I am working with AWS MWAA (Apache Airflow). I want to send an email in MWAA upon completion of my pipeline.I have set the following configuration
Now when I run my dag using an Email Operator, it gives me an error.
File "/usr/lib64/python3.7/socket.py", line 707, in create_connection
for res in getaddrinfo(host, port, 0, SOCK_STREAM):
File "/usr/lib64/python3.7/socket.py", line 752, in getaddrinfo
for res in _socket.getaddrinfo(host, port, family, type, proto, flags):
socket.gaierror: [Errno -2] Name or service not known
[2022-05-19, 11:11:21 UTC] {{local_task_job.py:154}} INFO - Task exited with return code 1
[2022-05-19, 11:11:21 UTC] {{local_task_job.py:264}} INFO - 0 downstream tasks scheduled from follow-on schedule check
Then I changed my configuration to
It now gives the following error
File "/usr/lib64/python3.7/smtplib.py", line 642, in auth
raise SMTPAuthenticationError(code, resp)
smtplib.SMTPAuthenticationError: (530, b'Must issue a STARTTLS command first')
[2022-05-19, 12:22:39 UTC] {{local_task_job.py:154}} INFO - Task exited with return code 1
[2022-05-19, 12:22:39 UTC] {{local_task_job.py:264}} INFO - 0 downstream tasks scheduled from follow-on schedule check
Can you please tell me where I am doing wrong or how should I configure this to send an email to a particular email address from any domain?
Your smtp host variable is an email address and not a host.
It should be smtp.gmail.com not smtp#gmail.com
You've hopefully also changed your password as you have shared it publicly in that screenshot and anyone could use it now.
Related
So i when to the airflow documentation for aws redshift there is 2 operator that can execute the sql query they are RedshiftSQLOperator and RedshiftDataOperator. I already implemented my job using RedshiftSQLOperator but i want to do it using RedshiftDataOperator instead, because i dont want to using postgres connection in RedshiftSQLOperator but AWS API.
RedshiftDataOperator Documentation
I had read this documentation there is aws_conn_id in the parameter. But when im trying to use the same connection id there is error.
[2023-01-11, 04:55:56 UTC] {base.py:68} INFO - Using connection ID 'redshift_default' for task execution.
[2023-01-11, 04:55:56 UTC] {base_aws.py:206} INFO - Credentials retrieved from login
[2023-01-11, 04:55:56 UTC] {taskinstance.py:1889} ERROR - Task failed with exception
Traceback (most recent call last):
File "/home/airflow/.local/lib/python3.7/site-packages/airflow/providers/amazon/aws/operators/redshift_data.py", line 146, in execute
self.statement_id = self.execute_query()
File "/home/airflow/.local/lib/python3.7/site-packages/airflow/providers/amazon/aws/operators/redshift_data.py", line 124, in execute_query
resp = self.hook.conn.execute_statement(**filter_values)
File "/home/airflow/.local/lib/python3.7/site-packages/botocore/client.py", line 415, in _api_call
return self._make_api_call(operation_name, kwargs)
File "/home/airflow/.local/lib/python3.7/site-packages/botocore/client.py", line 745, in _make_api_call
raise error_class(parsed_response, operation_name)
botocore.exceptions.ClientError: An error occurred (UnrecognizedClientException) when calling the ExecuteStatement operation: The security token included in the request is invalid.
From task id
redshift_data_task = RedshiftDataOperator(
task_id='redshift_data_task',
database='rds',
region='ap-southeast-1',
aws_conn_id='redshift_default',
sql="""
call some_procedure();
"""
)
What should i fill in the airflow connection ? Because in the documentation there is no example of value that i should fill to airflow. Thanks
Airflow RedshiftDataOperator Connection Required Value
Have you tried using the Amazon Redshift connection? There is both an option for authenticating using your Redshift credentials:
Connection ID: redshift_default
Connection Type: Amazon Redshift
Host: <your-redshift-endpoint> (for example, redshift-cluster-1.123456789.us-west-1.redshift.amazonaws.com)
Schema: <your-redshift-database> (for example, dev, test, prod, etc.)
Login: <your-redshift-username> (for example, awsuser)
Password: <your-redshift-password>
Port: <your-redshift-port> (for example, 5439)
(source)
and an option for using an IAM role (there is an example in the first link).
