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Pelican: A building block for exascale cold data storage
Shobana Balarishnan, Richard Black, Austin Donnelly, Paul England, Adam Glass, Dave Harper, Sergey Legtchenko, Aaron Ogus, Eric Peterson, Antony Rowstron Microsoft Research, Microsoft Adapted from their OSDI and SDC slides. EECS 582 – W16
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Background: cold data in the cloud
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Background: cold data in the cloud
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Right-provisioning EECS 582 – W16
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Pelican: rack-scale appliance for cold data
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Prototype EECS 582 – W16
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Impact of right provisioning on resources
x12 x6 EECS 582 – W16 x16
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Data placement: maximizing request concurrency
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Data placement: maximizing request concurrency
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Data placement: maximizing request concurrency
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IO scheduling: “spin up is the new seek”
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Challenges of right-provisioning
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Evaluation FP: full provisioning EECS 582 – W16
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Throughput EECS 582 – W16
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Time to first byte EECS 582 – W16
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Power consumption EECS 582 – W16
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Conclusion Pros and Cons Reduce capital cost and operating cost
Meet requirements from cold data workload Sensitive to hardware changes Manually handle many constraints EECS 582 – W16
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x4 x2 Related Works Amazon Glacier Facebook cold storage datacenter
Two billion photos Maybe right-provisioning idea Blue-ray optical disk x4 x2 EECS 582 – W16
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Q&A Thank You! EECS 582 – W16
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