Deploy a Dash application

A Dash app runs on Sevalla as an application. Dash is built on Flask, so Ingot, Sevalla’s builder, treats it as a Flask application: it installs requirements.txt, finds the Flask server that app.py creates and starts it with Gunicorn in the web process, on the port in the PORT environment variable. Every callback is an HTTP request to /_dash-update-component, so the app needs no WebSocket and no sticky sessions.

At a glance


Source	A Git repository
Build	Ingot (Python 3.14, pip), or the Dockerfile
Start command	`gunicorn -c /etc/ingot/gunicorn.conf.py app:server`, which Ingot detects from `server = Flask(__name__)` in `app.py`
Port	The `PORT` environment variable, `8080` by default
Processes	Web process
Services	None
Disk	None
Health check	`GET /healthz` returns `200` with `ok` (readiness probe)
Size	H1 for the web process

Environment variables

Variable	Required	Available during	Secret	Value
`WEB_CONCURRENCY`	No	Runtime	No	Gunicorn worker processes, `1` when unset. Raise it on sizes larger than H1
`PORT`	No	Runtime	No	Set by Sevalla to the web process port

Before you begin

A Sevalla company with a payment method, and a GitHub, GitLab or Bitbucket account for the repository. See Git providers.
Python 3.14 on your computer.

Create the project

Create a virtual environment and install Dash and Gunicorn:

mkdir sales-dashboard && cd sales-dashboard
python3 -m venv .venv
source .venv/bin/activate
pip install dash gunicorn

Package	What it does
`dash`	Dash 4.5, with Flask 3.1 and Plotly 7.1
`gunicorn`	The production WSGI server. Ingot starts the web process with it when it’s installed.

Keep local files out of the repository:

.gitignore

.venv/
__pycache__/

Create the app, a bar chart that a dropdown updates through a callback:

app.py

import plotly.graph_objects as go
from dash import Dash, Input, Output, dcc, html
from flask import Flask

MONTHS = ["Jul", "Aug", "Sep", "Oct"]
SALES = {"Mugs": [120, 135, 160, 150], "Shirts": [80, 95, 90, 110]}

server = Flask(__name__)
app = Dash(__name__, server=server, title="Storefront sales")

app.layout = html.Div(
    [
        html.H1("Storefront sales"),
        dcc.Dropdown(list(SALES), "Mugs", id="product", clearable=False),
        dcc.Graph(id="chart"),
    ]
)


@app.callback(Output("chart", "figure"), Input("product", "value"))
def update_chart(product):
    return go.Figure(go.Bar(x=MONTHS, y=SALES[product]))


@server.get("/healthz")
def healthz():
    return "ok"


if __name__ == "__main__":
    app.run(debug=True)

Run python app.py and open http://127.0.0.1:8050. The page shows Storefront sales and a chart; choose Shirts and the chart changes. Press Ctrl+C to stop it.

Prepare the project for Sevalla

Create the Flask server in app.py

Ingot has no Dash detection of its own. Dash depends on Flask, so Ingot treats the project as a Flask application, looks for a Flask object created at the top level of main.py, app.py or another common module, and serves it with Gunicorn. server = Flask(__name__) is that object, and Dash’s server argument runs the app on it instead of on a Flask object of its own. Many Dash apps write server = app.server instead. That’s the same Flask object, but Ingot can’t see it without running the code, so it runs python app.py, Dash’s development server, which listens on 127.0.0.1 only: see Troubleshoot. app.run(debug=True) sits under if __name__ == "__main__":, so it runs only when you start the file yourself. Gunicorn imports app.py without running it, so Dash’s debug tools and hot reload stay off in production.

Pin the Python version

Ingot builds on Python 3.14, its default line, unless the project sets a version. Pin the version you develop with in .python-version, so the build doesn’t change when a new Ingot release moves its default line:

.python-version

3.14

See Pin the Python version.

List the dependencies

Ingot installs requirements.txt with pip, into a virtual environment at /app/.venv that’s on the PATH:

pip freeze > requirements.txt

pip freeze lists Flask, which Dash installed. Ingot looks for the Flask server only when Flask is in requirements.txt, so keep it there if you write the file by hand.

File	Why Sevalla needs it
`app.py`	Creates the Flask server that Ingot finds and Gunicorn serves, `app:server`.
`requirements.txt`	Ingot installs the exact versions in it, and reads Flask and Gunicorn from it to choose the start command.
`.python-version`	Ingot builds on the Python line it names, 3.14.

