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.
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.
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
Amazon Aurora Storage Demystified: How It All Works (DAT363) - AWS re:Invent ...Amazon Web Services
Amazon Aurora is a high performance, highly scalable database service with MySQL- and PostgreSQL-compatibility. One of its key components is an innovative storage system that is optimized for database workloads and specifically designed to take advantage of modern cloud technology. Hear from the team that built Amazon Aurora's storage system on how the system is designed, how it works, and what you need to know to get the most out of it.
Kafka Tutorial - Introduction to Apache Kafka (Part 1)Jean-Paul Azar
Why is Kafka so fast? Why is Kafka so popular? Why Kafka? This slide deck is a tutorial for the Kafka streaming platform. This slide deck covers Kafka Architecture with some small examples from the command line. Then we expand on this with a multi-server example to demonstrate failover of brokers as well as consumers. Then it goes through some simple Java client examples for a Kafka Producer and a Kafka Consumer. We have also expanded on the Kafka design section and added references. The tutorial covers Avro and the Schema Registry as well as advance Kafka Producers.
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 RDS allows you to launch an optimally configured, secure and highly available database with just a few clicks. It provides cost-efficient and resizable capacity while managing time-consuming database administration tasks, freeing you up to focus on your applications and business. We’ll discuss Amazon RDS fundamentals, learn about the six available database engines (with the seventh on the way), and examine customer success stories.
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.
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
Amazon Aurora Storage Demystified: How It All Works (DAT363) - AWS re:Invent ...Amazon Web Services
Amazon Aurora is a high performance, highly scalable database service with MySQL- and PostgreSQL-compatibility. One of its key components is an innovative storage system that is optimized for database workloads and specifically designed to take advantage of modern cloud technology. Hear from the team that built Amazon Aurora's storage system on how the system is designed, how it works, and what you need to know to get the most out of it.
Kafka Tutorial - Introduction to Apache Kafka (Part 1)Jean-Paul Azar
Why is Kafka so fast? Why is Kafka so popular? Why Kafka? This slide deck is a tutorial for the Kafka streaming platform. This slide deck covers Kafka Architecture with some small examples from the command line. Then we expand on this with a multi-server example to demonstrate failover of brokers as well as consumers. Then it goes through some simple Java client examples for a Kafka Producer and a Kafka Consumer. We have also expanded on the Kafka design section and added references. The tutorial covers Avro and the Schema Registry as well as advance Kafka Producers.
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 RDS allows you to launch an optimally configured, secure and highly available database with just a few clicks. It provides cost-efficient and resizable capacity while managing time-consuming database administration tasks, freeing you up to focus on your applications and business. We’ll discuss Amazon RDS fundamentals, learn about the six available database engines (with the seventh on the way), and examine customer success stories.
Dive deep into some of the key innovations behind Amazon Aurora, discuss best practices and configurations, and share early customer experience from the field.
Architecture patterns for distributed, hybrid, edge and global Apache Kafka d...Kai Wähner
Architecture patterns for distributed, hybrid, edge and global Apache Kafka deployments
Multi-cluster and cross-data center deployments of Apache Kafka have become the norm rather than an exception. This session gives an overview of several scenarios that may require multi-cluster solutions and discusses real-world examples with their specific requirements and trade-offs, including disaster recovery, aggregation for analytics, cloud migration, mission-critical stretched deployments and global Kafka.
Key takeaways:
In many scenarios, one Kafka cluster is not enough. Understand different architectures and alternatives for multi-cluster deployments.
Zero data loss and high availability are two key requirements. Understand how to realize this, including trade-offs.
Learn about features and limitations of Kafka for multi cluster deployments
Global Kafka and mission-critical multi-cluster deployments with zero data loss and high availability became the normal, not an exception.
This presentation shortly describes key features of Apache Cassandra. It was held at the Apache Cassandra Meetup in Vienna in January 2014. You can access the meetup here: http://www.meetup.com/Vienna-Cassandra-Users/
State, Local and Education customers are using the AWS cloud to enable faster disaster recovery of their mission critical IT systems without incurring the infrastructure expense of a second physical site. Join us for an informative webinar on how AWS cloud supports many popular disaster recovery (DR) architectures from “pilot light” environments that are ready to scale up at a moment’s notice to “hot standby” environments that enable rapid failover. With infrastructure centers in 10 regions around the world, AWS provides a set of cloud-based DR services that enable rapid recovery of your IT infrastructure and data.
Amazon DynamoDB Under the Hood: How We Built a Hyper-Scale Database (DAT321) ...Amazon Web Services
Come to this session to learn how Amazon DynamoDB was built as the hyper-scale database for internet-scale applications. In January 2012, Amazon launched DynamoDB, a cloud-based NoSQL database service designed from the ground up to support extreme scale, with the security, availability, performance, and manageability needed to run mission-critical workloads. This session discloses for the first time the underpinnings of DynamoDB, and how we run a fully managed nonrelational database used by more than 100,000 customers. We cover the underlying technical aspects of how an application works with DynamoDB for authentication, metadata, storage nodes, streams, backup, and global replication.
