> ## Documentation Index
> Fetch the complete documentation index at: https://wavefront.rootflo.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Running several apps

> Keep apps isolated when they share Redis, a cluster or a console

Each app is its own floware deployment with its own worker, database and bucket. Apps often share infrastructure: one Kubernetes cluster, one Redis, one Wavefront Console. That works, provided each app's settings keep it separate.

## What must be unique per app

| Setting | Why |
| - | - |
| `CELERY_QUEUE_NAME` | Apps on one Redis would otherwise take each other's background runs from the shared `celery` queue. Use the app's name (`orders`, `claims`) on **both** its floware and its worker |
| `APP_NAME` | Prefixes the app's cache keys and its result stream, so one app's worker results never reach another app |
| Database (`DB_NAME` or a separate server) | Users, agents, workflows, executions and audit data per app |
| `APPLICATION_BUCKET` (or a separate prefix) | Definitions and execution files |
| The secret shared with the console | Each app trusts only requests signed for it |

A worker reads `CELERY_QUEUE_NAME` at start-up, and refuses to start if the value is invalid rather than silently falling back to the default queue.

## Checking isolation

After deploying a second app on shared Redis:

1. Start a background run in app A and watch the logs: only **app A's worker** should pick up the task.
2. Check that each app's floware consumes its own stream. The result consumer logs its stream key, which should begin with the app's `APP_NAME`.
3. In Redis, each app's queue key is named after its `CELERY_QUEUE_NAME`.

## Sharing a console

One Wavefront Console can manage every app. Register each app with its own public and private URL; console users see all registered apps. Keep production and non-production apps on separate consoles if different people should manage them.

## Model capacity

Apps that share a model deployment (the same provider key and deployment) share its rate limits. Give apps with heavy image or video workloads their own deployment, or capacity planned for both.


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