Disclaimer: I work at Astronomer :)
EDIT: Tested the following with Airflow 2.5.0 and Amazon provider 6.2.0:
Added the IP of my Airflow instance to the VPC security group with "All traffic" access.
Airflow Connection with the connection id aws_default, Connection type "Amazon Web Services", extra: { "aws_access_key_id": "<your-access-key-id>", "aws_secret_access_key": "<your-secret-access-key>", "region_name": "<your-region-name>" }. All other fields blank. I used a root key for my toy-aws. If you use other credentials you need to make sure that IAM role has access and the right permissions to the Redshift cluster (there is a list in the link above).
Operator code:
red = RedshiftDataOperator(
task_id="red",
database="dev",
sql="SELECT * FROM dev.public.users LIMIT 5;",
cluster_identifier="redshift-cluster-1",
db_user="awsuser",
aws_conn_id="aws_default"
)
I'm using RabbitMQ 3.8.2 with Erlang 22.2.7 and having a problem while consuming tasks. My configuration is django-celery-rabbitmq. While publishing messages in a queue everything goes ok until the length of the queue reaches 1200 messages. After this point RabbitMQ starts to close AMQP connection with following errors:
...
2022-11-01 09:35:25.327 [info] <0.20608.9> accepting AMQP connection <0.20608.9> (185.121.83.107:60447 -> 185.121.83.116:5672)
2022-11-01 09:35:25.483 [info] <0.20608.9> connection <0.20608.9> (185.121.83.107:60447 -> 185.121.83.116:5672): user 'rabbit_admin' authenticated and granted access to vhost '/'
...
2022-11-01 09:36:59.129 [warning] <0.19994.9> closing AMQP connection <0.19994.9> (185.121.83.108:36149 -> 185.121.83.116:5672, vhost: '/', user: 'rabbit_admin'):
client unexpectedly closed TCP connection
...
[error] <0.11162.9> closing AMQP connection <0.11162.9> (185.121.83.108:57631 -> 185.121.83.116:5672):
{writer,send_failed,{error,enotconn}}
...
2022-11-01 09:35:48.256 [error] <0.20201.9> closing AMQP connection <0.20201.9> (185.121.83.108:50058 -> 185.121.83.116:5672):
{inet_error,enotconn}
...
Then the django-celery consumer disappears from queue list, messages become "ready" and celery pods are unable to ack the message after the job is finished with the following error:
ERROR: [2022-11-01 09:20:23] /usr/src/app/project/celery.py:114 handle_message Error while handling Rabbit task: [Errno 104] Connection reset by peer
Traceback (most recent call last):
File "/usr/local/lib/python3.10/site-packages/amqp/connection.py", line 514, in channel
return self.channels[channel_id]
KeyError: None
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/src/app/project/celery.py", line 76, in handle_message
message.ack()
File "/usr/local/lib/python3.10/site-packages/kombu/message.py", line 125, in ack
self.channel.basic_ack(self.delivery_tag, multiple=multiple)
File "/usr/local/lib/python3.10/site-packages/amqp/channel.py", line 1407, in basic_ack
return self.send_method(
File "/usr/local/lib/python3.10/site-packages/amqp/abstract_channel.py", line 70, in send_method
conn.frame_writer(1, self.channel_id, sig, args, content)
File "/usr/local/lib/python3.10/site-packages/amqp/method_framing.py", line 186, in write_frame
write(buffer_store.view[:offset])
File "/usr/local/lib/python3.10/site-packages/amqp/transport.py", line 347, in write
self._write(s)
ConnectionResetError: [Errno 104] Connection reset by peer
I have noticed that the message size also affects this behavior. In the above case there are like 1000-1500 symbols in each message. If I decrease it to 50 symbols, then the threshold at which RabbitMQ starts to close AMQP connection shifts to 4000-5000 messages.
I suspect that the problem is with lack of resources for RabbitMQ, but I don't know how find what exactly is going wrong. If I run htop on the server, I see that 2 available CPU are not at high load at any time (loaded less than 20% each) and RAM is 400mb / 3840mb used. So nothing seems to be wrong. Is there any resource checking command for RabbitMQ? The tasks do not take long time to complete, about 10 seconds each.
Also maybe there are some missing heartbeats from the client (I had the problem earlier, but not now, there are currently no error messages about that).
Also if I run sudo journalctl --system | grep rabbitmq, I get the following output:
......
