Docker in the Cloud
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Shows how to abstract Cloud specific infrastructure in AWS, Azure and own DC using a demo application written in Vertx.
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Docker in the Cloud
- 1. Sascha Möllering | zanox AG Docker in the Cloud
- 2. About me Sascha Möllering [email protected] [email protected] Lead Engineer / DevOps Hipster zanox AG http://autoscaling.io @sascha242
- 3. About me Java Magazin 11.14 Architektur im Kontext der Cloud: Patterns und Best Prac AWS Virtual Cloud Summit Continuous delivery in AWS using Docker http://aws-summit.de/ Entwickler Spezial: Docker Über den Wolken: Ein Erfahrungsbericht zum Docker-Ein
- 4. Agenda • Problem? • Real World example • Docker implementations • Deployment • Q&A
- 6. Problem? • Using different Cloud providers • Additionally: own DC • Different infrastructure • Different deployment mechanisms
- 7. Solution! • Different applications! • For each deployment target -> different package!
- 10. • One container to rule them all! • Application detects deployment target • Application uses specific infrastructure Real Solution!
- 11. Real World example • JVM based event-driven application • Ingests data into bus system • Uses Redis as a cache • Base framework is Vert.x • Pre-build Docker image
- 13. Real World example • Deployment targets: – Own data center – Amazon Web Services – Microsoft Azure
- 14. Real World example • Our own data center: – Linux servers with Docker 1.6 – Apache Kafka 0.8.1/0.8.2 • Topics and partitions • Easy to write, hard to read from – Redis 2.8
- 15. Real World example • Amazon Web Services: – EC2 instance with Docker 1.6 – Amazon Kinesis • Amazon’s implementation of Kafka (?) • Streams and shards • KCL does the heavy lifting – ElastiCache with Redis engine • Amazon’s implementation of Redis
- 16. Real World example • Microsoft Azure: – Azure Ubuntu VM with Docker 1.6 – Azure Service Bus • Bus system in Azure • AMQP and JMS • Problem: no partitioning for Java – Azure Cache • Redis implementation in Azure
- 17. Real World example • For Redis: Jedis client in all cases • Difference: bus system – mod-kafka – mod-kinesis – mod-service-bus
- 18. Real World example • mod-kafka: – Vert.x module for Apache Kafka – Recieves events by other verticles – Sends events to Kafka broker – Either Strings or binary data – Supports StatsD – Based on Apache Kafka Java API
- 19. Real World example • mod-kinesis: – Vert.x module for Amazon Kinesis – Recieves events by other verticles – Sends events to Kinesis stream – Either Strings or binary data – Support for partitioning in events – Based on AWS Java SDK
- 20. Real World example • mod-service-bus: – Vert.x module for Azure Service Bus – Recieves events by other verticles – Support for binary data only ATM – No partitioning (Service Bus problem) – Based on AMQP and JMS
- 21. Real World example But … how can we detect where the application is running?
- 23. Real World example boolean isAzure = true; try { RoleEnvironment.getRoles(); } catch (Exception exc) { isAzure = false;}
- 24. Real World example • Problem: not working in Docker container • Alternative: check for /etc/waagent.conf • File has to be mapped in Docker container
- 25. Real World example • StarterVerticle pattern: – Bootstrapping Vert.x application – Start all verticles in StarterVerticle – Deploy all modules in StartVerticle
- 28. Docker implementations • Basic implementation: – EC2 using User Data – Install Docker and start service – Either pull Container in User Data script – Or Remote API
- 29. Docker implementations • AWS OpsWorks: – No “official” support – Docker Chef Cookbook by AWS – Problem: Docker Images are build in the Cookbook
- 30. Docker implementations • Amazon Elastic Beanstalk: – Support for single/multi container environments – ELB support on container level – Multi container environments -> ECS resources – Running containers locally is possible
- 31. Docker implementations • Amazon EC2 Container Service: – Container management service for Docker – Description language for applications (“task definition”) – Supports batch mode (taks that only run once) – Supports long running taks – ELB support on container level
- 33. Docker implementations • xplat-cli: – Support for: • Ubuntu from Azure Image Gallery • Custom Linux image with Azure Linux VM Agent – Similar to plain EC2 approach
- 34. Docker implementations • xplat-cli: – azure vm docker create – Docker remote API
- 36. Deployment
- 37. Deployment Amazon Cloud Workstation GitHub Jenkins Python/Boto Docker Image Docker Registry S3 bucket with Docker Images
- 38. Deployment
- 39. Deployment
- 40. Deployment • AWS OpsWorks: – Docker Chef Cookbook by AWS – Add a new stack containing the Cookbook – Add a new layer and add custom recipes – Docker Images are build in the Cookbook – Use custom JSON to modify stack configuration
- 41. Deployment • Amazon Elastic Beanstalk: – Create an application using console or CLI – Create Dockerrun.aws.json to deploy a Docker container – Create a ZIP-file containing application files (optional)
- 42. Deployment 1. Create a cluster 2. Create a task definition 3. Create a service 4. Configure cluster 5. Run task
- 43. Deployment
- 44. Deployment • Remote API is exposed docker --tls -H tcp://<vm-name- you-used>.cloudapp.net:4243 info
- 45. Deployment • Useful Docker clients: – Spotify Docker Client – docker-py
- 46. Deployment
- 47. Deployment
- 48. Q&A