add some details about k8s deployments and how to run the test suite

docs/deploy.md

@@ -16,7 +16,7 @@ podman run -it -p 8080:8080 --env-file .env -v LOCAL_DB_PATH:DB_FILE gantry
 
 Where `LOCAL_DB_PATH` is the absolute path to the database file on your local system. `DB_FILE` is where you would like the application to access the database. Make sure this lines up with your environment.
 
-When running Gantry within Kubernetes, you could use [persistent volumes](https://kubernetes.io/docs/concepts/storage/persistent-volumes/). The only requirement is that the database should exist outside the container for backup and persistence purposes.
+When running Gantry within Kubernetes, you could use [persistent volumes](https://kubernetes.io/docs/concepts/storage/persistent-volumes/). The only requirement is that a copy of the database should exist outside the container for backup and persistence purposes.
 
 ## Environment
 
@@ -34,3 +34,15 @@ The following variables should be exposed to the container. Those **bolded** are
 - `PREDICT_STRATEGY` - optional mode for the prediction algorithm
     - options: 
         - `ensure_higher`: if the predicted resource usage is below current levels, it will disregard the prediction and keep what would be allocated without Gantry's intervention
+
+## Kubernetes
+
+Gantry can be deployed in a Kubernetes cluster. For an example of how we do this within Spack's web infrastructure, see [this folder](https://github.com/spack/spack-infrastructure/tree/main/k8s/production/spack/gantry-spack-io) containing configuration files and instructions. 
+
+While most details are better suited to be documented with the cluster, there are some considerations that are general to any Gantry deployment.
+
+### Database
+
+We have made an architectural decision to depend on SQLite as the database engine. Before you deploy Gantry into a cluster, you should ensure that the file will be backed up on a regular basis, in the case that unexpected circumstances corrupt your data. This can be achieved using [Litestream](https://litestream.io), which will continuously replicate the database with the storage provider of your choice. See the cluster configuration linked above for details.
+
+When you first deploy the application on the cluster, be sure to run `/db/init_db.py <db_path>` to initialize an SQLite file with default tables, and to apply any migrations.

docs/readme.md

@@ -6,5 +6,6 @@
 2. [Data Collection](data-collection.md)
 3. [Architecture](arch.md)
 4. [Prediction](prediction.md)
-5. [Deployment](deploy.md)
-6. [API Endpoints](api.md)
+5. [Testing](testing.md)
+6. [Deployment](deploy.md)
+7. [API Endpoints](api.md)

docs/testing.md

@@ -0,0 +1,19 @@
+# Testing
+
+Gantry uses `pytest` to manage its testing suite. Make sure you have installed `pytest`, `pytest-aiohttp`, and `pytest-mock` in your environment.
+
+The tests cover the collection and prediction functionalities, as well as core functionalities like helper functions and database actions.
+
+Running all tests:
+
+```
+python -m pytest -s gantry
+```
+
+If you would like to see details about test coverage, install `coverage` and run:
+
+```
+coverage run -m pytest -s gantry && coverage html
+```
+
+This will create a folder in the top-level directory containing an `index.html` file which you can open in a browser.