Мау 24 05:15:49 oms-git.omsystem sshd[809111]: pam_unix(sshd:auth): authentication failure; logname= uid=0 euid=0 tty=ssh ruser= rhost=43.154.63.169 user=rabbitmq
Мау 24 05:15:51 oms-git.omsystem sshd[809111]: Failed password for rabbitmq from 43.154.63.169 port 37010 ssh2
Мау 24 05:15:51 oms-git.omsystem sshd[809111]: Disconnected from authenticating user rabbitmq 43.154.63.169 port 37010 [preauth]
Мау 24 16:12:32 oms-git.omsystem sudo[842182]: ad : TTY=pts/3 ; PWD=/var/log/rabbitmq ; USER=root ; COMMAND=/usr/bin/tail -f -n 1000 rabbit#XXX-git.log
......
Maybe here is another issue with firewall, but I don't see any error messages about that in /var/log/rabbitmq/rabbit#XXX.log.
My Celery configuration on client is like:
CELERY_TASK_IGNORE_RESULT = True
CELERY_RESULT_BACKEND = 'django-db'
CELERY_CACHE_BACKEND = 'django-cache'
CELERY_SEND_EVENTS = False
CELERY_BROKER_POOL_LIMIT = 30
CELERY_BROKER_HEARTBEAT = 30
CELERY_BROKER_CONNECTION_TIMEOUT = 600
CELERY_PREFETCH_MULTIPLIER = 1
CELERY_SEND_EVENTS = False
CELERY_WORKER_CONCURRENCY = 1
CELERY_TASK_ACKS_LATE = True
Currently I'm running the pod using following command:
celery -A project.celery worker -l info -f /var/log/celery/celery.log -Ofair
Also I have tried to use various arguments to limit prefetch or turn off heartbit but it didn't work:
celery -A project.celery worker -l info -f /var/log/celery/celery.log --without-heartbeat --without-gossip --without-mingle
celery -A project.celery worker -l info -f /var/log/celery/celery.log --prefetch-multiplier=1 --pool=solo --
I expect that there are no limitations on queue length and every celery pod in my kubernetes cluster consumes and acks messages without errors.
I am running a GCP composer cluster on GKE. I am defining a DAG to submit a job to dataproc cluster. I have read GCP doc, and it says that Composer's service account will get used by the workers to send the dataproc api requests.
But DataprocSubmitJobOperator reports error in getting the auth credentials.
Stack trace below. Composer env info attached.
I need suggestion to fix this issue.
[2022-08-23, 16:03:25 UTC] {taskinstance.py:1448} INFO - Exporting the following env vars:
AIRFLOW_CTX_DAG_OWNER=harshit.bapna#dexterity.ai
AIRFLOW_CTX_DAG_ID=dataproc_spark_operators
AIRFLOW_CTX_TASK_ID=pyspark_task
AIRFLOW_CTX_EXECUTION_DATE=2022-08-23T16:03:16.986859+00:00
AIRFLOW_CTX_DAG_RUN_ID=manual__2022-08-23T16:03:16.986859+00:00
[2022-08-23, 16:03:25 UTC] {dataproc.py:1847} INFO - Submitting job
[2022-08-23, 16:03:25 UTC] {credentials_provider.py:312} INFO - Getting connection using `google.auth.default()` since no key file is defined for hook.
