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®
© 2014 MapR Technologies 1
®
© 2014 MapR Technologies
®
© 2014 MapR Technologies 2
Evolution Beyond Massive Monolithic Systems
•  In monoliths, complexity of mainframe systems led to
specialization
–  Storage
–  DB
–  Systems analysis
–  Programmers
–  Operations
–  Data entry
•  This made n-tier architectures a natural next step
®
© 2014 MapR Technologies 3
3-tier Architecture
Web tier
Middle tier
Data tier
®
© 2014 MapR Technologies 4
3-tier Architecture (essence)
Web tier
Middle tier
Data tier
®
© 2014 MapR Technologies 5
3-tier, in Practice, Multiple Monoliths
Web tier
Middle tier
Data tier
Web tier
Middle tier
Data tier
Web tier
Middle tier
Data tier
Web tier
Middle tier
Data tier
®
© 2014 MapR Technologies 6
3-tier, in Practice, Multiple Monoliths
Web tier
Middle tier
Data tier
Web tier
Middle tier
Data tier
Web tier
Middle tier
Data tier
Web tier
Middle tier
Data tier
®
© 2014 MapR Technologies 7
Summary 1
•  Tiering leads to tic-tac-toe architectures
•  ESB leads to control-heavy balls of string
–  Better than balls of mud, but only just barely
–  Massive amounts of coupling via shared schemas, brittle protocols
•  ESB inverts implementation hiding
•  This isn’t the answer
®
© 2014 MapR Technologies 8
RPC layer
Logic
Disk
RPC layer
Logic
Disk
RPC layer
Logic
Disk
Start with Service Partitioning
®
© 2014 MapR Technologies 9
RPC layer
Logic
Disk
RPC layer
Logic
Disk
RPC layer
Logic
Disk
Start with Service Partitioning
®
© 2014 MapR Technologies 10
RPC layer
Logic
Disk
RPC layer
Logic
Disk
RPC layer
Logic
Disk
Make Services Opaque
®
© 2014 MapR Technologies 11
Give Them a Job, and a Way to Communicate
Keep it very
light-weight!
Coupling minimized by
not knowing details
Flexible protocols
are required
®
© 2014 MapR Technologies 12
This	is	called		
micro-services
®
© 2014 MapR Technologies 13
A	micro-service	is	
	
loosely	coupled	
with	bounded	context
®
© 2014 MapR Technologies 14
But …
•  Much of the discussion talks about RPC (call/response) services
•  This fine, but limiting
•  Key idiom is deferred processing
–  Do something urgently
–  Queue message to complete later
®
© 2014 MapR Technologies 15
For Message Based Services
•  The message receiver may not even be running right now
–  Required by decoupling goal
–  So we need a persistent queue
•  The number of messages is plausibly very high
–  Total number of external requests (x 5-10)
–  Total number of persistence ops (x 2-3)
•  Millions of messages, GB/s of traffic quite plausible
•  Moving this to enterprise from startups adds challenges
®
© 2014 MapR Technologies 16
Summary 2
•  Micro-services requires durable, high-performance message
queues
•  These systems don’t just like durable, high performance queues
•  These systems require durability. And high performance.
•  Old school queues need not apply
®
© 2014 MapR Technologies 17
What	does	this	mean?
®
© 2014 MapR Technologies 18
Real World Implications
•  Messaging must be durable and infrastructural
–  Can’t depend on sender or receiver actually running
•  Messages aren’t great for everything
–  1TB message?
•  We need (scalable) files
•  We need (scalable) tables
•  We need (scalable) streams
•  We still should isolate persistence if possible
®
© 2014 MapR Technologies 19
What is Convergence?
Files
tokyo
Streams
User
profiles
Tables
®
© 2014 MapR Technologies 20
Thank You!
®
© 2014 MapR Technologies 21
Streaming Architecture
by Ted Dunning and Ellen Friedman © 2016 (published by O’Reilly)
http://bit.ly/mapr-ebook-streams
®
© 2014 MapR Technologies 22
Short Books by Ted Dunning & Ellen Friedman
•  Published by O’Reilly in 2014 - 2016
•  For sale from Amazon or O’Reilly
•  Free e-books currently available courtesy of MapR
http://bit.ly/ebook-real-
world-hadoop
http://bit.ly/mapr-tsdb-
ebook
http://bit.ly/ebook-
anomaly
http://bit.ly/
recommendation-
ebook
®
© 2014 MapR Technologies 23
Q&A
@mapr maprtech
tdunning@mapr.tech.com
Engage with us!
