instability: some clues

Daniel, Tobias, Renato and myself have been looking a little bit at the potential underlying reason
for why is instable, and have found some clues. I want to share them here
to give people with more experience in the frameworks used by LNT (flask, sqlalchemy, wsgi, …)
a chance to check if our reasoning below seems plausible.

Daniel noticed the following backtrace in the log after started giving “Internal Server Error”

2015-05-08 22:57:05,309 ERROR: Exception on /db_default/v4/nts/287/graph [GET] [in /opt/venv/perf/lib/python2.7/site-packages/Flask-0.10.1-py2.7.egg/flask/]

Traceback (most recent call last):

File “/opt/venv/perf/lib/python2.7/site-packages/Flask-0.10.1-py2.7.egg/flask/”, line 1817, in wsgi_app

response = self.full_dispatch_request()

File “/opt/venv/perf/lib/python2.7/site-packages/Flask-0.10.1-py2.7.egg/flask/”, line 1477, in full_dispatch_request

rv = self.handle_user_exception(e)

File “/opt/venv/perf/lib/python2.7/site-packages/Flask-0.10.1-py2.7.egg/flask/”, line 1381, in handle_user_exception

reraise(exc_type, exc_value, tb)

File “/opt/venv/perf/lib/python2.7/site-packages/Flask-0.10.1-py2.7.egg/flask/”, line 1475, in full_dispatch_request

rv = self.dispatch_request()

File “/opt/venv/perf/lib/python2.7/site-packages/Flask-0.10.1-py2.7.egg/flask/”, line 1461, in dispatch_request

return self.view_functionsrule.endpoint

File “/opt/venv/perf/lib/python2.7/site-packages/LNT-0.4.1dev-py2.7.egg/lnt/server/ui/”, line 67, in wrap

result = f(**args)

File “/opt/venv/perf/lib/python2.7/site-packages/LNT-0.4.1dev-py2.7.egg/lnt/server/ui/”, line 385, in v4_run_graph

ts = request.get_testsuite()

File “/opt/venv/perf/lib/python2.7/site-packages/LNT-0.4.1dev-py2.7.egg/lnt/server/ui/”, line 76, in get_testsuite

testsuites = self.get_db().testsuite

File “/opt/venv/perf/lib/python2.7/site-packages/LNT-0.4.1dev-py2.7.egg/lnt/server/ui/”, line 55, in get_db

self.db = current_app.old_config.get_database(g.db_name, echo=echo)

File “/opt/venv/perf/lib/python2.7/site-packages/LNT-0.4.1dev-py2.7.egg/lnt/server/”, line 148, in get_database

return lnt.server.db.v4db.V4DB(db_entry.path, self, echo=echo)

File “/opt/venv/perf/lib/python2.7/site-packages/LNT-0.4.1dev-py2.7.egg/lnt/server/db/”, line 108, in init

.filter_by(id = lnt.testing.PASS).first()

File “/opt/venv/perf/lib/python2.7/site-packages/SQLAlchemy-0.9.6-py2.7.egg/sqlalchemy/orm/”, line 2334, in first

ret = list(self[0:1])

File “/opt/venv/perf/lib/python2.7/site-packages/SQLAlchemy-0.9.6-py2.7.egg/sqlalchemy/orm/”, line 2201, in getitem

return list(res)

File “/opt/venv/perf/lib/python2.7/site-packages/SQLAlchemy-0.9.6-py2.7.egg/sqlalchemy/orm/”, line 2405, in iter

return self._execute_and_instances(context)

File “/opt/venv/perf/lib/python2.7/site-packages/SQLAlchemy-0.9.6-py2.7.egg/sqlalchemy/orm/”, line 2418, in _execute_and_instances


File “/opt/venv/perf/lib/python2.7/site-packages/SQLAlchemy-0.9.6-py2.7.egg/sqlalchemy/orm/”, line 2409, in _connection_from_session


File “/opt/venv/perf/lib/python2.7/site-packages/SQLAlchemy-0.9.6-py2.7.egg/sqlalchemy/orm/”, line 846, in connection


File “/opt/venv/perf/lib/python2.7/site-packages/SQLAlchemy-0.9.6-py2.7.egg/sqlalchemy/orm/”, line 850, in _connection_for_bind

return self.transaction._connection_for_bind(engine)

File “/opt/venv/perf/lib/python2.7/site-packages/SQLAlchemy-0.9.6-py2.7.egg/sqlalchemy/orm/”, line 315, in _connection_for_bind

conn = bind.contextual_connect()