[2022-08-23, 16:03:25 UTC] {taskinstance.py:1776} ERROR - Task failed with exception
Traceback (most recent call last):
File "/opt/python3.8/lib/python3.8/site-packages/airflow/providers/google/cloud/operators/dataproc.py", line 1849, in execute
job_object = self.hook.submit_job(
File "/opt/python3.8/lib/python3.8/site-packages/airflow/providers/google/common/hooks/base_google.py", line 439, in inner_wrapper
return func(self, *args, **kwargs)
File "/opt/python3.8/lib/python3.8/site-packages/airflow/providers/google/cloud/hooks/dataproc.py", line 869, in submit_job
client = self.get_job_client(region=region)
File "/opt/python3.8/lib/python3.8/site-packages/airflow/providers/google/cloud/hooks/dataproc.py", line 258, in get_job_client
credentials=self._get_credentials(), client_info=CLIENT_INFO, client_options=client_options
File "/opt/python3.8/lib/python3.8/site-packages/airflow/providers/google/common/hooks/base_google.py", line 261, in _get_credentials
credentials, _ = self._get_credentials_and_project_id()
File "/opt/python3.8/lib/python3.8/site-packages/airflow/providers/google/common/hooks/base_google.py", line 240, in _get_credentials_and_project_id
credentials, project_id = get_credentials_and_project_id(
File "/opt/python3.8/lib/python3.8/site-packages/airflow/providers/google/cloud/utils/credentials_provider.py", line 321, in get_credentials_and_project_id
return _CredentialProvider(*args, **kwargs).get_credentials_and_project()
File "/opt/python3.8/lib/python3.8/site-packages/airflow/providers/google/cloud/utils/credentials_provider.py", line 229, in get_credentials_and_project
credentials, project_id = self._get_credentials_using_adc()
File "/opt/python3.8/lib/python3.8/site-packages/airflow/providers/google/cloud/utils/credentials_provider.py", line 307, in _get_credentials_using_adc
credentials, project_id = google.auth.default(scopes=self.scopes)
File "/opt/python3.8/lib/python3.8/site-packages/google/auth/_default.py", line 459, in default
credentials, project_id = checker()
File "/opt/python3.8/lib/python3.8/site-packages/google/auth/_default.py", line 221, in _get_explicit_environ_credentials
credentials, project_id = load_credentials_from_file(
File "/opt/python3.8/lib/python3.8/site-packages/google/auth/_default.py", line 107, in load_credentials_from_file
raise exceptions.DefaultCredentialsError(
google.auth.exceptions.DefaultCredentialsError: File celery was not found.
[2022-08-23, 16:03:25 UTC] {taskinstance.py:1279} INFO - Marking task as UP_FOR_RETRY. dag_id=dataproc_spark_operators, task_id=pyspark_task, execution_date=20220823T160316, start_date=20220823T160324, end_date=20220823T160325
[2022-08-23, 16:03:25 UTC] {standard_task_runner.py:93} ERROR - Failed to execute job 32837 for task pyspark_task (File celery was not found.; 356144)
[2022-08-23, 16:03:26 UTC] {local_task_job.py:154} INFO - Task exited with return code 1
[2022-08-23, 16:03:26 UTC] {local_task_job.py:264} INFO - 0 downstream tasks scheduled from follow-on schedule check
GCP Composer Env
Based on the error File celery was not found, I think that the Application Default Credentials (ADC) tries to read a file named celery, and it doesn't find it, so check if you set the environment variable GOOGLE_APPLICATION_CREDENTIALS, because if you set it, ADC will read the the file to use it:
If the environment variable GOOGLE_APPLICATION_CREDENTIALS is set, ADC uses the service account key or configuration file that the variable points to.
If the environment variable GOOGLE_APPLICATION_CREDENTIALS isn't set, ADC uses the service account that is attached to the resource that is running your code.
This service account might be a default service account provided by Compute Engine, Google Kubernetes Engine, App Engine, Cloud Run, or Cloud Functions. It might also be a user-managed service account that you created.
GCP doc
I am trying to have Airflow email me using AWS SES whenever a task in my DAG fails to run or retries to run. I am using my AWS SES credentials rather than my general AWS credentials too.
My current airflow.cfg
[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 = emailsmtpserver.region.amazonaws.com
smtp_starttls = True
smtp_ssl = False
# Uncomment and set the user/pass settings if you want to use SMTP AUTH
smtp_user = REMOVEDAWSACCESSKEY
smtp_password = REMOVEDAWSSECRETACCESSKEY
smtp_port = 25
smtp_mail_from = myemail#myjob.com
Current task in my DAG that is designed to intentionally fail and retry:
testfaildag_library_install_jar_jdbc = PythonOperator(
task_id='library_install_jar',
retries=3,
retry_delay=timedelta(seconds=15),
python_callable=add_library_to_cluster,
params={'_task_id': 'cluster_create', '_cluster_name': CLUSTER_NAME, '_library_path':s3000://fakepath.jar},
dag=dag,
email_on_failure=True,
email_on_retry=True,
email=’myname#myjob.com’,
provide_context=True
)
Everything works as designed as the task retries the set number of times and ultimately fails, except no emails are being sent. I have checked the logs in the task mentioned above too, and smtp is never mentioned.
