diff --git a/config/airflow.cfg b/config/airflow.cfg
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+[core]
+# The folder where your airflow pipelines live, most likely a
+# subfolder in a code repository. This path must be absolute.
+dags_folder = /opt/airflow/dags
+
+# The folder where airflow should store its log files
+# This path must be absolute
+base_log_folder = /opt/airflow/logs
+
+# Airflow can store logs remotely in AWS S3, Google Cloud Storage or Elastic Search.
+# Set this to True if you want to enable remote logging.
+remote_logging = False
+
+# Users must supply an Airflow connection id that provides access to the storage
+# location.
+remote_log_conn_id =
+remote_base_log_folder =
+encrypt_s3_logs = False
+
+# Logging level
+logging_level = INFO
+
+# Logging level for Flask-appbuilder UI
+fab_logging_level = WARN
+
+# Logging class
+# Specify the class that will specify the logging configuration
+# This class has to be on the python classpath
+# Example: logging_config_class = my.path.default_local_settings.LOGGING_CONFIG
+logging_config_class =
+
+# Flag to enable/disable Colored logs in Console
+# Colour the logs when the controlling terminal is a TTY.
+colored_console_log = True
+
+# Log format for when Colored logs is enabled
+colored_log_format = [%%(blue)s%%(asctime)s%%(reset)s] {{%%(blue)s%%(filename)s:%%(reset)s%%(lineno)d}} %%(log_color)s%%(levelname)s%%(reset)s - %%(log_color)s%%(message)s%%(reset)s
+colored_formatter_class = airflow.utils.log.colored_log.CustomTTYColoredFormatter
+
+# Format of Log line
+log_format = [%%(asctime)s] {{%%(filename)s:%%(lineno)d}} %%(levelname)s - %%(message)s
+simple_log_format = %%(asctime)s %%(levelname)s - %%(message)s
+
+# Log filename format
+log_filename_template = {{ ti.dag_id }}/{{ ti.task_id }}/{{ ts }}/{{ try_number }}.log
+log_processor_filename_template = {{ filename }}.log
+dag_processor_manager_log_location = /opt/airflow/logs/dag_processor_manager/dag_processor_manager.log
+
+# Name of handler to read task instance logs.
+# Default to use task handler.
+task_log_reader = task
+
+# Hostname by providing a path to a callable, which will resolve the hostname.
+# The format is "package:function".
+#
+# For example, default value "socket:getfqdn" means that result from getfqdn() of "socket"
+# package will be used as hostname.
+#
+# No argument should be required in the function specified.
+# If using IP address as hostname is preferred, use value ``airflow.utils.net:get_host_ip_address``
+hostname_callable = socket:getfqdn
+
+# Default timezone in case supplied date times are naive
+# can be utc (default), system, or any IANA timezone string (e.g. Europe/Amsterdam)
+default_timezone = utc
+
+# The executor class that airflow should use. Choices include
+# SequentialExecutor, LocalExecutor, CeleryExecutor, DaskExecutor, KubernetesExecutor
+executor = SequentialExecutor
+
+# The SqlAlchemy connection string to the metadata database.
+# SqlAlchemy supports many different database engine, more information
+# their website
+# sql_alchemy_conn = sqlite:////tmp/airflow.db
+
+# The encoding for the databases
+sql_engine_encoding = utf-8
+
+# If SqlAlchemy should pool database connections.
+sql_alchemy_pool_enabled = True
+
+# The SqlAlchemy pool size is the maximum number of database connections
+# in the pool. 0 indicates no limit.
+sql_alchemy_pool_size = 5
+
+# The maximum overflow size of the pool.
+# When the number of checked-out connections reaches the size set in pool_size,
+# additional connections will be returned up to this limit.
+# When those additional connections are returned to the pool, they are disconnected and discarded.
+# It follows then that the total number of simultaneous connections the pool will allow
+# is pool_size + max_overflow,
+# and the total number of "sleeping" connections the pool will allow is pool_size.
+# max_overflow can be set to -1 to indicate no overflow limit;
+# no limit will be placed on the total number of concurrent connections. Defaults to 10.
+sql_alchemy_max_overflow = 10
+
+# The SqlAlchemy pool recycle is the number of seconds a connection
+# can be idle in the pool before it is invalidated. This config does
+# not apply to sqlite. If the number of DB connections is ever exceeded,
+# a lower config value will allow the system to recover faster.
+sql_alchemy_pool_recycle = 1800
+
+# Check connection at the start of each connection pool checkout.
+# Typically, this is a simple statement like "SELECT 1".
+# More information here:
+# https://docs.sqlalchemy.org/en/13/core/pooling.html#disconnect-handling-pessimistic
+sql_alchemy_pool_pre_ping = True
+
+# The schema to use for the metadata database.
