I've managed to reproduce the issue locally. In order to reproduce it, you need to: 
1) setup a vm with 4 cores and 32G of RAM (or whatever, just ensure the ram is enough). 
2) restore the DB taken from the reporter's environment
3) install MAAS 3.2.9 (or a newer version)
4) hammer MAAS with a script like for at least 1 minute (in order to overload MAAS) and keep it running

```
import asyncio
import aiohttp 
import time
import uuid
import random 
import numpy as np
import json 


base_url = 'http://10.0.2.46:5240'  # Replace with your MAAS URL


async def make_http_request(session, http_method, url):
    headers = {"Authorization": "OAuth oauth_version=1.0, oauth_signature_method=PLAINTEXT, oauth_consumer_key=<REDACTED>, oauth_token=<REDACTED>, oauth_signature=&<REDACTED>, oauth_nonce=" + str(uuid.uuid4()) + ", oauth_timestamp=" + str(int(time.time()))}
    full_url = f"{base_url}{url}"
    print(full_url)
    try:
        body = {}
        if http_method == "POST":
            body = {'mode': 'AUTO', 'subnet': 2}
        async with session.request(http_method, full_url, data=json.dumps(body), headers=headers) as response:
            while True:
                chunk = await response.content.read(512)  # Adjust the chunk size as needed
                if not chunk:
                    break
                await asyncio.sleep(0.5) # just slow down the download speed
            print("OK")
            return full_url, response.status
    except Exception as e:
        print("EXCEPTION")
        print(str(e))
        return full_url, str(e)

# Some of the HTTP calls from the reporter's environment
urls = [
("GET", "/MAAS/api/2.0/machines/?agent_name=9a7502fa-3149-4d63-8b92-aec26ae8d7eb&id=hydcaa"), # This is the most problematic one, as usual.
("GET", "/MAAS/api/2.0/version/"),
("GET", "/MAAS/api/2.0/users/?op=whoami"),
("GET", "/MAAS/api/2.0/zones/"),
("GET", "/MAAS/api/2.0/spaces/"),
("GET", "/MAAS/api/2.0/static-routes/"),
("GET", "/MAAS/rpc/"),
("GET", "/MAAS/api/2.0/devices/?hostname=juju-ad2531-5-lxd-8"),
("POST", "/MAAS/api/2.0/nodes/mdyndn/interfaces/519149/?op=link_subnet")
]

async def main():
    async with aiohttp.ClientSession() as session:
        while True:
            # pick a request to shoot according to the probabilities calculated on the reporter's logs 
            bullet = np.random.choice(range(len(urls)), p=[
                0.207619047619047616,
                0.2161904761904762,
                0.14761904761904763,
                0.02857142857142857,
                0.0761904761904762,
                0.03333333333333333,
                0.047619047619047616,
                0.09047619047619047,
                0.1523809523809524
            ])
            method, url = urls[bullet]
            # sleep a bit between every request.
            # the less we sleep, the more you'll hit the issue. 
            await asyncio.sleep(0.07)
            asyncio.ensure_future(make_http_request(session, method, url))

if __name__ == '__main__':
    loop = asyncio.get_event_loop()
    loop.run_until_complete(main())
```
5) run the following bash script
```
#!/bin/bash

for i in {1..6}; do
  curl --header "Authorization: OAuth oauth_version=1.0, oauth_signature_method=PLAINTEXT, oauth_consumer_key=<REDACTED> oauth_token=<REDACTED>, oauth_signature=&<REDACTED>, oauth_nonce=$(uuidgen), oauth_timestamp=$(date +%s)" http://10.0.2.46:5240/MAAS/api/2.0/machines/?op=allocate -X POST &
done

wait
```
6) after around 90 seconds, you should get a 409 for a request. 

The underlying issue should be that the allocate operation uses a database lock and the request that is accessing the database is so slow that all the others are blocked until the first transaction is committed/aborted. 

I think this issue is actually caused by the slowness of the MAAS api. A redesign of MAAS is on the roadmap in order to address this known issue. For the time being my suggestion is to add another region machine, add HA proxy and/or use a more powerful machine (I noticed that the 5 MAAS processes are using from 70% to 100% cpu during high load and this is causing the unpredictable issues you've hit).