File “/opt/venv/perf/lib/python2.7/site-packages/SQLAlchemy-0.9.6-py2.7.egg/sqlalchemy/engine/”, line 1737, in contextual_connect


File “/opt/venv/perf/lib/python2.7/site-packages/SQLAlchemy-0.9.6-py2.7.egg/sqlalchemy/”, line 332, in connect

return _ConnectionFairy._checkout(self)

File “/opt/venv/perf/lib/python2.7/site-packages/SQLAlchemy-0.9.6-py2.7.egg/sqlalchemy/”, line 630, in _checkout

fairy = _ConnectionRecord.checkout(pool)

File “/opt/venv/perf/lib/python2.7/site-packages/SQLAlchemy-0.9.6-py2.7.egg/sqlalchemy/”, line 433, in checkout

rec = pool._do_get()

File “/opt/venv/perf/lib/python2.7/site-packages/SQLAlchemy-0.9.6-py2.7.egg/sqlalchemy/”, line 945, in _do_get

(self.size(), self.overflow(), self._timeout))

TimeoutError: QueuePool limit of size 5 overflow 10 reached, connection timed out, timeout 30

After browsing through the sqlalchemy documentation and bits of the LNT implementation,
it seems so far that the following pieces may be the key parts that cause the problem
shown in the log.

The SQLAlchemy documentation seems to recommend to have a sqlalchemy session per web
request. Looking at the following pieces of LNT, I got the impression that instead a
session is shared between many or all requests:

From ui/, it shows Request.get_db() basically caches get_database from “config”:

class Request(flask.Request):

def get_db(self):

if self.db is None:

echo = bool(self.args.get(‘db_log’) or self.form.get(‘db_log’))

self.db = current_app.old_config.get_database(g.db_name, echo=echo)

return self.db

in, it is shown that get_database returns a V4DB object by calling a constructor:

def get_database(self, name, echo=False):

Instantiate the appropriate database version.

if db_entry.db_version == ‘0.4’:

return lnt.server.db.v4db.V4DB(db_entry.path, self,



This constructor is in db/

class V4DB(object):

def init(self, path, config, baseline_revision=0, echo=False):

self.session = sqlalchemy.orm.sessionmaker(self.engine)()

Add several shortcut aliases.

self.add = self.session.add

self.commit = self.session.commit

self.query = self.session.query

self.rollback = self.session.rollback

It seems like a single session object is created in this constructor that will ultimately
be shared across all Requests. It seems that instead, the request.get_db method should
create a new session for each request. And close that session when the request is finalized
which probably needs to be done by hooking into something Flask-specific.

The self.add and following lines in the constructor show that it probably will be
non-trivial to refactor code so that there will not be a single session per v4db object.

We’re not sure if making separate sessions per Request is going to solve the
instability problems; but that’s the best idea we’ve got so far.



Hi Kristof,

It has been a long time since I looked at this, but aren’t we just caching the DB on the request object, thus ensuring there is one opened DB, and hence session, per request? The V4DB is essentially just wrapping the session.

  • Daniel

Daniel is correct.

I have been dealing with issues like this a lot recently with our internal LNT. Assuming this is the same issue, I’ll share what I have figured out so far. I run LNT from gunicorn, proxied with apache. We were getting a lot of timeouts on submissions, and exhausted database connections. In our case, we are using Postgres, and LNT would easily use all 100 connections Postgres creates by default. Apache like to mask these things by timing you out early.

I traced our issue back to the submitRun being extremely slow on about 1 in 5 submissions. I get a feeling it was the submissions for particular machines possibly some of the older machines, though I could not reproduce it reliably. I found that with timeout removed, some submissions were taking 200s to process, and a few were as long as 400s. I did this by putting print statements in our production server and watching the submit requests being processed. All this time is spent generating the field changes, I did not dig in any further than that. What was happening is that as we were running more runs, we had more and more submissions taking that long, and eventually the server would start throwing errors like this, because all database connections were in use doing submissions.

My solution: I jacked our timeouts way up (1000s) and upped our database connections even further. We do now process all our submissions, and I only feel sort of dirty when I think about it.

The real solution: we have to find out what is going in in field change generation that is sucking up so much time! Submit run is interesting, it is the only place in LNT were we write into the database, and we are doing a lot of processing of the data when it comes in.

Maybe we should track this with a PR? I am willing to help track this down. I’ve found the lack of request logging makes it sort of tricky to nail down how often this happens, the only insights I have are from adding print statements to suspect code paths.