Hey. I have successfully deployed a containerized version of the app to Heroku. The UI and scheduler are running (a scheduled job finishes, and I can access UI). However, I am not able to load Extractors/Loaders or Pipelines. I get stuck. Docker:

# This configuration is inspired by: <https://pythonspeed.com/articles/activate-conda-dockerfile/>
# use official Docker image for CONDA
FROM continuumio/miniconda3:4.9.2-alpine

WORKDIR /project

# install supervisor, git and bash
RUN apk --update add supervisor git bash

# create the Python environment:
COPY ./requirements.txt .
COPY ./environment.yml .
RUN conda env create -f environment.yml

# make RUN commands use the new environment:
ENV PATH /opt/conda/envs/meltano-demo/bin:$PATH

# ENV variables
# don't allow changes to containerized project files
ENV MELTANO_PROJECT_READONLY true
ENV MELTANO_READONLY true
ENV MELTANO_UI_READONLY true
ENV MELTANO_SEND_ANONYMOUS_USAGE_STATS false
ENV MELTANO_DISABLE_TRACKING true
ENV MELTANO_DISCOVERY_URL false
ENV MELTANO_UI_ANALYSIS false

# install all plugins into the `.meltano` directory
COPY ./meltano.yml .
RUN meltano install

# configuration for supervisord - to run all services
COPY supervisord.conf /etc/supervisor/conf.d/supervisord.conf

# copy over remaining project files
COPY . .

## install scheduler
#RUN meltano add files airflow

# create ouptut directory - project relevant
RUN mkdir outputs

# expose default port for the app
EXPOSE $PORT

# run services to execute the data pipeline from supervisors
CMD ["/usr/bin/supervisord"]

supervisord.conf:

# Run services to support the Data Pipeline
[supervisord]  # this is the main process for the Supervisor
nodaemon=true  # this setting is to specify that we are not running in daemon mode

[program:scheduler] # the first service - scheduler
command=/bin/bash -c "meltano invoke airflow scheduler" # this is the main command to run the 1st service
startsecs=0
autostart=true
autorestart=true # this setting specifies that the supervisor will restart the service in case of failure
stderr_logfile=/dev/stdout # this setting specifies that the supervisor will log the errors in the standard output
stderr_logfile_maxbytes = 0
stdout_logfile=/dev/stdout # this setting specifies that the supervisor will log the output in the standard output
stdout_logfile_maxbytes = 0

[program:meltano_ui] # the second service - UI for the Meltano Instance... configuration is similar
command=/bin/bash -c "meltano ui"
autostart=true
autorestart=true
startsecs=0
stderr_logfile=/dev/stdout
stderr_logfile_maxbytes = 0
stdout_logfile=/dev/stdout
stdout_logfile_maxbytes = 0