MapR
maprtech
mapr-technologies
®
© 2014 MapR Technologies 24
®
© 2014 MapR Technologies 25
Streaming	Example
®
© 2014 MapR Technologies 26
mySQL
mySQL
files
Web-site
Auth
service
Upload
service
Image
extractor
Transcoder
User
profiles
Search
User action
logging
Recommendation
analysis
mySQL
mySQL
mySQL
Oracle
Solr
Elastic
®
© 2014 MapR Technologies 27
mySQL
mySQL
files
Web-site
Auth
service
Upload
service
Image
extractor
Transcoder
User
profiles
Search
User action
logging
Recommendation
analysis
mySQL
mySQL
mySQL
Oracle
Solr
Elastic
®
© 2014 MapR Technologies 28
Upload
service
Image
extractor
Transcoder
Video
metadata
Transition to Micro-service
®
© 2014 MapR Technologies 29
Micro-service Diagram
File upload
web service
Raw
files
Thumbnail
extraction
Transcoding
Video
metadata
Video
files
uploads
thumbs
recodes
Image
files
®
© 2014 MapR Technologies 30
Some Omitted Details
File upload
web service
Files
Thumbnail
extraction
Transcoding
uploads
thumbs
recodes
Files
®
© 2014 MapR Technologies 31
More Omitted details
Thumbnail
extraction
uploads
thumbs
metrics
exceptions
checkpoints
Input
Output
Monitoring
Restart
®
© 2014 MapR Technologies 32
Q&A
@mapr maprtech
tdunning@mapr.tech.com
Engage with us!
MapR
maprtech
mapr-technologies
®
© 2014 MapR Technologies 33
®
© 2014 MapR Technologies 34
Migration	to	Streams
®
© 2014 MapR Technologies 35
Shared
state
Application
Application
Application
Migration from Medieval Architectures
®
© 2014 MapR Technologies 36
Shared
state
Application
Application
Application
Migration from Medieval Architectures
®
© 2014 MapR Technologies 37
Shared
state
Application
Application
Application
events
Private
state
Migration from Medieval Architectures
®
© 2014 MapR Technologies 38
Q&A
@mapr maprtech
tdunning@mapr.tech.com
Engage with us!
MapR
maprtech
mapr-technologies

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HUG_Ireland_Streaming_Ted_Dunning

  • 1. ® © 2014 MapR Technologies 1 ® © 2014 MapR Technologies
  • 2. ® © 2014 MapR Technologies 2 Evolution Beyond Massive Monolithic Systems •  In monoliths, complexity of mainframe systems led to specialization –  Storage –  DB –  Systems analysis –  Programmers –  Operations –  Data entry •  This made n-tier architectures a natural next step
  • 3. ® © 2014 MapR Technologies 3 3-tier Architecture Web tier Middle tier Data tier
  • 4. ® © 2014 MapR Technologies 4 3-tier Architecture (essence) Web tier Middle tier Data tier
  • 5. ® © 2014 MapR Technologies 5 3-tier, in Practice, Multiple Monoliths Web tier Middle tier Data tier Web tier Middle tier Data tier Web tier Middle tier Data tier Web tier Middle tier Data tier
  • 6. ® © 2014 MapR Technologies 6 3-tier, in Practice, Multiple Monoliths Web tier Middle tier Data tier Web tier Middle tier Data tier Web tier Middle tier Data tier Web tier Middle tier Data tier
  • 7. ® © 2014 MapR Technologies 7 Summary 1 •  Tiering leads to tic-tac-toe architectures •  ESB leads to control-heavy balls of string –  Better than balls of mud, but only just barely –  Massive amounts of coupling via shared schemas, brittle protocols •  ESB inverts implementation hiding •  This isn’t the answer
  • 8. ® © 2014 MapR Technologies 8 RPC layer Logic Disk RPC layer Logic Disk RPC layer Logic Disk Start with Service Partitioning
  • 9. ® © 2014 MapR Technologies 9 RPC layer Logic Disk RPC layer Logic Disk RPC layer Logic Disk Start with Service Partitioning
  • 10. ® © 2014 MapR Technologies 10 RPC layer Logic Disk RPC layer Logic Disk RPC layer Logic Disk Make Services Opaque
  • 11. ® © 2014 MapR Technologies 11 Give Them a Job, and a Way to Communicate Keep it very light-weight! Coupling minimized by not knowing details Flexible protocols are required
  • 12. ® © 2014 MapR Technologies 12 This is called micro-services
  • 13. ® © 2014 MapR Technologies 13 A micro-service is loosely coupled with bounded context
  • 14. ® © 2014 MapR Technologies 14 But … •  Much of the discussion talks about RPC (call/response) services •  This fine, but limiting •  Key idiom is deferred processing –  Do something urgently –  Queue message to complete later
  • 15. ® © 2014 MapR Technologies 15 For Message Based Services •  The message receiver may not even be running right now –  Required by decoupling goal –  So we need a persistent queue •  The number of messages is plausibly very high –  Total number of external requests (x 5-10) –  Total number of persistence ops (x 2-3) •  Millions of messages, GB/s of traffic quite plausible •  Moving this to enterprise from startups adds challenges
  • 16. ® © 2014 MapR Technologies 16 Summary 2 •  Micro-services requires durable, high-performance message queues •  These systems don’t just like durable, high performance queues •  These systems require durability. And high performance. •  Old school queues need not apply
  • 17. ® © 2014 MapR Technologies 17 What does this mean?
