Slides for my talk on Microservices given at MCJUG on Sep 2015

1. Introduction to Microservices
Vlad Korolev
vlad@dblfuzzr.com

2. Microservices
2 / 50

3. Microservices
What are the micro services?
3 / 50

4. Microservices
What are the micro services?
Where did they come from?
3 / 50

5. Microservices
What are the micro services?
Where did they come from?
Core principles
3 / 50

6. Microservices
What are the micro services?
Where did they come from?
Core principles
Why should I bother?
3 / 50

7. Microservices
What are the micro services?
Where did they come from?
Core principles
Why should I bother?
Challenges and pitfalls
3 / 50

8. Microservices
What are the micro services?
Where did they come from?
Core principles
Why should I bother?
Challenges and pitfalls
Good practices
3 / 50

9. Microservices
What are the micro services?
Where did they come from?
Core principles
Why should I bother?
Challenges and pitfalls
Good practices
Pro-tips
3 / 50

10. Microservices : what’s that?
4 / 50

11. Microservices : what’s that?
Post continuous delivery SOA
5 / 50

12. Microservices : what’s that?
Post continuous delivery SOA
Small independently releasable services, that work together,
modeled around a business domain.
5 / 50

13. Prehistoric technology
6 / 50

14. Prehistoric technology
SOA
7 / 50

15. Prehistoric technology
SOA
Domain driven design
7 / 50

16. Prehistoric technology
SOA
Domain driven design
Continous delivery
7 / 50

17. Case study
8 / 50

18. Case study
9 / 50

19. Case study
Catalog
Recommendations / Promotions
Shopping Cart
Search
Orders
RMA
Customer Support
10 / 50

20. Application Composition : Monolith
11 / 50

21. Application Composition : Monolith
Works most of the time
Somewhat scalable
Manageable up to a point
All or nothing updates
Tight coupling
12 / 50

22. SOA
Break up application into set of independent services
13 / 50

23. SOA
Break up application into set of independent services
Add extra layers
Integration Layer (ESB)
Service Layer
13 / 50

24. SOA
Break up application into set of independent services
Add extra layers
Integration Layer (ESB)
Service Layer
Rename existing layers
Frontend → Consumer Interface Layer
Database → Operational System
Middleware → Business Process Layer
13 / 50

25. Application Composition : SOA
14 / 50

26. Application Composition : SOA
Did well in some organizations
Not so well in others
Reasons for failure
Conway’s Law
Ignoring CAP theorem
Ignoring Fallacies of distributed
computing
15 / 50

27. Conway’s Law
16 / 50

28. Conway’s Law
organizations which design systems ... are constrained to produce
designs which are copies of the communication structures of these
organizations
– M. Conway
17 / 50

29. Conway’s Law
organizations which design systems ... are constrained to produce
designs which are copies of the communication structures of these
organizations
18 / 50

30. Fallacies of distributed
computing
19 / 50

31. Fallacies of distributed computing
The network is reliable
Latency is zero
Bandwidth is infinite
The network is secure
Topology doesn’t change
There is one administrator
Transport cost is zero
The network is homogeneous
20 / 50

32. CAP Theorem
21 / 50

33. CAP Theorem
Consistency
Availability
Partitioning tolerance
22 / 50

34. Domain Driven Design
23 / 50

35. Domain Driven Design
Bounded contexts
24 / 50

36. Domain Driven Design
Bounded contexts
Draw boundaries around business domains
24 / 50

37. Domain Driven Design
Bounded contexts
Draw boundaries around business domains
Do not partition system based on technology
24 / 50

38. Application Composition :
Microservices
25 / 50

39. Application Composition : Microservices
26 / 50

40. Application Composition : Microservices
Modeled around business domain
Autonomous
Hide implementation detail
Decentralized
Isolate the failure
Highly observable
Culture of automation
27 / 50

41. Microservices : Good Parts
28 / 50

42. Microservices : Good Parts
Small and focused
29 / 50

43. Microservices : Good Parts
Small and focused
Independent
29 / 50

44. Microservices : Good Parts
Small and focused
Independent
Loosely coupled
29 / 50

45. Microservices : Good Parts
Small and focused
Independent
Loosely coupled
Allow try and pilot new tech
29 / 50

46. Microservices : Good Parts
Small and focused
Independent
Loosely coupled
Allow try and pilot new tech
Firm module boundaries
29 / 50

47. Microservices : Good Parts
Small and focused
Independent
Loosely coupled
Allow try and pilot new tech
Firm module boundaries
Decentralized data
29 / 50

48. Why bother?
30 / 50

49. Why bother?
Latest Buzzword
31 / 50

50. Why bother?
Latest Buzzword
All the cool kids are doing it
31 / 50

51. Why bother?
Latest Buzzword
All the cool kids are doing it
Probably, not good reasons
31 / 50

52. Why bother?
Faster dev cycles
32 / 50

53. Why bother?
Faster dev cycles
Team autonomy
32 / 50

54. Why bother?
Faster dev cycles
Team autonomy
Smoother scaling
32 / 50

55. Challenges
Complex runtime
33 / 50

56. Challenges
Complex runtime
Distributed deployment
33 / 50

57. Challenges
Complex runtime
Distributed deployment
Extensive communication
33 / 50

58. Challenges
Complex runtime
Distributed deployment
Extensive communication
Handling failures
33 / 50

59. Good practices
Humane registries
34 / 50

60. Good practices
Humane registries
Team composition
34 / 50

61. Good practices
Humane registries
Team composition
Isolate failures
34 / 50

62. Good practices
Humane registries
Team composition
Isolate failures
Fail fast
34 / 50

63. Good practices
Humane registries
Team composition
Isolate failures
Fail fast
Bulkheading
34 / 50

64. Good practices
Humane registries
Team composition
Isolate failures
Fail fast
Bulkheading
Standardize communications
34 / 50