+# SqlAlchemy supports databases with the concept of multiple schemas.
+sql_alchemy_schema =
+
+# The amount of parallelism as a setting to the executor. This defines
+# the max number of task instances that should run simultaneously
+# on this airflow installation
+parallelism = 32
+
+# The number of task instances allowed to run concurrently by the scheduler
+dag_concurrency = 16
+
+# Are DAGs paused by default at creation
+dags_are_paused_at_creation = True
+
+# The maximum number of active DAG runs per DAG
+max_active_runs_per_dag = 16
+
+# Whether to load the examples that ship with Airflow. It's good to
+# get started, but you probably want to set this to False in a production
+# environment
+load_examples = True
+
+# Where your Airflow plugins are stored
+plugins_folder = /opt/airflow/plugins
+
+# Secret key to save connection passwords in the db
+fernet_key = $FERNET_KEY
+
+# Whether to disable pickling dags
+donot_pickle = False
+
+# How long before timing out a python file import
+dagbag_import_timeout = 30
+
+# How long before timing out a DagFileProcessor, which processes a dag file
+dag_file_processor_timeout = 50
+
+# The class to use for running task instances in a subprocess
+task_runner = StandardTaskRunner
+
+# If set, tasks without a ``run_as_user`` argument will be run with this user
+# Can be used to de-elevate a sudo user running Airflow when executing tasks
+default_impersonation =
+
+# What security module to use (for example kerberos)
+security =
+
+# If set to False enables some unsecure features like Charts and Ad Hoc Queries.
+# In 2.0 will default to True.
+secure_mode = False
+
+# Turn unit test mode on (overwrites many configuration options with test
+# values at runtime)
+unit_test_mode = False
+
+# Whether to enable pickling for xcom (note that this is insecure and allows for
+# RCE exploits). This will be deprecated in Airflow 2.0 (be forced to False).
+enable_xcom_pickling = True
+
+# When a task is killed forcefully, this is the amount of time in seconds that
+# it has to cleanup after it is sent a SIGTERM, before it is SIGKILLED
+killed_task_cleanup_time = 60
+
+# Whether to override params with dag_run.conf. If you pass some key-value pairs
+# through ``airflow dags backfill -c`` or
+# ``airflow dags trigger -c``, the key-value pairs will override the existing ones in params.
+dag_run_conf_overrides_params = False
+
+# Worker initialisation check to validate Metadata Database connection
+worker_precheck = False
+
+# When discovering DAGs, ignore any files that don't contain the strings ``DAG`` and ``airflow``.
+dag_discovery_safe_mode = True
+
+# The number of retries each task is going to have by default. Can be overridden at dag or task level.
+default_task_retries = 0
+
+# Whether to serialises DAGs and persist them in DB.
+# If set to True, Webserver reads from DB instead of parsing DAG files
+# More details: https://airflow.apache.org/docs/stable/dag-serialization.html
+store_serialized_dags = False
+
+# Updating serialized DAG can not be faster than a minimum interval to reduce database write rate.
+min_serialized_dag_update_interval = 30
+
+# On each dagrun check against defined SLAs
+check_slas = True
+
+[cli]
+# In what way should the cli access the API. The LocalClient will use the
+# database directly, while the json_client will use the api running on the
+# webserver
+api_client = airflow.api.client.local_client
+
+# If you set web_server_url_prefix, do NOT forget to append it here, ex:
+# ``endpoint_url = http://localhost:8080/myroot``
+# So api will look like: ``http://localhost:8080/myroot/api/experimental/...``
+endpoint_url = http://localhost:8080
+
+[debug]
+# Used only with DebugExecutor. If set to True DAG will fail with first
+# failed task. Helpful for debugging purposes.
+fail_fast = False
+
+[api]
+# How to authenticate users of the API
+auth_backend = airflow.api.auth.backend.default
+
+[lineage]
+# what lineage backend to use
+backend =
+
+[atlas]
+sasl_enabled = False
+host =
+port = 21000
+username =
+password =
+
+[operators]
+# The default owner assigned to each new operator, unless
+# provided explicitly or passed via ``default_args``
+default_owner = airflow
+default_cpus = 1
+default_ram = 512
+default_disk = 512
+default_gpus = 0
+
+[hive]
+# Default mapreduce queue for HiveOperator tasks
+default_hive_mapred_queue =
+
+[webserver]
+# The base url of your website as airflow cannot guess what domain or
+# cname you are using. This is used in automated emails that
+# airflow sends to point links to the right web server
+base_url = http://localhost:8080
+
+# The ip specified when starting the web server
+web_server_host = 0.0.0.0
+
+# The port on which to run the web server
+web_server_port = 8080
+
+# Paths to the SSL certificate and key for the web server. When both are
+# provided SSL will be enabled. This does not change the web server port.
