a tale of two technologies
DESCRIPTION
A Tale of Two Technologies. A Story of the IoT “revolution”. It was the age of connectedness. It was the age of disconnectedness. Failure tolerance is not optional. It was the age of wisdom. It was the age of foolishness. It was the epoch of complexity. It was the epoch of simplicity. - PowerPoint PPT PresentationTRANSCRIPT
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A Tale of Two Technologies
A Story of the IoT “revolution”
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It was the age of connectedness
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It was the age of disconnectedness
Failure tolerance is not optional
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It was the age of wisdom
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It was the age of foolishness
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It was the epoch of complexity
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It was the epoch of simplicity
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What is the Internet of Things?
“The Internet of Things (IoT) refers to uniquely identifiable objects and their virtual representations in an Internet-like structure.”-Wikipedia
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No really what is IoT?
● It’s literally the act of connecting “things” to the Internet
● It predates the World Wide Web● It shouldn’t be surprising to anybody
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So IoT is old news?
Most definitely
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So IoT is just hype?
Home security and automation
Fitness trackers
Your (driverless?) car
Medical devicesSensors
Industrial equipment
NO!
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Been there done that.
● DataStax and Cassandra have been dealing with event streams (time series) information at scale for years.
● But Cassandra is relatively dumb storage.● Put data in. Get data out.
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What is Cassandra?
● A massively scalable distributed database● Chooses availability over strong consistency
(yes, that really is a fundamental tradeoff)● With its wide partitions it is able to take
advantage of data locality even at “web scale”
Chocolate!
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What is Spark?
● DAG is a logical superset of M/R● Adopts much of the Hadoop ecosystem,
without being bound by it● Intelligent use of caching (RDDs) for
massive performance gains● Incorporate Streaming to make ingestion-
time processing a first class citizen
Peanut butter!
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What does IoT need from big data?
● Log time-series events -- at scale● Gather meaning from that data -- at scale● Report on that data -- at scale● Take action on that data -- at scale
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Logging events at scale
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Gathering meaning at scale
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Reporting at scale
● Canned reports● Ad-hoc querying and reporting● Drill down / exploratory ● Alerting● Aggregation● Clustering (K-means, et al)● Generalized machine learning
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Take action at scale
● Stateless application servers● Horizontally scaled and co-located with
Cassandra and Spark in each DC● Any platform with a CQL driver
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The architecture...
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Spark to Cassandra
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Cassandra to Spark
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Multi-DC
DC1 DC2
Write anywhere.
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Things that go together
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Things that go together
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A Tale of Two Summits