65. Good practices
Humane registries
Team composition
Isolate failures
Fail fast
Bulkheading
Standardize communications
REST or Message Queues
34 / 50

66. Good practices
Humane registries
Team composition
Isolate failures
Fail fast
Bulkheading
Standardize communications
REST or Message Queues
Robust Service Discovery
34 / 50

67. Good practices
Humane registries
Team composition
Isolate failures
Fail fast
Bulkheading
Standardize communications
REST or Message Queues
Robust Service Discovery
Consider something like Consul / Zookeeper / ETCd
34 / 50

68. Good practices
Humane registries
Team composition
Isolate failures
Fail fast
Bulkheading
Standardize communications
REST or Message Queues
Robust Service Discovery
Consider something like Consul / Zookeeper / ETCd
Monitor everything
34 / 50

69. Deployments
Avoid huge build jobs
35 / 50

70. Deployments
Avoid huge build jobs
One service per host
35 / 50

71. Deployments
Avoid huge build jobs
One service per host
Host is either physical host, VM or container
35 / 50

72. Deployments
Avoid huge build jobs
One service per host
Host is either physical host, VM or container
Test
35 / 50

73. Deployments
Avoid huge build jobs
One service per host
Host is either physical host, VM or container
Test
Contract Tests
35 / 50

74. Deployments
Avoid huge build jobs
One service per host
Host is either physical host, VM or container
Test
Contract Tests
Consumer driven development
35 / 50

75. Potential pitfalls
Incorrect partitioning
36 / 50

76. Potential pitfalls
Incorrect partitioning
Distributed point of failure
36 / 50

77. Potential pitfalls
Incorrect partitioning
Distributed point of failure
Misunderstanding your network
36 / 50

78. Refactoring to Microservices
Strangler pattern
37 / 50

79. Refactoring to Microservices
Strangler pattern
Use static analysis tool to find natural boundaries
37 / 50

80. Refactoring to Microservices
Strangler pattern
Use static analysis tool to find natural boundaries
Shadow systems
37 / 50

81. Personal Experiences
38 / 50

82. Monitor Everything
Exception catchers
39 / 50

83. Monitor Everything
Exception catchers
Centralized log collections
39 / 50

84. Monitor Everything
Exception catchers
Centralized log collections
39 / 50

85. Monitor Everything
Exception catchers
Centralized log collections
Synthetic transactions
39 / 50

86. Understand your networking
Microservices increase network chatter
40 / 50

87. Understand your networking
Microservices increase network chatter
More failures with UDP based protocols (DNS, discovery)
40 / 50

88. Understand your networking
Microservices increase network chatter
More failures with UDP based protocols (DNS, discovery)
More hiccups with TCP based protocols
40 / 50

89. Understand your networking
Microservices increase network chatter
More failures with UDP based protocols (DNS, discovery)
More hiccups with TCP based protocols
Run out of sockets
Decrease TCP timeouts, seconds instead of minutes
40 / 50

90. Understand your networking
Microservices increase network chatter
More failures with UDP based protocols (DNS, discovery)
More hiccups with TCP based protocols
Run out of sockets
Decrease TCP timeouts, seconds instead of minutes
Batch the transactions.
But can’t have batching service
40 / 50

91. Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact
41 / 50

92. Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact
Instantaneous deployments
41 / 50

93. Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact
Instantaneous deployments
Pre-build AMis, Containers
41 / 50

94. Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact
Instantaneous deployments
Pre-build AMis, Containers
Test coverage
41 / 50

95. Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact
Instantaneous deployments
Pre-build AMis, Containers
Test coverage
Consumer Driven Tests
41 / 50

96. Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact
Instantaneous deployments
Pre-build AMis, Containers
Test coverage
Consumer Driven Tests
Avoid integration tests written by service devs
41 / 50

97. Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact
Instantaneous deployments
Pre-build AMis, Containers
Test coverage
Consumer Driven Tests
Avoid integration tests written by service devs
https://github.com/realestate-com-au/pact
41 / 50

98. Consider using client side load balancing
Service side load balancers create point of failure
42 / 50

99. Consider using client side load balancing
Service side load balancers create point of failure
Hard to deploy and manage HW load balancers
42 / 50

100. Consider using client side load balancing
Service side load balancers create point of failure
Hard to deploy and manage HW load balancers
Problem of running out of sockets
42 / 50

101. Consider using client side load balancing
Service side load balancers create point of failure
Hard to deploy and manage HW load balancers
Problem of running out of sockets
Netflix Ribbon Library
https://github.com/Netflix/ribbon/wiki/Working-with-load-
balancers
42 / 50

102. Never make MapReduce pipeline talk to service outside of
your cluster
43 / 50

103. Never make MapReduce pipeline talk to service outside of
your cluster
44 / 50

104. Further resources
45 / 50

105. Further resources
46 / 50

106. Further resources
47 / 50

107. Further resources
Toughtworks Youtube channel
48 / 50

108. ???
49 / 50

109. Thank you
50 / 50