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Proper Celery Monitoring and File-Management with Web-Services

We are working on an Internet and Intranet platform, that serves client-requests over website applications.
There are heavy-weight computations on database entries and files. We want to update the state of those computations via push-notification to the client and make changes to files without the risk of race-conditions. The architecture is supposed to run on both, low- scaled one-server environments and high-scaled cluster environments.
So far, we are running a Django Webserver with Postgresql, the Python-Library Channels and RabbitMQ as Messagebroker.
Once a HTTP-Request from a client arrives in Django, we trigger the task via task.delay() and immediatly return the task_id to the client. The client then opens a websocket to another Django-route and hands over the task_ids he is interested in. Django then polls the state of the task via AsyncResult(task_id).state. Once the state changes, we read the results via AsyncResult(task_id).get and push the task_results to the client.
Here a similar sequence diagramm, from another project I found online.
Source(18.09.21)
Something that is not seen on the diagram, the channels_worker have to fetch the file they are working on from Django. A part of the result is not for the client, but to update the file. Django locks and updates the file localy as soon, as the client asks for and Django receives the task_results from celery (the changes only add attributes and will not be in conflict with each other).
My thoughts about this architecture are:
monitoring of the celery-events is bad so far.
It is only triggered by the client, which has to know about the tasks to begin with.
Django is not suited for monitoring
and polling is not efficient in general.
The file management seems fishy.
I would prefer a proper monitoring, where events are pushed to Django and the client. The client have to be able to consume the events at any time later.
I have some thoughts about solutions, but I would like to hear your opinion first. Later I can bring them in the discussion too.
Greetings
Python
Edit 1
From other sources I got helpful information regarding a good strategy.
Instead of Django "monitoring" the celery tasks, we can use a dedicated Websocket-Service, like FastAPI thand monitors task events and propagates them to the clients via websocket.
The client doesn't have to know about it's running tasks per se. Instead we can have ownership of tasks and the client only has to authenticate himself. The whole Security Blog will be implemented anyways and its supported by Celery.
For the file management, we should use a dedicated object storage like minio. This service can become subscriber to task-events related to files.

We all like Python, but we don't have to re-invent the wheel whenever we want a better monitoring or more control on the behavior of our systems.
That being said, I would recommend re-architecture the solution to decrease the complexity of your django application by exploring what native cloud solutions are offering in terms of micro-service architecture (API-Gateway), AWS SQS and SNS, computation, and storage options for your files.
Such an approach will carry out a lot of the monitoring, configurations, file management activities, and most importantly your monolithic application could scale without code changes or additional configurations.

Asynchronous Socket connections in Python or Node

I am creating an application that basically has multiple connections to a third party Chat Streaming API(Socket based).
The way it works is - Every user has an account on my app and another account on the third party app. He gives me an access token for the third party chat app and I connect to the third party API to stream his chats. This happens for hundreds of users.
I need to create a socket connection pool for every user and run parallel threads. I am using a python library(for that API) and am able to achieve real time feeds for single users. How do I implement an asynchronous socket connection pool in Python or NodeJS? I have a Linux micro instance on EC2 and I need to run this application for 1000 users.
I am exploring Redis+Tornado to implement this. Are there any better alternatives?

This will be messy and also a couple of things to consider.
If you are going to use multiple threads remember that you can only run so many per CPU as the OS permits, rather go multiprocessing.
If you are going async with long polling processes it will prevent other clients from processing requests.
Solution
When your application absolutely needs to be real-time I would suggest websockets for server-client interaction.
Then from your clients request start a single process that listens\polls on your streaming API using multiprocessing in python. So you will essentially create a separate process for each client.
And now, to make your WebSocketHandler and Background API Streamer interact with each other you can use the Observer Pattern (https://en.wikipedia.org/wiki/Observer_pattern) to notify the WebSocket that you have received data from the API.
Make sure that you assign a unique ID to every client and make sure that you only post the data to the intended client when using websockets.
EDIT:
Web:
Also on your question regarding Tornado. It is a good lightweight framework for running a couple of users maybe 1000. But anything more than that I would suggest looking at Django as it will allow you to be more productive in producing code and also there are lots of tools out there that the community have developed over time.
Database:
Red.is is a good choice if you need a very fast no-sql db, also have a look at mongodb. If you require a multi-region DB I would suggest going with Cassandra or CouchDB due to the partitioned nodes. The image below might help you better decide which DB to use.

Python: Listening to Pusher API events

So I've made a Flask application and I'm using it to push out data on certain events, through Pusher's python client.
My challenge is to now implement a method which can listen to events from a presence channel. From what I could gather by reading the source of the python client, there isn't much scope with that package. Any other libraries I could use? Conversely, any implementations I can see and figure out how it's done? Thanks

You can receive events via WebHooks:
http://pusher.com/docs/webhooks#presence
Or you could use the Pusher Python Client (which handles subscription functionality rather than publishing):
https://github.com/ekulyk/PythonPusherClient
The officially supported option would be to use WebHooks.

