Cloud Patterns Beuth Hochschule
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This document provides an overview of cloud architecture and best practices for deploying applications in the AWS cloud. It begins with an introduction to key AWS services like EC2, ELB, RDS, and Auto Scaling. It then walks through creating a basic cloud deployment and improving it by separating concerns, adding redundancy, caching, and autoscaling. Finally, it discusses a real-world example using services like Kinesis and deploying containers with ECS.
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Cloud Patterns Beuth Hochschule
- 1. CLOUD ARCHITECTURE Sascha Möllering | zanox AG
- 2. Sascha Möllering [email protected] Lead Engineer / DevOps Hipster zanox AG http://autoscaling.io @sascha242 ABOUT ME
- 3. JAVA MAGAZIN 11.14 ARCHITEKTUR IM KONTEXT DER CLOUD: PATTERNS UND BEST PRACTICES AWS VIRTUAL CLOUD SUMMIT CONTINUOUS DELIVERY IN AWS USING DOCKER ENTWICKLER SPEZIAL: DOCKER ÜBER DEN WOLKEN: EIN ERFAHRUNGSBERICHT ZUM DOCKER- EINSATZ IN DER AMAZON CLOUD ABOUT ME
- 4. AGENDA ●AWS Overview ●Creating a cloud service ●Real World example ●Cloud deployment ●Q&A
- 5. HOW CAN WE SCALE?
- 6. HOW CAN WE SCALE?
- 7. AWS OVERVIEW RegionUS-WEST (N. California) EU-WEST (Ireland) ASIA PAC (Tokyo) ASIA PAC (Singapore) US-WEST (Oregon) SOUTH AMERICA (Sao Paulo) US-EAST (Virginia) GOV CLOUD ASIA PAC (Sydney) EU-CENTRAL (Frankfurt)
- 9. AWS OVERVIEW EC2: Resizable compute capacity AutoScaling: scale up or down Route 53: Domain Name System ELB: Load Balancing Elastic IP: Static IP address
- 10. AWS OVERVIEW RDS: Managed database service DynamoDB: NoSQL implementation Redshift: data warehouse solution ElastiCache: Managed cache Kinesis: Service for streaming data
- 11. AWS OVERVIEW S3: Highly-scalable object storage CloudFront: CDN implementation CloudWatch: Monitoring service IAM: Identity and Access Management EMR: Managed Hadoop
- 12. STARTING POINT ●How can we leverage the Cloud? ●Our application: ● Simple Java based web application ● One application ● One database ● Runs in our own DC
- 13. CREATING A CLOUD SERVICE ●Initial setup: ●Route53 for DNS ●One Elastic IP (static IPs for the Cloud) ●One EC2 instance ● Web Application ● Database ●One AZ
- 14. CREATING A CLOUD SERVICE Availability Zone
- 15. CREATING A CLOUD SERVICE ●Simple approach to scale: ●More RAM ●More CPU power ●More IOPS ●Different EC2 instance type ●Approach will hit a barrier
- 16. CREATING A CLOUD SERVICE ●Problems: ●No failover ●No redundancy ●Database and application on one instance ●Does not scale very well
- 17. CREATING A CLOUD SERVICE ●Separate Web Application from DB ●One EC2 instance for the Web Application ●One EC2 instance for the DB ●Or: Managed DB service (RDS) ●One AZ
- 18. CREATING A CLOUD SERVICE Availability Zone Database
- 19. CREATING A CLOUD SERVICE ●Problems: ●No failover ●No redundancy ●Does still not scale very well
- 20. CREATING A CLOUD SERVICE ●Add an ELB ●Add EC2 instance for Web Application ●Different AZs ●Standby DB instance ●Multi AZ setup in RDS
- 21. CREATING A CLOUD SERVICE
- 22. CREATING A CLOUD SERVICE Availability Zone Database Availability Zone Database
- 23. CREATING A CLOUD SERVICE ●Problems: ●Still limited scaling capabilities ●If one EC2 instance crashes, 50% less capability
- 24. CREATING A CLOUD SERVICE ●Add additional EC2 instances ●Add read replicas in RDS
- 25. CREATING A CLOUD SERVICE Availability Zone Database Availability Zone Database
- 26. CREATING A CLOUD SERVICE ●Problems: ●Naive implementation ●Does not leverage AWS services ●Limited scaling ●Can be quite expensive
- 27. CREATING A CLOUD SERVICE ●Refactoring ●Introduce caches to take load from DB ●Use S3 and CloudFront to ship static content ●Store session data in DynamoDB ●Add Autoscaling
- 28. CREATING A CLOUD SERVICE ●Autoscaling ●Automatic resizing of compute clusters based on demand ●Integrated to Amazon CloudWatch ●Maximum and minimum pool sizes ●Autoscaling policies triggered by CloudWatch alarms
- 29. CREATING A CLOUD SERVICE Availability Zone Auto Scaling group
- 30. CREATING A CLOUD SERVICE ●Started with a simple web application ●Added several Amazon services ●Managed to shift load from application to services ●Added caches and CDN ●Added Autoscaling
