1.
Ultimate Guide to
Microservice Architecture
on Kubernetes
Huseyin BABAL
Software & DevOps Consultant

2.
Who Am I?
Software & DevOps Consultant
Ex-Sony and Ex-eBay Engineer (Microservice Transformation Project Architect)
Google Developer Expert on Web Technologies
Organizer of Docker Istanbul, NodeSchool Istanbul, DevOps Underground meetups

3.
Who we are ?
● Microservice Transition
● DevOps as A Service
● Test Automation as A Service
● Managed Kubernetes

4.
Who we are ?

5.
Customers

6.
Ready to Start ?

7.
Once upon a time while we are in monolithic app
days

8.
After switching to Microservice Architecture ...

9.
And yes, the truth is, only the name Microservice Architecture cannot solve your
architectural problems.
You need to consider applying best practices to Microservices to do it in an efficient
way

10.
#1 Try to Reach Glory of
REST

11.
Leonard Richardson’s Maturity Model

12.
#2 Use HATEOAS

13.
HATEOAS
Hypermedia As The Engine Of Application State

14.
User Model

15.
Article Model

16.
Article Resource

17.
User Resource

18.
Article Controller

19.
User Controller

20.
The Result

21.
Pro Tip
If you don’t want to convert models/dtos to resources manually, you can use Resource
Assembler.

22.
#3 Distributed Configuration

23.
Why Not Project Specific Configs?
● Sensitive data walks around Git
● Unable to inherit common properties like spring.main.banner-mode=OFF

24.
How to Centralized Config?
● Consul can be used to keep config data as Key/Value
● Create a project for just keeping project configurations.
● Git2Consul for sync configuration to Consul

25.
Architecture
Git2Consull
Daemon
Config Project
Git push new config change
Polling
Sync configs to Consul
User

26.
Spring Boot Config

27.
Spring Boot Config (Test)

28.
Git2Consul
npm install -g git2consul
Create a file called git2consul.json and add necessary config
git2consul --endpoint <consul_host> --port 8500 --config-file git2consul.json

29.
Git2Consul Config File

30.
Pro Tip
By default, Spring Boot refreshes its context on config change on Consul. This may
cause down time problems, so disable config change watching with following.

31.
#4 Client Code Generation

32.
How?
You can either use Swagger to generate your client code on any supported language, or
feign client with a little annotation and client side load balancing with Ribbon.

33.
Feign Client

34.
Swagger Doc

35.
Swagger Doc
Now you are able to access;
http://your_api/swagger-ui.html for api documentation
http://your_api/v2/api-docs for json specification of API doc.

36.
Swagger Codegen

37.
Pro Tip
The best place to generate api client is while Jenkins build section.
● If you are deploying a feature to non-prod environment you can generate client
library with snapshot version and push to nexus.
● If you are deploying a feature to prod environment, you can generate client with
stable and push to nexus artifactory

38.
#5 k8s Warm-up

39.
Project Structure

40.
deployment.yml

41.
service.yml

42.
Kubectl configuration
Kubectl is a client app for k8s api server in order to manage k8s cluster. If you use
minikube, your kubectl will be automatically configured, and it is different for other
cloud providers.

43.
Simple deployment
git clone <http://project>
cd <project>
kubectl apply -f k8s

44.
Event
Service
(LB)
Pod-1
Pod-2
Pod-3
Internet

45.
#6 CI / CD

46.
Build
Test
Deploy
Cloud
Provider

47.
Slack Notifications

48.
Deployment Script

49.
Deployment Types
● Rolling Update
● Canary Deployment
● Blue / Green Deployment

50.
Rolling Update
Deployment resource on k8s uses RollingUpdate strategy by default. Within this
strategy, pods deployed one by one instead of taking entire service down.

51.
Canary Deployment
You deploy an experimental feature and allow small amount of request traffic to this
deployment. You increment the size of traffic and after a while, canary replaces the
production one

52.
After a while...
You confirmed that, the feature on canary deployment works, replace prod image with
canary one and delete canary deployment

53.
Blue & Green Deployment
In this strategy, there will be 2 environments with same properties except application
version. The current version will be called blue and new version will be green. Just
update ingress rules to redirect traffic to green deployment.

