From AWS to GCP, TABLEAPP Architecture Story
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TABLEAPP is migrating from AWS to GCP due to scaling issues with their AWS architecture. They propose using Kubernetes on GCP to containerize their application and allow for easier auto-scaling. This will eliminate wasted resources and slow provisioning times. They present a new GCP architecture using Kubernetes, Cloud SQL, Cloud Load Balancing, and other GCP services. Migrating has reduced costs by 40% while maintaining availability and performance.
From AWS to GCP, TABLEAPP Architecture Story
- 1. Migrate From AWS to GCP TABLEAPP Architecture Story Yen-Wen Chen TABLEAPP Architect 29 May 2017
- 2. TABLEAPP AWS Architecture TABLEAPP Cloudfront CDN Assets / Images S3 DNS Route53 Mail Server SES Notification SNS Load Balancer Application Clusters EC2 / AutoScale Database RDS / HA
- 3. It’s good, but ...
- 4. AWS Architecture Resource Problem Scaling!! ● Auto Scaling Benefit ○ Maintain availability ○ Maintain performance ○ Decrease capacity during lulls to reduce costs ● But ○ Other instance resource is waste ○ EC2 requiring is slow ■ about 1~2min to activate a ec2 ■ about 1~2min to update latest source code ■ about 30s to run health check
- 5. Our solution is Container
- 6. Virturalized Infrastructure Infrastructure Host OS Docker Engine BINS/LIBS APP Container BINS/LIBS APP Container BINS/LIBS APP Container We can ignore resource problem
- 7. Container Auto Scaling Container A Container B Container C Container A Container B Container C Container A Container C Machine 1 Machine 2 Machine 3 If Container C causes CPU overload Then put a new C into Machine 3
- 8. Service Auto Discovery Container A Container B Container C Container A Container B Container C Container A Container C Machine 1 Machine 2 Machine 3 Service A Service B Service C Service auto discovery / configuration / load balance
- 9. Other Benefits of Docker Moby ● Version Control ○ push code and build ○ every commit has its own images ● Lightweight ○ fast activation (~ 10s) and rollback ○ small image ● Isolation ○ applications and resources are isolated and segregated ● Protable ○ Multi-cloud platform support ○ BOSS asked that
- 10. We want to run moby on …?
- 11. Kubernetes vs EC2 Container Service Kubernetes EC2 Container Service Open Source NO PaaS Google Compute Engine, Rackspace, Microsoft Azure, vSphere, ... AWS Community x Management Kubectl / API AWS CLI / API Protable Run anywhere AWS only Service / Discovery built-in Elastic Load Balance
- 12. How about K8s on AWS?
- 13. Deploy Kubernetes on EC2 ● Maintain Kubernetes yourself ○ Install ○ Testing ○ Update ○ and …. ● Handle auto-scale manually ○ remove pods before remove ec2 ● Using CI to deploy image ● Set up logging and monitoring policy ● Integrate AWS resource and Kubernetes manually ○ It must be scalable No, it sucks ...
- 14. Kubernetes on Google Cloud is awesome
- 15. Google Container Engine (GKE) ● Easy ● Full managed ○ even update kubernetes ● Logging and Monitoring support (stackdrive) ● Automatic and configurable cluster scaling ● Google Cloud Platform resource integration
- 17. TABLEAPP GCP Architecture Cloud Load Balancing Database Cloud SQL EastAsia Cluster Container Engine TABLEAPP Cloud CDN TABLEAPP Cloudfront CDN Assets / Images S3 DNS Route53 Mail Server SES Notification SNS
- 18. Architecture inside kubernetes TABLEAPP Kubernetes Cluster Front Service API Service Manage Service Front Front Manage Manage API CloudSQL Proxy API CloudSQL Proxy API Cloud Load Balancing Manage Cloud Load Balancing WWW Cloud Load Balancing Database Cloud SQL Logger Service Logger Logging
- 19. Deployment EastAsia Cluster Container Engine BitBucket Build Trigger Container Registry Build Images Container Registry Base Images Code Repository ImageUpdate Pub/Sub Pods Update Cloud Functions Config Files Cloud Storage 2 1 Base Images Dockerfile Updated 2 Web Source Code Updated 3 Build Images Process 4 Pull Latest Config File 5 Trigger Image Update 6 Notified Image Update 7 Pull Latest Docker Image 8 Pull Latest Config File From Pods startup script 9 Migrate Database From Pods startup script Database Cloud SQL 1 3 4 7 8 5 6 9
- 20. Log Collection EastAsia Cluster Container Engine BitBucket Build Trigger Container Registry Build Images Container Registry Code Repository Base Images ImageUpdate Pub/Sub Pods Update Cloud Functions Config Files Cloud Storage Database Cloud SQL Cloud Load Balancing Tableapp Cloud CDN Logging Build Log Log Files Cloud StorageBackup
- 21. Cost and Usage
- 22. Request History Requests has grown 5 times in past year5x
- 23. Payment History ● cost increased almost 2 times in six month ● We start optimize AWS architecture at 2016-11 Start Optimize 2x
- 24. Payment History ● After reduce cost ● We start maintain architecture in Google at 2017-02 Start Test Google
- 25. Payment History Now We redece cost successful We can afford more request
- 26. Conclusion ● We still remain some service in AWS ○ SES ○ SNS ○ S3 ○ Read replica Database ● CloudCDN is really fast ○ very low latency ○ optimize network ○ POP is stable ● Lower price ○ based on new arch, we save 40% cost