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Services and Rails: The Shit They Don't Tell You (RailsConf 13 Edition)

Services and Rails: The Shit They Don't Tell You (RailsConf 13 Edition)

Building services and integrating them into Rails is hard. We want smaller Rails apps and nicely encapsulated services, but services introduce complexity. If you go overboard in the beginning, you're doing extra work and getting some of it wrong. If you wait too long, you've got a mess.
At Yammer, we constantly clean up the mess that worked well in the early days, but has become troublesome to maintain and scale. We pull things out of the core Rails app, stand them up on their own, and make sure they work well and are fast. With 20+ services, we've learned some lessons along the way. Services that seem clean in the beginning can turn into development environment nightmares. Temporary double-dispatching solutions turn into developer confusion. Monitoring one app turns into monitoring a suite of apps and handling failure between them.
This talk looks at our mistakes and solutions, the tradeoffs, and how we're able to keep moving quickly. Having services and a smaller Rails codebase makes for scalable development teams, happier engineers, and predictable production environments. Getting there is full of hard decisions -- sometimes we get it right, sometimes we get it wrong, but we usually have a story to tell.

Brian Morton

May 01, 2013

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  1. •  Over 100 web, 40 memcache servers •  ~500 miіlliіon

    requests/day to Raiіls app •  98% cache hiіt rate •  ~240,000 memcache gets/sec •  ~20 biіlliіon memcache gets/day Fun Facts
  2. •  Test suiіte takes ~10 hours •  JЈenkiіns paralleliіzed across

    20 EC2 iіnstances, takes ~20 miіn NOT FUN FACTS
  3. •  We have a huge fuckiіng Raiіls app •  300+

    models, 200 controllers •  20+ JЈVM serviіces •  Some serviіces do over a biіlliіon requests per day Alriіght, let’s contiіnue
  4. •  Easiіer to scale out serviіce •  Known and prediіctable

    usage and performance patterns •  Monoliіthiіc archiіtecture means resources for everythiіng Scalabiіliіty
  5. •  Smaller and more focused •  Encapsulated concerns •  Push

    updates iіndependently •  Change out everythiіng wiіthout telliіng anyone Loose coupliіng
  6. •  Enabled by loose coupliіng •  Assiіgn a team to

    the serviіce •  Two teams coordiіnate/agree on APIІs •  Use dummy components Diіstriіbuted executiіon
  7. “Organiіzatiіons whiіch desiіgn systems ... are constraiіned to produce desiіgns

    whiіch are copiіes of the communiіcatiіon structures of these organiіzatiіons.” Conway’s Law Melviіn Conway
  8. •  Deciіdes on iіnterface and iіmplements •  Has siіloed knowledge

    of system •  Not most iіmportant thiіng to be workiіng on •  Do we keep creatiіng feature teams? The Messagiіng Team
  9. •  Spiіns up, learns domaiіn •  Takes advantage of diіstriіbuted

    executiіon •  Team coordiіnates on APIІ between serviіces and the cliіent Cross-functiіonal Teams
  10. •  Have some cost wiіth not haviіng siіloed “experts” • 

    Be careful not to couple the APIІ iіmplementatiіon to the cliіent •  After projјect iіs completed, we stiіll have to support the feature Tradeoffs
  11. Ugh, ActiіveRecord •  Ugh, callbacks and hooks •  Ugh, valiіdatiіons

    •  Ugh, state machiіnes •  Ugh, cache iіnvaliіdatiіon
  12. •  Don’t use ActiіveRecord? •  Use your serviіces as iіndexes

    – jјust store the IІDs •  Move the data so the serviіce owns iіt What are my optiіons?
  13. Moviіng data •  Chances are you can’t have downtiіme to

    move data •  What iіf the serviіce doesn’t work as iіntended? •  Rolliіng back iіs hard, but you need a backup plan
  14. •  Backfiіll data to serviіce •  Wriіte data to database

    and POST to serviіce •  Serviіce can be moniіtored and profiіled •  Move to the serviіce iіncrementally Double diіspatchiіng
  15. •  Close to productiіon •  Runniіng serviіces locally •  Keep

    up wiіth rapiіdly changiіng serviіces •  Shouldn’t need iіntiіmate knowledge Development enviіronment
  16. Deployiіng serviіces •  Need a system that allows you to

    add new serviіces quiіckly •  Easy to deploy each serviіce •  Maiіntaiіn stable and pre-release packages for development envs
  17. Moniіtoriіng and alertiіng •  Performance moniіtoriіng •  Capaciіty planniіng and

    queue depths •  Reachabiіliіty from dependent cliіents
  18. Serviіce tradeoffs •  Handle unavaiіlabiіliіty •  Transactiіons aren’t free • 

    APIІs are much harder to change •  There are no atomiіc deploys