How Ingot starts the app

Ingot starts the web process with gunicorn -c /etc/ingot/gunicorn.conf.py app:server, which the build plan shows in its Start row:

Gunicorn listens on 0.0.0.0 and the port in the PORT environment variable, which Sevalla sets to the web process’s port (8080 by default).
Ingot’s Gunicorn settings run 1 worker process with 4 threads, so 4 callbacks run at once, and give requests 20 seconds to finish after SIGTERM. On a larger size, set the WEB_CONCURRENCY environment variable to the number of worker processes, for example 2: Gunicorn reads it at start.
Dash serves its JavaScript and CSS from the app itself, so no build step and no static file server are needed.

To start Gunicorn with other options, set the web process’s start command; see Set the start command. Commit everything and push it to your Git provider:

git init
git add .
git commit -m "Prepare for Sevalla"
git branch -M main
git remote add origin https://github.com/acme/sales-dashboard.git
git push -u origin main

Deploy to Sevalla

These steps build with Ingot. To build from your own Dockerfile instead, see Deploy with a Dockerfile.

Create the application

In the sidebar, click Applications, then click Create > Application. Under Source, click Private repository, then choose the Git provider, the Repository and the Branch. Under Location, choose a Data center. Keep the Size at H1 or choose a larger one, then click Create application. The application opens on its Overview tab with the status Not deployed yet: creating an application doesn’t deploy it.

Deploy

Click the Overview tab, then click Deploy now under Recent deployments. Check the Branch and click Deploy.

Turn on auto-deploy

To deploy every push to the branch automatically, click the Settings tab, then click Update auto-deploy in the Auto-deploy section. Turn on Auto-deploy and click Update auto-deploy. See Deployments.

Verify the deployment

On the Deployments tab, click the deployment. Its Build log shows Ingot’s build plan: Python 3.14 from .python-version, pip from requirements.txt, and Flask with the Gunicorn command for app:server.

Build log

╭─ ■ Flask · Python 3.14 ─────────────────────────────────────────────────────────────────────╮
│ Python           3.14                                                .python-version "3.14" │
│ Package manager  pip                                                 requirements.txt       │
│ Framework        Flask                                               app.py                 │
│ Start            gunicorn -c /etc/ingot/gunicorn.conf.py app:server  Flask                  │
├─ Image ─────────────────────────────────────────────────────────────────────────────────────┤
│ Build            python:3.14-slim-trixie                                                    │
│ Runtime          python:3.14-slim-trixie                                                    │
│ User             1000:1000                                                                  │
│ Init             tini                                                                       │
│ Port             $PORT, default 8080                                                        │
╰────────────────────────────────────────────────────────────────────────────── Ingot v0.4.1 ─╯

Wait for the deployment’s status to change to Deployed. The application’s status next to its name changes to Running, and the web process’s runtime logs show Listening at: http://0.0.0.0:8080 and Using worker: gthread.
Click the domain under the application’s name, for example sales-dashboard-x7k2m.sevalla.app. The page shows Storefront sales and the chart; choose Shirts and the chart changes, which means the callback ran on the server.

Check the page, the health route and a callback from a terminal, with your application’s domain. The last command sends the request that the browser sends when you choose Shirts, and prints the chart’s values:

curl -s https://sales-dashboard-x7k2m.sevalla.app/ | grep -o '<title>.*</title>'
curl -s https://sales-dashboard-x7k2m.sevalla.app/healthz; echo
curl -s https://sales-dashboard-x7k2m.sevalla.app/_dash-update-component \
  -H "Content-Type: application/json" \
  -d '{"output":"chart.figure","outputs":{"id":"chart","property":"figure"},"inputs":[{"id":"product","property":"value","value":"Shirts"}],"changedPropIds":["product.value"]}' \
  | jq -c '.response.chart.figure.data[0].y'

<title>Storefront sales</title>
ok
[80,95,90,110]

To check the deployment through the API, use APP_ID and DEPLOYMENT_ID from Deploy with the API. Get deployment (getDeploymentV3) returns the status, and Get application deployment logs (getApplicationDeploymentLogsV3) returns the build log, which search filters:
curl -s https://api.sevalla.com/v3/applications/$APP_ID/deployments/$DEPLOYMENT_ID \ -H "Authorization: Bearer $SEVALLA_API_KEY" | jq -r .status curl -s "https://api.sevalla.com/v3/applications/$APP_ID/deployments/$DEPLOYMENT_ID/logs?search=has%20been" \ -H "Authorization: Bearer $SEVALLA_API_KEY" | jq -r '.[].message'
success 🚀 Web has been deployed successfully.
The log’s messages carry terminal color codes around the text. The CLI has sevalla apps deployments get and sevalla apps deployments logs, and the MCP server get_deployment and get_deployment_logs.