  • 18. ® © 2014 MapR Technologies 18 Real World Implications •  Messaging must be durable and infrastructural –  Can’t depend on sender or receiver actually running •  Messages aren’t great for everything –  1TB message? •  We need (scalable) files •  We need (scalable) tables •  We need (scalable) streams •  We still should isolate persistence if possible
  • 19. ® © 2014 MapR Technologies 19 What is Convergence? Files tokyo Streams User profiles Tables
  • 20. ® © 2014 MapR Technologies 20 Thank You!
  • 21. ® © 2014 MapR Technologies 21 Streaming Architecture by Ted Dunning and Ellen Friedman © 2016 (published by O’Reilly) http://bit.ly/mapr-ebook-streams
  • 22. ® © 2014 MapR Technologies 22 Short Books by Ted Dunning & Ellen Friedman •  Published by O’Reilly in 2014 - 2016 •  For sale from Amazon or O’Reilly •  Free e-books currently available courtesy of MapR http://bit.ly/ebook-real- world-hadoop http://bit.ly/mapr-tsdb- ebook http://bit.ly/ebook- anomaly http://bit.ly/ recommendation- ebook
  • 23. ® © 2014 MapR Technologies 23 Q&A @mapr maprtech [email protected] Engage with us! MapR maprtech mapr-technologies
  • 24. ® © 2014 MapR Technologies 24
  • 25. ® © 2014 MapR Technologies 25 Streaming Example
  • 26. ® © 2014 MapR Technologies 26 mySQL mySQL files Web-site Auth service Upload service Image extractor Transcoder User profiles Search User action logging Recommendation analysis mySQL mySQL mySQL Oracle Solr Elastic
  • 27. ® © 2014 MapR Technologies 27 mySQL mySQL files Web-site Auth service Upload service Image extractor Transcoder User profiles Search User action logging Recommendation analysis mySQL mySQL mySQL Oracle Solr Elastic
  • 28. ® © 2014 MapR Technologies 28 Upload service Image extractor Transcoder Video metadata Transition to Micro-service
  • 29. ® © 2014 MapR Technologies 29 Micro-service Diagram File upload web service Raw files Thumbnail extraction Transcoding Video metadata Video files uploads thumbs recodes Image files
  • 30. ® © 2014 MapR Technologies 30 Some Omitted Details File upload web service Files Thumbnail extraction Transcoding uploads thumbs recodes Files
  • 31. ® © 2014 MapR Technologies 31 More Omitted details Thumbnail extraction uploads thumbs metrics exceptions checkpoints Input Output Monitoring Restart
  • 32. ® © 2014 MapR Technologies 32 Q&A @mapr maprtech [email protected] Engage with us! MapR maprtech mapr-technologies
  • 33. ® © 2014 MapR Technologies 33
  • 34. ® © 2014 MapR Technologies 34 Migration to Streams
  • 35. ® © 2014 MapR Technologies 35 Shared state Application Application Application Migration from Medieval Architectures
  • 36. ® © 2014 MapR Technologies 36 Shared state Application Application Application Migration from Medieval Architectures
  • 37. ® © 2014 MapR Technologies 37 Shared state Application Application Application events Private state Migration from Medieval Architectures
  • 38. ® © 2014 MapR Technologies 38 Q&A @mapr maprtech [email protected] Engage with us! MapR maprtech mapr-technologies