I've looked at the similar question here, but the only solution there did not work for me. Additionally, Airflow's documentation such as their example here does not seem to work for me either.
Does SES work with Airflow's email_on_failure and email_on_retry functions?
What I am currently thinking of doing is using the on_failure_callback function to call a python script provided by AWS here to send an email on failure, but that is not the preferable route at this point.
Thank you, appreciate any help.
--updated 6/8 with working SES
here's my write up on how we got it all working. There is a small summary at the bottom of this answer.
Couple of big points:
We decided not to use Amazon SES, and rather use sendmail We now have SES up and working.
It is the airflow worker that services the email_on_failure and email_on_retry features. You can do journalctl –u airflow-worker –f to monitor it during a Dag run. On your production server, you do NOT need to restart your airflow-worker after changing your airflow.cfg with new smtp settings - it should be automatically picked up. No need to worry about messing up currently running Dags.
Here is the technical write-up on how to use sendmail:
Since we changed from ses to sendmail on localhost, we had to change our smtp settings in the airflow.cfg.
The new config is:
[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 = False
smtp_ssl = False
# Uncomment and set the user/pass settings if you want to use SMTP AUTH
#smtp_user = not used
#smtp_password = not used
smtp_port = 25
smtp_mail_from = myjob#mywork.com
This works in both production and local airflow instances.
Some common errors one might receive if their config is not like mine above:
socket.error: [Errno 111] Connection refused -- you must change your smtp_host line in airflow.cfg to localhost
smtplib.SMTPException: STARTTLS extension not supported by server. -- you must change your smtp_starttls in airflow.cfg to False
In my local testing, I tried to simply force airflow to show a log of what was going on when it tried to send an email – I created a fake dag as follows:
# Airflow imports
from airflow import DAG
from airflow.operators.python_operator import PythonOperator
from airflow.operators.bash_operator import BashOperator
from airflow.operators.dummy_operator import DummyOperator
# General imports
from datetime import datetime,timedelta
def throwerror():
raise ValueError("Failure")
SPARK_V_2_2_1 = '3.5.x-scala2.11'
args = {
'owner': ‘me’,
'email': ['me#myjob'],
'depends_on_past': False,
'start_date': datetime(2018, 5,24),
'end_date':datetime(2018,6,28)
}
dag = DAG(
dag_id='testemaildag',
default_args=args,
catchup=False,
schedule_interval="* 18 * * *"
)
t1 = DummyOperator(
task_id='extract_data',
dag=dag
)
t2 = PythonOperator(
task_id='fail_task',
dag=dag,
python_callable=throwerror
)
t2.set_upstream(t1)
If you do the journalctl -u airflow-worker -f, you can see that the worker says that it has sent an alert email on the failure to the email in your DAG, but we were still not receiving the email. We then decided to look into the mail logs of sendmail by doing cat /var/log/maillog. We saw a log like this:
Jun 5 14:10:25 production-server-ip-range postfix/smtpd[port]: connect from localhost[127.0.0.1]
Jun 5 14:10:25 production-server-ip-range postfix/smtpd[port]: ID: client=localhost[127.0.0.1]
Jun 5 14:10:25 production-server-ip-range postfix/cleanup[port]: ID: message-id=<randomMessageID#production-server-ip-range-ec2-instance>
Jun 5 14:10:25 production-server-ip-range postfix/smtpd[port]: disconnect from localhost[127.0.0.1]
Jun 5 14:10:25 production-server-ip-range postfix/qmgr[port]: MESSAGEID: from=<myjob#mycompany.com>, size=1297, nrcpt=1 (queue active)
Jun 5 14:10:55 production-server-ip-range postfix/smtp[port]: connect to aspmx.l.google.com[smtp-ip-range]:25: Connection timed out
Jun 5 14:11:25 production-server-ip-range postfix/smtp[port]: connect to alt1.aspmx.l.google.com[smtp-ip-range]:25: Connection timed out
So this is probably the biggest "Oh duh" moment. Here we are able to see what is actually going on in our smtp service. We used telnet to confirm that we were not able to connect to the targeted IP ranges from gmail.
We determined that the email was attempting to be sent, but that the sendmail service was unable to connect to the ip ranges successfully.
