.NET Developer Days - Launching Patterns for Containers
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When you design your microservices strategy you will likely come up with patterns for when and how your services should execute. Traditional container scheduling services often deal with running container instances and distributing those instances across your cluster according to resource constraints – but your microservices design may also have other requirements such as message-based services that run and listen for topics; services that run on a scheduled job cycle; and services that may run in different ways based on initialization and have many instances running in parallel at any given time. This session looks at architecture patterns for container-based solutions; and illustrates the execution of these patterns with Docker containers and related tools. Concepts are platform independent but demos will be based on Kafka and Azure Container Service with Mesosphere DC/OS, Mesos, Marathon and Chronos.
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.NET Developer Days - Launching Patterns for Containers
- 1. Launching patterns for containers Michele Leroux Bustamante Cofounder / CIO Solliance Microservices / Security Architect @michelebusta
- 2. Container Platforms & Topology Amazon ECS Google Container Engine Azure Container Service Mesosphere DC/OS Kubernetes Docker Swarm / Docker EE Azure Service Fabric … Orchestration Cluster / Master Nodes Agent Nodes
- 3. Required Infrastructure Management cluster Agent node cluster Proxy/routing/discovery infrastructure Docker registry
- 4. Core Platform Features Scheduler Service registration and discovery Load balancing Routing Auto-scaling Self-healing Upgrade, rollback, recovery
- 5. Scheduling / Orchestration LEADER Master Nodes / Cluster Agent Nodes Schedule services Pull image Run container Service Description Registry
- 6. ### Docker commands on swarm master # ssh to the swarm master # show running containers (swarm and consul) $ docker ps # view consul logs $ docker logs --tail 20 containers_consul_1 # view swarm logs $ docker logs --tail 20 containers_swarm_1
- 7. ### making use of the swarm cluster #Show swarm cluster info $ docker -H tcp://0.0.0.0:2375 info #Show containers $ docker -H tcp://0.0.0.0:2375 ps #Run container on cluster $ docker -H tcp://0.0.0.0:2375 run -d -p 3000:3000 dasblonde/content-web $ docker -H tcp://0.0.0.0:2375 ps #Run another container, same port (gets different node) $ docker -H tcp://0.0.0.0:2375 run -d -p 3000:3000 dasblonde/content-web $ docker -H tcp://0.0.0.0:2375 ps
- 9. Resource Constraints Implicit constraints Physical hardware Technical limitation (port reuse) Explicit constraints CPU, memory, IO Determines node distribution Enables containment of resource usage Multi-tenancy Avoiding noisy neighbor
- 10. ### container constraints (port) #Run another container, same port (no more 8080 ports available, error) $ docker -H tcp://0.0.0.0:2375 run -d -p 8080:8080 dasblonde/helloworlddocker $ docker logs --tail 20 containers_swarm_1 #Make request to containers $ curl 10.0.0.4:8080 $ curl 10.0.0.7:8080
- 11. ### container constraints (image affinity, memory) #Memory affinity and image affinity $ docker -H tcp://0.0.0.0:2375 run -d -m 3G dasblonde/helloworlddocker $ docker -H tcp://0.0.0.0:2375 info $ docker -H tcp://0.0.0.0:2375 run -d -e affinity:image==dasblonde/helloworlddocker dasblonde/helloworlddocker #Failure due to applied constraints $ docker -H tcp://0.0.0.0:2375 run -d -m 3G -e affinity:image==dasblonde/helloworlddocker dasblonde/helloworlddocker #Node allocation with available memory $ docker -H tcp://0.0.0.0:2375 run -d -m 2G dasblonde/helloworlddocker $ docker -H tcp://0.0.0.0:2375 ps
- 14. Azure Load Balancer Public Agents /web No Load Balancer 80 3000 Private Agents 300180 /api 3001
- 15. Azure Load Balancer Public Agents /web Discovery via Load Balancer /web /web 80 /web 10101 ? ? 80 10101 ? ? Marathon-lb Private Agents /api /api /api /api 10102 ? ? 10102 ? ? Marathon-lb 80 Marathon-lb Marathon-lb
- 16. Server Density
- 17. Server Density
- 18. Room for Upgrades, Restarts What about me???
- 19. Adding Nodes What about me???
- 20. Redistribution of Instances What about me???
- 21. Room for New Instances What about me???
- 22. Scheduling Variations Long running HA tasks Web apps Web APIs Processing tasks Not HA OK to fail, restart Jobs Scheduled Run once, repeat n times Run on demand
- 23. IdentityServer Web Config Runtime API User Runtime API Users DB Config DB User Profile Web User Profile API User Profile Web User Profile API Redis Cache Client Web Client API Elastic Search Kibana Audit Kafka Projectors Projectors read eventually consistent
- 24. DEMO
Editor's Notes
- When you design your microservices strategy you will likely come up with patterns for when and how your services should execute. Traditional container scheduling services often deal with running container instances and distributing those instances across your cluster according to resource constraints – but your microservices design may also have other requirements such as message-based services that run and listen for topics; services that run on a scheduled job cycle; and services that may run in different ways based on initialization and have many instances running in parallel at any given time. This session looks at architecture patterns for container-based solutions; and illustrates the execution of these patterns with Docker containers and related tools. Concepts are platform independent but demos will be based on Kafka and Azure Container Service with Mesosphere DC/OS, Mesos, Marathon and Chronos.