54.
#7 Monitoring

55.
Monitor Everything

56.
Prometheus
Prometheus is capable of collecting metrics from known sources like cAdvisor.
Prometheus is mainly used for collecting metrics and alert manager to notify you on
any kind of problem

57.
Prometheus Operator
Hopefully, CoreOS team developed a project called prometheus operator to collect k8s
specific metrics automatically.
https://github.com/coreos/prometheus-operator

58.
Getting Started
You can install Prometheus with Helm charts

59.
Visualization
Prometheus lets us to keep track of external services by using some endpoint via
exporters. To visualize metrics, we will use grafana.

60.
Alert Manager

61.
#8 Logging

62.
Spring Boot Logging

63.
Logging Types
● Node Level Logging
● Cluster Level Logging

64.
Node Level Logging

65.
Cluster-Level Logging

66.
You can use several technology to send your logs to logging backend. It can be
Graylog, ELK, etc...

67.
logz.io

68.
Kubernetes Setup
You can run a daemonset to send your logs to logz.io as stated here:
https://github.com/DanielBerman/k8s_logging_files/blob/master/logging_logz/daemons
et-logz.yaml

69.
#9 APM & Service Mesh

70.
Why to Monitor Service Metrics?
Beautiful graphs and dashboard fetched from log resources may not be helpful for you
every time when you face a difficult issue. You may need to see your service insights to
find the root cause.

71.
Tools Can Be Used
NewRelic, AppDynamics, DynaTrace, Zipkin can be suggestion for your APM
monitoring. However, in a containerized microservices world, you may need to have a
tool that works in real-time and has some AI capabilities.

72.
Instana
Instana is an AI Powered Application and Infrastructure Monitoring

73.
#10 API GATEWAY

74.
Microservice Patterns?
In most cases, we have foundation services to access data, and aggregation layer to
aggregate data to serve specific clients. According to my experience, you can handle
microservice division in two ways. (There are many more, but those two are general)

75.
Aggregation Layer
Service 1
Service 2
Service 3
DB 1
DB 2
DB 3
Cache 1
Cache 1
Cache 1
Aggregation
Service
Load
Balancer

76.
Aggregation Layer
When client wants to get data that contains data from multiple services, it consults to
endpoint on aggregation layer.
GET /users/1
User Response = Data(Service1) + Data(Service2) + Data(Service3)

77.
Proxy Pattern
In this pattern, you can use API Gateway to proxy requests to downstream
microservices. Kong, and Tyk are the more popular options for API Gateway

78.
Service 2
Service 1
Service 3
Service 5
Service 6
Service 4
Service 7
Load Balancer

79.
● Proxy ~3000 req/sec with 65 ms latency
● Proxy ~2000 rew/sec with 85ms latency including key validation, security check,
quota management
● 2-Core 2GB Virtual Server

80.
#11 Event Sourcing &
CQRS

81.
CRUD Nature
In services, we always try to change a state of a resource at one time in one transaction.
When more instance needed, we started to use distributed transactions by applying 2-
Phase-Commit protocol in Extended Architecture (a.k.a XA).
Whenever you do a change current state of an entity, old transaction logs gone.

82.
Event Sourcing
Instead of saving current state of entity, save state-changing events belongs to entity in
a time series format
You can replay events within event store, even you can reproduce a bug if exists on
your production!
There is no update to past state of an entity, instead of use an updated event entity in
new row.

83.
Product Events
Product(‘Computer’, 1000 USD)
Product(‘Laptop’, 1000 USD)
Product(‘Laptop’, 900 USD)
ProductMetadataUpdateEvent
ProductPriceUpdateEvent

84.
How?
You can use Apache Kafka, Cassandra, etc … to keep you revents to make them
available to any kind of consumer.
Just save event on any action for example user creation, but you don’t have to return
response immediately.
Event handlers, handle event to populate their views to make available to query

85.
CQRS
Command and Query Responsibility Segregation
A Command alters the state of an object, but does not returns data
A Query returns data, but does not alter state of object

86.
Product Service
Create
Product
Update
Product
Delete
Product
ProductCreateHandler
Topic per Event
Or
Topic per Object and event type in log
Apache Kafka
Database
APIGATEWAY
Create Product Request
Read Product Request

87.
Frameworks

88.
Thank You
http://bit.ly/huseyinbabal
http://bit.ly/kloia-daas
http://bit.ly/k8s-microservice