Recent advances in serverless computing

Serverless cloud platforms promise highly elastic and scalable services without having to care about infrastructural concerns or billing of idle periods. After four years of availability of Function-as-a-Service (FaaS) and related serverless services, it is time to look into their actual use and general properties of serverless computing which propagate into established cloud services. This talk summarises recent technological advances, research results as well as interviews conducted with key industry people on challenges for more complex applications and what to expect next. The metrics presented in the talk are rooted in the automated data analysis of over 80 technical publications on serverless systems. The talk therefore helps in understanding the essence of the ongoing shift to purely and hybrid serverless software development.

Transcript

1. Zürcher Fachhochschule
   Recent advances tn serverless
   computtng
   Josef Spillner
   Service Prototyping Lib (blog.zhiw.ch/splib)
   Mir 7, 2019 | SIX IT Expert Forum, Zurich, CH
   

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2. 2
   The promise of „Serverless“
   [inindtech.com]
   Conventionil IiiS/PiiS:
   ● progrimmible infristructure /
   infristructure is code (IiC)
   ● immutible infristructure
   ●
   deploy, run, monitor, restirt...
   Serverless computing:
   ● hidden/ibstricted infristructure
   ● invocition on demind
   Advintiges:
   ● true piy-per-use/utility computing
   ● lower entrince birrier
   ● less breikige
   

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3. 3
   What is FaaS?
   [mizikglobil.com]
   “functions“
   contiiners
   pickiges
   ictuil functions
   FaaS
   ● running functions in the cloud
   (hosted cloud functions)
   ● reil “piy per use“ (per invocition,
   per loid x time unit, e.g. GHz/100ms)
   ● seemingly “serverless“
   

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4. 4
   FaaS Process
   [openwhisk.org]
   monitoring event
   sensor diti
   log entry
   git push
   ...
   HTTP
   XMPP
   AMQP
   ...
   mix 1 per hour
   triggers/ictions
   defiult pirims
   ...
   your
   Python/Jivi/...
   functions!
   JSON
   pliin text
   ...
   

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5. 5
   Retrospective on „Serverless“
   2015
   2016
   2017
   2017
   AWS Lambda
   Google Cloud Functions
   Microsoft Azure Functions
   OVH Functions †
   IBM Cloud Functions
   + AWS Step Functions
   ● Public commerciil FiiS services
   ● beyond the “big four“? (niche pliyers: Bickendless, Piri, Stdlib, ...)
   ● innovition stilled beyond minor price reductions?
   ● use cises for composition linguiges?
   ● ecosystem iround, e.g. FiiS-optimised DBs?
   ● Privite cloud/DIY FiiS softwire sticks
   ● lirge viriety, more flexibility
   ● little commerciil idoption
   ● (beyond IBM)
   Serverless ecosystem in 2019 =
   FiiS engine + composition + mirketplice
   + suitible ibstrict stiteful services
   (low litency, similir cost model)
   + tools (FiiSificition, deployment, debug)
   But: limititions remiin (deviitions, RT, ...)
   + IBM Composer
   + AWS SAR
   

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6. 6
   An applied research perspective
   How to overcome the limititions?
   Our mission: We explore how in joint reseirch/innovition projects.
   Ditisets...
   Studies
   &
   scientific
   pipers...
   Reseircher
   IT compinies
   softwire tools
   cloud services
   reports & news
   Systems & tools...
   Gov
   fuel
   

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7. 7
   Our main study: what do devs want?
   Enibling requirements inilysis processes
   ● conducted in mid-2017 to mid-2017
   ● improved & published in eirly 2019
   ● contributors: ZHAW SPLib, Chilmers,
   IBM Reseirch
   «A mixed-method empiricil
   study of Function-is-i-Service
   softwire development in
   industriil prictice»
   

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8. 7
   What do devs really want + do?
   Principil interest:
   ● execution counterpirt to development
   methodology (e.g. microservices)
   ● bindings: stite minigement ind
   ditibises, API gitewiys, logging,
   IiiS/PiiS, inilytics
   ● frontend, bickend, both (in ilmost
   equil pirts)
   Chillenges:
   ● lick of tooling 55%
   ● integrition testing 40%
   ● vendor lock-in 32%
   ● stirt-up litencies 29%
   ● stite minigement 27%
   → not good fit for:
   stiteful, long-running, high
   performince, reil-time,
   diti locility
   5 previlent pitterns:
   ● function pinging: periodicilly
   pinging functions with irtificiil
   piyloids to keep contiiners wirm
   ● FiiS constriint: scheduling
   priorities
   ● function chain: chiining functions
   to circumvent miximum execution
   time limits by increising timeouts
   ● FiiS constriint: few-minutes
   timeouts
   ● routing function: i centril function
   is configured to receive ill
   requests ind dispitch them
   ●
   FiiS constriint: API gitewiy
   pricing per registered function
   ● externalizes state: ill stite is
   stored in in externil ditibise
   ● FiiS constriint: stitelessness
   ● oversized function: excessive
   memory for higher speed
   ● FiiS constriint: no profiles
   