+web_server_ssl_cert =
+
+# Paths to the SSL certificate and key for the web server. When both are
+# provided SSL will be enabled. This does not change the web server port.
+web_server_ssl_key =
+
+# Number of seconds the webserver waits before killing gunicorn master that doesn't respond
+web_server_master_timeout = 120
+
+# Number of seconds the gunicorn webserver waits before timing out on a worker
+web_server_worker_timeout = 120
+
+# Number of workers to refresh at a time. When set to 0, worker refresh is
+# disabled. When nonzero, airflow periodically refreshes webserver workers by
+# bringing up new ones and killing old ones.
+worker_refresh_batch_size = 1
+
+# Number of seconds to wait before refreshing a batch of workers.
+worker_refresh_interval = 30
+
+# Secret key used to run your flask app
+# It should be as random as possible
+secret_key = temporary_key
+
+# Number of workers to run the Gunicorn web server
+workers = 4
+
+# The worker class gunicorn should use. Choices include
+# sync (default), eventlet, gevent
+worker_class = sync
+
+# Log files for the gunicorn webserver. '-' means log to stderr.
+access_logfile = -
+
+# Log files for the gunicorn webserver. '-' means log to stderr.
+error_logfile = -
+
+# Expose the configuration file in the web server
+expose_config = True
+
+# Expose hostname in the web server
+expose_hostname = True
+
+# Expose stacktrace in the web server
+expose_stacktrace = True
+
+# Set to true to turn on authentication:
+# https://airflow.apache.org/security.html#web-authentication
+authenticate = False
+
+# Filter the list of dags by owner name (requires authentication to be enabled)
+filter_by_owner = False
+
+# Filtering mode. Choices include user (default) and ldapgroup.
+# Ldap group filtering requires using the ldap backend
+#
+# Note that the ldap server needs the "memberOf" overlay to be set up
+# in order to user the ldapgroup mode.
+owner_mode = user
+
+# Default DAG view. Valid values are:
+# tree, graph, duration, gantt, landing_times
+dag_default_view = tree
+
+# "Default DAG orientation. Valid values are:"
+# LR (Left->Right), TB (Top->Bottom), RL (Right->Left), BT (Bottom->Top)
+dag_orientation = LR
+
+# Puts the webserver in demonstration mode; blurs the names of Operators for
+# privacy.
+demo_mode = False
+
+# The amount of time (in secs) webserver will wait for initial handshake
+# while fetching logs from other worker machine
+log_fetch_timeout_sec = 5
+
+# Time interval (in secs) to wait before next log fetching.
+log_fetch_delay_sec = 2
+
+# Distance away from page bottom to enable auto tailing.
+log_auto_tailing_offset = 30
+
+# Animation speed for auto tailing log display.
+log_animation_speed = 1000
+
+# By default, the webserver shows paused DAGs. Flip this to hide paused
+# DAGs by default
+hide_paused_dags_by_default = False
+
+# Consistent page size across all listing views in the UI
+page_size = 100
+
+# Use FAB-based webserver with RBAC feature
+rbac = False
+
+# Define the color of navigation bar
+navbar_color = #007A87
+
+# Default dagrun to show in UI
+default_dag_run_display_number = 25
+
+# Enable werkzeug ``ProxyFix`` middleware for reverse proxy
+enable_proxy_fix = False
+
+# Number of values to trust for ``X-Forwarded-For``.
+# More info: https://werkzeug.palletsprojects.com/en/0.16.x/middleware/proxy_fix/
+proxy_fix_x_for = 1
+
+# Number of values to trust for ``X-Forwarded-Proto``
+proxy_fix_x_proto = 1
+
+# Number of values to trust for ``X-Forwarded-Host``
+proxy_fix_x_host = 1
+
+# Number of values to trust for ``X-Forwarded-Port``
+proxy_fix_x_port = 1
+
+# Number of values to trust for ``X-Forwarded-Prefix``
+proxy_fix_x_prefix = 1
+
+# Set secure flag on session cookie
+cookie_secure = False
+
+# Set samesite policy on session cookie
+cookie_samesite =
+
+# Default setting for wrap toggle on DAG code and TI log views.
