scalable transactions in the cloud
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CloudSave. CloudTran. Scalable Transactions in the Cloud. Matthew Fowler, NT/e. ?. And the answer is platform for mainstream Java developers to use IMDG for scalable, commercial applications without worry and minimal hassle for commercial advantage It's a lump of middleware - PowerPoint PPT PresentationTRANSCRIPT
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Scalable Transactions in the Cloud
Matthew Fowler, NT/e
CloudTranCloudSave
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?
• And the answer is– platform for mainstream Java developers– to use IMDG– for scalable, commercial applications– without worry and minimal hassle– for commercial advantage
• It's a lump of middleware– built on, adding value to GigaSpaces
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2001
• WebLogic/J2EE specialisation
• One week training course– 4-point architecture for dummies
• Messed-up architecture– revenue down
• Automating server-side applications– J2EE/EJB– Spring/Hibernate
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3-5...5-10...10-20...1,000,000 • Tracy's story: the path of successful apps
– Database– Caching– In-memory Data Grid
• The 50,000 club• Application scale drivers
– Mobile phone growth, iPhone Apps– Micropayments– e-commerce continued growth
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Get an edge with performance
Please wait
“Latency really matters ... 100ms of latency costs
1% in sales.” Amazon
.....................“... almost half of visitors will abandon a site if they perceive a page or feature
takes longer than 2 seconds to load. ”
GetElastic
“An extra 0.5 seconds in
search page generation time
dropped traffic by 20%.” Google
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6.5m, x10yrs, $400bn/yr
• Mainstream Java developers– 6.5m– most have 5-10 years experience– 50 million man-years experience
• Plain old application development market– $400bn/year
• Can they build an IMDG application?– How can IMDG go mainstream?
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Explaining it to your Mom / Boss
IMDG - SOR
Persistent Storage
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Explaining it to a techie
1. System of Record in IMDG. Keep DB for• warehouse apps/BI• sleeping at night.
2. Catching the money:– ACID transactions
– throughput, scalability, bullet-proof reliability – distributed, data + messaging
3. ORM - Object references, not foreign keys.Easy to program. Entity groups for performance.
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In-Memory Data Bases - Are You Crazy?
• What's it worth:– Loss of sales, traffic - 5% vulnerable, saved by
speed of IMDG
• For $100m/year co:– $5m/year revenue for good behaviour– Customer/order/product data - 2million * 16Kb– 8 servers in grid for 32GB live data
• 8 servers isn't a lot• Worth doing the numbers!
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Low Reliability
Complicated Programming
Unintended Consequencesof
Unknowing
Distributed Transactions
Fear and loathing ...
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, 1, 2, 3, ...
• Other alternatives– forget transactions, forget databases
• Dan's the Man
• GoogleApps on V2 last we heard
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How is it possible?
Distributed Cloud Transactions
• Grid connected– Helland's get out clause
• System of Record is in the grid– No voting - 1PC not 2PC
• Commit to backed-up memory• Leverage the GigaSpaces platform
– SBA/Entity Groups, Transactions, SQL Queries, Backups
Redefining the problem
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200/ ... 2,000 ... 20,000/second
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Transactions you can count on
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Transactions you can count on
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Herding Cats - Java Style
• How to distribute data
• How to find it
• How to resolve references – IMDG versus user view: FK ↔ OO
• Atomicity on failure
• Timeouts
• Scalability
• Consistency and isolation
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The 'T' Word
• GigaSpaces Local Transactions
• GigaSpaces Distributed Transactions
• Mirror service– see Cat-Herding 101
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How CloudTran ORM works
Client
TxB
Gridsearch
OL
Data Data
OrderService
Partitioning
(entity groups)
Co
mm
it
Confirm
Con
firm Com
mit
Commit
Datasources
Tx
Messaging
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300 .. 700 .. 900 .. 2,100
• Performance of transaction buffer– Tiny Transactions per second
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Virgin Airways
LastMinute.com
IMDG
In-Cloud Federated Applications
IMDG
CloudTran -Federated
Transaction Buffer
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Scalable transactions in the cloud?
– platform for mainstream Java developers– to use IMDG– for scalable, commercial applications– without worry and minimal hassle– for commercial advantage– GigaSpaces
CloudTran
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End