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![apiVersion: apps/v1
kind: Deployment
. . .
template:
metadata:
labels:
app: greeting
kube-monkey/enabled: enabled
kube-monkey/identifier: redis-master
kube-monkey/mtbf: 2
kube-monkey/kill-mode: random-max-percent
kube-monkey/kill-value: 40
spec:
containers:
- name: greeting
apiVersion: v1
kind: Confirm
metadata:
name: kube-monkey-config-map
namespace: kube-system
data:
config.toml: |
[kubemonkey]
run_hour = 8
start_hour = 10
end_hour = 16
blacklisted_namespaces = ["kube-system"]
whitelisted_namespaces = [”default”]
time_zone = “UTC”](https://image.slidesharecdn.com/chaosengineeringinactionforkubernates-181126080035/85/Kubernates-Chaos-Engineering-in-Action-AWS-39-320.jpg)
![apiVersion: apps/v1
kind: Deployment
. . .
template:
metadata:
labels:
app: greeting
kube-monkey/enabled: enabled
kube-monkey/identifier: redis-master
kube-monkey/mtbf: 2
kube-monkey/kill-mode: random-max-percent
kube-monkey/kill-value: 40
spec:
containers:
- name: greeting
apiVersion: v1
kind: Confirm
metadata:
name: kube-monkey-config-map
namespace: kube-system
data:
config.toml: |
[kubemonkey]
run_hour = 8
start_hour = 10
end_hour = 16
blacklisted_namespaces = ["kube-system"]
whitelisted_namespaces = [”default”]
time_zone = “UTC”](https://image.slidesharecdn.com/chaosengineeringinactionforkubernates-181126080035/75/Kubernates-Chaos-Engineering-in-Action-AWS-39-2048.jpg)
Uploaded byChanny Yun
Kubernates를 위한 Chaos Engineering in Action :: 윤석찬 (AWS 테크에반젤리스트)
Chaos engineering involves intentionally introducing failures into systems to test resilience. It reveals issues that may otherwise remain undetected. Some key aspects of chaos engineering include using tools like Chaos Toolkit and Gremlin to fail components, running experiments at specified times using a configuration file, and introducing faults into service meshes between microservices. The goal is to build confidence in systems by identifying weaknesses before real failures occur.
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Kubernates를 위한 Chaos Engineering in Action :: 윤석찬 (AWS 테크에반젤리스트)
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- 5. Failures are agiven and everything will eventually fail over time. https://www.allthingsdistributed.com/2016/03/10-lessons-from-10-years-of-aws.html
- 6. https://www.youtube.com/watch?v=zoz0ZjfrQ9s Amazon 2006 GameDay: Creating ResiliencyThrough Destruction Jesse Robbins
- 7. Netflix 2011 Chaos Monkeys: Testthe resilience of its Infrastructure Simian Army – Open Source https://github.com/Netflix/SimianArmy
- 8. T T r T ao W D e W A W E n (c) Dave Hahn, A Day in the Life of a Netflix Engineer Using 37% of the Internet, re:Invent 2015 W 0 5 5 9 • ( E n Un NS • ( , c • ( - 1 T T c 31 /-12 • ( /3 /12 • ( ) 31 /12 ( - 8 - 8 • ( i
- 9. ELB Zuul API (c) Josh Evans,Mastering Chaos A Netflix Guide to Microservices, QCon SF 2016
- 10. E • ( • (/ F o Sv c dB xe n B l F +/ +/ k F D y u c d • +/ / ( v n L Cp r : v b Cp e t s R ic E • ( • ( , / / / c i c c as • ) • ) / ) c c d d B e / u y m
- 11. (c) Ruslan Meshenberg,From Asgard to Zuul, re:Invent 2014
- 12. F A I R( c R a Z d )/ , ( c R e o nP dS e F (c) Josh Evans, Mastering Chaos A Netflix Guide to Microservices, QCon SF 2016
- 13. Chaos Monkey https://github.com/ne tflix/chaosmonkey Instance Fail? ChaosGorilla Zone Fail? Chaos Kong Region Fail? .
- 14. , ) )(. j a l o i c e n tF r I n
- 15. • • U • P • •), ( ) • P CP !
- 17. Chaos doesn’t causeproblems. It reveals them.
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- 37. mycluster.eks.amazonaws.com Availability Zone 1 Availability Zone 2 Availability Zone3 Kubectl x x Health check? Dead node?
- 38.
- 39. apiVersion: apps/v1 kind: Deployment .. . template: metadata: labels: app: greeting kube-monkey/enabled: enabled kube-monkey/identifier: redis-master kube-monkey/mtbf: 2 kube-monkey/kill-mode: random-max-percent kube-monkey/kill-value: 40 spec: containers: - name: greeting apiVersion: v1 kind: Confirm metadata: name: kube-monkey-config-map namespace: kube-system data: config.toml: | [kubemonkey] run_hour = 8 start_hour = 10 end_hour = 16 blacklisted_namespaces = ["kube-system"] whitelisted_namespaces = [”default”] time_zone = “UTC”
- 40.
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- 42.
- 43.
- 45. apiVersion: networking.istio.io/v1alpha3 kind: DestinationRule metadata: name:ratings-destination-rule spec: host: ratings subsets: - name: ratings labels: ratings: hello trafficPolicy: connectionPool: tcp: maxConnections: 100 apiVersion: networking.istio.io/v1alpha3 kind: VirtualService metadata: name: reviews spec: hosts: - reviews http: - route: - destination: host: reviews subset: v1 weight: 75 - destination: host: reviews subset: v2 weight: 25
- 47. apiVersion: networking.istio.io/v1alpha3 kind: VirtualService metadata: name:ratings spec: hosts: - ratings http: - fault: delay: fixedDelay: 10s percent: 100 route: - destination: host: ratings subset: v1 apiVersion: networking.istio.io/v1alpha3 kind: VirtualService metadata: name: ratings spec: hosts: - ratings http: - fault: abort: httpStatus: 500 percent: 100 route: - destination: host: ratings subset: v1
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- 54. • @LLH NAJ BJ@ L / 5 H=J 2 = 183A H • @LLH ?J= A • @LLH = = J? =L A -A • @LLH L J== ?A ==JA ? A • @LLH ?AL@ : L=J? = = J= • @LLH = AP J? L= A = =J= = A A H H=J H • @LLH = A .4=L AP7= @0 ? • @LLH H= =J = L : L @ = ?A ==JA ? : L H • @LLH ?AL@ : @ J = = @ = ?A ==JA ? • @LLH A HJ= = L LA =L AP @ A J =JNA = • @LLH J HA ? H L= L H HA ? 8 HLA =8 @= L8 @==L H • @LLH A ? =? =JA J L = A References
- 55.