Cloud Don McGregor Research Associate MOVES Institute mcgredo@nps.edu

Cloud

Don McGregor

Research Associate

MOVES Institute

mcgredo@nps.edu

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Data Centers

• What sorts of things go on in a data center?

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Data Center Problems

• “I want to set up a publicly visible web server”

• “I want to have 50 servers working in parallel on my social modeling simulation”

• “I’m a facebook competitor and will start with 500 webservers and 50 databases, then scale up from there”

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Data Centers

• Really old solution: you buy some computers to do this task for your group. Say, ten desktops, crammed into a spare room

• A better solution: there’s a central data center on campus with AC, backup generator, fire suppression, power, access control, etc

• But this involves having your organization buy, rack, set up, and configure N boxes

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Virtual Servers

• A key piece of technology is “virtual machines”. The idea is to have one piece of hardware run multiple operating systems at once

• Often seen with VMWare, Virtual Box, Xen, and others.

• The idea is to run multiple operating systems on one piece of hardware—say, two Linux instances, one windows instance, etc

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One Box, Multiple OSes

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Virtual Machines

• Most modern hardware is hardly taxed most of the time

• We can run multiple operating systems at the same time on one piece of hardware, just like we can run multiple programs at the same time within one OS

• So the idea is to buy racks full of powerful hardware and run multiple VMs on each piece of hardware

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Virtual Machines

• This gives us all sorts of benefits: for example we can migrate a VM from one physical machine to another if we have hardware problems

• Lets us make better use of the hardware• Instead of buying and configuring a new web

server, call the IT department and tell them to spin up a new OS VM on existing hardware

• The virtual machine can be configured in an automated way in a few seconds

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VM Configuration

• Start up an operating system on a virtual machine. But depending on the purpose of the VM, we might want to configure it differently

• Some have web servers, some have databases, some run your simulation, and different software needs to be installed on the VM for each purpose

• It’s not practical to do this by hand• There are tools to configure the VM automatically,

which is important if you want to start new VMs based on load

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Data Centers

• But once you have this capability, you start asking yourself: why am I running a physical data center in the first place? It’s expensive, takes trained people, infrastructure is not cheap, it’s not a core competency for many businesses, and there are economies of scale to building a 10,000 CPU data center

• Companies have sprung up that provide data center services

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Scale Out

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Scale Out

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Cloud Providers

• Amazon Web Services—preferred cloud provider for the Navy– Has approved infrastructure for ITAR issues

• Rackspace• Many providers for games

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Data Center Scale Out

• You can make really big data centers, and make management of devices within those data centers very scalable

• The marginal costs of adding another 100 hosts to a big data center is much smaller than for most small data centers, as is the marginal cost of management

• http://opencompute.org/ for standards on data centers: CPUs, racks, storage, power supplies, etc

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OpenStack

• OpenCompute deals with hardware and datacenter issues

• OpenStack deals with the software side of the house– How to handle multiple images (OS virtual

machines that can be started)– Storage – Networking– Management– Compute

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OpenStack

• Very fast-moving project; major releases every six months

• Most hardcopy documentation is out of date as a result (eg, O’Reilly books, which are usually quite good)

• Supported by Rackspace, compatible with Amazon Web Services (aws)

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Clouds

• Old model: Call IT department, have them spin up a new VM for your web server

• New model: call cloud provider, have them spin up new VM for your web server on their very cheap and scalable data center

• What are we losing here? – Control of data (maybe)– Central point of failure (network, power,

building) (maybe)– Latency (maybe)

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Clouds

• Amazon Elastic Cloud (EC): call them, they spin up a VM for web server

• Call Rackspace, have them spin up 500 Linux compute nodes for two hours to run a cultural sim, along with one Windows node for a month

• You can get sophisticated and have the number of nodes spun up depend on the load: for example, under heavy load you have 200 web servers, then on the weekend dial back to 50 web servers

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Cloud

• Platform as a Service (PaaS): the cloud vendor sells operating system VMs

• Software as a Service (SaaS): the cloud vendor sells an application (calendaring, email, etc.)

• Will your business survive several days of downtime?

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Scalability

• Famously, Zynga used clouds for Farmville. How many people would play Farmville? They didn’t know, and they didn’t want to build a data center themselves

• Outsourced data center, number of hosts they use depends on load; as load goes up, more pre-configured hosts are spun up to handle it

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Business Model Implications

• Old way: come up with idea, code, get VC money, lease space, buy AC, buy boxes, buy network, upgrade plan for boxes …

• New way: Come up with idea, deploy demo on cloud with your credit card. If it works, get VC/angel money. Done.

• Dramatically lower cost of entry

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Private Clouds

• For the cases were you can’t outsource because of concerns about data, you can set up “private clouds”

• Use the same software as the commercial providers, but with a data center your organization controls

• For example, maybe a DoD private cloud, or an NPS private cloud

• Amazon EC does some FIPS (http://aws.amazon.com/federal/)

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Examples

• “I want to run a publicly visible web server”– Call Amazon EC, small web sites free, roughly 5

cents per compute hour after that (depending on lots of options), plus data bandwidth charges

• “I need 500 nodes to do my social modeling compute sim”– Large compute VM at 10 cents per compute

hour

• Compare this to the cost of setting up your own data center

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Implications for M&S?

• If you can do web-based M&S, you can put the back end on the cloud

• Implications for dynamic scaling at short notice

• From a program management standpoint, fewer big projects depending on up-front planning, lower risk