Deployment

General

Alfalfa is a containerized application that can be deployed via docker-compose, Docker Swarm, or Kubernetes. Experience deploying and troubleshooting Docker applications is a pre-requisite.

Caveats

1. All deployment instructions here use environment variables that are committed to the repo. These are set to allow local deployments to work seamlessly out of the box, but it is your responsibility to update any sensitive variables (ie credentials) before deploying.
2. As configured in these examples, none of the deployed filesystems are persisted. This means that restarting any container will reset its state (think databases and uploaded files).
3. Unlike your average web application, Alfalfa is heavily dependent on in-memory state because the underlying models must run in memory. This means that deployments are not resilient to worker restarts; if a worker is restarted while a model is running, that model state will be lost.

Historian

Alfalfa includes optional Historian functionality, which is enabled by setting the HISTORIAN_ENABLE=true environment variable for the worker container and adding two containers to the stack:

1. InfluxDB for timeseries data storage
2. Grafana for visualization

Notes

1. Note that in images published to DockerHub, the datasource has been provisioned to connect to InfluxDB using the username and password in the repo's .env file. If you have updated these (as you should) for your deployment, you will also need to manually update them via the Grafana UI, which can be accessed at <grafana-host>/datasources/edit/1/
2. Model time is always treated as UTC, which is also the default for chart display. This means that plot filters like "past 6 hours" are relative to current UTC time.
3. The Historian only considers model time and has no concept of the real-world time as simulations run. All plots are of model time.
4. FMU time is weird and starts at epoch 0, which translates to start time 1970-01-01 00:00:00 in the Grafana time range selection tool.

Deploy with docker-compose

This assumes that you have installed Docker and docker-compose and are in the root of this repo.

1. update .env file: replace any credentials with real values and modify VERSION_TAG if appropriate to a tag available on DockerHub. To build the containers yourself, docker the pull command and append --build to the up commands below.
2. Without Historian: docker-compose pull && docker-compose up -d
3. With Historian: HISTORIAN_ENABLE=true && docker-compose -f docker-compose.yml -f docker-compose-historian.yml pull && docker-compose -f docker-compose.yml -f docker-compose-historian.yml up -d
4. Visit the web server at http://localhost
5. Visit the minio (file upload) server at http://localhost:9000
6. Visit the historian (if applicable) at http://localhost:3000
7. Clean up with docker-compose down or docker-compose -f docker-compose.yml -f docker-compose-historian.yml down

Deploy with Docker Swarm

1. Swarm deployments don't load .env, so do that explicitly: export $(cat .env | xargs)
2. Without Historian: docker stack deploy -c docker-compose.yml alfalfa
3. With Historian: HISTORIAN_ENABLE=true && docker stack deploy -c docker-compose.yml -c docker-compose-historian.yml alfalfa
4. Visit the web server at http://localhost
5. Visit the minio (file upload) server at http://localhost:9000
6. Visit the historian (if applicable) at http://localhost:3000
7. Clean up: docker stack rm alfalfa

Deploy with Kubernetes

Sample yaml files for Kubernetes deployments with and without historian are included in the deploy directory of this repo. Ingress is not included.

Ingress:

1. Web workload on port 80
2. Minio workload on port 9000
3. If historian enabled, Grafana container on port 3000

Env var updates

In addition to updating usernames and passwords as appropriate, if you are accessing your stack via ingress you will need the following update to env variables for the web container:

1. S3_URL should point to the configured host for minio.
2. S3_URL_EXTERNAL can be removed.