+default_wrap = False
+
+# Allow the UI to be rendered in a frame
+x_frame_enabled = True
+
+# Send anonymous user activity to your analytics tool
+# choose from google_analytics, segment, or metarouter
+# analytics_tool =
+
+# Unique ID of your account in the analytics tool
+# analytics_id =
+
+# Update FAB permissions and sync security manager roles
+# on webserver startup
+update_fab_perms = True
+
+# Minutes of non-activity before logged out from UI
+# 0 means never get forcibly logged out
+force_log_out_after = 0
+
+# The UI cookie lifetime in days
+session_lifetime_days = 30
+
+instance_name = "eFlows4HPC Pipelines"
+
+[email]
+email_backend = airflow.utils.email.send_email_smtp
+
+[smtp]
+
+# If you want airflow to send emails on retries, failure, and you want to use
+# the airflow.utils.email.send_email_smtp function, you have to configure an
+# smtp server here
+smtp_host = localhost
+smtp_starttls = True
+smtp_ssl = False
+# Example: smtp_user = airflow
+# smtp_user =
+# Example: smtp_password = airflow
+# smtp_password =
+smtp_port = 25
+smtp_mail_from = airflow@example.com
+
+[sentry]
+
+# Sentry (https://docs.sentry.io) integration
+sentry_dsn =
+
+[celery]
+
+# This section only applies if you are using the CeleryExecutor in
+# ``[core]`` section above
+# The app name that will be used by celery
+celery_app_name = airflow.executors.celery_executor
+
+# The concurrency that will be used when starting workers with the
+# ``airflow celery worker`` command. This defines the number of task instances that
+# a worker will take, so size up your workers based on the resources on
+# your worker box and the nature of your tasks
+worker_concurrency = 16
+
+# The maximum and minimum concurrency that will be used when starting workers with the
+# ``airflow celery worker`` command (always keep minimum processes, but grow
+# to maximum if necessary). Note the value should be max_concurrency,min_concurrency
+# Pick these numbers based on resources on worker box and the nature of the task.
+# If autoscale option is available, worker_concurrency will be ignored.
+# http://docs.celeryproject.org/en/latest/reference/celery.bin.worker.html#cmdoption-celery-worker-autoscale
+# Example: worker_autoscale = 16,12
+worker_autoscale = 16,12
+
+# When you start an airflow worker, airflow starts a tiny web server
+# subprocess to serve the workers local log files to the airflow main
+# web server, who then builds pages and sends them to users. This defines
+# the port on which the logs are served. It needs to be unused, and open
+# visible from the main web server to connect into the workers.
+worker_log_server_port = 8793
+
+# The Celery broker URL. Celery supports RabbitMQ, Redis and experimentally
+# a sqlalchemy database. Refer to the Celery documentation for more
+# information.
+# http://docs.celeryproject.org/en/latest/userguide/configuration.html#broker-settings
+broker_url = redis://redis:6379/1
+
+# The Celery result_backend. When a job finishes, it needs to update the
+# metadata of the job. Therefore it will post a message on a message bus,
+# or insert it into a database (depending of the backend)
+# This status is used by the scheduler to update the state of the task
+# The use of a database is highly recommended
+# http://docs.celeryproject.org/en/latest/userguide/configuration.html#task-result-backend-settings
+result_backend = db+postgresql://airflow:airflow@postgres/airflow
+
+# Celery Flower is a sweet UI for Celery. Airflow has a shortcut to start
+# it ``airflow flower``. This defines the IP that Celery Flower runs on
+flower_host = 0.0.0.0
+
+# The root URL for Flower
+# Example: flower_url_prefix = /flower
+flower_url_prefix =
+
+# This defines the port that Celery Flower runs on
+flower_port = 5555
+
+# Securing Flower with Basic Authentication
+# Accepts user:password pairs separated by a comma
+# Example: flower_basic_auth = user1:password1,user2:password2
+flower_basic_auth =
+
+# Default queue that tasks get assigned to and that worker listen on.
+default_queue = default
+
+# How many processes CeleryExecutor uses to sync task state.
+# 0 means to use max(1, number of cores - 1) processes.
+sync_parallelism = 0
+
+# Import path for celery configuration options
+celery_config_options = airflow.config_templates.default_celery.DEFAULT_CELERY_CONFIG
+
+# In case of using SSL
+ssl_active = False
+ssl_key =
+ssl_cert =
+ssl_cacert =
+
+# Celery Pool implementation.
+# Choices include: prefork (default), eventlet, gevent or solo.
+# See:
+# https://docs.celeryproject.org/en/latest/userguide/workers.html#concurrency
+# https://docs.celeryproject.org/en/latest/userguide/concurrency/eventlet.html
+pool = prefork
+
+# The number of seconds to wait before timing out ``send_task_to_executor`` or
+# ``fetch_celery_task_state`` operations.
+operation_timeout = 2
+
+[celery_broker_transport_options]
+
+# This section is for specifying options which can be passed to the
+# underlying celery broker transport. See:
+# http://docs.celeryproject.org/en/latest/userguide/configuration.html#std:setting-broker_transport_options
+# The visibility timeout defines the number of seconds to wait for the worker
+# to acknowledge the task before the message is redelivered to another worker.
