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Putting the F in FaaS
! @trieloff
⚡⚡⚡
#serverlessconf ! 2017
#serverlessconf! 2016
(glad to be back)
! @adobeio
Opinions are my own
Ideas are not
⚡ Putting the F in FaaS
WTF?
WT !?
F is for Functions
Fundamentally, there
are only two
programming styles:
functional and
dysfunctional.
Functions in FaaS
Stateless
Stateless
Short-lived
Stateless
Short-lived
Single-purpose
Stateless
Short-lived
Single-purpose
Boring
!"
⚡ Serverless Functional
Patterns for the
Aspiring Enterprise
Architect
Fundamentally, there
are only two
architecture styles:
functional and
dysfunctional.
#serverlessconf ! 2017
#serverlessconf ! 2017
(sorry, I missed it)
#serverlessconf ! 2017
(sorry, I missed it)
(but I read all the tweets)
! @timallenwagner
The Serverless Manifesto
1. Functions are the unit of deployment and scaling
2. bla
3. bla
4. bla
5. Never pay for idle
! @yochayk
Applied Serverless Design Patterns
1. Function Chaining
2. ASync HTTP (HTTP 202)
3. Fanout (Parallel)
4. Fanout + Fan-in
5. Long Running Function with Timeout
! @ben11kehoe
What's Missing From
Serverless Providers
Node is the WRONG runtime for serverless
! @ben11kehoe
What's Missing From Serverless Providers
Node is the WRONG
runtime for serverless
! @ben11kehoe
What's Missing From Serverless Providers
Node is the WRONG
runtime for serverless
(because it’s making you do async wrong)
!
!
Greenspun's tenth rule
Any sufficiently complicated C or Fortran program
contains an ad-hoc, informally-specified, bug-ridden,
slow implementation of half of Common Lisp.
tl;dr: LISP did it first
⚡ What LISP can Teach
You About Serverless
Patterns
LISP !" Clojure
map/pmap (a.k.a. Fan-Out)
(map some-function some-data)
Apply some-function to each entry of the array of
data in some-data. Then return the result as a new
array. In parallel: use pmap.
Why? To process lots of data.
apply (a.k.a. Proxy)
(apply some-function x y z)
Call some-function with arguments x, y, and z.
Why? To make the function to be called a variable
itself.
comp (a.k.a. Function Chaining)
(comp some-function some-other-function)
Create a function that first calls some-function on
the arguments, and then some-other-function
on the results.
Why? To call multiple services in order.
reduce (a.k.a. Fan-In)
(reduce some-function some-data)
Call some-function on the first item of some-
data, then call some-function again, using the
result of the prior invocation and the next item in
some-data as arguments.
Why? To compress large data sets into small results.
fold (a.k.a. Fan-In with ! on Top)
(fold reducef combined some-data)
Break some-data into multiple sets, run (reduce
reducef) on each, then run (combine
combinef) on the results.
Why? To compress really large data sets into small
results, in multiple steps.
iterate (a.k.a. Endless Function)
(iterate start-value some-function)
Create a function that creates a data stream starting
with start-value from repeated calls to some-
function.
Why? To turn some-function into a data emitter,
without some-function needing state.
juxt (a.k.a. Parallel Functions)
(juxt some-function some-other-function)
Makes a function that calls some-function and
some-other-function and returns a combined
result.
Why? To combine the results of multiple functions in
one call.
memoize (a.k.a. Good Ol’ Cache)
(memoize some-function)
Return a cached version of some-function that
returns the same value for the same arguments.
Why? To trade slow computing against fast cache
lookups.
partial (a.k.a. Wrapper)
(partial some-function value)
Creates a function that calls some-function with
value as an argument, in addition to other
arguments.
Why? To provide default values and make powerful
functions less dangerous.
That’s all the F you
need
⏰❓
Can my Serverless
Vendor do this?
Probably. You need:
1. A Serverless (FaaS) Runtime
2. An Event Passing System
3. A Document Database with Triggers
! @trieloff

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Putting the F in FaaS: Functional Compositional Patterns in a Serverless World