Kafka's basic terminologies, its architecture, its protocol and how it works.
Kafka at scale, its caveats, guarantees and use cases offered by it.
How we use it @ZaprMediaLabs.
Amazon Relational Database Service (Amazon RDS) is a web service that makes it easier to set up, operate, and scale a relational database in the cloud. It provides cost-efficient, re-sizable capacity for an industry-standard relational database and manages common database administration tasks
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 savings 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 relational database management system investments to Amazon RDS.
Kafka Tiered Storage separates compute and data storage in two independently scalable layers. Uber's Kafka Improvement Proposal (KIP) #405 describes two-tiered storage, which is a major step towards cloud-native Kafka. It stores the most recent data locally and offloads older data to a remote storage service. Operationally, the benefit is faster routine cluster maintenance activities. In Linkedin, Kafka tiered storage is strongly desired to reduce the cost of running Kafka in the Azure cloud environment. As KIP-405 does not dictate the implementation of remote storage substrate, Linkedin's choice for tiering Kafka in Azure deployments is the Azure Blob Service. This presentation will begin with the motivation behind Linkedin efforts to adopt Kafka Tiered Storage. Next, the architecture of KIP-405 will be discussed. Finally, the Remote Storage Manager for Azure Blobs, which is a work-in-progress, will be presented.
Video: https://youtu.be/V5gaBE5CMwg?t=1387
Apache BookKeeper State Store: A Durable Key-Value Store - Pulsar Summit NA 2021StreamNative
Apache Pulsar is used for various streaming use cases. There is a strong requirement for storing checkpoints while processing the stream in Pulsar Functions, so that in case of any interruption stream processing engine could go back to the last checkpoint.
Pulsar uses Zookeeper not only for leader elections or service discovery like critical use cases but also for storing various metadata which puts unnecessary load on zookeeper which hampers mission critical use of Zookeeper.
A durable key value store based off of the Apache Pulsar ecosystem addresses the above mentioned use cases nicely.
This talk focuses on taking existing Apache Bookkeeper Table Service/State store implementation and taking it to production. Furthermore this talk also touches upon contributing all the features, bug fixes, tools and other improvements back to open source.
Disaster Recovery of on-premises IT infrastructure with AWSAmazon Web Services
The objective of this session is to enable customers with any level of DR experience to gain actionable guidance to advance their business up the ladder of DR readiness. AWS enables fast disaster recovery of critical on-premises IT systems without incurring the complexity and expense of a second physical site. With 28 availability zones in 11 regions around the world and a broad set of services, AWS can deliver rapid recovery of on-premises IT infrastructure and data. During this session we will walk you through the ascending levels of DR options made possible with AWS and review the technologies and services that help deliver various DR capabilities, starting from cloud backups all the way up to hot site DR. We will also explore various DR architectures and the balance of recovery time and cost.
An overview of the Amazon ElastiCache managed service, with examples of how it can be used to increase performance, lower costs and augment other database services and databases to make things faster, easier and less expensive.
Capacity Planning Your Kafka Cluster | Jason Bell, DigitalisHostedbyConfluent
"There's little talk about capacity planning Kafka clusters, it's very much learn as you go, every cluster is different. In this talk Kafka DevOps Engineer Jason Bell takes you through the things that will help you, from broker capacity, thinking about topics and how the other Confluent components can affect throughput and performance. With a number of production deployments under his watchful gaze for over six years Jason has plenty of experience, stories and useful information that will help you.
By the end of the talk you'll have a good understanding of designing the cluster for various scenarios, where the points of latency are to watch and monitor. And also how to prevent teams breaking the cluster behind your back.
This talk is designed for everyone, anyone who is just starting to those who are operating Kafka on a daily basis."
Have you ever wondered what the relative differences are between two of the more popular open source, in-memory data stores and caches? In this session, we will describe those differences and, more importantly, provide live demonstrations of the key capabilities that could have a major impact on your architectural Java application designs.
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.
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.
Dive deep into some of the key innovations behind Amazon Aurora, discuss best practices and configurations, and share early customer experience from the field.
Architecture patterns for distributed, hybrid, edge and global Apache Kafka d...Kai Wähner
Architecture patterns for distributed, hybrid, edge and global Apache Kafka deployments
Multi-cluster and cross-data center deployments of Apache Kafka have become the norm rather than an exception. This session gives an overview of several scenarios that may require multi-cluster solutions and discusses real-world examples with their specific requirements and trade-offs, including disaster recovery, aggregation for analytics, cloud migration, mission-critical stretched deployments and global Kafka.
Key takeaways:
In many scenarios, one Kafka cluster is not enough. Understand different architectures and alternatives for multi-cluster deployments.