The application header with its name, Running status, repository, branch and the domain that opens the application

If the deployment fails, read its build log, then see Troubleshoot and Troubleshoot Ingot builds.

Add a health check

Without a readiness probe, a new instance receives traffic as soon as its container starts, before Gunicorn has imported the app. Point the probe at /healthz, the Flask route in app.py, which returns ok:

Open the web process

On the application’s Processes tab, click ⋯ on the Web process, then click Update process.

Turn on the readiness probe

Under Health checks, turn on Readiness probe and set the Path to /healthz. Keep the Port at the web process’s port, 8080 unless you changed it.

Save and deploy

Click Update process, then click Deploy in the undeployed changes bar at the bottom of the page.

The deployment reaches Deployed once the new instance passes the probe. See Health checks. Deploy with the API sets the same probe. Get process (getProcessV3) returns it in readiness_probe:

curl -s https://api.sevalla.com/v3/applications/$APP_ID/processes/$WEB_ID \
  -H "Authorization: Bearer $SEVALLA_API_KEY" | jq -c .readiness_probe

{"httpGet":{"path":"/healthz","port":8080,"scheme":"HTTP"},"initialDelaySeconds":0,"periodSeconds":10,"timeoutSeconds":1,"successThreshold":1,"failureThreshold":3}

Scale the app

Dash keeps no session on the server: each callback request carries the inputs it needs, so any worker process on any instance can answer it. Scale in two ways:

More instances. On the Processes tab, raise the web process’s instance count, or turn on autoscaling. Sevalla spreads requests across the instances with no sticky sessions, which Dash doesn’t need. See Scaling.
More worker processes per instance. Set the WEB_CONCURRENCY environment variable, for example to 2. With 2 instances on H1 and WEB_CONCURRENCY set to 2, each instance used about 140 MB of its 0.3 GB.

Each worker process has its own memory, so a value that one callback stores in a global variable isn’t there for the next callback, which can run in another process. Keep per-user data in the browser with dcc.Store, and shared data in a database.

Deploy with a Dockerfile

Ingot needs no Dockerfile. Write your own when you want full control of the image: the base image, the system packages and every layer. Add a Dockerfile and a .dockerignore to the root of the repository:

Dockerfile

FROM python:3.14-slim-trixie

ENV PYTHONUNBUFFERED=1 \
    PORT=8080

RUN useradd --uid 1000 --create-home app
WORKDIR /app

COPY requirements.txt .
RUN pip install --no-cache-dir --root-user-action=ignore -r requirements.txt

COPY . .
RUN python -m compileall -q .

USER 1000:1000
EXPOSE 8080
CMD ["gunicorn", "app:server", \
     "--threads", "4", "--keep-alive", "0", \
     "--graceful-timeout", "20", "--worker-tmp-dir", "/dev/shm"]

Line or choice	Why
`python:3.14-slim-trixie`	The Python line that `.python-version` pins, on Debian 13, as Ingot builds it. A line tag picks up each patch release and security fix when you deploy again; a digest would stay on one release.
One stage	pip installs prebuilt wheels, so the build needs no compiler and leaves nothing to clean up.
`requirements.txt` before the code	Docker reuses the installed packages until `requirements.txt` changes, so a code change rebuilds only the last layers.
`pip install` into the image’s Python	The image runs one application, so it needs no virtual environment. `--root-user-action=ignore` silences pip’s warning about installing as root.
`compileall`	Compiles the code at build time, because the app can’t write to `/app` when it runs.
`useradd` and `USER 1000:1000`	Runs Gunicorn as an unprivileged user with a home directory, where Gunicorn keeps its control socket. The code stays owned by root, so the app can’t change it.
Gunicorn options	Gunicorn listens on `0.0.0.0` and the port in `PORT` on its own, and reads `WEB_CONCURRENCY`. `--threads 4`, `--graceful-timeout 20` and `--worker-tmp-dir /dev/shm` match Ingot’s settings. `--keep-alive 0` closes each connection after its response: otherwise Gunicorn 26.2 waits out the whole graceful timeout before it stops when the proxy holds an idle connection open.
No init process	Gunicorn runs as PID 1, handles `SIGTERM` itself, finishes the callbacks in progress and exits.

