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Deep Dive on Microservices and Amazon ECS

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Explore the reasoning and concepts behind microservices and how containers simplify building microservices based applications.

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Deep Dive on Microservices and Amazon ECS

  1. 1. © 2015, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Pierre Steckmeyer, Solutions Architect September 22nd, 2016 Deep Dive on Microservices and Amazon ECS
  2. 2. What to Expect from this Session Microservices: What are They? Challenges of Microservices Microservices on Amazon ECS
  3. 3. What are Microservices?
  4. 4. “service-oriented architecture composed of loosely coupled elements that have bounded contexts” Adrian Cockcroft (former Cloud Architect at Netflix, now Technology Fellow at Battery Ventures)
  5. 5. Monolithic vs. SOA vs. Microservices SOA Coarse- grained Microservices Fine-grained Monolithic Single Unit
  6. 6. Order UI User UI Shipping UI Order Service User Service Shipping Service Data Access Monolithic Architecture
  7. 7. Monolithic Architecture – Scaling
  8. 8. Order UI User UI Shipping UI Order Service User Service Shipping Service Microservices Architecture
  9. 9. Order UI User UI UI Order Service Service Shipping Service Order UI Order UI User UI UIShipping UI Order ServiceOrder Service Service Service Service Service User Service Shipping Service Microservices Architecture – Scaling
  10. 10. Characteristics of Microservices Architectures Do one thing well Independent Decentralized Black Box Polyglot You build it, you run it
  11. 11. What are Microservices challenges? Resource and State Management Monitoring Service Discovery Deployment
  12. 12. What are Microservices challenges? Resource and State Management Monitoring Service Discovery Deployment
  13. 13. Amazon EC2 Container Service
  14. 14. Containers are natural for services Simple to model Any app, any language Image is the version Test & deploy same artifact Stateless servers decrease change risk
  15. 15. Server Guest OS Bins/Libs Bins/Libs App2App1 Managing one host is straightforward
  16. 16. Managing a fleet is hard Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS Server Guest OS AZ 1 AZ 2 AZ 3
  17. 17. Easily Manage Clusters for Any Scale Nothing to run Complete state Control and monitoring Scale
  18. 18. Scalable
  19. 19. Flexible Container Placement Applications Batch jobs Multiple schedulers
  20. 20. Designed for use with other AWS services Elastic Load Balancing Amazon Elastic Block Store Amazon Virtual Private Cloud AWS Identity and Access Management AWS CloudTrail
  21. 21. Clusters Regional Resource pool Grouping of Container Instances Start empty, dynamically scalable
  22. 22. Tasks Unit of work Grouping of related Containers Run on Container Instances
  23. 23. Services Good for long-running applications Load Balance traffic across containers Automatically recover unhealthy containers Discover services
  24. 24. What are Microservices challenges? Resource and State Management Monitoring Service Discovery Deployment
  25. 25. Monitoring with Amazon CloudWatch Metric data sent to CloudWatch in 1-minute periods and recorded for a period of two weeks Available metrics: CPUReservation, MemoryReservation, CPUUtilization, MemoryUtilization Available dimensions: ClusterName, ServiceName
  26. 26. Monitoring with Amazon CloudWatch
  27. 27. Monitoring with Amazon CloudWatch Use the Amazon CloudWatch Monitoring Scripts to monitor additional metrics, e.g. disk space: # Edit crontab > crontab -e # Add command to report disk space utilization to CloudWatch every five minutes */5 * * * * <path_to>/mon-put-instance-data.pl --disk-space-util --disk-space-used --disk- space-avail --disk-path=/ --from-cron
  28. 28. Monitoring Amazon ECS with Datadog
  29. 29. Monitoring Amazon ECS with Sysdig Cloud
  30. 30. What are Microservices challenges? Resource and State Management Monitoring Service Discovery Deployment
  31. 31. Service Discovery with ECS Services & Route 53 Route 53 private hosted zone Set search path on hosts with DHCP option sets Define ECS services with ELB Create CNAMEs for each ELB
  32. 32. Service Discovery with ECS Services & Route 53 Task Task TaskTask ECS Service Application router, e.g. nginx Internal ELB with CNAME, e.g. api.example.com Route 53 private zone, e.g. example.com
  33. 33. Service Discovery with Weaveworks DNS interface for cross-host container communication Gossip protocol to share grouped updates Overlay network between hosts
  34. 34. Service Discovery with Weaveworks
  35. 35. Service Discovery and Configuration Management with Consul Three main components: • Consul agent - Runs on each node, responsible for checking the health of the services and of the node itself. • One or more Consul servers - Store and replicate data, leader elected using the Raft consensus algorithm • Registrator agent - Automatically register/deregisters services based on published ports and metadata from the container environment variables defined in the ECS task definition
  36. 36. Service Discovery and Configuration Management with Consul ECSCluster consul-server ECS Instance consul-agent registrator ECS Instance Back end 1 Back end 2 consul-agent registrator ECS Instance Front end ECSCluster
  37. 37. What are Microservices challenges? Resource and State Management Monitoring Service Discovery Deployment
  38. 38. Scheduling Containers on ECS Batch Jobs ECS Task scheduler Run tasks once Batch jobs RunTask (random) StartTask (placed) Long-Running Apps ECS Service scheduler Health management Scale-up and scale-down AZ aware Grouped Containers
  39. 39. Scheduling Containers: Long-running App Optionally run your service behind a load balancer. ELB currently supports a fixed relationship between the load balancer port and the container instance port. If a task fails the ELB health check, the task is killed and restarted (until service reaches desired capacity).
  40. 40. Scheduling Containers: Long-running App Update service’s task definition (rolling update) Specify a deployment configuration for your service: • minimumHealthyPercent: lower limit (as a percentage of the service's desiredCount) of the number of running tasks that must remain running in a service during a deployment. • maximumPercent: upper limit (as a percentage of the service's desiredCount) of the number of running tasks that can be running in a service during a deployment.
  41. 41. Scheduling Containers: Long-running app Deploy using the least space: minimumHealthyPercent = 50%, maximumPercent = 100%
  42. 42. Scheduling Containers: Long-running App Deploy quickly without reducing service capacity: minimumHealthyPercent = 100%, maximumPercent = 200%
  43. 43. Scheduling Containers: Long-running App Blue-Green Deployments • Define two ECS services • Each service is associated w/ ELB • Both ELBs in Route 53 record set with weighted routing policy, 100% Primary, 0% Secondary • Deploy to Blue or Green service and switch weights TaskTask Route 53 record set with weighted routing policy 0% 100%
  44. 44. Microservices development lifecycle developers delivery pipelinemicroservices build pipeline build pipeline build pipeline build pipeline build pipeline build pipeline build pipeline build pipeline build pipeline build pipeline build pipeline build pipeline build pipeline build pipeline build pipeline
  45. 45. Continuous Delivery to ECS with Jenkins 4. Push image to Docker registry 2. Build image from sources 3. Run test on image 1. Code push triggers build 5. Update Service 6. Pull image
  46. 46. Continuous Delivery to ECS with Jenkins Easy Deployment Developers – Merge into master, done! Jenkins Build Steps Trigger via Webhooks, Monitoring, Lambda Build Docker image via Build and Publish plugin Push Docker image into Registry Register Updated Job with ECS API
  47. 47. ECS CI/CD Partners
  48. 48. Continuous Delivery to ECS with Shippable
  49. 49. Demo
  50. 50. Demo TaskTask Task
  51. 51. Thank you!

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