$30 off During Our Annual Pro Sale. View Details »

Building Adaptive Systems

Chris Keathley
May 28, 2020
Programming
25
1.3k

Building Adaptive Systems

Chris Keathley

May 28, 2020
Tweet

More Decks by Chris Keathley

See All by Chris Keathley
Solid code isn't flexible
keathley
1
690
Contracts for building reliable systems
keathley
4
440
Kafka, the hard parts
keathley
2
1k
Building Resilient Elixir Systems
keathley
6
1.4k
Consistent, Distributed Elixir
keathley
5
1.1k
Telling stories with data visualization
keathley
0
310
Easing into continuous deployment
keathley
1
130
Leveling up your git skills
keathley
0
450
Generative Testing in Elixir
keathley
0
250

Other Decks in Programming

See All in Programming
RuboCop Under a Microscope
koic
8
1.2k
Kaigi_on_Rails_2022スポンサーLT登壇資料.pdf
yuta_onishi_97
1
260
The Kotlin Features You’ve Been Missing Out On
manuelernest0
2
110
Spring for the Architecturally Curious Developer
olivergierke
3
610
サーバーレスなメール送信システムをAWS CDKで構築し数千人規模の環境で運用した話 / aws dev day cdk mail
gotok365
2
700
組織と技術の両輪で開発を加速させるkintoneチームの取り組み / JJUG CCC 2022 Fall Cybozu kintone
itchyny
0
250
JSConf JP 2022 introduce React Query
maminami373
0
3k
開発チームの生産性向上に取り組む
ytakahashi
1
160
やさしく入門するOAuth2.0/easy-entry-oauth
marchin1989
3
430
Behat en 2022
pocky
1
140
Kubernetes Admission Webhook Deep Dive
zoetrope
6
610
Navigating the Streaming Landscape
dunithd
0
230

Featured

See All Featured
Mobile First: as difficult as doing things right
swwweet
213
7.7k
What’s in a name? Adding method to the madness
productmarketing
11
1.8k
Building a Modern Day 
E-commerce SEO Strategy
aleyda
4
3.6k
It's Worth the Effort
3n
174
26k
Statistics for Hackers
jakevdp
782
210k
Fight the Zombie Pattern Library - RWD Summit 2016
marcelosomers
226
16k
StorybookのUI Testing Handbookを読んだ
zakiyama
7
3k
Teambox: Starting and Learning
jrom
124
7.8k
Automating Front-end Workflow
addyosmani
1352
200k
Debugging Ruby Performance
tmm1
67
11k
Designing on Purpose - Digital PM Summit 2013
jponch
107
5.8k
Designing the Hi-DPI Web
ddemaree
273
32k

