Function-as-a-Service "serverless" cloud offerings provide you with a super easy way to run custom code in response to events. One promise of FaaS model is the ability to scale without limits, up or down, whenever needed. But how does that work in practice? Can AWS Lambda handle thousands of messages per second? How fast can Azure Functions scale up under sudden heavy load? What kind of latency can you expect from Google Cloud Functions? During this session Mikhail will share with you short tales, each of them teaching a lesson about practical scalability of serverless applications. You will also explore the steps to evaluate whether your application profile is suitable for serverless today.

1. Performance
Tales of Serverless
CloudNative London | September 28 | 2018

2. WHAT IS
CloudNative?
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2

3. EMBRACE
THE CLOUD!
EXPLOIT
the inherent
properties
3

4. 4
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WHAT IS
CloudNative?

5. Is this
Cloud Native?
Serverless
Architecture

6. Welcome to
CloudNative
London 2018!

10. м
10
The Story …

11. 2012 2013
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12. 12

13. What did we want?
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$

14. 14

15. м
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2017 2018

16. 16

17. What do we want?
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$

18. 18
Function-as-a-Service Cloud Offerings

19. 19
Ideal Scalability: Throughput

20. Ideal Scalability: Latency
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21. 21
Application Overview

22. OCCASIONAL USERS:
MVP just launched,
we get several visitors
per hour
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23. Visitors during sample 5 hours
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24. Dependency Call Duration (ms)
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25. Target End-to-End Latency (ms)
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26. AWS Lambda Latency (ms)
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27. Google Cloud Functions Latency (ms)
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28. Azure Functions Latency (ms)
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29. 29
Cold Start

30. 29
Warm Start

31. Subsequent Cold Starts after quiet periods
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32. UNDERSTAND
THE RUNTIME
1.
Lesson
Learned
32

33. COLD STARTS
ARE SLOW(-ER)
…and depend on language
and package size
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2.
Lesson
Learned

34. LOAD TESTING:
How do we load test?
With serverless!
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35. Load Testing Setup
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36. Load Testing Setup
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37. Load Testing Setup
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38. Serverless Artillery

39. BE CREATIVE
IN USAGE SCENARIOS
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3.
Lesson
Learned

40. PROJECTED LOAD:
Simulated at the target
amount of users
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41. Requests/sec during 5 hours of load test
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42. End-to-End Latency (ms)
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43. End-to-End Latency (ms)
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44. SERVERLESS SCALABILITY
IS LIMITED BY
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NON-SERVERLESS DEPENDENCIES
4.
Lesson
Learned

45. 45
SERVERLESS APPLICATION
CAN DDOS
ANY MERE MORTAL SERVICE
5.
Lesson
Learned

46. ETL:
Asynchronous data
processing
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47. How to improve it
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48. Serverless ETL
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49. GCP Functions + Pub/Sub Processing 1 Million Points
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50. Azure Functions + Event Hub Processing 1 Million Points
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51. AWS Lambda + Kinesis Processing 1 Million Points
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52. AWS Processing Speed per Reserved RAM
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0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

53. SERVERLESS IS NOT JUST HTTP
EVENT BASED ASYNC FTW
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6.
Lesson
Learned

54. 54
LEARN THE RESOURCE MODEL:
LIMITS, SCALING MODE,
RAM & CPU ALLOCATION
7.
Lesson
Learned

55. TV EFFECT:
We are going to be
live on TV!!!
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56. Requests/sec during the load test
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57. Azure Functions Response Percentiles (ms)
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58. Azure Functions Response 99th Percentile (ms)
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59. AWS Lambda Response Percentiles (ms)
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60. Google Cloud Functions: Throttled
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61. Google Cloud Functions: Persist Connections
const http = require('http');
const agent = new http.Agent({keepAlive: true});
exports.mycloudfunction = (req, res) => {
req = http.get({
host: '...',
port: 80,
path: '...',
agent: agent
}, // ...
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62. Google Functions Response Percentiles (ms)
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63. 63
REUSE CONNECTIONS,
POOL & CACHE
8.
Lesson
Learned

64. SERVERLESS IS UNIQUELY
SUITABLE FOR SPIKY LOAD…
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BUT KNOW THE LIMITS
9.
Lesson
Learned

65. RUNNING IN
PRODUCTION
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66. 66
Actual
Outcome
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

67. DESIGN FOR SUCCESS
BUT BE PREPARED TO
67
A FAILURE
10.
Lesson
Learned

68. Is Serverless
Good for
My Next
Project?
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69. 69
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Is Serverless
Good for My
Next Project?

70. Perfect
Scenarios for
Serverless
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71. Serverless
Cold Start War