We decided to allow all outbound traffic on port 25 in AWS (as our airflow production environment is an ec2 instance), and it now works successfully. We are now able to receive emails on failures and retries (tip: email_on_failure and email_on_retry are defaulted as True in your DAG API Reference - you do not need to put it into your args if you do not want to, but it is still good practice to explicitly state True or False in it).
SES now works. Here is the airflow config:
[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 = emailsmtpserver.region.amazonaws.com
smtp_starttls = True
smtp_ssl = False
# Uncomment and set the user/pass settings if you want to use SMTP AUTH
smtp_user = REMOVEDAWSACCESSKEY
smtp_password = REMOVEDAWSSECRETACCESSKEY
smtp_port = 587
smtp_mail_from = myemail#myjob.com (Verified SES email)
Thanks!
Similar case here, I tried to follow the same debugging process but got no log output. Also, the outbound rule for my airflow ec2 instance is open to all ports and ips, so it should be some other causes.
I noticed that when you create the SMTP credential from SES, it will also create an IAM user. I am not sure how is airflow running in your case (bare metal on ec2 instance or wrapped in containers), and how that user access is set up.
I will try to setup outgoing mail server in odoo 9 .so i fill all the field and test connection and the connection also success , but at the time of send mail it will generate an error .
Field fill like that:-
Name : sendmail
Priority: 10
SMTP Server : smtp.office365.com
SMTP Port:25
Debugging: enable
Connection Security:TLS (STARTTLS)
Username:my yser name
Password:password
But, when we send any mail then it will generate the below error
16-12-06 10:04:28,440 426 INFO test openerp.addons.base.ir.ir_mail_server: Mail delivery failed via SMTP server 'smtp.office365.com'.
SMTPDataError: 550
5.7.60 SMTP; Client does not have permissions to send as this sender
2016-12-06 10:04:28,443 426 ERROR test openerp.addons.mail.models.mail_mail: failed sending mail (id: 136) due to Mail Delivery Failed
Mail delivery failed via SMTP server 'smtp.office365.com'.
SMTPDataError: 550
5.7.60 SMTP; Client does not have permissions to send as this sender
Traceback (most recent call last):
File "/usr/lib/python2.7/dist- packages/openerp/addons/mail/models/mail_mail.py", line 262, in send
res = IrMailServer.send_email(msg, mail_server_id=mail.mail_server_id.id)
File "/usr/lib/python2.7/dist-packages/openerp/api.py", line 248, in wrapper
return new_api(self, *args, **kwargs)
File "/usr/lib/python2.7/dist-packages/openerp/api.py", line 490, in new_api
result = method(self._model, cr, uid, *args, **old_kwargs)
File "/usr/lib/python2.7/dist-packages/openerp/addons/base/ir/ir_mail_server.py", line 483, in send_email
raise MailDeliveryException(_("Mail Delivery Failed"), msg)
MailDeliveryException: (u'Mail Delivery Failed', u"Mail delivery failed via SMTP server 'smtp.office365.com'.\nSMTPDataError: 550\n5.7.60 SMTP; Client does not have permissions to send as this sender")
So i tried too much for this , but i am not getting any solution , if you have any solutin , please share with me .
Use port 587.
The error message tells you that the sender is invalid - you can only send as the mailbox owner (primary SMTP address) or as one of the proxy addresses associated with the mailbox.
Removing all catchall parameters (mail.catchall.domain and mail.catchall.alias) under "Settings" -> "Technical" -> "Parameters" -> "System Parameters" and it work like charm .
WORKS LIKE CHARM :
Removing all catchall parameters (mail.catchall.domain and mail.catchall.alias) under "Settings" -> "Technical" -> "Parameters" -> "System Parameters" and it work like charm . TY Debasish
I'm on Odoo V12
It was not suffisient for my problem, I had to delete the alias domain but there another thing to check :
I initialy created my odoo installation with a GMAIL address, worked a bit but had to switch for a pro e-mail because all my invitations e-mail was blocked by Google Bot beacause it look liked suspicious. It did this only in Odoo v12 because there is more links in the mail.
So I configured my real smtp server in Odoo but get the error 550. Odoo kept in the COMPANY settings the primary gmail address and tried to send on my other smtp server with the gmail name. The other server didn't accepted it so sent me back error 550.
Once i putted my new e-mail address in the company description, and deleted alias domain it worked !!
PS : Don't try to edit ir_mail_server.py to put in bruteforce your e-mail ... Doesn't work ..