.dockerignore

.git
.venv
**/__pycache__
.env*
Dockerfile
.dockerignore

Commit and push both files. Ingot doesn’t use the Dockerfile, so you can keep it in a repository that builds with Ingot, but it adds the .dockerignore patterns to its own: its build plan shows an Ignored row with 6 patterns from .dockerignore. Then switch the application to the Dockerfile build strategy:

Choose the Dockerfile build strategy

On the application’s Settings tab, in the Build strategy section, click Update build strategy. Click Dockerfile, keep the Dockerfile path Dockerfile and the Docker context ., then click Update build strategy.

Deploy

Click the Overview tab, then click Deploy now under Recent deployments. Check the Branch and click Deploy.

The Update build strategy sheet with Dockerfile selected, the Dockerfile path, the Docker context and the Docker registry credential

The build log shows 📦 Building and pushing docker image using Dockerfile... where Ingot’s build plan was. The checks in Verify the deployment print the same output, and the deployment’s Dockerfile tab shows your Dockerfile. When an instance stops, its runtime logs end with Shutting down: Master. See Dockerfile, and Build from the Dockerfile with the API to switch with the API.

Deploy changes

With Auto-deploy on, every push to the branch starts a deployment; otherwise, click Deploy now for each change. Each deployment builds the image, then replaces the web process’s instances. After you install a package, run pip freeze > requirements.txt again and commit it. See Deployments.

Use environment variables

Keep API keys and connection strings in environment variables and read them with os.environ, for example os.environ["SALES_API_TOKEN"] in a callback. Variables apply at the next deployment.

Add a custom domain

To serve the app from your own domain, such as dashboard.example.com, add the domain on the application’s Domains tab and create the DNS records that Sevalla shows. Dash and Flask accept any host by default, so no code change is needed. Custom domains need a web process larger than H1, so scale the web process first. See Custom domains.

Troubleshoot

Symptom	Cause	Fix
The build plan’s Start row shows `python app.py`, and the build log warns `Flask is a dependency, but no module Ingot searches creates its application at the top level, so the image runs app.py`. The runtime logs show `Dash is running on http://127.0.0.1:8080/`, and with the readiness probe the deployment ends with `Failed to deploy Web.`	`app.py` gets the Flask server with `server = app.server`, which Ingot can’t see, so the image runs Dash’s development server. It listens on `127.0.0.1`, which nothing outside the container reaches.	Create the server with `server = Flask(__name__)` and pass it to `Dash(server=server)`, as in Create the Flask server in app.py, then push.
The build plan’s Start row shows `python app.py`, without the warning	`requirements.txt` doesn’t list Flask, so Ingot doesn’t look for a Flask server.	Run `pip freeze > requirements.txt` and push.
The access logs show `200` for paths such as `/.env` or `/wp-config.php`	Dash answers every path it has no route for with its own page, so that multi-page apps can route in the browser. Scanners request such paths on every new domain.	Nothing leaks: the response is the app’s HTML. `curl -s https://sales-dashboard-x7k2m.sevalla.app/.env \| grep -o '<title>.*</title>'` prints `<title>Storefront sales</title>`.
The runtime logs show `dash.exceptions.DependencyException: "dash" is registered but the path requested is not valid.`	A request for a file under `/_dash-component-suites/` that the installed Dash doesn’t have, as scanners send. Dash answers `500`.	Nothing to fix when the path isn’t one your pages load. If the app’s own pages fail to load a component, check that `requirements.txt` has the Dash version you tested.

For more causes, see Troubleshoot Ingot builds and Troubleshoot builds and deployments.

Deploy with the API

These calls make the same deployment as Deploy to Sevalla and Add a health check, in an order that a script or an AI agent runs as it is. Each step names the Sevalla API operation, then the CLI command and the MCP server tool that do the same. You need:

An API key with the Company developer role, or the APP:CREATE, APP:READ and APP:UPDATE permissions, in the SEVALLA_API_KEY environment variable. The CLI reads the key from SEVALLA_API_TOKEN.
The repository on a Git provider that’s connected to your Sevalla account. See Git providers. Creating the application checks it: when Sevalla can’t read the repository, the call returns 400 with Cannot access repository https://github.com/acme/sales-dashboard: Repository not found or you don't have access., followed by where to grant access.
curl and jq.

