Use cases and limitations of Serverless and FaaS (Function as a Service).

1. The Rise of Serverless -
When to FaaS?
Photo by Shane Perry
Icon by Serverless

2. ◉ Cloud Architecture & Development Consulting
◉ Serverless Enthusiast
◉ Ex-
Find me at @benikbauer
I am Benny Bauer
Shalom!

3. EvolutionGenesis Custom Built Product (+ rental) Commodity (+ utility)
Cloud evolution in 60 sec
Data center
Hosting
Virtualization IaaS
Icons made by freepik from www.flaticon.com & unlimicon from Noun Project
On
Premise
Compute
Platform PaaS Serverless

4. What is Serverless
FaaS BaaS B2D SaaS

5. What is FaaS - Function as a
Service
Fully-managed
compute
Provisioning,
patching, scaling,
monitoring, logging
are provided
out-of-the- box
Deploy your code
Just package and
upload the code
Pay for actual usage
Getting charged only
upon code execution,
per 100ms
100%
UTILIZATION
LESS OPS

6. How it works
Deploy your
code
Define
triggers
Code
execution
(ephemeral
instance)
EVENT-DRIVEN
AUTO SCALING
+
AVAILABILITY

7. Event-driven on steroids
◉ HTTP requests
◉ Storage (e.g. file upload)
◉ DB (e.g. row insert)
◉ Events stream
◉ Queue/Messaging
◉ Scheduled job
◉ Monitoring
◉ Infrastructure events
◉ Code build events
◉ Many more...

8. Distributed architecture on steroids
Monolith Microservices Serverless
Source: http://ryanjbaxter.com/2015/07/15/using-microservices-to-build-cloud-native-applications-part-1/

9. Bad
◉ Monitoring
◉ Debugging
◉ Deployment
◉ Security
Distributed architecture on steroids
Good
◉ Scaling
◉ Fault tolerance
◉ Ownership
◉ Cost (better utilization)

10. Let’s combine these building blocks to something useful
Use Cases

12. Use case: Web backend

13. Use case: Web backend
Source: https://www.linkedin.com/pulse/serverless-architecture-cloud-guru-ryan-kroonenburg

15. Use case: Mobile backend

16. Use case: Mobile backend
Async request

18. Use case: File processing

19. Use case: File processing

21. Use case: Bot
by

22. Use case: Bot

24. Use case: Distributed compute
import pywren
def my_function(x):
return x + 7
wrenexec = pywren.default_executor()
futures = wrenexec.map(my_function, range(10))
pywren.get_all_results(futures)
pywren

26. Use case: Stream processing
◉ Log processing
◉ Analytics
◉ etc.

28. Use case: Scheduled tasks
◉ Health checks
◉ Monitoring
◉ Periodical digest
◉ etc.

30. Use case: Operations
Policy enforcement on AWS resources.
Examples:
● Unmanaged instances handling
● Low utilized instances resizing
Triggered by:
● CloudWatch events
● Scheduled

32. Use case: CI
Source: https://github.com/lambci/lambci

33. Use case: CI
Source: https://github.com/lambci/lambci
LambCI
(Travis alternative)

35. Use case: IoT backend
Source: https://www.hackster.io/jose-troche/alexa-drone-pilot-7f2deb

36. Use case: IoT backend
Source: https://medium.com/serverless-stories/building-a-serverless-garden-monitoring-system-with-lambda-c72c54113df2
Garden Monitoring
System

38. Use case: CDN
Source: https://www.slideshare.net/AmazonWebServices/new-launch-bringing-aws-lambda-to-the-edge
◉ Purpose:
○ Better UX
○ Reduce load from
backend
◉ Use cases:
○ Request validation
○ A/B testing
○ Content customizations
according to user-agent

39. Use case: CDN
Source: https://www.slideshare.net/AmazonWebServices/new-launch-bringing-aws-lambda-to-the-edge

41. Source: https://www.slideshare.net/AmazonWebServices/aws-welcome-to-reinvent-recap-20161214
Use case: @Device

42. Use case: @Device - example
Source: https://www.slideshare.net/AmazonWebServices/aws-welcome-to-reinvent-recap-20161214

44. Use case: More

45. But isn’t it limitationless??
Mind The Limitations

46. Limitations: Stateless
◉ Instances are ephemeral (memory, storage)
but not necessarily disposable
◉ No sticky sessions
◉ Workarounds:
○ Websockets through IoT (MQTT)
○ Manage state yourself:
■ Pass on request
■ Store in cache/db

47. Execution
time:
5 min
Memory:
1.5GB
Disk:
500MB
Package
(zip):
50MB
Limitations: Provider limits

48. ◉ Ephemeral => cold start on first or
infrequent calls
◉ Inconsistent
Limitations: Latency
Source: http://www.yusp.com/blog/cold-start-problem-recommender-systems/

49. Limitations: Latency
Source: https://blog.newrelic.com/2017/01/11/aws-lambda-cold-start-optimization/
Frequency:
1 minute
10 minutes
30 minutes
60 minutes

50. Limitations: Latency
Source: http://ericjonas.com/pywren.html

51. Limitations: Costs
AWS Lambda EC2
Duration Per 100 ms
Per 1 hour
Reduced cost for RI
Cost of
ownership
Low High
Additional costs Requests
Redundancy
Storage
Cost effective For low or changing load For high utilization

52. Limitations: Costs
Cost
Usage
EC2
AWS Lambda

53. Limitations: Vendor lock-in
◉ The real lock-in is the integrated services
◉ A tradeoff: control vs. convenience
Source: https://www.slideshare.net/AmazonWebServices/reinvent-recap-session-1-whats-new-with-aws-lambda

54. Limitations: Vendor lock-in
(alternatives)
Kubeless
funktion

55. Limitations: Vendor lock-in
(alternatives)

56. Know the challenges
◉ Development
○ Local development
○ Integration tests
○ Debugging
◉ Granularity
○ Deployment
○ Monitoring
○ Logging
○ Security
○ Service discovery

57. Frameworks
Chalise

58. Tools

59. The FaaS effect
New emerging practices
Photo by TimOve (https://flic.kr/p/4aTMMx)

60. Business model
◉ Worth Based Development (“FinDev”)
https://hackernoon.com/why-the-fuss-about-serverless-4370b1596da0#.yct5knd7h by Simon Wardley

61. Business model
◉ API Marketplace

62. Architecture
◉ More distributed and pluggable
◉ More event-driven
◉ Frameworks are changing

63. Operations
DevOps is changing
◉ Less about provisioning, capacity planning
◉ More about distributed systems:
○ Monitoring & visibility
○ Debuggability
○ Graceful degradation & Resiliency
○ CI/CD
○ Costs optimisations

64. Summary
What was it all about?

65. Predicting the future
◉ Lower costs
◉ Less limitations
◉ More use cases
◉ More tooling

66. Takeaways
◉ Deliver faster with lower costs for many use
cases
◉ Consider limitations
◉ Get ready for new emerging practices

67. Any questions?
Thanks!
Slides template by SlidesCarnival
You can find me at
◉ @benikbauer
◉ bennybauer@gmail.com
This work is licensed under a CC Attribution 4.0 International License.