Transcript

  1. Chris Keathley / @ChrisKeathley / c@keathley.io Building Adaptive Systems

  2. Server Server

  3. Server Server I have a request

  4. Server Server

  5. Server Server

  6. Server Server No Problem!

  7. Server Server

  8. Server Server Thanks!

  9. Server Server

  10. Server Server I have a request

  11. Server Server

  12. Server Server

  13. Server Server I’m a little busy

  14. Server Server I’m a little busy I have more requests!

  15. Server Server I’m a little busy I have more requests!

  16. Server Server I’m a little busy I have more requests!

  17. Server Server I’m a little busy I have more requests!

  18. Server Server I’m a little busy I have more requests!

  19. Server Server I’m a little busy I have more requests!

  20. Server Server I’m a little busy I have more requests!

  21. Server Server I’m a little busy I have more requests!

  22. Server Server I don’t feel so good

  23. Server

  24. Server Welp

  25. Server Welp

  26. All services have objectives

  27. A resilient service should be able to withstand a 10x

    traffic spike and continue to meet those objectives

  28. Lets Talk About… Queues Overload Mitigation Adaptive Concurrency

  29. Lets Talk About… Queues Overload Mitigation Adaptive Concurrency

  30. What causes overload?

  31. What causes overload? Server Queue

  32. What causes overload? Server Queue Processing Time Arrival Rate >

  33. Little’s Law Elements in the queue = Arrival Rate *

    Processing Time

  34. Little’s Law Server 1 requests = 10 rps * 100

    ms 100ms

  35. Little’s Law Server 1 requests = 10 rps * 100

    ms 100ms

  36. Little’s Law Server 1 requests = 10 rps * 100

    ms 100ms

  37. Little’s Law Server 2 requests = 10 rps * 200

    ms 200ms

  38. Little’s Law Server 2 requests = 10 rps * 200

    ms 200ms

  39. Little’s Law Server 2 requests = 10 rps * 200

    ms 200ms

  40. Little’s Law Server 2 requests = 10 rps * 200

    ms 200ms

  41. Little’s Law Server 2 requests = 10 rps * 200

    ms 200ms

  42. Little’s Law Server 2 requests = 10 rps * 200

    ms 200ms BEAM Processes

  43. Little’s Law Server 2 requests = 10 rps * 200

    ms 200ms BEAM Processes CPU Pressure

  44. Little’s Law Server 3 requests = 10 rps * 300

    ms 300ms BEAM Processes CPU Pressure

  45. Little’s Law Server 30 requests = 10 rps * 3000

    ms 3000ms BEAM Processes CPU Pressure

  46. Little’s Law Server 30 requests = 10 rps * ∞

    ms ∞ BEAM Processes CPU Pressure

  47. Little’s Law 30 requests = 10 rps * ∞ ms

  48. Little’s Law ∞ requests = 10 rps * ∞ ms

  49. Little’s Law ∞ requests = 10 rps * ∞ ms

    This is bad

  50. Lets Talk About… Queues Overload Mitigation Adaptive Concurrency

  51. Lets Talk About… Queues Overload Mitigation Adaptive Concurrency

  52. Overload Arrival Rate > Processing Time

  53. Overload Arrival Rate > Processing Time We need to get

    these under control

  54. Load Shedding Server Queue Server

  55. Load Shedding Server Queue Server Drop requests

  56. Load Shedding Server Queue Server Drop requests Stop sending

  57. Autoscaling

  58. Autoscaling

  59. Autoscaling Server DB Server

  60. Autoscaling Server DB Server Requests start queueing

  61. Autoscaling Server DB Server Server

  62. Autoscaling Server DB Server Server Now its worse

  63. Autoscaling needs to be in response to load shedding

  64. Circuit Breakers

  65. Circuit Breakers

  66. Circuit Breakers Server Server

  67. Circuit Breakers Server Server

  68. Circuit Breakers Server Server Shut off traffic

  69. Circuit Breakers Server Server

  70. Circuit Breakers Server Server I’m not quite dead yet

  71. Circuit Breakers are your last line of defense

  72. Lets Talk About… Queues Overload Mitigation Adaptive Concurrency

  73. Lets Talk About… Queues Overload Mitigation Adaptive Concurrency

  74. We want to allow as many requests as we can

    actually handle
  75. None

  76. Adaptive Limits Time Concurrency

  77. Adaptive Limits Actual limit Time Concurrency

  78. Adaptive Limits Actual limit Dynamic Discovery Time Concurrency

  79. Load Shedding Server Server

  80. Load Shedding Server Server Are we at the limit?

  81. Load Shedding Server Server Am I still healthy?

  82. Load Shedding Server Server

  83. Load Shedding Server Server Update Limits

  84. Adaptive Limits Time Concurrency Increased latency

  85. Latency Successful vs. Failed requests Signals for Adjusting Limits

  86. Additive Increase Multiplicative Decrease Success state: limit + 1 Backoff

    state: limit * 0.95 Time Concurrency

  87. Prior Art/Alternatives https://github.com/ferd/pobox/ https://github.com/fishcakez/sbroker/ https://github.com/heroku/canal_lock https://github.com/jlouis/safetyvalve https://github.com/jlouis/fuse

  88. Regulator https://github.com/keathley/regulator

  89. Regulator.install(:service, [ limit: {Regulator.Limit.AIMD, [timeout: 500]} ]) Regulator.ask(:service, fn ->

    {:ok, Finch.request(:get, "https://keathley.io")} end) Regulator

  90. Conclusion

  91. Queues are everywhere

  92. Those queues need to be bounded to avoid overload

  93. If your system is dynamic, your solution will also need

    to be dynamic

  94. Go and build awesome stuff

  95. Thanks Chris Keathley / @ChrisKeathley / c@keathley.io