+# Make sure to increase the visibility timeout to match the time of the longest
+# ETA you're planning to use.
+# visibility_timeout is only supported for Redis and SQS celery brokers.
+# See:
+# http://docs.celeryproject.org/en/master/userguide/configuration.html#std:setting-broker_transport_options
+# Example: visibility_timeout = 21600
+# visibility_timeout =
+
+[dask]
+
+# This section only applies if you are using the DaskExecutor in
+# [core] section above
+# The IP address and port of the Dask cluster's scheduler.
+cluster_address = 127.0.0.1:8786
+
+# TLS/ SSL settings to access a secured Dask scheduler.
+tls_ca =
+tls_cert =
+tls_key =
+
+[scheduler]
+# Task instances listen for external kill signal (when you clear tasks
+# from the CLI or the UI), this defines the frequency at which they should
+# listen (in seconds).
+job_heartbeat_sec = 5
+
+# The scheduler constantly tries to trigger new tasks (look at the
+# scheduler section in the docs for more information). This defines
+# how often the scheduler should run (in seconds).
+scheduler_heartbeat_sec = 5
+
+# After how much time should the scheduler terminate in seconds
+# -1 indicates to run continuously (see also num_runs)
+run_duration = -1
+
+# The number of times to try to schedule each DAG file
+# -1 indicates unlimited number
+num_runs = -1
+
+# The number of seconds to wait between consecutive DAG file processing
+processor_poll_interval = 1
+
+# after how much time (seconds) a new DAGs should be picked up from the filesystem
+min_file_process_interval = 0
+
+# How often (in seconds) to scan the DAGs directory for new files. Default to 5 minutes.
+dag_dir_list_interval = 300
+
+# How often should stats be printed to the logs. Setting to 0 will disable printing stats
+print_stats_interval = 30
+
+# If the last scheduler heartbeat happened more than scheduler_health_check_threshold
+# ago (in seconds), scheduler is considered unhealthy.
+# This is used by the health check in the "/health" endpoint
+scheduler_health_check_threshold = 30
+child_process_log_directory = /opt/airflow/logs/scheduler
+
+# Local task jobs periodically heartbeat to the DB. If the job has
+# not heartbeat in this many seconds, the scheduler will mark the
+# associated task instance as failed and will re-schedule the task.
+scheduler_zombie_task_threshold = 300
+
+# Turn off scheduler catchup by setting this to False.
+# Default behavior is unchanged and
+# Command Line Backfills still work, but the scheduler
+# will not do scheduler catchup if this is False,
+# however it can be set on a per DAG basis in the
+# DAG definition (catchup)
+catchup_by_default = True
+
+# This changes the batch size of queries in the scheduling main loop.
+# If this is too high, SQL query performance may be impacted by one
+# or more of the following:
+# - reversion to full table scan
+# - complexity of query predicate
+# - excessive locking
+# Additionally, you may hit the maximum allowable query length for your db.
+# Set this to 0 for no limit (not advised)
+max_tis_per_query = 512
+
+# Statsd (https://github.com/etsy/statsd) integration settings
+statsd_on = False
+statsd_host = localhost
+statsd_port = 8125
+statsd_prefix = airflow
+
+# If you want to avoid send all the available metrics to StatsD,
+# you can configure an allow list of prefixes to send only the metrics that
+# start with the elements of the list (e.g: scheduler,executor,dagrun)
+statsd_allow_list =
+
+# The scheduler can run multiple threads in parallel to schedule dags.
+# This defines how many threads will run.
+max_threads = 2
+authenticate = False
+
+# Turn off scheduler use of cron intervals by setting this to False.
+# DAGs submitted manually in the web UI or with trigger_dag will still run.
+use_job_schedule = True
+
+# Allow externally triggered DagRuns for Execution Dates in the future
+# Only has effect if schedule_interval is set to None in DAG
+allow_trigger_in_future = False
+
+[ldap]
+# set this to ldaps://<your.ldap.server>:<port>
+uri =
+user_filter = objectClass=*
+user_name_attr = uid
+group_member_attr = memberOf
+superuser_filter =
+data_profiler_filter =
+bind_user = cn=Manager,dc=example,dc=com
+bind_password = insecure
+basedn = dc=example,dc=com
+cacert = /etc/ca/ldap_ca.crt
+search_scope = LEVEL
+
+# This setting allows the use of LDAP servers that either return a
+# broken schema, or do not return a schema.
+ignore_malformed_schema = False
+
+[mesos]
+# Mesos master address which MesosExecutor will connect to.