Zero data loss and high availability are two key requirements. Understand how to realize this, including trade-offs.
Learn about features and limitations of Kafka for multi cluster deployments
Global Kafka and mission-critical multi-cluster deployments with zero data loss and high availability became the normal, not an exception.
This presentation shortly describes key features of Apache Cassandra. It was held at the Apache Cassandra Meetup in Vienna in January 2014. You can access the meetup here: http://www.meetup.com/Vienna-Cassandra-Users/
State, Local and Education customers are using the AWS cloud to enable faster disaster recovery of their mission critical IT systems without incurring the infrastructure expense of a second physical site. Join us for an informative webinar on how AWS cloud supports many popular disaster recovery (DR) architectures from “pilot light” environments that are ready to scale up at a moment’s notice to “hot standby” environments that enable rapid failover. With infrastructure centers in 10 regions around the world, AWS provides a set of cloud-based DR services that enable rapid recovery of your IT infrastructure and data.
Amazon DynamoDB Under the Hood: How We Built a Hyper-Scale Database (DAT321) ...Amazon Web Services
Come to this session to learn how Amazon DynamoDB was built as the hyper-scale database for internet-scale applications. In January 2012, Amazon launched DynamoDB, a cloud-based NoSQL database service designed from the ground up to support extreme scale, with the security, availability, performance, and manageability needed to run mission-critical workloads. This session discloses for the first time the underpinnings of DynamoDB, and how we run a fully managed nonrelational database used by more than 100,000 customers. We cover the underlying technical aspects of how an application works with DynamoDB for authentication, metadata, storage nodes, streams, backup, and global replication.
Kafka's basic terminologies, its architecture, its protocol and how it works.
Kafka at scale, its caveats, guarantees and use cases offered by it.
How we use it @ZaprMediaLabs.
Amazon Relational Database Service (Amazon RDS) is a web service that makes it easier to set up, operate, and scale a relational database in the cloud. It provides cost-efficient, re-sizable capacity for an industry-standard relational database and manages common database administration tasks
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 savings 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 relational database management system investments to Amazon RDS.
Kafka Tiered Storage separates compute and data storage in two independently scalable layers. Uber's Kafka Improvement Proposal (KIP) #405 describes two-tiered storage, which is a major step towards cloud-native Kafka. It stores the most recent data locally and offloads older data to a remote storage service. Operationally, the benefit is faster routine cluster maintenance activities. In Linkedin, Kafka tiered storage is strongly desired to reduce the cost of running Kafka in the Azure cloud environment. As KIP-405 does not dictate the implementation of remote storage substrate, Linkedin's choice for tiering Kafka in Azure deployments is the Azure Blob Service. This presentation will begin with the motivation behind Linkedin efforts to adopt Kafka Tiered Storage. Next, the architecture of KIP-405 will be discussed. Finally, the Remote Storage Manager for Azure Blobs, which is a work-in-progress, will be presented.
Video: https://youtu.be/V5gaBE5CMwg?t=1387
Apache BookKeeper State Store: A Durable Key-Value Store - Pulsar Summit NA 2021StreamNative
Apache Pulsar is used for various streaming use cases. There is a strong requirement for storing checkpoints while processing the stream in Pulsar Functions, so that in case of any interruption stream processing engine could go back to the last checkpoint.
Pulsar uses Zookeeper not only for leader elections or service discovery like critical use cases but also for storing various metadata which puts unnecessary load on zookeeper which hampers mission critical use of Zookeeper.
A durable key value store based off of the Apache Pulsar ecosystem addresses the above mentioned use cases nicely.
This talk focuses on taking existing Apache Bookkeeper Table Service/State store implementation and taking it to production. Furthermore this talk also touches upon contributing all the features, bug fixes, tools and other improvements back to open source.
Disaster Recovery of on-premises IT infrastructure with AWSAmazon Web Services
The objective of this session is to enable customers with any level of DR experience to gain actionable guidance to advance their business up the ladder of DR readiness. AWS enables fast disaster recovery of critical on-premises IT systems without incurring the complexity and expense of a second physical site. With 28 availability zones in 11 regions around the world and a broad set of services, AWS can deliver rapid recovery of on-premises IT infrastructure and data. During this session we will walk you through the ascending levels of DR options made possible with AWS and review the technologies and services that help deliver various DR capabilities, starting from cloud backups all the way up to hot site DR. We will also explore various DR architectures and the balance of recovery time and cost.
An overview of the Amazon ElastiCache managed service, with examples of how it can be used to increase performance, lower costs and augment other database services and databases to make things faster, easier and less expensive.
Capacity Planning Your Kafka Cluster | Jason Bell, DigitalisHostedbyConfluent
"There's little talk about capacity planning Kafka clusters, it's very much learn as you go, every cluster is different. In this talk Kafka DevOps Engineer Jason Bell takes you through the things that will help you, from broker capacity, thinking about topics and how the other Confluent components can affect throughput and performance. With a number of production deployments under his watchful gaze for over six years Jason has plenty of experience, stories and useful information that will help you.
By the end of the talk you'll have a good understanding of designing the cluster for various scenarios, where the points of latency are to watch and monitor. And also how to prevent teams breaking the cluster behind your back.
This talk is designed for everyone, anyone who is just starting to those who are operating Kafka on a daily basis."
Have you ever wondered what the relative differences are between two of the more popular open source, in-memory data stores and caches? In this session, we will describe those differences and, more importantly, provide live demonstrations of the key capabilities that could have a major impact on your architectural Java application designs.
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.
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.
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.
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. 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
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 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: 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.
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’ll cover how each service might help support your application, how much each service costs, and how to get started.
Speaker:
Shaun Pearce, AWS Solutions Architect
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.
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: 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.
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.
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.
ENT305 Migrating Your Databases to AWS: Deep Dive on Amazon Relational Databa...Amazon Web Services
Amazon RDS allows you to launch an optimally configured, secure and highly available database with just a few clicks. It provides cost-efficient and resizable capacity, automates time-consuming database administration tasks, and provides you with six familiar database engines to choose from: Amazon Aurora, Oracle, Microsoft SQL Server, PostgreSQL, MySQL and MariaDB. In this session, we will take a close look at the capabilities of Amazon RDS and explain how it works. We’ll also discuss the AWS Database Migration Service and AWS Schema Conversion Tool, which help you migrate databases and data warehouses with minimal downtime from on-premises and cloud environments to Amazon RDS and other Amazon services. Gain your freedom from expensive, proprietary databases while providing your applications with the fast performance, scalability, high availability, and compatibility they need.
Similar to Amazon RDS with Amazon Aurora | AWS Public Sector Summit 2016 (20)
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.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
2. What is Amazon RDS?
• Managed relational database in the cloud
• 6 familiar engines and multiple versions to chose from
• Managed for you:
• Amazon RDS handles routine database tasks such as
provisioning, patching, backup, recovery, failure detection,
and repair.
3. Why did AWS build Amazon RDS?
• There’s a lot of repetitive
labor that must be done, but
doesn’t directly add value
• Backups and restores
• Software installs and
patching
• Managing hardware
• Achieving many important
capabilities requires lots of
spend, lots of engineering,
or both
• Scaling
• High availability
• Migration
Managing relational databases is hard
4. With a traditional DB you:
• Acquire hardware (purchase, rack and stack)
• Load OS
• Load clustering software
• Load database software
• Create a database
• Optimize your query logic
• Design and implement a backup strategy
• Perform patching (OS, clustering software,
database)
• Perform software and hardware upgrades
• Deal with hardware failures
How does RDS compare to traditional DB hosting?
With RDS you:
• Create a database (selecting
options for backup and
maintenance)
• Optimize your query logic and
execution
5. Amazon RDS is simple and fast to deploy
• Get a production-ready
database instance in
minutes
• No need to acquire
servers, rack and stack,
install OS and
database software
7. A simple application architecture
RDS database instance
Application, in an
Amazon EC2 instance
Elastic Load Balancing
load balancer instance
DB snapshots in
Amazon S3
8. Choose Multi-AZ for greater availability, durability
• An Availability Zone is a physically distinct, independent
infrastructure
• With Multi-AZ operation, your database is synchronously
replicated to another AZ in the same AWS Region
• Failover occurs automatically in response to the most
important failure scenarios
• Planned maintenance is applied first to backup
9. A resilient, durable, still simple application
architecture
RDS database instances:
master and Multi-AZ standby
Application, in Amazon
EC2 instances
Elastic Load Balancing
load balancer instance
DB snapshots in
Amazon S3
10. Amazon RDS offers fast, predictable storage
General Purpose
(SSD) for most
workloads
Provisioned IOPS
(SSD) for OLTP
workloads up to 30,000
IOPS
Magnetic for small
workloads with
infrequent access
11. Amazon RDS Read Replicas offer scale-out
• Offload read traffic to
automatically maintained
Read Replicas
• Load-share traffic across
multiple Read Replicas
• Easy to set up
12. Amazon RDS provides levels of security difficult to
achieve on-premises
• AWS has achieved major compliances
• Amazon RDS gives each database instance IP firewall
protection
• Amazon VPC lets you isolate and control network
configuration and connect securely to your IT infrastructure
• AWS Identity and Access Management provides resource-
level permission controls
• Amazon RDS offers encryption at rest and SSL protection for
data in transit
13. 13
Amazon RDS is easy to monitor with
Amazon CloudWatch CloudWatch RDS Metrics
CPU utilization
Storage
Memory
Swap usage
DB connections
I/O (read and write)
Latency (read and write)
Throughput (read and write)
Replica lag
Many more
CloudWatch Alarms
Similar to on-premises custom
monitoring tools
14. Amazon RDS is cost-effective
Monthly
bill = GB+
Assumes DB instance accessed only from Amazon EC2
Further details at http://aws.amazon.com/rds/pricing/
= 720 hrs * $0.35 + 100 GB * $0.115
= $263.50
db.m4.xlarge; MySQL; N.