Choose the location

List clusters (listClustersV3) returns the locations your company can use, each with its id, the display_name that the dashboard shows and its region ID in location. Keep the ID of the one you want by its region ID, such as eu-frankfurt-1 for Frankfurt, Germany. Locations lists them all:

CLUSTER_ID=$(curl -s https://api.sevalla.com/v3/resources/clusters \
  -H "Authorization: Bearer $SEVALLA_API_KEY" \
  | jq -r '.[] | select(.location == "eu-frankfurt-1") | .id')

CLI: sevalla resources clusters. MCP: get_platform_options.

Create the application

Create application (createApplicationV3) creates the application with a web process and auto-deploy off. It builds with Ingot (build_type is ingot) and isn’t deployed yet:

APP_ID=$(curl -s -X POST https://api.sevalla.com/v3/applications \
  -H "Authorization: Bearer $SEVALLA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"display_name":"sales-dashboard","cluster_id":"'"$CLUSTER_ID"'","source":"privateGit","git_type":"github","repo_url":"https://github.com/acme/sales-dashboard","default_branch":"main"}' \
  | jq -r .id)

CLI:

sevalla apps create --name sales-dashboard --cluster $CLUSTER_ID --source privateGit --git-type github --repository https://github.com/acme/sales-dashboard --branch main

. MCP: create_application with deploy set to false.

Find the domain

List application domains (listApplicationDomainsV3) returns the domain that Sevalla gives the application. It appears a few seconds after the application is created, so ask until it’s there:

for i in $(seq 1 24); do
  HOST=$(curl -s https://api.sevalla.com/v3/applications/$APP_ID/domains \
    -H "Authorization: Bearer $SEVALLA_API_KEY" | jq -r '.data[]? | select(.is_primary) | .name')
  [ -n "$HOST" ] && break
  sleep 5
done
echo "$HOST"

sales-dashboard-x7k2m.sevalla.app

CLI: sevalla apps domains list --app-id $APP_ID. MCP: get_application.

Find the web process

List processes (listProcessesV3) returns the web process that the application was created with:

WEB_ID=$(curl -s https://api.sevalla.com/v3/applications/$APP_ID/processes \
  -H "Authorization: Bearer $SEVALLA_API_KEY" \
  | jq -r '.data[] | select(.type == "web") | .id')

CLI: sevalla apps processes list --app-id $APP_ID. MCP: get_application.

Find the H1 size

List process resource types (listProcessResourceTypesV3) returns the sizes by name, in lowercase:

H1_ID=$(curl -s https://api.sevalla.com/v3/resources/process-resource-types \
  -H "Authorization: Bearer $SEVALLA_API_KEY" \
  | jq -r '.[] | select(.name == "h1") | .id')

CLI: sevalla resources process-types. MCP: get_platform_options.

Set the size and the readiness probe

The API creates the web process at S1, where the dashboard’s default is H1. Update process (updateProcessV3) sets the size and adds the readiness probe from Add a health check, with the dashboard’s default timings. Send timeoutSeconds: a probe without it gets 120 seconds, where the dashboard sets 1.

curl -s -X PATCH https://api.sevalla.com/v3/applications/$APP_ID/processes/$WEB_ID \
  -H "Authorization: Bearer $SEVALLA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"resource_type_id":"'"$H1_ID"'","readiness_probe":{"httpGet":{"path":"/healthz","port":8080,"scheme":"HTTP"},"initialDelaySeconds":0,"periodSeconds":10,"timeoutSeconds":1,"successThreshold":1,"failureThreshold":3}}' \
  | jq -c '{resource_type_name, readiness: .readiness_probe.httpGet.path, timeout: .readiness_probe.timeoutSeconds}'

{"resource_type_name":"h1","readiness":"/healthz","timeout":1}

CLI: sevalla apps processes update $WEB_ID --app-id $APP_ID --resource-type $H1_ID sets the size; the CLI can’t set probes. MCP: scale_process with size_id for the size, and sevalla_api_update with updateProcessV3 and the same body for the probe.

Turn on auto-deploy

Update application (updateApplicationV3) turns on automatic deployments for every push to the branch:

curl -s -X PATCH https://api.sevalla.com/v3/applications/$APP_ID \
  -H "Authorization: Bearer $SEVALLA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"auto_deploy":true}' | jq .auto_deploy

true

CLI: sevalla apps update $APP_ID --data '{"auto_deploy":true}'. MCP: sevalla_api_update with updateApplicationV3.