+master = localhost:5050
+
+# The framework name which Airflow scheduler will register itself as on mesos
+framework_name = Airflow
+
+# Number of cpu cores required for running one task instance using
+# 'airflow run <dag_id> <task_id> <execution_date> --local -p <pickle_id>'
+# command on a mesos slave
+task_cpu = 1
+
+# Memory in MB required for running one task instance using
+# 'airflow run <dag_id> <task_id> <execution_date> --local -p <pickle_id>'
+# command on a mesos slave
+task_memory = 256
+
+# Enable framework checkpointing for mesos
+# See http://mesos.apache.org/documentation/latest/slave-recovery/
+checkpoint = False
+
+# Failover timeout in milliseconds.
+# When checkpointing is enabled and this option is set, Mesos waits
+# until the configured timeout for
+# the MesosExecutor framework to re-register after a failover. Mesos
+# shuts down running tasks if the
+# MesosExecutor framework fails to re-register within this timeframe.
+# Example: failover_timeout = 604800
+# failover_timeout =
+
+# Enable framework authentication for mesos
+# See http://mesos.apache.org/documentation/latest/configuration/
+authenticate = False
+
+# Mesos credentials, if authentication is enabled
+# Example: default_principal = admin
+# default_principal =
+# Example: default_secret = admin
+# default_secret =
+
+# Optional Docker Image to run on slave before running the command
+# This image should be accessible from mesos slave i.e mesos slave
+# should be able to pull this docker image before executing the command.
+# Example: docker_image_slave = puckel/docker-airflow
+# docker_image_slave =
+
+[kerberos]
+ccache = /tmp/airflow_krb5_ccache
+
+# gets augmented with fqdn
+principal = airflow
+reinit_frequency = 3600
+kinit_path = kinit
+keytab = airflow.keytab
+
+[github_enterprise]
+api_rev = v3
+
+[admin]
+# UI to hide sensitive variable fields when set to True
+hide_sensitive_variable_fields = True
+
+[elasticsearch]
+# Elasticsearch host
+host =
+
+# Format of the log_id, which is used to query for a given tasks logs
+log_id_template = {{dag_id}}-{{task_id}}-{{execution_date}}-{{try_number}}
+
+# Used to mark the end of a log stream for a task
+end_of_log_mark = end_of_log
+
+# Qualified URL for an elasticsearch frontend (like Kibana) with a template argument for log_id
+# Code will construct log_id using the log_id template from the argument above.
+# NOTE: The code will prefix the https:// automatically, don't include that here.
+frontend =
+
+# Write the task logs to the stdout of the worker, rather than the default files
+write_stdout = False
+
+# Instead of the default log formatter, write the log lines as JSON
+json_format = False
+
+# Log fields to also attach to the json output, if enabled
+json_fields = asctime, filename, lineno, levelname, message
+
+[elasticsearch_configs]
+use_ssl = False
+verify_certs = True
+
+[kubernetes]
+# The repository, tag and imagePullPolicy of the Kubernetes Image for the Worker to Run
+worker_container_repository =
+worker_container_tag =
+worker_container_image_pull_policy = IfNotPresent
+
+# If True (default), worker pods will be deleted upon termination
+delete_worker_pods = True
+
+# Number of Kubernetes Worker Pod creation calls per scheduler loop
+worker_pods_creation_batch_size = 1
+
+# The Kubernetes namespace where airflow workers should be created. Defaults to ``default``
+namespace = default
+
+# The name of the Kubernetes ConfigMap containing the Airflow Configuration (this file)
+# Example: airflow_configmap = airflow-configmap
+airflow_configmap =
+
+# The name of the Kubernetes ConfigMap containing ``airflow_local_settings.py`` file.
+#
+# For example:
+#
+# ``airflow_local_settings_configmap = "airflow-configmap"`` if you have the following ConfigMap.
+#
+# ``airflow-configmap.yaml``:
+#
+# .. code-block:: yaml
+#
+#   ---
+#   apiVersion: v1
+#   kind: ConfigMap
+#   metadata:
+#     name: airflow-configmap
+#   data:
+#     airflow_local_settings.py: |
+#         def pod_mutation_hook(pod):
+#             ...
+#     airflow.cfg: |
+#         ...