Virginia; Single-AZ;
On-Demand
100 GB
General Purpose
(SSD)
4 vCPUs;
16 GiB
RAM
• Pay only for what you use; no minimum charge
Example:
15. Save money with Amazon RDS Reserved Instances
• Pay a low up-front fee to get a lower hourly price on
database instances for a 1- or 3-year term
• Your lower Reserved Instance price applies to any
running instance matching the description you specified
at purchase time
Start saving here
Cumulative spend
Month 1 Month 2 Month 3 Month 4 Month 5 Month 6 Month 7 Month 8 Month 9 Month 10 Month 11 Month 12
On-Demand 263.50 527.00 790.50 1,054.00 1,317.50 1,581.00 1,844.50 2,108.00 2,371.50 2,635.00 2,898.50 3,162.00
1-Yr RI 1,777.50 1,789.00 1,800.50 1,812.00 1,823.50 1,835.00 1,846.50 1,858.00 1,869.50 1,881.00 1,892.50 1,904.00
16. How Amazon RDS backups work
Automated backups
• Restore your database to a
point in time
• Enabled by default
• Choose a retention period, up
to 35 days
Manual snapshots
• Build a new database instance
from a snapshot when needed
• Initiated by you
• Persist until you delete them
• Stored in Amazon S3
17. Choose cross-region snapshot copy for even greater
durability, ease of migration
• Copy a database
snapshot to a
different AWS Region
• Warm standby for
disaster recovery
• Or use it as a base
for migration to a
different region
18. Easily migrate to Amazon RDS
• AWS Schema Conversion Tool
• Move schema to new DB
• Convert schema to new DB platform
• AWS Database Migration Service
• Homogenous (A to A)
• Heterogeneous (A to B)
More info: http://aws.amazon.com/dms/
19. Why should I use RDS?
Let AWS handle these
So you can focus on these
Migration
Backup and recovery
Configuration
Patching
Software upgrades
Storage upgrades
Server upgrades
Hardware issues
Database schema
Query design
Query optimization
21. MySQL-compatible relational database
Performance and availability of
commercial databases
Simplicity and cost-effectiveness of
open source databases
Delivered as a managed service
What is Amazon Aurora?
22. Re-imagined for the cloud
Architected for the cloud—that is, we
moved the logging and storage layer into a
multitenant, scale-out database-optimized
storage service
Leverages existing AWS services: Amazon
EC2, Amazon VPC, Amazon DynamoDB,
Amazon SWF, and Amazon S3
Maintains compatibility with MySQL—
customers can migrate their MySQL
applications as-is and use all MySQL tools
Control PlaneData Plane
Amazon
DynamoDB
Amazon
SWF
Amazon Route 53
Logging + Storage
SQL
Transactions
Caching
Amazon S3
1
2
3
23. WRITE PERFORMANCE READ PERFORMANCE
MySQL SysBench results
R3.8XL: 32 cores / 244 GB RAM
5X faster than RDS MySQL 5.6 and 5.7
Five times higher throughput than stock MySQL
based on industry standard benchmarks.
0
25,000
50,000
75,000
100,000
125,000
150,000
0
100,000
200,000
300,000
400,000
500,000
600,000
700,000
Aurora MySQL 5.6 MySQL 5.7
24. WRITE PERFORMANCE READ PERFORMANCE
Scaling with instance sizes
Aurora scales with instance size for both read and write.
Aurora MySQL 5.6 MySQL 5.7
26. Do fewer I/Os
Minimize network packets
Cache prior results
Offload the database engine
DO LESS WORK
Process asynchronously
Reduce latency path
Use lock-free data structures
Batch operations together
BE MORE EFFICIENT
How did we achieve this?