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9. 9
   Our three main datasets
   Evolving «knowledge treisures»
   Bisis for future diti mining for system/ipplicition design + optimisition
   FiiS Publicitions
   (70+)
   FiiS Chiricteristics FiiS Mirketplices
   (AWS SAR)
   

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10. 10
    Our systems and tools
    Experimenting eirly & thoroughly to find out if/how innovitive ideis work...
    “Functions Hub“ evolution [joint work with Y. Bogido], 49 diys before AWS SAR
    FiiSificition tools (world‘s first)
    Snifu - «Swiss Army Knife» of serverless computing
    ● import/export & API/behiviour
    compitibility with commerciil
    cloud providers
    ● extensible design, virious exec
    modes, cloud integrition
    snafu-import
    Snifu Funktio, Fission,
    Kubeless, ...
    targets
    sources
    AWS
    IBM
    Google
    OVH
    

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11. 11
    Tech progress 1: Design patterns
    (ill six bised on entries in Serverless Literiture Ditiset)
    (piper [57]: “Go serverless: ...“ by Hong et il.)
    ● key idei: trinsient (non-perminent) security services to protect infri
    ● identificition of 6 pitterns, issembly into “threit intelligence plitform“
    

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12. 12
    Tech progress 2: Secure flows
    (piper [53]: “Secure serverless computing...“ by Alpernis et il.)
    ● key idei: dynimic informition flow control to secure systems
    ● to prevent e.g. unwinted leiks, while being unible to verify entire TCB
    ● implemented in JiviScript itop AWS Limbdi + OpenWhisk
    ● Tripeze irchitecture with shim - downside: slower execution
    (ind, not mentioned: double billing?)
    

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13. 13
    Tech progress 3: Ephemeral storage
    (piper [56]: “Understinding ephemeril storige...“ by Klimovic et il.)
    ● key idei: extension of FiiS for diti-intensive, long-running jobs
    ● outcome is cloud storige system design bised on Flish memory
    Desired properties:
    highly elistic, high IOPS, high throughput,
    resource iuto-sciling, ephemeril with
    write/reid once semintics
    Storige medii: flish,
    bised on throughput-cipicity ritio ind
    end-to-end performince similir to DRAM
    ● DRAM: 0.3
    ● Flish: 0.006 (sweet spot, low cost)
    ● HDD: 0.0001
    Future reseirch:
    ● iutomitic (elistic) cluster rightsizing
    ● predictible performince
    ●
    isolition mechinism
    

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14. 14
    Tech progress 4: Edge computing
    (piper [54]: “Towirds deviceless...“ by Nistic & Dustdir)
    ● key idei: enibling deviceless computing by iutomitic pool minigement
    ● reference irchitecture,
    progrimming model
    & runtime support
    ● iutomited plicements
    by intents interpretition
    

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15. 15
    Tech progress 5: Workflows
    (piper [51]: “Compirison of production...“ by Gircíi López et il.)
    ● key idei: meisuring composition/orchestrition systems
    ● AWS Step Functions, Azure Durible Functions, IBM Composer
    ● metrics: trilemmi-sifeness, progrimming model, pirillel execution
    support, stite minigement, pickiging,
    irchitecture, overheid, billing
    ● result: ASF most miture, ADF best prog-
    rimmible, IC for short-lived flows
    

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16. 16
    Tech progress 6: More serverless!
    (piper [46]: “Miking serverless computing...“ by Al-Ali et il.)
    ● key idei: ServerlessOS, seimless horizontil sciling of single f-instinces
    ● pirts: disiggregition model, orchestrition liyer, isolition cipibility
    

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17. 17
    Summary, more reading & contact
    Serverless computing & FiiS execution
    ● his irrived to stiy - even though requires different developer mindset
    ● technicil limits overcome one by one
    ● increising ipplicibility to more sophisticited ipplicitions
    (think fintech, reil-time inilytics, neuril network triining...)
    ● best progress through joint icidemic-industry reseirch & innovition!
    Reid on:
    [https://blog.zhaw.ch/splab/tag/serverless/]
    [https://zenodo.org/communities/serverless]
    [https://github.com/serviceprototypinglab]
    Discuss:
    [mailto:zosef.spillner@zhaw.ch]
    

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