution and talks through several case studies of customers that are using Amazon DynamoDB today.
Mobile app development can be complex and time-consuming. Learn how to rapidly deliver mobile apps with AWS Mobile Hub. We will demonstrate how AWS Mobile Hub abstracts the undifferentiated heavy lifting by providing a single, integrated experience for discovering, provisioning and configuring AWS cloud resources you need to build, test, and monitor usage of your mobile apps.
In this talk from the Dublin Websummit 2014 AWS Technical Evangelist Danilo Poccia discusses building mobile apps on AWS.
This talk includes an introduction to the AWS mobile services that were launched earlier in 2014 and how you can use these services to fulfill common application functions such as authenticating users, synchronizing data and analyzing user behavior, as well as providing direct access to other AWS services from with your Android or iOS applicatons.
Improve the quality of your iOS, Android, and web applications by testing them against real smartphones and tablets in the AWS Cloud. Run tests across a large selection of physical devices in parallel from various manufacturers with varying hardware, OS versions and form factors. Unlike emulators, physical devices provide a more accurate understanding of how users interact with your app, by taking into account factors such as memory, CPU usage, location, and modifications done by manufactures and carriers to the firmware and software.
We built event-driven user interfaces for decades. What about bringing the same approach to mobile, web, and IoT backend applications? You have to understand how data flows and what is the propagation of changes, using reactive programming techniques. You can focus on the core functionalities to build and the relationships among the resources you use. Your application behaves similarly to a “spreadsheet”, where depending resources are updated automatically when something “happens”, and is decomposed into scalable microservices without having to manage the infrastructure. The resulting architecture is efficient and cost effective to run on AWS and managing availability, scalability and security becomes part of the implementation itself.
본 세션에서는 Amazon의 관리형 데이터베이스 서비스(RDS) 중 기존 상용데이터베이스의 5배 성능 및 1/10 가격으로도 확장성을 보장하는 Aurora에 대한 소개 및 사용법 그리고 기존의 DB에서의 마이그레이션 방법에 대해 소개해드립니다. 10월 리인벤트를 통해 동경 리전에 Aurora를 사용가능하게 되었습니다.
In this talk from the Dublin Websummit 2014 AWS Technical Evangelist Danilo Poccia discusses the approaches that you can take to improve monitoring and monetization of your mobile apps.
Includes a discussion of A/B testing in mobile apps, monetization strategies & metrics. Also covers relevant AWS services such as Amazon Mobile Analytics, SNS Mobile Push and the AWS mobile SDKs for Android and iOS devices.
Amazon Aurora: The New Relational Database Engine from AmazonAmazon Web Services
Amazon Aurora is a MySQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. The service is now in preview. Come to our session for an overview of the service and learn how Aurora delivers up to five times the performance of MySQL yet is priced at a fraction of what you'd pay for a commercial database with similar performance and availability.
Amazon Aurora is a MySQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. This session introduces you to Amazon Aurora, explains common use cases for the service, and helps you get started with building your first Amazon Aurora–powered application.
Amazon Aurora is a MySQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. This session introduces you to Amazon Aurora, explains common use cases for the service, and helps you get started with building your first Amazon Aurora–powered application.
Amazon Aurora is a MySQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. This session introduces you to Amazon Aurora, explains common use cases for the service, and helps you get started with building your first Amazon Aurora–powered application.
Amazon Aurora Getting started Guide -level 0kartraj
Introduction To Amazon Aurora, Amazon Aurora
applying a Service-oriented architecture
to the database
Aurora Makes it Easy to Run Your Databases
Aurora simplifies storage management
Aurora simplifies Data Security
Aurora is Highly Available
Amazon RDS with Amazon Aurora | AWS Public Sector Summit 2016Amazon Web Services
This session provides the attendee with an overview of Amazon RDS across different database types and then dives deep into the benefits and performance of Amazon Aurora.
Amazon Aurora is a MySQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. This session introduces you to Amazon Aurora, explains common use cases for the service, and helps you get started with building your first Amazon Aurora–powered application.
Amazon Aurora is a MySQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. This session introduces you to Amazon Aurora, explains common use cases for the service, and helps you get started with building your first Amazon Aurora–powered application.
AWS January 2016 Webinar Series - Amazon Aurora for Enterprise Database Appli...Amazon Web Services
Relational databases are a cornerstone of the enterprise IT landscape, powering business-critical applications of many kinds. Though they have been around for a while, current commercial relational databases have lagged behind in innovation. Amazon Aurora, a managed database service built for the cloud, is intended to change that. It targets the high-performance needs of business-critical applications with an emphasis on cost-effectiveness.
In this session, we will look into how Aurora fits the needs of applications built and bought by enterprises to power their business.
Learning Objectives:
Learn about the overall architecture, capabilities, and cost-effectiveness of Aurora, comparing it to current commercial database offerings
Explore best practices for enterprises adopting Aurora for existing and new applications, as well as strategies, tools, and techniques for migrating existing databases to Aurora
Who Should Attend:
IT Managers, DBAs, Enterprise and Solution Architects , DevOps Engineers and Developers
Amazon Aurora for the Enterprise - August 2016 Monthly Webinar SeriesAmazon Web Services
Relational databases are a cornerstone of the enterprise IT landscape, powering business-critical applications of many kinds. Though they have been around for a while, current commercial relational databases have lagged behind in innovation. Amazon Aurora, a managed database service built for the cloud, is intended to change that. It fulfils the high-performance, high-availability needs of business-critical applications with an emphasis on cost-effectiveness. In this session, we will look into how Aurora fits the needs of applications built and bought by enterprises to power their business.
Learning Objectives:
• Explore the overall architecture, capabilities, and cost-effectiveness of Aurora and see how it compares to commercial database offerings
• Learn best practices for enterprises adopting Aurora for existing and new workloads, as well as strategies, tools, and techniques for migrating existing databases to Aurora
Amazon Aurora is a MySQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. This session introduces you to Amazon Aurora, explains common use cases for the service, and helps you get started with building your first Amazon Aurora–powered application.
NEW LAUNCH! Introducing PostgreSQL compatibility for Amazon AuroraAmazon Web Services
After we launched Amazon Aurora, a cloud-native relational database with region-wide durability, high availability, fast failover, up to 15 read replicas, and up to five times the performance of MySQL, many of you asked us whether we could deliver the same features - but with PostgreSQL compatibility. We are now delivering a preview of Amazon Aurora with this functionality: we have built a PostgreSQL-compatible edition of Amazon Aurora, sharing the core Amazon Aurora innovations with the object-oriented capabilities, language interfaces, JSON compatibility, ANSI:SQL:2008 compliance, and broad functional richness of PostgreSQL. Amazon Aurora will provide full PostgreSQL compatibility while delivering more than twice the performance of the community PostgreSQL database on many workloads. At this session, we will be discussing the newest addition to Amazon Aurora in detail.
AWS re:Invent 2016: Getting Started with Amazon Aurora (DAT203)Amazon Web Services
Amazon Aurora is a MySQL-compatible relational database engine with the speed, reliability, and availability of high-end commercial databases at one-tenth the cost. This session introduces you to Amazon Aurora, explores the capabilities and features of Aurora, explains common use cases, and helps you get started with Aurora. Debanjan Saha, general manager for Aurora, explains how Aurora differs from other commonly available databases while staying compatible with MySQL and providing a high-end, cost-effective alternative to commercial and open-source database engines. In addition, Linda Xu, data architect at Ticketmaster, walks you through Ticketmaster's journey to Amazon Aurora, starting with evaluation through production migration of a critical Ticketmaster database to Amazon Aurora. Ticketmaster is one of the world's top 10 e-commerce companies and the global market leader in ticketing. In this session, Linda discusses how Aurora lets Ticketmaster provide better services to their fans, customers, and clients, and helps reduce the cost and operational burden while giving greater flexibility to support heavy traffic spikes.
In addition to running databases in Amazon EC2, AWS customers can choose among a variety of managed database services. These services save effort, save time, and unlock new capabilities and economies. In this session, we make it easy to understand how they differ, what they have in common, and how to choose one or more. We explain the fundamentals of Amazon DynamoDB, a fully managed NoSQL database service; Amazon RDS, a relational database service in the cloud; Amazon ElastiCache, a fast, in-memory caching service in the cloud; and Amazon Redshift, a fully managed, petabyte-scale data-warehouse solution that can be surprisingly economical. We will cover how each service might help support your application, how much each service costs, and how to get started. We will also have with us Jeongsang Baek, the VP of Engineering from IGAWorks, Korea’s No.1 mobile business platform, who will walk us through their architecture and share with us the key insights that they gained from using the various AWS database technologies to deliver a reliable, efficient and cost-effective experience.
Amazon Aurora is a MySQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. This session introduces you to Amazon Aurora, explains common use cases for the service, and helps you get started with building your first Amazon Aurora–powered application.
by Joyjeet Banerjee, Enterprise Solutions Architect, AWS
Amazon Aurora is a MySQL- and PostgreSQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. In this deep dive session, we’ll discuss best practices and explore new features in areas like high availability, security, performance management and database cloning. Level 300
Similar to Amazon Aurora Let's Talk About Performance (20)
Data analysis is being used to transform businesses, increase efficiency, and drive innovation. But organizations need to perform increasingly complex analysis on their data (streaming analytics, ad-hoc querying and predictive analytics) in order to get better insights and actionable business intelligence. The growing data volume, speed, and complexity of diverse data formats make legacy tools inadequate or difficult to use. The AWS Cloud has a comprehensive portfolio of analytics services to help you process data of any volume and automate how you put that data to work for your organization. In this session we’ll see how to put those services at work on structured, unstructured and real-time data.
Building Event-Driven Serverless ApplicationsDanilo Poccia
We built event-driven user interfaces for decades. What about bringing the same approach to mobile, web, and IoT backend applications? You have to understand how data flows and what is the propagation of changes, using reactive programming techniques. You can focus on the core functionalities to build and the relationships among the resources you use. Your application behaves similarly to a “spreadsheet”, where depending resources are updated automatically when something “happens”, and is decomposed into scalable microservices without having to manage the infrastructure. The resulting architecture is efficient and cost effective to run on AWS and managing availability, scalability and security becomes part of the implementation itself.
Connecting the Unconnected: IoT Made SimpleDanilo Poccia
Connecting physical devices to the cloud can enhance the user experience. AWS IoT is a new managed service that enables Internet-connected things (sensors, actuators, devices, and applications) to easily and securely interact with each other and the cloud. In this session, we will discuss how constrained devices can send data to the cloud and receive commands back to the device. Devices can securely connect using MQTT, HTTP protocols and developers can leverage several features of AWS IoT such as the Rules Engine and Thing Shadows to quickly and easily build a real connected product. This session will take a practical approach to developing real-world IoT and mobile applications in which the back end is serverless and can scale from one to virtually unlimited users without any infrastructure or servers to manage.
The slides from my session at the AWS User Group Luxembourg meeting on December 16th, 2015. The session was mostly a live demo, so there is not much content in the slides :)
From my session at DevTernity in Riga, December 1st 2015. Have you always wanted to add predictive capabilities to your application, but haven’t been able to find the time or the right technology to get started? Everybody wants to build smart apps, but only a few are Data Scientists. We had the same issue inside Amazon, so we created a Machine Learning engine that Developers can easily use. The same approach is now available in the AWS cloud. We demonstrate how to use Amazon Machine Learning (Amazon ML) to create machine learning models, deploy them to production, and obtain predictions in real-time. We then demonstrate how to build a complete smart application using Amazon ML, Amazon Kinesis, and AWS Lambda. We walk you through the process flow and architecture, demonstrate outcomes, and then dive into the implementation. In this session, you learn how to use Amazon ML as well as how to integrate Amazon ML into your applications to take advantage of predictive analysis in the cloud.
Slides from the Cloudyna event in Katowice, Poland on November 14th, 2015. In this session we will discuss how you can leverage the new cross-platform AWS Mobile Services to build a highly scalable and reliable mobile app, powered by the AWS Cloud. We will explore core functionality like authentication and authorization of users, data synchronization, backend infrastructure without the need to manage servers, understanding your user behavior, engaging your users and bringing your users back to your app. No matter if you are building the next great social app, or a front-office enterprise mobile app, this session will discuss best practices and reference architectures for building reliable and scalable mobile apps.
Using Amazon EC2 Container Service (ECS) to manage Docker containers in production with high availability and scalability. From the Docker Meetup in Leuven, Belgium on October 1st, 2015.
Infrastructure as Code: Manage your Architecture with GitDanilo Poccia
Containers make packaging and distribution of your application easy. With the AWS Cloud you have an on-demand, programmable infrastructure that you can manage using tools and practices from software development. You can create resources when you need and dispose of them when you don’t. Using Amazon CloudFormation you can describe your architecture in text files. To change your infrastructure, you edit those files. Having application and infrastructure code in a single, robust, versioned repository like Git gives a lot of advantages. Using AWS Elastic Beanstalk you can link your Git branches to different infrastructure environments (e.g. test, production) and automate deployments. You can create test environments on-demand, even for a short time. Instead of continuously update your resources, you can recreate them quickly from scratch, simplifying lifecycle management and making deployments immutable. Using Amazon EC2 Container Service (ECS) you can manage containers at scale. As a result, you have more time to focus on the unique features of your application.
Infrastructure as Code: Manage your Architecture with GitDanilo Poccia
With the AWS Cloud you have an on-demand, programmable infrastructure that you can manage using tools and practices from software development. You can create resources when you need and dispose of them when you don’t. Using Amazon CloudFormation you can describe your architecture in text files. To change your infrastructure, you edit those files. Having application and infrastructure code in a single, robust, versioned repository like Git gives a lot of advantages. Using AWS Elastic Beanstalk you can link your Git branches to different infrastructure environments (e.g. test, production) and automate deployments. You can create test environments on-demand, even for a short time. Instead of continuously update your resources, you can recreate them quickly from scratch, simplifying lifecycle management and making deployments immutable. As a result, you have more time to focus on the unique features of your application.
Cloud-powered Cross-platform Mobile Apps on AWSDanilo Poccia
We’ll see with a real application how to use AWS Mobile Services & SDK to focus the development your mobile app on the unique features of your implementation, using high level services such as Amazon Cognito (for identity and data synchronization across devices), Amazon SNS (for Mobile Push notifications), Amazon Mobile Analytics (to understand your users), Amazon S3 (for object storage), Amazon DynamoDB (for low-latency NoSQL database), or Amazon Kinesis (for data streaming) directly from the device, optimizing performance and costs of the solution.
Microservice Architecture on AWS using AWS Lambda and Docker ContainersDanilo Poccia
The use of microservices as an architectural pattern, decomposing an application into small, independent components, can improve development, deployment and security. We’ll build a real architecture using AWS Lambda to run event-based functions and Amazon EC2 Container Service and AWS Elastic Beanstalk to manage backend and frontend Docker containers. We’ll evolve from a web based interface to a mobile, cross platform architecture, using a least-privilege approach on security based on AWS Identity and Access Management roles.
Microservices on AWS using AWS Lambda and Docker ContainersDanilo Poccia
Using AWS Lambda and Docker Containers to build a Microservice Architecture on Amazon Web Services.
From the AWS User Group Hungary meeting in Budapest on Friday March 20th, 2015.
Building Cloud-Powered Mobile Apps using AWS Mobile services and SDKs, with an overview of Cognito identity and synchronization, Mobile Analytics, S3 Transfer Manager, DynamoDB Object Mapper, Kinesis Connector.
Listen to the keynote address and hear about the latest developments from Rachana Ananthakrishnan and Ian Foster who review the updates to the Globus Platform and Service, and the relevance of Globus to the scientific community as an automation platform to accelerate scientific discovery.
Quarkus Hidden and Forbidden ExtensionsMax Andersen
Quarkus has a vast extension ecosystem and is known for its subsonic and subatomic feature set. Some of these features are not as well known, and some extensions are less talked about, but that does not make them less interesting - quite the opposite.
Come join this talk to see some tips and tricks for using Quarkus and some of the lesser known features, extensions and development techniques.
Advanced Flow Concepts Every Developer Should KnowPeter Caitens
Tim Combridge from Sensible Giraffe and Salesforce Ben presents some important tips that all developers should know when dealing with Flows in Salesforce.
Accelerate Enterprise Software Engineering with PlatformlessWSO2
Key takeaways:
Challenges of building platforms and the benefits of platformless.
Key principles of platformless, including API-first, cloud-native middleware, platform engineering, and developer experience.
How Choreo enables the platformless experience.
How key concepts like application architecture, domain-driven design, zero trust, and cell-based architecture are inherently a part of Choreo.
Demo of an end-to-end app built and deployed on Choreo.
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
Multiple Your Crypto Portfolio with the Innovative Features of Advanced Crypt...Hivelance Technology
Cryptocurrency trading bots are computer programs designed to automate buying, selling, and managing cryptocurrency transactions. These bots utilize advanced algorithms and machine learning techniques to analyze market data, identify trading opportunities, and execute trades on behalf of their users. By automating the decision-making process, crypto trading bots can react to market changes faster than human traders
Hivelance, a leading provider of cryptocurrency trading bot development services, stands out as the premier choice for crypto traders and developers. Hivelance boasts a team of seasoned cryptocurrency experts and software engineers who deeply understand the crypto market and the latest trends in automated trading, Hivelance leverages the latest technologies and tools in the industry, including advanced AI and machine learning algorithms, to create highly efficient and adaptable crypto trading bots
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
top nidhi software solution freedownloadvrstrong314
This presentation emphasizes the importance of data security and legal compliance for Nidhi companies in India. It highlights how online Nidhi software solutions, like Vector Nidhi Software, offer advanced features tailored to these needs. Key aspects include encryption, access controls, and audit trails to ensure data security. The software complies with regulatory guidelines from the MCA and RBI and adheres to Nidhi Rules, 2014. With customizable, user-friendly interfaces and real-time features, these Nidhi software solutions enhance efficiency, support growth, and provide exceptional member services. The presentation concludes with contact information for further inquiries.
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
Paketo Buildpacks : la meilleure façon de construire des images OCI? DevopsDa...Anthony Dahanne
Les Buildpacks existent depuis plus de 10 ans ! D’abord, ils étaient utilisés pour détecter et construire une application avant de la déployer sur certains PaaS. Ensuite, nous avons pu créer des images Docker (OCI) avec leur dernière génération, les Cloud Native Buildpacks (CNCF en incubation). Sont-ils une bonne alternative au Dockerfile ? Que sont les buildpacks Paketo ? Quelles communautés les soutiennent et comment ?
Venez le découvrir lors de cette session ignite
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
SOCRadar Research Team: Latest Activities of IntelBrokerSOCRadar
The European Union Agency for Law Enforcement Cooperation (Europol) has suffered an alleged data breach after a notorious threat actor claimed to have exfiltrated data from its systems. Infamous data leaker IntelBroker posted on the even more infamous BreachForums hacking forum, saying that Europol suffered a data breach this month.
The alleged breach affected Europol agencies CCSE, EC3, Europol Platform for Experts, Law Enforcement Forum, and SIRIUS. Infiltration of these entities can disrupt ongoing investigations and compromise sensitive intelligence shared among international law enforcement agencies.
However, this is neither the first nor the last activity of IntekBroker. We have compiled for you what happened in the last few days. To track such hacker activities on dark web sources like hacker forums, private Telegram channels, and other hidden platforms where cyber threats often originate, you can check SOCRadar’s Dark Web News.
Stay Informed on Threat Actors’ Activity on the Dark Web with SOCRadar!
Your Digital Assistant.
Making complex approach simple. Straightforward process saves time. No more waiting to connect with people that matter to you. Safety first is not a cliché - Securely protect information in cloud storage to prevent any third party from accessing data.
Would you rather make your visitors feel burdened by making them wait? Or choose VizMan for a stress-free experience? VizMan is an automated visitor management system that works for any industries not limited to factories, societies, government institutes, and warehouses. A new age contactless way of logging information of visitors, employees, packages, and vehicles. VizMan is a digital logbook so it deters unnecessary use of paper or space since there is no requirement of bundles of registers that is left to collect dust in a corner of a room. Visitor’s essential details, helps in scheduling meetings for visitors and employees, and assists in supervising the attendance of the employees. With VizMan, visitors don’t need to wait for hours in long queues. VizMan handles visitors with the value they deserve because we know time is important to you.
Feasible Features
One Subscription, Four Modules – Admin, Employee, Receptionist, and Gatekeeper ensures confidentiality and prevents data from being manipulated
User Friendly – can be easily used on Android, iOS, and Web Interface
Multiple Accessibility – Log in through any device from any place at any time
One app for all industries – a Visitor Management System that works for any organisation.
Stress-free Sign-up
Visitor is registered and checked-in by the Receptionist
Host gets a notification, where they opt to Approve the meeting
Host notifies the Receptionist of the end of the meeting
Visitor is checked-out by the Receptionist
Host enters notes and remarks of the meeting
Customizable Components
Scheduling Meetings – Host can invite visitors for meetings and also approve, reject and reschedule meetings
Single/Bulk invites – Invitations can be sent individually to a visitor or collectively to many visitors
VIP Visitors – Additional security of data for VIP visitors to avoid misuse of information
Courier Management – Keeps a check on deliveries like commodities being delivered in and out of establishments
Alerts & Notifications – Get notified on SMS, email, and application
Parking Management – Manage availability of parking space
Individual log-in – Every user has their own log-in id
Visitor/Meeting Analytics – Evaluate notes and remarks of the meeting stored in the system
Visitor Management System is a secure and user friendly database manager that records, filters, tracks the visitors to your organization.
"Secure Your Premises with VizMan (VMS) – Get It Now"
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
2. Current DB architectures are monolithic
Multiple layers of
functionality all on a
single box
SQL
Transactions
Caching
Logging
3. Current DB architectures are monolithic
Even when you scale
it out, you’re still
replicating the same
stack
SQL
Transactions
Caching
Logging
SQL
Transactions
Caching
Logging
Application
4. Current DB architectures are monolithic
SQL
Transactions
Caching
Logging
SQL
Transactions
Caching
Logging
Application Even when you scale
it out, you’re still
replicating the same
stack
5. Current DB architectures are monolithic
SQL
Transactions
Caching
Logging
SQL
Transactions
Caching
Logging
Storage
Application Even when you scale
it out, you’re still
replicating the same
stack
6. This is a problem.
For cost. For flexibility. And for availability.
7. Reimagining the relational database
What if you were inventing the database today?
You wouldn’t design it the way we did in 1970. At least not entirely.
You’d build something that can scale out, that is self-healing, and that
leverages existing AWS services.
8. Relational databases reimagined for the cloud
Speed and availability of high-end commercial databases
Simplicity and cost-effectiveness of open source databases
Drop-in compatibility with MySQL
Simple pay as you go pricing
Delivered as a managed service
9. A service-oriented architecture applied to the database
• Moved the logging and storage layer
into a multi-tenant, scale-out
database-optimized storage service
• Integrated with other AWS services
like Amazon EC2, Amazon VPC,
Amazon DynamoDB, Amazon SWF,
and Amazon Route 53 for control
plane operations
• Integrated with Amazon S3 for
continuous backup with
99.999999999% durability
Control PlaneData Plane
Amazon
DynamoDB
Amazon SWF
Amazon Route 53
Logging + Storage
SQL
Transactions
Caching
Amazon S3
10. Simple pricing
• No licenses
• No lock-in
• Pay only for what you use
Discounts
• Up to 45% with a 1-year RI
• Up to 66% with a 3-year RI
vCPU Mem Hourly Price
db.r3.large 2 15.25 $0.29
db.r3.xlarge 4 30.5 $0.58
db.r3.2xlarge 8 61 $1.16
db.r3.4xlarge 16 122 $2.32
db.r3.8xlarge 32 244 $4.64
• Storage consumed, up to 64 TB, is $0.10/GB-month
• IOs consumed are billed at $0.20 per million I/O
• Prices are for Virginia
Enterprise grade, open source pricing
12. Establishing our ecosystem
Business Intelligence Data Integration Query and Monitoring SI and Consulting
“It is great to see Amazon Aurora remains MySQL compatible; MariaDB connectors
work with Aurora seamlessly. Today, customers can take MariaDB Enterprise with
MariaDB MaxScale drivers and connect to Aurora, MariaDB, or MySQL without worrying about
compatibility. We look forward to working with the Aurora team in the future to further
accelerate innovation within the MySQL ecosystem.”— Roger Levy, VP Products, MariaDB
13. 1 – Establish baseline
a) MySQL dump/import
b) RDS MySQL to Aurora DB
snapshot migration
2 – Catch-up changes
a) Binlog replication
b) Tungsten Replicator
AuroraMySQL
2 - Replication
1 - Baseline
Achieving near zero downtime migration to Aurora
15. Aurora storage
• Highly available by default
– 6-way replication across 3 AZs
– 4 of 6 write quorum
• Automatic fallback to 3 of 4 if an
Availability Zone (AZ) is unavailable
– 3 of 6 read quorum
• SSD, scale-out, multi-tenant storage
– Seamless storage scalability
– Up to 64 TB database size
– Only pay for what you use
• Log-structured storage
– Many small segments, each with their own redo logs
– Log pages used to generate data pages
– Eliminates chatter between database and storage
SQL
Transactions
AZ 1 AZ 2 AZ 3
Caching
Amazon S3
16. Self-healing, fault-tolerant
• Lose two copies or an AZ failure without read or write availability impact
• Lose three copies without read availability impact
• Automatic detection, replication, and repair
SQL
Transaction
AZ 1 AZ 2 AZ 3
Caching
SQL
Transaction
AZ 1 AZ 2 AZ 3
Caching
Read and write availabilityRead availability
17. Traditional databases
• Have to replay logs since the last
checkpoint
• Single-threaded in MySQL;
requires a large number of disk
accesses
Amazon Aurora
• Underlying storage replays redo
records on demand as part of a
disk read
• Parallel, distributed, asynchronous
Checkpointed Data Redo Log
Crash at T0 requires
a re-application of the
SQL in the redo log since
last checkpoint
T0 T0
Crash at T0 will result in redo
logs being applied to each segment
on demand, in parallel, asynchronously
Instant crash recovery
18. Survivable caches
• We moved the cache out of
the database process
• Cache remains warm in the
event of a database restart
• Lets you resume fully loaded
operations much faster
• Instant crash recovery +
survivable cache = quick and
easy recovery from DB
failures
SQL
Transactions
Caching
SQL
Transactions
Caching
SQL
Transactions
Caching
Caching process is outside the DB process
and remains warm across a database restart
19. Multiple failover targets—no data loss
Page cache
invalidation
Aurora Master
30% Read
70% Write
Aurora Replica
100% New
Reads
Shared Multi-AZ Storage
MySQL Master
30% Read
70% Write
MySQL Replica
30% New Reads
70% Write
Single-threaded
binlog apply
Data Volume Data Volume
MySQL read scaling
• Replicas must replay logs
• Replicas place additional load on master
• Replica lag can grow indefinitely
• Failover results in data loss
20. Faster, more predictable failover
Failure Detection DNS Propagation
Recovery Recovery
App
running
DB
Failure
Failure Detection
Recovery
App
running
DB
Failure
?
DNS Propagation
21. Simulate failures using SQL
• To cause the failure of a component at the database node:
ALTER SYSTEM CRASH [{INSTANCE | DISPATCHER | NODE}]
• To simulate the failure of disks:
ALTER SYSTEM SIMULATE percent_failure DISK failure_type IN
[DISK index | NODE index] FOR INTERVAL interval
• To simulate the failure of networking:
ALTER SYSTEM SIMULATE percent_failure NETWORK failure_type
[TO {ALL | read_replica | availability_zone}] FOR INTERVAL interval
23. Write performance (console screenshot)
• MySQL Sysbench
• R3.8XL with 32 cores
and 244 GB RAM
• 4 client machines with
1,000 threads each
24. Read performance (console screenshot)
• MySQL Sysbench
• R3.8XL with 32 cores
and 244 GB RAM
• Single client with
1,000 threads
25. Read replica lag (console screenshot)
• Aurora Replica with 7.27 ms replica lag at 13.8 K updates per second
• MySQL 5.6 on the same hardware has ~2 s lag at 2 K updates per second
26. Writes scale with table count
-
10
20
30
40
50
60
70
10 100 1,000 10,000
Thousandsofwritespersecond
Number of tables
Write performance and table count
Aurora
MySQL on I2.8XL
MySQL on I2.8XL with RAM Disk
RDS MySQL with 30,000 IOPS (Single AZ)
Tables
Amazon
Aurora
MySQL
I2.8XL
local SSD
MySQL
I2.8XL
RAM disk
RDS MySQL
30K IOPS
(single AZ)
10 60,000 18,000 22,000 25,000
100 66,000 19,000 24,000 23,000
1,000 64,000 7,000 18,000 8,000
10,000 54,000 4,000 8,000 5,000
Write-only workload
1,000 connections
Query cache (default on for Amazon Aurora, off for MySQL)
27. Better concurrency
-
20
40
60
80
100
120
50 500 5,000
Thousandsofwritespersecond
Concurrent connections
Write performance and concurrency
Aurora
RDS MySQL with 30,000 IOPS (Single AZ)
Connections
Amazon
Aurora
RDS MySQL
30K IOPS
(single AZ)
50 40,000 10,000
500 71,000 21,000
5,000 110,000 13,000
OLTP Workload
Variable connection count
250 tables
Query cache (default on for Amazon Aurora, off for MySQL)
28. Replicas have up to 400 times less lag
2.6 3.4 3.9 5.4
1,000 2,000 5,000 10,000
0
50,000
100,000
150,000
200,000
250,000
300,000
Updates per second
Readreplicalaginmilliseconds
Read replica lag
Aurora
RDS MySQL;30,000 IOPS (Single AZ)
Updates per
second
Amazon
Aurora
RDS MySQL
30K IOPS
(single AZ)
1,000 2.62 ms 0 s
2,000 3.42 ms 1 s
5,000 3.94 ms 60 s
10,000 5.38 ms 300 s
Write workload
250 tables
Query cache on for Amazon Aurora, off for MySQL (best
settings)
30. Simplify database management
• Create a database in minutes
• Automated patching
• Push-button scale compute
• Continuous backups to Amazon S3
• Automatic failure detection and failover
Amazon RDS
31. Simplify storage management
• Read replicas are available as failover targets—no data loss
• Instantly create user snapshots—no performance impact
• Continuous, incremental backups to Amazon S3
• Automatic storage scaling up to 64 TB—no performance or availability
impact
• Automatic restriping, mirror repair, hot spot management, encryption
32. Simplify data security
• Encryption to secure data at rest available soon
– AES-256; hardware accelerated
– All blocks on disk and in Amazon S3 are encrypted
– Key management via AWS KMS
• SSL to secure data in transit
• Network isolation via Amazon VPC by default
• No direct access to nodes
• Supports industry standard security and data
protection certifications
Storage
SQL
Transactions
Caching
Amazon S3
Application
33. Business Value
• Enables new applications and features
• Improved developer and IT productivity
• Simple, easy to manage infrastructure with less downtime
• Quick recovery from failures
• Low cost (1/10th of commercial databases)
34. Use Cases
• New Applications
• All MySQL applications
• High traffic web applications using relational databases
• Read/Write intensive databases
• SaaS applications/Multitenant products
• Existing RDS customers with volume size limitations (up to 64TB
with Aurora)
• Commercial database applicaitons that do not heavily rely on
vendor specific functionality (PL/SQL)