Designing for on-demand capacity: cloudbursting in .NET

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Designing for on-demand capacity: cloudbursting
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or a loop in a background thread). It continuously watches for the number of incoming requests (user sessions, perhaps) to be processed. Should it become obvious that your processing capacities aren t enough to keep up with the demand, it will issue requests to the cloud-computing API to deploy new virtual machines (Amazon EC2 already has such a REST-based API available; Windows Azure and others will follow suit). Each virtual machine usually comes preconfigured with a worker role. This preconfiguration can be done by
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Deploying an application or scripts to the cloud (if this cloud service is a PaaS provider, such as Google App Engine or Windows Azure) Uploading a preconfigured VM image (if the cloud is an IaaS provider, such as Amazon EC2)
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When this worker boots up in the cloud, it only needs the addresses of the task and result queues to start processing jobs. These parameters are usually passed as arguments along with the deployment calls. To let the cloud workers access these queues in a secure way, you need to expose them via some encrypted service API, implemented in a flavor of communication framework of your choice (such as Amazon SQS). When the Manager detects that you no longer need the same processing power from the cloud, it shuts down these workers, again providing you the cloud benefit of only paying for what you use.
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A cloudbursting appliance
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Nothing yet exists that meets the general need for cloudbursting, but it soon will. The idea would be to have a virtualized server environment that runs in your data center that builds virtual machine instances compatible with the cloud provider of choice. When the local environment is taxed to its limits, the next virtual machine instances are created by the same appliance up on the cloud, and the appliance handles all data-center-to-cloud communication transparently. Local users never know the application had to expand out to the cloud. Note that the IBM cloudbursting appliance isn t this. It s useful only for building private clouds and wasn t appropriately named.
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Cloudbursting: calling out for standards
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Provisioning instances in Amazon EC2 is relatively easy; moving live workloads across a wide area network isn t. In most modern dynamic applications, the idea of having a hot cloud standby or a prebuilt virtual machine waiting in the wings would solve a lot of problems. But in reality, a number of complexities need to be overcome. These complexities range from network optimization to secure data transfer and replication to load-balancing across geographically diverse hosting environments, to name a few.
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Designing and architecting for cloud scale
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Case study: USA.gov
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USA.gov, one of the busiest U.S. government websites, has achieved significant cost savings by embracing cloud computing. The U.S. General Services Administration (GSA) has migrated all the core resources of the USA.gov web portal to Terremark s IaaS platform, The Enterprise Cloud. By cloudbursting to The Enterprise Cloud, USA.gov can maintain a small persistent footprint and deploy on-demand scaling as traffic fluctuates. GSA said this migration to the cloud has brought about a number of benefits and savings, such as avoiding idle server costs while still accommodating huge traffic spikes, acting on users requests in real time, and applying security constraints on this platform. With infrastructure flexibility at the foundation, GSA has found both cost savings and capability improvement with its new cloud platform.
The data-access problem with cloudbursting
Cloudbursting promises to maximize agility while minimizing cost, but there s the nagging question of what exactly to do about the data such distributed applications require or generate. The original data-center-resident version of this application probably never envisioned that it might expand to the cloud; but when it does, where does it get its input data, and where should it store its output data (In the Eventseer case study, the company addressed this head-on by having all interactions with the cloud extension of the data center in batch mode see case 4 in the following subsections.) Let s look at several strategies for dealing with cloudburst data. The following are five scenarios as described by Joe Weinman of AT&T Business Solutions. One of them may fit both your application s requirements and your enterprise s overall business model.
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