DATABASES ARE ALL ABOUT I/O
NETWORK-ATTACHED STORAGE IS ALL ABOUT PACKETS/SECOND
HIGH-THROUGHPUT PROCESSING DOES NOT ALLOW CONTEXT SWITCHES
27. I/O traffic in MySQL
BINLOG DATA DOUBLE-WRITELOG FRM FILES
T Y P E O F W R IT E
MYSQL WITH REPLICA
EBS mirrorEBS mirror
AZ 1 AZ 2
Amazon S3
EBS
Amazon Elastic
Block Store (EBS)
Primary
Instance
Replica
Instance
1
2
3
4
5
Issue write to EBS—EBS issues to mirror, ack when both done
Stage write to standby instance through DRBD
Issue write to EBS on standby instance
I/O FLOW
Steps 1, 3, 5 are sequential and synchronous
This amplifies both latency and jitter
Many types of writes for each user operation
Have to write data blocks twice to avoid torn writes
OBSERVATIONS
780 K transactions
7,388 K I/Os per million txns (excludes mirroring, standby)
Average 7.4 I/Os per transaction
PERFORMANCE
30 minute SysBench write-only workload, 100 GB dataset, RDS Multi-AZ, 30 K PIOPS
28. IO traffic in Aurora
AZ 1 AZ 3
Primary
Instance
Amazon S3
AZ 2
Replica
Instance
AMAZON AURORA
ASYNC
4/6 QUORUM
DISTRIBUTED
WRITES
BINLOG DATA DOUBLE-WRITELOG FRM FILES
T Y P E O F W R IT E
IO FLOW
Only write redo log records; all steps asynchronous
No data block writes (checkpoint, cache replacement)
6X more log writes, but 9X less network traffic
Tolerant of network and storage outlier latency
OBSERVATIONS
27,378 K transactions 35X MORE
950 K I/Os per 1M txns (6X amplification) 7.7X LESS
PERFORMANCE
Boxcar redo log records—fully ordered by LSN
Shuffle to appropriate segments—partially ordered
Boxcar to storage nodes and issue writesReplica
Instance
29. “In RDS MySQL, we saw replica lag spike to almost 12 minutes, which
is almost absurd from an application’s perspective. The maximum
read replica lag across 4 replicas never exceeded beyond 20 ms.”
Real-life data—read replica latency
30. I/O traffic in Aurora Replicas
PAGE CACHE
UPDATE
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
Logical: Ship SQL statements to replica
Write workload similar on both instances
Independent storage
Can result in data drift between master and replica
Physical: ship redo from master to replica
Replica shares storage; no writes performed
Cached pages have redo applied
Advance read view when all commits seen
MYSQL READ SCALING AMAZON AURORA READ SCALING
32. Storage durability
Storage volume automatically grows up to 64 TB
Quorum system for read/write; latency tolerant
Peer to peer gossip replication to fill in holes
Continuous backup to S3 (built for 11 9s durability)
Continuous monitoring of nodes and disks for repair
10 GB segments as unit of repair or hotspot rebalance
Quorum membership changes do not stall writes
AZ 1 AZ 2 AZ 3
Amazon S3
33. Six copies across three Availability Zones
4 out 6 write quorum; 3 out of 6 read quorum
Peer-to-peer replication for repairs
Volume striped across hundreds of storage nodes
SQL
Transaction
AZ 1 AZ 2 AZ 3
Caching
SQL
Transaction
AZ 1 AZ 2 AZ 3
Caching
Read and write availabilityRead availability
Fault-tolerant storage
34. Survivable caches
We moved the cache out of the
database process
Cache remains warm in the event of
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
35. Aurora Replicas are failover targets
Aurora cluster contains primary node
and up to 15 secondary nodes
Failing database nodes are
automatically detected and replaced
Failing database processes are
automatically detected and recycled
Secondary nodes automatically
promoted on persistent outage, no
single point of failure
Customer application can scale out
read traffic across secondary nodes
AZ 1 AZ 3AZ 2
Primary
Node
Primary
Node
Primary
Node
Primary
Node
Primary
Node
Secondary
Node
Primary
Node
Primary
Node
Secondary
Node
Customer specifiable failover order
Read balancing across Aurora Replicas
36. ALTER SYSTEM CRASH [{INSTANCE | DISPATCHER | NODE}]
ALTER SYSTEM SIMULATE percent_failure DISK failure_type IN
[DISK index | NODE index] FOR INTERVAL interval
ALTER SYSTEM SIMULATE percent_failure NETWORK failure_type
[TO {ALL | read_replica | availability_zone}] FOR INTERVAL interval
Simulate failures using SQL
To cause the failure of a component at the database node:
To simulate the failure of disks:
To simulate the failure of networking:
38. Well-established MySQL ecosystem
Business Intelligence Data Integration Query and Monitoring SI and Consulting
Source: Amazon
“We ran our compatibility test suites against Amazon Aurora and everything
just worked." —Dan Jewett, Vice President of Product Management at Tableau
41. Why Aurora?
• Architected for 99.99% availability
• Enterprise performance (5x) at 1/10 the cost
• Compatible with MySQL 5.6
• Automatically grows storage as needed, up to 64 TB
• Easy migration from MySQL
• Up to 15 Aurora Replicas in a region
• Cross-region replication
• Encryption in-transit and at rest
• Continuous backup to S3 (11 9’s data durability)
• Fully managed
42. Recent feature releases for Amazon RDS
May 18, 2016 Amazon Aurora now supports sharing database snapshots across accounts
May 6, 2016 Deploy Siebel CRM applications on Amazon RDS for Oracle
May 4, 2016 RDS Enhanced Monitoring is now available in South America (Sao Paulo) and China (Beijing)
April 27, 2016 MariaDB audit plug-in now available for RDS MySQL and MariaDB
April 26, 2016 Amazon RDS MySQL now supports point-and-click upgrade from MySQL 5.6 to 5.7
April 22, 2016 Enhanced Monitoring is now available for Amazon RDS for SQL Server
April 8, 2016 Amazon RDS for PostgreSQL now supports version 9.5 with minor version 9.5.2, and minor versions 9.4.7 and 9.3.12
April 1, 2016 Cluster view for Amazon Aurora in RDS console
April 1, 2016 Amazon RDS now supports January PSU patches, improved custom Oracle directories and read privileges support
Detailed listing available here: http://aws.amazon.com/rds/whats-new/
43. Try Amazon RDS for free
• For your first year, at no charge…
• 750 free instance-hours allow you to run a micro database
instance continuously
• 20 GB of database instance storage
• 20 GB for automated backups
• 10,000 I/Os
• Learn more about the AWS free
tier: http://aws.amazon.com/free/
Show of hands:
How many people are familiar with Amazon RDS?
How many people have used one of the RDS database platforms?
A database instance is a virtual database server in the cloud,with the compute and storage resources you specify. You can create and delete DB Instances, define/refine infrastructure attributes of your DB Instance(s), and control access and security via the AWS Management Console, Amazon RDS APIs, and Command Line Tools. You can run one or more DB Instances, and each DB Instance can support one or more databases or database schemas, depending on engine type.
DB Instances are simple to create, using either the AWS Management Console, Amazon RDS APIs, or Command Line Tools. To launch a DB Instance using the AWS Management Console, click "RDS," then the "Launch a DB Instance" button on the "Amazon RDS" tab. From there, you can specify the fundamental parameters for your DB instance:
DB engine: MySQL, Oracle, Microsoft SQL Server, PostgreSQL (and, now in preview, Amazon Aurora)
DB engine version (optional)
License Model (optional)
DB Instance type
Amount of allocated storage (in GB)
Whether your DB Instance should run as a Multi-AZ deployment
Storage type
DB Instance identifier
Master user name
Master user password
You also have the ability to change your DB Instance’s backup retention policy, preferred backup window, and scheduled maintenance window. Alternatively, you can create your DB Instance using the CreateDBInstance API or rds-create-db-instance command.
The automated backup feature of Amazon RDS enables point-in-time recovery of your DB Instance. You can initiate a point-in-time restore and specify any second during your retention period, up to the Latest Restorable Time.
Amazon RDS provides backup storage up to 100% of your provisioned database storage at no additional charge. For example, if you have 10GB-months of provisioned database storage, we will provide up to 10GB-months of backup storage at no additional charge.
Amazon RDS allows you to control if and when the relational database software powering your DB Instance is upgraded to new versions supported by Amazon RDS. This provides you with the flexibility to maintain compatibility with specific engine versions, test new versions with your application before deploying in production, and perform version upgrades on your own terms and timelines.
We’ll explain Multi-AZ on the next slide.
In this simple application stack, an application running in an Amazon EC2 instance is supported by a master database running in an Amazon RDS database instance. It is a best practice to present an application out to its consumers behind an Elastic Load Balancer, so that compute resiliency and scaling features such as Auto Scaling and ELB groups can be adopted in the future.
Amazon RDS Multi-AZ deployments provide enhanced availability and durability for Database (DB) Instances, making them a natural fit for production database workloads. When you provision a Multi-AZ DB Instance, Amazon RDS automatically creates a primary DB Instance and synchronously replicates the data to a standby instance in a different Availability Zone (AZ). Each AZ runs on its own physically distinct, independent infrastructure, and is engineered to be highly reliable. In case of an infrastructure failure (for example, instance hardware failure, storage failure, or network disruption), Amazon RDS performs an automatic failover to the standby, so that you can resume database operations as soon as the failover is complete. Since the endpoint for your DB Instance remains the same after a failover, your application can resume database operation without the need for manual administrative intervention.
Multi-AZ is available for all RDS engines.
Because Multi-AZ minimizes the downtime impact of scheduled maintenance, it gives value even to deployments in which the app servers are in a single AZ. But it’s still best to have the instances spread across multiple AZs.
This application stack employs AWS reliability and durability features. An ELB group of Amazon EC2 instances supports the application logic. The instances use a Multi-AZ Amazon RDS deployment. In the event of infrastructure failure, the database fails over to a standby instance. The application logic retries its database connections, to the same endpoint as before, and service resumes using the new master. Meanwhile, a new standby is instantiated.
In addition to Amazon RDS’s automatic backups, the database snapshot feature is employed to ensure that backups are durably retained. You can create a new database instance from a database snapshot whenever you desire.