+# Example: airflow_local_settings_configmap = airflow-configmap
+airflow_local_settings_configmap =
+
+# For docker image already contains DAGs, this is set to ``True``, and the worker will
+# search for dags in dags_folder,
+# otherwise use git sync or dags volume claim to mount DAGs
+dags_in_image = False
+
+# For either git sync or volume mounted DAGs, the worker will look in this subpath for DAGs
+dags_volume_subpath =
+
+# For DAGs mounted via a volume claim (mutually exclusive with git-sync and host path)
+dags_volume_claim =
+
+# For volume mounted logs, the worker will look in this subpath for logs
+logs_volume_subpath =
+
+# A shared volume claim for the logs
+logs_volume_claim =
+
+# For DAGs mounted via a hostPath volume (mutually exclusive with volume claim and git-sync)
+# Useful in local environment, discouraged in production
+dags_volume_host =
+
+# A hostPath volume for the logs
+# Useful in local environment, discouraged in production
+logs_volume_host =
+
+# A list of configMapsRefs to envFrom. If more than one configMap is
+# specified, provide a comma separated list: configmap_a,configmap_b
+env_from_configmap_ref =
+
+# A list of secretRefs to envFrom. If more than one secret is
+# specified, provide a comma separated list: secret_a,secret_b
+env_from_secret_ref =
+
+# Git credentials and repository for DAGs mounted via Git (mutually exclusive with volume claim)
+git_repo =
+git_branch =
+git_subpath =
+
+# The specific rev or hash the git_sync init container will checkout
+# This becomes GIT_SYNC_REV environment variable in the git_sync init container for worker pods
+git_sync_rev =
+
+# Use git_user and git_password for user authentication or git_ssh_key_secret_name
+# and git_ssh_key_secret_key for SSH authentication
+git_user =
+git_password =
+git_sync_root = /git
+git_sync_dest = repo
+
+# Mount point of the volume if git-sync is being used.
+# i.e./opt/airflow/dags
+git_dags_folder_mount_point =
+
+# To get Git-sync SSH authentication set up follow this format
+#
+# ``airflow-secrets.yaml``:
+#
+# .. code-block:: yaml
+#
+#   ---
+#   apiVersion: v1
+#   kind: Secret
+#   metadata:
+#     name: airflow-secrets
+#   data:
+#     # key needs to be gitSshKey
+#     gitSshKey: <base64_encoded_data>
+# Example: git_ssh_key_secret_name = airflow-secrets
+git_ssh_key_secret_name =
+
+# To get Git-sync SSH authentication set up follow this format
+#
+# ``airflow-configmap.yaml``:
+#
+# .. code-block:: yaml
+#
+#   ---
+#   apiVersion: v1
+#   kind: ConfigMap
+#   metadata:
+#     name: airflow-configmap
+#   data:
+#     known_hosts: |
+#         github.com ssh-rsa <...>
+#     airflow.cfg: |
+#         ...
+# Example: git_ssh_known_hosts_configmap_name = airflow-configmap
+git_ssh_known_hosts_configmap_name =
+
+# To give the git_sync init container credentials via a secret, create a secret
+# with two fields: GIT_SYNC_USERNAME and GIT_SYNC_PASSWORD (example below) and
+# add ``git_sync_credentials_secret = <secret_name>`` to your airflow config under the
+# ``kubernetes`` section
+#
+# Secret Example:
+#
+# .. code-block:: yaml
+#
+#   ---
+#   apiVersion: v1
+#   kind: Secret
+#   metadata:
+#     name: git-credentials
+#   data:
+#     GIT_SYNC_USERNAME: <base64_encoded_git_username>
+#     GIT_SYNC_PASSWORD: <base64_encoded_git_password>
+git_sync_credentials_secret =
+
+# For cloning DAGs from git repositories into volumes: https://github.com/kubernetes/git-sync
+git_sync_container_repository = k8s.gcr.io/git-sync
+git_sync_container_tag = v3.1.1
+git_sync_init_container_name = git-sync-clone
+git_sync_run_as_user = 65533
+
+# The name of the Kubernetes service account to be associated with airflow workers, if any.
+# Service accounts are required for workers that require access to secrets or cluster resources.
+# See the Kubernetes RBAC documentation for more:
+# https://kubernetes.io/docs/admin/authorization/rbac/
+worker_service_account_name =
+
+# Any image pull secrets to be given to worker pods, If more than one secret is
+# required, provide a comma separated list: secret_a,secret_b
+image_pull_secrets =
+
+# GCP Service Account Keys to be provided to tasks run on Kubernetes Executors
+# Should be supplied in the format: key-name-1:key-path-1,key-name-2:key-path-2
+gcp_service_account_keys =
+
+# Use the service account kubernetes gives to pods to connect to kubernetes cluster.
+# It's intended for clients that expect to be running inside a pod running on kubernetes.
+# It will raise an exception if called from a process not running in a kubernetes environment.
+in_cluster = True
+
+# When running with in_cluster=False change the default cluster_context or config_file
+# options to Kubernetes client. Leave blank these to use default behaviour like ``kubectl`` has.
+# cluster_context =
+# config_file =
+
+# Affinity configuration as a single line formatted JSON object.
