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Steve LoughranJulio GuijarroHP Laboratories, Bristol, UK
November 2008
Farms, Fabrics and Clouds
[email protected]@hpl.hp.com
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Researcher at HP LaboratoriesArea of interest: DeploymentAuthor of Ant in Action
Steve Loughran
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Julio Guijarro
Researcher at HP Laboratories
Area of interest: Deployment
In charge of OSS release
http://smartfrog.org/
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• How to host big applications across distributed resources– Automatically– Repeatably– Dynamically– Correctly– Securely
• How to manage them from installation to removal
• How to make dynamically allocated servers useful
Our research - see smartfrog.org
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Who had breakfast this morning?
Question
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Who harvested wheat or corn, or killed an animal
for that breakfast?
Question
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Farms provide food.
It is somebody else's problem
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Who is wearing clothes they wove or knitted themselves?
Question
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Provisioning of clothing -fabrics- is outsourced
It is somebody else's problem
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Future applications are on the Web
• Web Browser, AJAX clients
• Richer: Flash, XUL, Silverlight
• "… as a Service "
⇒Lots of code running in the server
⇒Unpredictable demand
⇒Data mining/analysis problems
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Old world installation: single server
Single web server,Single DBRAID filestore
-SPOF-limitations of scale
firewall/router
Application serverDatabase
Database server
Application server
firewall/router
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yesterday: clustering
Multiple web servers,Replicated DBRAID Network filestoreLoad-balancing router
-Cost-Complexity-Limitations of scale
replication protocol
Application servers
firewall/router
DB Master DB Slave
Maintains the illusion of a single server
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Now: server farms
500 web servers,Distributed filestoreRented storage & CPU
Scales upNo capital outlayAgile infrastructure
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Tomorrow? grid fabric. 50000 servers
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Application architectures and deployment problems change radically in this world
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Application architectures
September 2008
IE
Your friends arehaving more funthan you
Mozilla
Your friendsare havingmore funthan you
Chrome
Your friendsare havingmore funthan you
iPhone
You are havingmore fun thanyourfriends
Scatter/gather?Message Queue?
Tuple Space?
Diskless frontend
MemcachedJSP?PHP?
Cloud Layer
HDFSHBase
MapReduceDLucene
Ops View
92% servers upNetwork OKCost: $200/hour
Management view
David Hasslehof isvery popular today
Affiliate View
David Hasslehofkeywords costmore today
Cloud Owner View
Customer #17 isusing lots of diskspace. NormalHDD failure rate
Developer View
MR job 17 completed.
REST APIs
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Application architectures
• ROA/REST• Virtualized• MapReduce• Shards• Tuple-spaces• XMPP
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Virtualization
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Why?
• Save on hardware (and power, space)• Dynamically move running servers• Demand creation of new images• Testing complex system configurations• Redistributing entire machine image• 'virtual appliance'
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Assumptions that are now invalid
• Systems have a long lifespan• It is slow/expensive to create a new system• It is expensive to duplicate one• Systems can/should be managed by hand• Clocks proceed at the same rate• Physical RAM doesn’t get swapped out• Running machines can't be moved/cloned• Virtualization is only for testing.
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Server Farms
http://www.linuxjournal.com/
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Assumptions that are now invalid
• System failure is an unusual event• 100% availability can be achieved• Data is always near the server• You need physical access to the servers• Databases are the best form of storage• You need millions of $/£/€ to play
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Who has the servers?
• Yahoo!, Google, MSN, Amazon, eBay: services• MMORPG Game Vendors:
World of Warcraft, Second Life• EU Grid: Scientists• HP, IBM, Sun: rent to companies (some resold)
-focus on CPU performance for enterprise• Amazon: rent to anyone with an Amazon account
-focus on startups
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Amazon EC2
• Pay as you go Virtual Machine Hosting• No persistent storage other than S3 filestore -
uses HTTP GET/PUT/DELETE operations• $0.10 per CPU/hour• Resold OS images for more
(RedHat, Windows)• Rent static IP addresses for failover/balancing• New: RAID-like storage
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Host
Amazon EC2
S3 Storage
AMI
(Xen VM)
AMI
(Xen VM)
/mnt
Host
AMI
(Xen VM)
AMI
(Xen VM)
Public Internet
/mnt /mnt /mnt
Fast (free) network
free access; slow initial read time pay per GET; per megabyte
$
$$$$
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Demo
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EC2 Limitations
• Can't talk to peers using public IP addresses• Persistent file system is a premium extra• Most addresses are dynamic• No managed redundancy/restart• No multicast IP• No movement of VMs off high-traffic racks
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Amazon S3
• Multiple geo-located data storage• No limits on size• Cost of write is high (guarantee of written remotely)• Read is cheap; may be out of date• Cost: Low
S3 is a global file system that any project can afford
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Amazon S3 Charges
Storage $0.15/GB/month
Upload $0.10 per GB - all data transfer in
Download$0.18 per GB - first 10 TB / month data transfer out$0.16 per GB - next 40 TB / month data transfer out$0.13 per GB - data transfer out / month over 50 TB
Requests$0.01 per 1,000 PUT or LIST$0.01 per 10,000 GET or HEAD $0 DELETE
•S3 sets the limit on costs for reliable data storage over the network
•For Amazon, indexing and writes are the big costs…small files are the enemy
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MapReduce
Commodity data processing for commodity data
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Assumptions that are now invalid
• Terabyte datasets are hard to work with• Code runs on a single machine• Sequential code is better than parallel code• RAID hardware is the best way to store data• Databases are better than filesystems• Low-value data isn't worth collecting
even if you don't have a use for it now
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Shards
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Assumptions that are now invalid
• A single farm needs to scale to infinity• You need to provide 100% availability to 100%
of users• You have to roll out simultaneous updates to
the application, changes to the DB schema, globally
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XMPP
post extends GoogleChatClientWorkflow {
to "[email protected]";
login "smartfrog.two";
password xmpp.password;
message "hello, world";
}
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Assumptions that are now invalid
• You can't send message to a laptop that moves around behind a firewall.
• You need to build your own monitoring infrastructure.
• Blocking RPC is a good metaphor for long-haul communications.
• You can't send messages to your server farm from your phone
• IT doesn't have their eyes on your protocol
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Problems for us farmers
• Power management• Predictive disk failure management• Load balancing for availability, power • File management• Billing• Routing• Security/Isolation• How will this change server hardware?• Managing/Configuring Machine Images• Diagnostics when things go wrong
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“Agile” Routers
• Handle hundreds to thousands of (concurrent) change requests/second
• Integrate with billing• Managed throttling to specific hosts• Propagation of state to peer rooters• 'agile' DHCP -short leases; mobile• Monitored bandwidth may trigger VM migration
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“Agile” Operating Systems
• Design for VM-only use• Limited functionality• Limited lifespan• Fully configurable before initial boot• Adapt to changes in surrounding environment• Viable licensing model