Here we look at web application asset and media serving with a docker swarm. Assets include java script, css, images and files required by the web application. Media means files that are uploaded by users. This media includes trained machine learning model files and out of bag data samples from this post.
Previously also assets and media were served by nginx on separate virtual machines. Scaling meant adding a new virtual machine to the group. Now these services have been moved to swarm and orchestrated with docker compose yml file. This way content distribution can be scaled faster. The whole application stack will move one-by-one to this swarm. All required docker images are built and stored locally. For more on using docker swarms see this official docker page.
The changes to architecture are highlighted in orange. There is a loadbalancer container, multiple (8) load balanced asset service containers and multiple (8) load balanced media service containers. As more capacity (# of replicas) is added to each of the services, the docker stack just needs to be updated.
* Jmeter test results before (4 replicas) and after scaling the services (8 replicas) are given at the end of this post. Note: Jmeter is set to follow and access embedded (media/asset) links on each page.
Steps
1. Create docker images for each component and verify that the containers work as expected.
Loadbalancer, Asset and Media services are based on nginx docker image. How to setup, build and test nginx docker images can be found here. For this web application, each service container is configured as needed with separate nginx conf files.
2. Create docker compose yaml file which will orchestrate the docker services.
Detailed steps on how to do this are here. This is essentially a file that lists out docker services that make up the application stack. Here loadbalancer, asset serving and media serving are services for the web application. Each service is configurable with the number of replicas (load balanced containers) and resource constraints per container. Each load balanced service is exposed via ports on the host machine. These ports as needed should be made available for access from downstream clients. Here only the loadbalancer is exposed over port 5000. The docker folder structure is as follows
$ docker stack deploy -c docker-compose.yml hud-cdn
4. Verifying services
5. Verifying the application by accessing via exposed port on docker host.
6. Jmeter load test results before and after scaling
6a. with 4 replicas each for asset service and media service, throughput is 156/sec
6b. with 8 replicas each for asset service and media service, throughput is 428/sec