+# See the affinity model for top-level key names (e.g. ``nodeAffinity``, etc.):
+# https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.12/#affinity-v1-core
+affinity =
+
+# A list of toleration objects as a single line formatted JSON array
+# See:
+# https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.12/#toleration-v1-core
+tolerations =
+
+# Keyword parameters to pass while calling a kubernetes client core_v1_api methods
+# from Kubernetes Executor provided as a single line formatted JSON dictionary string.
+# List of supported params are similar for all core_v1_apis, hence a single config
+# variable for all apis.
+# See:
+# https://raw.githubusercontent.com/kubernetes-client/python/master/kubernetes/client/apis/core_v1_api.py
+# Note that if no _request_timeout is specified, the kubernetes client will wait indefinitely
+# for kubernetes api responses, which will cause the scheduler to hang.
+# The timeout is specified as [connect timeout, read timeout]
+kube_client_request_args = {{"_request_timeout" : [60,60] }}
+
+# Specifies the uid to run the first process of the worker pods containers as
+run_as_user =
+
+# Specifies a gid to associate with all containers in the worker pods
+# if using a git_ssh_key_secret_name use an fs_group
+# that allows for the key to be read, e.g. 65533
+fs_group =
+
+[kubernetes_node_selectors]
+
+# The Key-value pairs to be given to worker pods.
+# The worker pods will be scheduled to the nodes of the specified key-value pairs.
+# Should be supplied in the format: key = value
+
+[kubernetes_annotations]
+
+# The Key-value annotations pairs to be given to worker pods.
+# Should be supplied in the format: key = value
+
+[kubernetes_environment_variables]
+
+# The scheduler sets the following environment variables into your workers. You may define as
+# many environment variables as needed and the kubernetes launcher will set them in the launched workers.
+# Environment variables in this section are defined as follows
+# ``<environment_variable_key> = <environment_variable_value>``
+#
+# For example if you wanted to set an environment variable with value `prod` and key
+# ``ENVIRONMENT`` you would follow the following format:
+# ENVIRONMENT = prod
+#
+# Additionally you may override worker airflow settings with the ``AIRFLOW__<SECTION>__<KEY>``
+# formatting as supported by airflow normally.
+
+[kubernetes_secrets]
+
+# The scheduler mounts the following secrets into your workers as they are launched by the
+# scheduler. You may define as many secrets as needed and the kubernetes launcher will parse the
+# defined secrets and mount them as secret environment variables in the launched workers.
+# Secrets in this section are defined as follows
+# ``<environment_variable_mount> = <kubernetes_secret_object>=<kubernetes_secret_key>``
+#
+# For example if you wanted to mount a kubernetes secret key named ``postgres_password`` from the
+# kubernetes secret object ``airflow-secret`` as the environment variable ``POSTGRES_PASSWORD`` into
+# your workers you would follow the following format:
+# ``POSTGRES_PASSWORD = airflow-secret=postgres_credentials``
+#
+# Additionally you may override worker airflow settings with the ``AIRFLOW__<SECTION>__<KEY>``
+# formatting as supported by airflow normally.
+
+[kubernetes_labels]
+
+# The Key-value pairs to be given to worker pods.
+# The worker pods will be given these static labels, as well as some additional dynamic labels
+# to identify the task.
+# Should be supplied in the format: ``key = value``
diff --git a/dockers/docker-compose.yaml b/dockers/docker-compose.yaml
index eee098e53fe651f4558b91d75199bb751a955c94..0c36e660776c05ca81e9313cfbfaf8525f3ba562 100644
--- a/dockers/docker-compose.yaml
+++ b/dockers/docker-compose.yaml
@@ -47,6 +47,8 @@ x-airflow-common:
   image: ${AIRFLOW_IMAGE_NAME:-apache/airflow:2.1.2}
   environment:
     &airflow-common-env
+    AIRFLOW_HOME: /opt/airflow
+    AIRFLOW__CORE_dags_folder: /opt/airflow/dags
     AIRFLOW__CORE__EXECUTOR: CeleryExecutor
     AIRFLOW__CORE__SQL_ALCHEMY_CONN: postgresql+psycopg2://airflow:airflow@postgres/airflow
     AIRFLOW__CELERY__RESULT_BACKEND: db+postgresql://airflow:airflow@postgres/airflow
@@ -60,6 +62,7 @@ x-airflow-common:
     - ./dags:/opt/airflow/dags
     - ./logs:/opt/airflow/logs
     - ./plugins:/opt/airflow/plugins
+    - ./config/airflow.cfg:/opt/airflow/airflow.cfg
   user: "${AIRFLOW_UID:-50000}:${AIRFLOW_GID:-50000}"
   depends_on:
     redis: