AI is the buzzword while ML is the underlying component... but when do we use ML? To solve problems that machines can find patterns without explicitly programming them to do so. But do you have a team building an ML model? How far are they from the IT team? Do they know how to deploy and serve that? Testing? And sharing what they have done? That's where a devops mindset comes in: reduce the batch size, continuous-everything and a culture of failure/experimentation are vital for your data team!

1. @thiagoavadore#devopsdays
AI WITH A DEVOPS MINDSET
EXPERIMENTATION, SHARING & EASY ML DEPLOYMENT
THIAGO DE FARIA
HEAD OF SOLUTIONS ENGINEERING @LINKIT

2. @thiagoavadore#devopsdays
▸ Pure Math —> Software Engineer
▸ ❤ 👶 🎸 🎹 %
▸ Anything-Data … I probably done it
▸ DevOps Amsterdam Alumnus

3. @thiagoavadore#devopsdays
GOOGLE AI MAKES PHONE
CALLS??!! CAN YOU DO
SOMETHING LIKE THAT USING
THAT TENSORFLOW STUFF?
USERS WOULD LOVE THAT!
PERSON A, VP OF PRODUCT
The real goal? A great PR

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WAIT… CAN YOU ALSO DO
THAT IN A CONTAINER USING
BLOCKCHAIN?
PERSON B, appointed new VP of product

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WHY DON’T WE CREATE AN AI
DEVOPS CLOUD-NATIVE APP ON
K8S USING BLOCKCHAIN BACKED
BY IOT DEVICES THAT THE USER
WILL EXPERIENCE WITH A VR
HEADSET? A TRULY DISRUPTIVE
DIGITAL TRANSFORMATION!
PERSON C, appointed CEO and master-of-all things
Gets funded and moves to the Bay Area
SERVICE MESH!

6. @thiagoavadore#devopsdays
Fighting the downwards spiral
TIMELESS CONFLICT

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Product
Dev
IT Ops
QA
Infosec

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AI
MAKE COMPUTERS
CAPABLE OF DOING
THINGS THAT WHEN
DONE BY A HUMAN,
WOULD BE THOUGHT
TO REQUIRE
INTELLIGENCE

9. @thiagoavadore#devopsdays
MAKE MACHINES
FIND PATTERNS
WITHOUT EXPLICITLY
PROGRAMMING
THEM TO DO SO
AI
MACHINE
LEARNING

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IF/ELSE, LOOPS & FUNCTIONS
NON-ML DEVELOPMENT

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DATA & HYPERPARAMETERS
ML DEVELOPMENT

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ML LIFECYCLE
DIFFERENT, BUT NOT THAT MUCH…

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15. @thiagoavadore#devopsdays
DATA
PIPELINE
Manual
INGESTION
EXPLORE
CLEAN
FEATURE
ENGINEERING

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DATA
PIPELINE
MODEL DEV
EXPLORE
CLEAN FEATURE
ENGINEERING
TRAIN
TESTTUNE
Manual
INGESTION

17. @thiagoavadore#devopsdays
DATA
PIPELINE
MODEL DEV
EXPLORE
CLEAN
FEATURE
ENGINEERING
TRAIN
TESTTUNE
Automated
INGESTION

18. @thiagoavadore#devopsdays

19. @thiagoavadore#devopsdays
DATA
PIPELINE
MODEL DEV
EXPLORE
CLEAN
FEATURE
ENGINEERING
TRAIN
TESTTUNE
Automated
INGESTION

20. @thiagoavadore#devopsdays
DATA
PIPELINE
MODEL DEVOPERATIONS
EXPLORE
CLEAN
FEATURE
ENGINEERING
TRAIN
TEST
TUNE
PACKAGE
LOGGING
MONITOR
DEPLOY
SERVE
Automated
INGESTION

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PROBLEMS ALONG THE WAY
SURPRISE SURPRISE, CULTURE IS THE BIGGEST ONE…

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▸ Explainability & Ethics
▸ Hard to measure efficacy
▸ Nobody wants to be “on-call”
▸ Local Dev & Data —> Rework

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SILVER BULLET
CULTURE CHANGE.
NEW WAYS OF WORKING.

24. @thiagoavadore#devopsdays
Product
Dev
IT Ops
QA
Infosec
ML Engineer
Data
Scientist

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LOCAL DATA
SCIENCE IS DEAD

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CI/CD FOR ML *MORE THAN IT… CONTINUOUS EVALUATION

27. @thiagoavadore#devopsdays
BIAS, DRIFT &
FRAGILITY

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!DEVOPS MOVEMENT!
!CULTURE CHANGE!
& many others…
COLLABORATION
VERSION - CODE & DATA
EVALUATION
PACKAGING
DEPLOYMENT
MODEL SERVING

29. @thiagoavadore#devopsdays
SPEED
INVISIBLE WORK
COLLABORATION
OBSERVABILITY
CI/CD BECOME CONTINUOS EVALUATION
TRACKING
SERVING
REDUCE WASTE
FAIL CULTURE

30. @thiagoavadore#devopsdays
TOOLS TO HELP…
▸ 2.3 on
▸Cloud-Native ML
▸.
▸.
▸Pachiderm
▸…

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OSS!
DO NOT
REINVENT
THE WHEEL!

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Questions
?
SHAMELESS PLUG…

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DEMO GODS, BE KIND…

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THE AMAZING PICTURES ARE FROM THE
GREAT JD HANCOCK!
PHOTOS.JDHANCOCK.COM