Webservices vs. Message Queues?

What are the implications of using webservices or message queues in an application?
In my case, I need to connect a Django web application with a python application, and I need two way communication between these applications. Sometimes the web app sends request to the python app to activate a few hardware devices, and sometimes the python app needs to be generally queried to obtain data.
The issue my entire application depends on instantaneous data received or sent to the python core application, so I cannot afford to waste system resources on querying everytime. I need to use something like a listener/receiver to send/receive data, without manually triggering a query every few seconds.
I am using Django for web application framework and Python for my core application.
I already have ZMQ being used internally for multiagent communication platform. If it is message queue, all I need to do is just connect to it, and send and receive data.
If it is a webservice, I need to freshly integrate the webservices. Again, what is the preferred method to create a webservice using Python?

Storage Backend based on Websockets

I spent quite some time now with researching Server Backends/API/Frameworks. I need a solution where I can store user content (JSON & Binary data).
The obvious choice would be a REST API. The only missing element is a push feature when data on server changed and clients should be notified instantly. With more research in this matter I discovered classic approaches (Comet, Push, Server sent events, Bayeux, BOSH, …) as well as the „new“ league, Websockets. I would definitely prefer the method with Websockets or using directly TCP Sockets. But this post is not about pros/cons of these two technologies so please restrain yourself from getting side tracked in comments.
At moment exists following projects which are very similar to my needs:
- Simperium (simperium.com), this looks very promising, but core/server is sadly not open source and god knows when, if ever, this step happens
- Realtime.co (framework.realtime.co/storage), hosted service, but same principle
- Some Frameworks for building servers such as Atmosphere (java, no WAMP), Cometd (java, project page looks like stuck in the 90’s), Autobahn (python, WAMP)
My actual favorite is the Autobahn framework (autobahn.ws). Especially using the WAMP protocol (subset of Websocket) as it offers exactly what I need. So the idea would be to build a python backend/server with Autobahn Python (based on Twisted framework) which manages all socket (WAMP) connections and include a Postgresql database for data storing. For all desired clients exists already WAMP libraries. The server would need to be able to do the typical REST API features:
- Send, update, delete requested data (JSON/Binary) from/to server/clients
- Synchronize & automatic conflict management
- Offline handling when connection breaks, automatic restart when connection available again
So finally the questions:
- Have I missed an open source project which covers exactly my needs?
- If I would like to develop my own server with autobahn and a database, could you point me to right direction? Have lot of concerns and not enough depth understanding.. I know Autobahn gives you already a server, but this one is not very close to my final needs.. how to build a server efficient so that he can handle all connected sockets? How handle when a client needs server push? Are there schemas, models or concept how such a server should look like?
- Twisted is a very powerful python framework but not regarded as the most convenient for writing apps.. But I guess a Socket based storage server with db access should be possible? When I run twisted as a web ressource and develop server components with other python framework, would this compromise the latency/performance much?
- Is such a desired server backend with lot of data storage (JSON fields and also binary data such as documents, images) reasonable to build with Sockets by a single devoloper/small team or is this smth. which only bigger companies like Dropbox can do at the moment?
Thank you very much for your help & time!

So finally the questions:
Have I missed an open source project which covers exactly my needs?
No you've covered the open source projects. Open source only gets you about halfway there though. To implement a Global Realtime Network requires equal parts implementation and equal parts operations. You have to think about dropped messages, retries, what happens if a particular geography gets hot how do you scale your servers ...etc. I would argue that an open source solution won't achieve what you want unless you're willing to invest significant resources into operations. I would recommend a service like PubNub: http://pubnub.com
If I would like to develop my own server with autobahn and a database, could you point me to right direction? Have lot of concerns and not enough depth understanding.. I know Autobahn gives you already a server, but this one is not very close to my final needs.. how to build a server efficient so that he can handle all connected sockets? How handle when a client needs server push? Are there schemas, models or concept how such a server should look like?
A good database to back a realtime framework would be Cassandra because it supports high write volumes and handles time series data well: http://cassandra.apache.org/.
Twisted is a very powerful python framework but not regarded as the most convenient for writing apps.. But I guess a Socket based storage server with db access should be possible? When I run twisted as a web ressource and develop server components with other python framework, would this compromise the latency/performance much?
I would not use Twisted. I would use Gevent:http://www.gevent.org/. Its coroutine based so you don't get into callback hell. To support more connections you just increase your greenlet pool to listen on the socket.
Is such a desired server backend with lot of data storage (JSON fields and also binary data such as documents, images) reasonable to build with Sockets by a single devoloper/small team or is this smth. which only bigger companies like Dropbox can do at the moment?
Again I would not build this on your own. A service like PubNub: http://pubnub.com which takes care of all the operational issues for you and has a clean API would service your needs with minimal cost. PubNub takes care of the protocol for you so if your on a mobile device that doesn't support WebSockets it will use TCP, HTTP or whatever the best transport is for the device.