Amazon RDS General Purpose (SSD) Storage is suitable for a broad range of database workloads that have moderate I/O requirements. With the baseline of 3 IOPS/GB and ability to burst up to 3,000 IOPS, this storage option provides predictable performance to meet the needs of most applications.
Amazon RDS Provisioned IOPS (SSD) Storage is an SSD-backed storage option designed to deliver fast, predictable, and consistent I/O performance. With Amazon RDS Provisioned IOPS (SSD) Storage, you specify an IOPS rate when creating a DB Instance, and Amazon RDS provisions that IOPS rate for the lifetime of the DB Instance. Amazon RDS Provisioned IOPS (SSD) Storage is optimized for I/O-intensive, transactional (OLTP) database workloads.
Formerly known as Standard storage, Amazon RDS Magnetic Storage is useful for small database workloads where data is accessed less frequently.
Choose the storage type most suited for your workload.
High-performance OLTP workloads: Amazon RDS Provisioned IOPS (SSD) Storage
Database workloads with moderate I/O requirements: Amazon RDS General Purpose (SSD) Storage
Small database workloads with infrequent I/O: Amazon RDS Magnetic Storage
The computation and memory capacity of a DB instance is determined by its DB instance class. You can change the CPU and memory available to a DB instance by changing its DB instance class; to change the DB instance class, you must modify the DB instance.
Here are the DB instance classes available through Amazon RDS:
Micro instances (db.t1.micro): An instance sufficient for testing but should not be used for production applications.
Standard - Current Generation (m3): Second generation instances that provide more computing capacity than the first generation db.m1 instance classes at a lower price.
Memory Optimized - Current Generation (db.r3): Second generation instances that provide memory optimization and more computing capacity than the first generation db.m2 instance classes at a lower price.
Burst Capable - Current Generation (db.t2): Instances that provide baseline performance level with the ability to burst to full CPU usage.
You can change from one database instance type to another. There will be a brief availability event during the changeover.
You can increase the amount of storage available to your database instance on demand for the MySQL, Oracle, and PostgreSQL database engines. This change is performed online, without an availability impact. Amazon Aurora automatically grows the database size on demand.
Encryption at rest is available with certain engines. SSL support for database connections is available with Amazon RDS for MySQL, PostgreSQL, SQL Server, and Amazon Aurora.
Amazon CloudWatch is a monitoring service for AWS cloud resources and the applications you run on AWS. You can use Amazon CloudWatch to collect and track metrics, collect and monitor log files, and set alarms. The system-wide visibility into resource utilization, application performance, and operational health that Amazon CloudWatch provides can help you keep your applications running smoothly.
This bill illustrates an example monthly bill for an Amazon RDS instance. (For the sake of simplicity, we’ll treat a month as 720 hours). The bill has two major components: the price for the hours during which the RDS instance ran, and the storage for that instance. An On-Demand m4.xlarge instance, running MySQL in the US East (N. Virginia) region, costs $0.35 per hour. General Purpose (SSD) storage costs $0.115 per gigabyte per month. The total monthly bill works out to $263.50. Further savings are available with Reserved Instances.
Amazon RDS Reserved Instances give you the option to make a low, one-time payment for each DB instance you want to reserve and in turn receive a significant discount on the hourly charge for that instance. The example, which compares the cumulative expenditure for an RDS instance purchased On-Demand versus through a 1-Year Heavy Utilization Reserved Instance, demonstrates that the break-even point is well in advance of the expiration of the term.
Reserved instances are keyed to DB instance class, DB engine, and the choice of Single-AZ vs. Multi-AZ. When you have purchased a reserved instance in an AWS account, the lower hourly rate applies to a database instance running under that account that matches that description.
Heavy RIs are appropriate for production database workloads.
When automated backups are turned on for your DB Instance, Amazon RDS automatically performs a full daily snapshot of your data (during your preferred backup window) and captures transaction logs (as updates to your DB Instance are made). When you initiate a point-in-time recovery, transaction logs are applied to the most appropriate daily backup in order to restore your DB Instance to the specific time you requested. Amazon RDS retains backups of a DB Instance for a limited, user-specified period of time called the retention period, which by default is one day but can be set to up to thirty five days.
Manual database snapshots are user-initiated and enable you to back up your DB Instance in a known state as frequently as you wish, and then restore to that specific state at any time. DB Snapshots can be created with the AWS Management Console or CreateDBSnapshot API and are kept until you explicitly delete them with the Console or DeleteDBSnapshot API.
Manual database snapshots are kept in Amazon Simple Storage Service (Amazon S3). Amazon S3 is designed for 99.999999999% durability.
Cross region snapshot copy is available for all Amazon RDS engines. You can copy snapshots of any size. Copies can be moved between any of the public AWS regions, and you can copy the same snapshot to multiple Regions simultaneously by initiating more than one transfer. There is no charge for the copy operation itself; you pay only for the data transfer out of the source region and for the data storage in the destination region.