cap and you
DESCRIPTION
CAP theorem is simple if we all use the same definitions. CAP follows from the requirements for nodes in distributed systems to send and receive messages before responding if the system requires atomic consistency. If the system can't pass messages, it can't be consistent. If consistency is a requirement, then losing messages implies the system cannot respond. These properties apply to any distributed systems.TRANSCRIPT
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Consistency…!Availability…!Messages…!
& You…
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CAP!theorem
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Consistent “…as if every request was executing on a single node, responding to operations one at a time.”
ACID Compliant
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Available “…every request received by a non-failing node
in the system must result in a response.”
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Partition Tolerant “…the network will be allowed to lose arbitrarily many messages sent from one node to another”
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Pick Any Two!?!! It’s complicated…
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Consistent & Partition Tolerant “…it is easy to achieve atomic data and partition
tolerance. The trivial system that ignores all requests meets these requirements.”
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Consistent & Available “If there are no partitions, it is clearly possible to
provide atomic, available data.”
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Available & Partition Tolerant “If there are no consistency requirements, the
service can trivially return v0, the initial value, in response to every request.”
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€
2 ⋅ tmessage + tlocalt-Connected Consistent
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What has been neglected? Latency Failure Computation Durability More™
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Latency Petite Partitions
the little deaths
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When the available consistency exceeds the required availability a choice must be made…
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Raising the question, how are business decisions made?
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What protocols are used to pass messages in your organization?
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Has your organization
chosen consistent, available
or partition tolerant?
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In any human interaction, the required amount of communication is inversely proportional to the level of trust…
@bhorowitz
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Andrew Clay Shafer @littleidea
work on stuff that matters