#!/usr/local/bin/python2.7 """ Copyright (c) 2016 Ad Schellevis All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. -------------------------------------------------------------------------------------- Aggregate flowd data for reporting """ import time import os import sys import signal import glob import copy import syslog import traceback sys.path.insert(0, "/usr/local/opnsense/site-python") from sqlite3_helper import check_and_repair from lib.parse import parse_flow from lib.aggregate import AggMetadata import lib.aggregates from daemonize import Daemonize MAX_FILE_SIZE_MB=10 MAX_LOGS=10 def aggregate_flowd(do_vacuum=False): """ aggregate collected flowd data :param do_vacuum: vacuum database after cleanup :return: None """ # init metadata (progress maintenance) metadata = AggMetadata() # register aggregate classes to stream data to stream_agg_objects = list() for agg_class in lib.aggregates.get_aggregators(): for resolution in agg_class.resolutions(): stream_agg_objects.append(agg_class(resolution)) # parse flow data and stream to registered consumers prev_recv = metadata.last_sync() commit_record_count = 0 for flow_record in parse_flow(prev_recv): if flow_record is None or (prev_recv != flow_record['recv'] and commit_record_count > 100000): # commit data on receive timestamp change or last record for stream_agg_object in stream_agg_objects: stream_agg_object.commit() metadata.update_sync_time(prev_recv) if flow_record is not None: # send to aggregator for stream_agg_object in stream_agg_objects: # class add() may change the flow contents for processing, its better to isolate # paremeters here. flow_record_cpy = copy.copy(flow_record) stream_agg_object.add(flow_record_cpy) commit_record_count += 1 prev_recv = flow_record['recv'] # expire old data for stream_agg_object in stream_agg_objects: stream_agg_object.cleanup(do_vacuum) del stream_agg_object del metadata def check_rotate(): """ Checks if flowd log needs to be rotated, if so perform rotate. We keep [MAX_LOGS] number of logs containing approx. [MAX_FILE_SIZE_MB] data, the flowd data probably contains more detailed data then the stored aggregates. :return: None """ if os.path.getsize("/var/log/flowd.log")/1024/1024 > MAX_FILE_SIZE_MB: # max filesize reached rotate filenames = sorted(glob.glob('/var/log/flowd.log.*'), reverse=True) file_sequence = len(filenames) for filename in filenames: sequence = filename.split('.')[-1] if sequence.isdigit(): if file_sequence >= MAX_LOGS: os.remove(filename) elif int(sequence) != 0: os.rename(filename, filename.replace('.%s' % sequence, '.%06d' % (int(sequence)+1))) file_sequence -= 1 # rename /var/log/flowd.log os.rename('/var/log/flowd.log', '/var/log/flowd.log.000001') # signal flowd for new log file if os.path.isfile('/var/run/flowd.pid'): pid = open('/var/run/flowd.pid').read().strip() if pid.isdigit(): try: os.kill(int(pid), signal.SIGUSR1) except OSError: pass class Main(object): def __init__(self): """ construct, hook signal handler and run aggregators :return: None """ self.running = True signal.signal(signal.SIGTERM, self.signal_handler) self.run() def run(self): """ run, endless loop, until sigterm is received :return: None """ # check database consistency / repair check_and_repair('/var/netflow/*.sqlite') vacuum_interval = (60*60*8) # 8 hour vacuum cycle vacuum_countdown = None while self.running: # should we perform a vacuum if not vacuum_countdown or vacuum_countdown < time.time(): vacuum_countdown = time.time() + vacuum_interval do_vacuum = True else: do_vacuum = False # run aggregate try: aggregate_flowd(do_vacuum) except: syslog.syslog(syslog.LOG_ERR, 'flowd aggregate died with message %s' % (traceback.format_exc())) return # rotate if needed check_rotate() # wait for next pass, exit on sigterm for i in range(30): if self.running: time.sleep(0.5) else: break def signal_handler(self, sig, frame): """ end (run) loop on signal :param sig: signal :pram frame: frame :return: None """ self.running = False if len(sys.argv) > 1 and 'console' in sys.argv[1:]: # command line start if 'profile' in sys.argv[1:]: # start with profiling import cProfile import StringIO import pstats pr = cProfile.Profile(builtins=False) pr.enable() Main() pr.disable() s = StringIO.StringIO() sortby = 'cumulative' ps = pstats.Stats(pr, stream=s).sort_stats(sortby) ps.print_stats() print s.getvalue() else: Main() else: # Daemonize flowd aggregator daemon = Daemonize(app="flowd_aggregate", pid='/var/run/flowd_aggregate.pid', action=Main) daemon.start()