- 31. CREATING A CLOUD SERVICE ●Next steps: ●SOA ●Loose coupling: decouple interactions ●Amazon services, don‘t reinvent the wheel ●Database federation ●Database sharding
- 32. REAL WORLD EXAMPLE ●Elastic architecture that grows and shrinks ●Multiple AZs ●Use case: streaming data ●Decoupling using Kinesis ●IAM Roles for managing credentials ●CloudWatch for monitoring
- 33. Internet Auto Scaling group Auto Scaling group Availability Zone Availability Zone ARCHITECTURE
- 34. ARCHITECTURE
- 35. “Vert.x is a lightweight, high performance application platform for the JVM that's designed for modern mobile, web, and enterprise applications.” Vert.x
- 36. ARCHITECTURE ●Main framework Vert.x ●mod-kinesis (Kinesis-Adapter for Vert.x) ●AWS Java SDK ●IAM roles for Amazon EC2 instances ●Coda Hale metrics and CloudWatch reporter ●Jedis (Redis client for Java) ●…
- 39. DEPLOYMENT EC2 instance with Docker registry (port 5000) S3 bucket to store Docker images
- 40. DEPLOYMENT Amazon Cloud Workstation GitHub Jenkins Python/Boto Docker Image Docker Registry S3 bucket with Docker Images
- 41. DEPLOYMENT
- 42. DEPLOYMENT
- 43. EC2 INSTANCES AND ELB python start_docker_instance.py -r <myregistry>:5000 -i tracking-ppv -t 95 -q 2 -s quality -d '-d -p 8080:8080' https://github.com/SaschaMoellering/aws-docker- scripts
- 44. EC2 INSTANCES AND ELB python start_elb.py -r <myregistry>:5000 -i tracking-ppv -t 95 -s quality -d '-d -p 8080:8080' https://github.com/SaschaMoellering/aws-docker- scripts
- 45. EC2 INSTANCES AND ELB
- 46. EC2 INSTANCES AND ELB
- 47. DEPLOYMENT ●Amazon EC2 Container Service (ECS): ● Container management service ● Fast ● Highly scalable ● Supports Docker
- 49. DEPLOYMENT
- 50. DEPLOYMENT
- 51. DEPLOYMENT
- 52. DEPLOYMENT #!/bin/bash echo ECS_CLUSTER = your_cluster_name >> /etc/ecs/ecs.config
- 53. DEPLOYMENT
- 54. DEPLOYMENT
- 55. DEPLOYMENT
- 56. DEPLOYMENT
- 57. DEPLOYMENT
- 58. DEPLOYMENT
- 59. DEPLOYMENT
- 60. DEPLOYMENT
Editor's Notes
- #6: Frage: wie können wir Skalieren? AWS als Basis Zeige heute: Patterns und Best Practices in der Cloud anhand von AWS Beispielapplikation in Java, die skaliert werden soll
- #8: 9 bzw. 10 verschiedene Regionen Region: separierte geographische Bereiche Neu: EU-Central in Frankfurt
- #9: Regions werden in Availability Zones unterteilt Jede AZ is isoliert, aber durch Leitungen mit niedriger Latenz verbunden A group of AZ is a Region A group of Datacenter is an AZ
- #15: Elastic IP addresses are static IP addresses designed for dynamic cloud computing. An Elastic IP address is associated with your account, not a particular instance, and you control that address until you choose to explicitly release it Im Fehlerfall (EC2-Instanz ist down) kann die EIP umgemappt werden
- #19: RDS: fully managed database service Supports: MySQL, Oracle, Microsoft SQL Server, PostgreSQL automatically patches the database software and backs up your database
- #21: - Multi AZ: Multi-AZ deployment option you can run mission critical workloads with high availability and built-in automated fail-over from your primary database to a synchronously replicated secondary database
- #22: - Multi AZ: Multi-AZ deployment option you can run mission critical workloads with high availability and built-in automated fail-over from your primary database to a synchronously replicated secondary database
- #29: - Minimum poolsizes is great if you have crashing EC2 instances,
- #32: Alle Bestandteile der Applikation in Services auslagern, die unabhängig voneinander skaliert werden können Lose Kopplung der Komponenten über Messaging Systeme
- #34: S3 DynamoDB RDS RedShift EMR
- #41: ----- Meeting Notes (26/10/14 22:22) ----- Fabric -> Boto
- #46: User-data script for ec2 - ein Mal bei initialen Setup der ec2-Instanz ausgeführt - Aktualisiert die Pakete - Installiert Docker - Startet Docker Service - Starten der Docker Instanzen mit den passenden Parametern
- #49: Cluster: logische Gruppierung von Container-Instanzen, auf die man Tasks plazieren kann Container Instance: Amazon EC2 Instanz, auf dem der ECS Agent läuft und die in einem Cluster registriert ist Task Definition: Beschreibung einer Applikation, die eine oder mehrere Container-Definitionen enthalten kann Task: Instanz einer Task Definition, die auf einer Container Instanz läuft Container: Ein Linux Container, der als Teil eines Tasks definiert wurde
- #56: - Task-definition