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AWS Architecture Center

AWS Architecture Center
The AWS Architecture Center is designed to provide you with the necessary guidance and best practices to build highly scalable and reliable applications in the AWS Cloud. These resources will help you understand the AWS platform, its services and features, and will provide architectural guidance for design and implementation of systems that run on the AWS infrastructure. Amazon Web Services provides a comprehensive set of services and tools for deploying Microsoft Windows-based workloads on its reliable and secure cloud infrastructure. The flexibility of AWS allows you to design your application architectures the way you like. The cloud reinforces some old concepts of building highly scalable Internet architectures and introduces some new concepts that entirely change the way applications are built and deployed. In the event of a disaster, you can quickly launch resources in Amazon Web Services (AWS) to ensure business continuity.

Amazon Web Services Blog wsdemo/results.md at results-v1 · ericmoritz/wsdemo Diving into OpenStack Network Architecture - Part 1 (Ronen Kofman's Blog) OpenStack networking has very powerful capabilities but at the same time it is quite complicated. In this blog series we will review an existing OpenStack setup using the Oracle OpenStack Tech Preview and explain the different network components through use cases and examples. The goal is to show how the different pieces come together and provide a bigger picture view of the network architecture in OpenStack. This can be very helpful to users making their first steps in OpenStack or anyone wishes to understand how networking works in this environment. We will go through the basics first and build the examples as we go. According to the recent Icehouse user survey and the one before it, Neutron with Open vSwitch plug-in is the most widely used network setup both in production and in POCs (in terms of number of customers) and so in this blog series we will analyze this specific OpenStack networking setup. # ovs-vsctl show 7ec51567-ab42-49e8-906d-b854309c9edf Bridge br-int Port br-int tag: 1

Using Amazon DynamoDB Object Mapping (OM) with the AWS SDK for Android : Articles & Tutorials Version 2 of the AWS Mobile SDK This article and sample apply to Version 1 of the AWS Mobile SDK. If you are building new apps, we recommend you use Version 2. For details, please visit the AWS Mobile SDK page. Amazon DynamoDB is a fast, highly scalable, highly available, cost-effective, non-relational database service. The AWS SDK for Android supports Amazon DynamoDB, and this article discusses a new AWS SDK for Android add-on library that enables you to map your client-side classes to the Amazon DynamoDB tables. The complete sample code and project files are included in the AWS SDK for Android. Overview In Amazon DynamoDB, a database is a collection of tables. The app demonstrates how to add, modify, and remove users, and retrieve their preference data using Amazon DynamoDB OM. Creating an Amazon DynamoDB Client and Mapper To make low-level service requests to Amazon DynamoDB, you need to instantiate an Amazon DynamoDB client. Defining Mapping Class Creating Users (Item Creation)

Srinath's Blog :My views of the World: List of Known Scalable Architecture Templates - (Current Session: Current) For most Architects, "Scale" is the most illusive aspect of software architectures. Not surprisingly, it is also one of the most sort-out goals of todays software design. However, computer scientists do not yet know of a single architecture that can scale for all scenarios. We learn art by learning masterpieces, and scale should not be different! LB (Load Balancers) + Shared nothing Units - This model includes a set of units that does not share anything with each other fronted with a load balancer that routes incoming messages to a unit based on some criteria (round-robin, based on load etc.). However, combining them to create a scalable architecture is not at all trivial undertaking.

The Role of the Cloud Architect Right! And with the movement towards cloud different public cloud providers have different offerings. For example, the product I lead at ATT is called Cloud Architect, and we also offer bare metal computing without a hypervisor. Amazon's public cloud, for example, is built on Xen. So it looks almost like a workload provisioning method, to where now you have an application or you have a large environment and you have to choose. Assuming there's a decision of public cloud, private cloud, hybrid cloud, in that case, it almost seems like there has to be a workload rationalization effort that says, for a big data application, the big data appliance really works well for me. So as infrastructure architects, as you say, we have to up our game.

My Blog: AWS Diagrams Adobe Illustrator Object Collection: First Release Due to popular demand I've decided to release the collection of vector graphics objects I use to draw Amazon Web Services architecture diagrams. This is the first release and more are on the way. This is an Adobe Illustrator CS5 (.AI) file. I've obtained this artwork from the original AWS Architecture PDF files published at the AWS Architecture Center. You can use Adobe Illustrator to open this file and to create your diagrams or you can export these objects to SVG format and use GNU software to work with them. The file has been saved in "PDF Compatibility Mode" so plenty of utilities can import it without the need of using Adobe Illustrator (With Inkscape for instance). Disclaimer: - I provide this content as it is. Download link: And that's it.

The System of Record Approach to Multi-Master Database Applications Multi-master database systems that span sites are an increasingly common requirement in business applications. Yet the way such applications work in practice is not quite what you would think from accounts of NoSQL systems like . In this article I would like to introduce a versatile design pattern for multi-master SQL applications in which individual schemas are updated in a single location only but may have many copies elsewhere both locally as well as on other sites. This pattern is known as a architecture. You can build it with off-the-shelf MySQL and master/slave replication. Let's start by picking a representative software-as-a-service (SaaS) application: call center automation. The ideal solution for most SaaS vendors would be to have call center data and applications for all customers live on multiple sites at all times. This solution has only one problem. What about a SQL DBMS? Fortunately we are not really stuck. The definitive and singular source of operational data.

Japanese Researchers Target HPC Cloud Barriers The National Institute of Advanced Industrial Science and Technology (AIST) has developed a technology to enable users to spin up a virtual HPC cluster on top of any cloud-based infrastructure. The impetus for the project was two-fold: 1. To allow a personalized high-performance computer to be created on-demand 2. In high-performance computing, clustering tools connect many computers so they can run as a single computer, yet often the hardware configuration is not uniform. Using the “Build Once, Run Everywhere” concept, once the environment to run the application has been established it may be run on any cloud, private or public. For this experiment, AIST verified that the technology did indeed operate on both its private cloud, AIST Super Green Cloud (ASGC), as well as the Amazon EC2 infrastructure. “With this technology, users and application fields that could not use high-performance computing previously can now use high-performance computing,” notes AIST.

Using Amazon DynamoDB and Amazon Elastic MapReduce The integration of Amazon Elastic MapReduce (Amazon EMR) with Amazon DynamoDB enables several scenarios. For example, using a Hive cluster launched within Amazon EMR, you can export data to Amazon Simple Storage Service (Amazon S3) or upload it to a Native Hive Table. This walkthrough is presented first in a video and then in step-by-step instructions. You'll learn how to set up a Hive cluster, export DynamoDB data to Amazon S3, upload data to a native Hive table, and execute complex queries for business intelligence reporting or data mining. You can run queries against the data without using a lot of DynamoDB capacity units or interfering with your running application. When you have completed this walkthrough, you will have an Amazon DynamoDB table with sample data, an Amazon S3 bucket with exported data, an EMR job flow, two Apache Hive external tables, and one native Hive table. Setting Up the Environment To set up the walkthrough environment Exporting Data to Amazon S3

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