Deploy

Trigger deployment (triggerDeploymentV3) deploys the latest commit on the branch:

DEPLOYMENT_ID=$(curl -s -X POST https://api.sevalla.com/v3/applications/$APP_ID/deployments \
  -H "Authorization: Bearer $SEVALLA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{}' | jq -r .id)

CLI: sevalla apps deployments trigger $APP_ID. MCP: trigger_deployment.

Wait for the deployment

Get deployment (getDeploymentV3) returns the deployment’s status: waiting and inProgress while it runs, then success or failed. Poll it every 15 seconds, for up to 30 minutes, until the status is final:

for i in $(seq 1 120); do
  STATUS=$(curl -s "https://api.sevalla.com/v3/applications/$APP_ID/deployments/$DEPLOYMENT_ID" \
    -H "Authorization: Bearer $SEVALLA_API_KEY" | jq -r '.status // empty')
  case $STATUS in success|failed|cancelled|skipped) break ;; esac
  sleep 15
done
echo "$STATUS"

success

CLI: sevalla apps deployments get $DEPLOYMENT_ID --app-id $APP_ID. MCP: get_deployment.

Read the build log

Get application deployment logs (getApplicationDeploymentLogsV3) returns the build log, oldest line first: the build plan from Verify the deployment, the build and the rollout, which ends with Web has been deployed successfully. When the status is failed, the last lines say why. Without limit, the call returns the latest 1,000 lines, so a longer log loses its start; 5000 is the most it allows.

curl -s "https://api.sevalla.com/v3/applications/$APP_ID/deployments/$DEPLOYMENT_ID/logs?limit=5000" \
  -H "Authorization: Bearer $SEVALLA_API_KEY" | jq -r '.[].message'

CLI: sevalla apps deployments logs $DEPLOYMENT_ID --app-id $APP_ID. MCP: get_deployment_logs.

Check the app

Run a callback the way the browser does, on the domain from the Find the domain step:

curl -s https://$HOST/_dash-update-component \
  -H "Content-Type: application/json" \
  -d '{"output":"chart.figure","outputs":{"id":"chart","property":"figure"},"inputs":[{"id":"product","property":"value","value":"Shirts"}],"changedPropIds":["product.value"]}' \
  | jq -c '.response.chart.figure.data[0].y'

[80,95,90,110]

Build from the Dockerfile with the API

After you push the Dockerfile from Deploy with a Dockerfile, Update application (updateApplicationV3) switches the build strategy. Then repeat the Deploy, Wait for the deployment and Check the app steps:

curl -s -X PATCH https://api.sevalla.com/v3/applications/$APP_ID \
  -H "Authorization: Bearer $SEVALLA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"build_type":"dockerfile","dockerfile_path":"Dockerfile","docker_context":"."}' \
  | jq -c '{build_type, dockerfile_path, docker_context}'

{"build_type":"dockerfile","dockerfile_path":"Dockerfile","docker_context":"."}

CLI: sevalla apps update $APP_ID --data '{"build_type":"dockerfile","dockerfile_path":"Dockerfile","docker_context":"."}'. MCP: sevalla_api_update with updateApplicationV3.

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Deploy a Dash application

At a glance

Environment variables

Before you begin

Create the project

Prepare the project for Sevalla

Create the Flask server in app.py

Pin the Python version

List the dependencies

How Ingot starts the app

Deploy to Sevalla

Verify the deployment

Add a health check

Scale the app

Deploy with a Dockerfile

Deploy changes

Use environment variables

Add a custom domain

Troubleshoot

Deploy with the API

Build from the Dockerfile with the API

​At a glance

​Environment variables

​Before you begin

​Create the project

​Prepare the project for Sevalla

​Create the Flask server in app.py

​Pin the Python version

​List the dependencies

​How Ingot starts the app

​Deploy to Sevalla

​Verify the deployment

​Add a health check

​Scale the app

​Deploy with a Dockerfile

​Deploy changes

​Use environment variables

​Add a custom domain

​Troubleshoot

​Deploy with the API

​Build from the Dockerfile with the API

At a glance

Environment variables

Before you begin

Create the project

Prepare the project for Sevalla

Create the Flask server in app.py

Pin the Python version

List the dependencies

How Ingot starts the app

Deploy to Sevalla

Verify the deployment

Add a health check

Scale the app

Deploy with a Dockerfile

Deploy changes

Use environment variables

Add a custom domain

Troubleshoot

Deploy with the API

Build from the Dockerfile with the API