How we use Kubernetes to improve the engineer efficiency and make the system more scalable

1. GCP x K8S

2. Agenda
1. Who are we / am I?
2. What is AfterShip
3. Our challenges
4. The solutions
5. Demo

3. teddy@aftership.com
Teddy Chan
CEO & Co-Founder
Credit
Nick SRE @aftership
GitHub: https://github.com/itnick

4. Who are we?
We love coding, solving the real problems and make it scalable
27 in HK
8 in India / Remote

5. The world #1 tracking API platform
Support 400+ couriers, 200+ countries

6. Our challenges
Coding
!Deployment
Automatic
!Manual
Deployment Fast !Slow
Scaling Fast
!Slow

7. Old Days Workflows
Run in AWS / GCP using Compute Instances
1. Commit
2. PR
3. Travis CI
4. Code Review
5. Merged to master
6. Manual Deployment

8. Manual Deployment
Run in AWS / GCP using Compute Instances
1. Lots of Steps
2. Human Error
3. Boring
4. Slow

9. Continuous Deployment
Manual Deployment → Auto Deployment
1. Lots of Steps
2. Human Error
3. Boring
4. Faster, but not FAST enough

10. Our challenges
Coding ✔
!Deployment
Automatic ✔ !Manual
Deployment Fast ? !Slow
Scaling Fast ?
!Slow
Cost Cheap ?

11. Deployment Flows
What is the problem?
1. Launch new instances (Blue / Green) ~ 8 mins
2. Update / Patch OS / Install binary ~ 5 mins
3. Git clone / npm install ~ 2 mins
15 - 25 mins

12. Kubernetes
K8S

13. Kubernetes
K8S
https://kubernetes.io/docs/concepts/workloads/pods/pod/#what-is-a-pod

14. K8S Flows
For new deployment
1. Build container image (Blue / Green)
2. Update / Patch OS / Install binary
3. Git clone / npm install ~ 2 mins
~ 2 mins

15. K8S Flows
For scaling up
1. Build container image (Blue / Green)
2. Update / Patch OS / Install binary
3. Git clone / npm install ~ 5 mins
< 20s

16. K8S Flows
Example

17. Our challenges
Coding ✔
!Deployment
Automatic ✔ !Manual
Deployment Fast ✔ !Slow
Scaling Fast ✔ !Slow
Cost Cheap ✔

18. Bible
How to Guide: https://goo.gl/f6YSJY
GitHub repo: https://goo.gl/h6eEBJ
This slide: https://www.slideshare.net/aftership

19. We’re hiring
www.aftership.com/jobs