3d6d20ae6a
Zuul now logs for every project + job the number of seconds taken and the number of nodes used. Using this we can scrape the logs to determine usage rates by project, repo, and job. Change-Id: Ie790df12e731f363ef7819d11b6d44c28e3d8320
158 lines
5.7 KiB
Python
158 lines
5.7 KiB
Python
import gzip
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import os
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import re
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import yaml
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def get_log_age(path):
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filename = os.path.basename(path)
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parts = filename.split('.')
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if len(parts) < 4:
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return 0
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else:
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return int(parts[2])
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class LogScraper(object):
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# Example log line
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# 2018-10-26 16:14:47,527 INFO zuul.nodepool: Nodeset <NodeSet two-centos-7-nodes [<Node 0000058431 ('primary',):centos-7>, <Node 0000058468 ('secondary',):centos-7>]> with 2 nodes was in use for 6241.08082151413 seconds for build <Build 530c4ca7af9e44dcb535e7074258e803 of tripleo-ci-centos-7-scenario008-multinode-oooq-container voting:False on <Worker ze05.openstack.org>> for project openstack/tripleo-quickstart-extras # noqa
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r = re.compile(r'(?P<timestamp>\d+-\d+-\d+ \d\d:\d\d:\d\d,\d\d\d) INFO zuul.nodepool: Nodeset <.*> with (?P<nodes>\d+) nodes was in use for (?P<secs>\d+(.[\d\-e]+)?) seconds for build <Build \w+ of (?P<job>[^\s]+) voting:\w+ on .* for project (?P<repos>[^\s]+)') # noqa
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def __init__(self):
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self.repos = {}
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self.sorted_repos = []
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self.jobs = {}
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self.sorted_jobs = []
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self.total_usage = 0.0
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self.projects = {}
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self.sorted_projects = []
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self.start_time = None
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self.end_time = None
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def scrape_file(self, fn):
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if fn.endswith('.gz'):
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open_f = gzip.open
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else:
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open_f = open
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with open_f(fn, 'rt') as f:
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for line in f:
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if 'nodes was in use for' in line:
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m = self.r.match(line)
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if not m:
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continue
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g = m.groupdict()
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repo = g['repos']
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secs = float(g['secs'])
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nodes = int(g['nodes'])
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job = g['job']
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if not self.start_time:
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self.start_time = g['timestamp']
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self.end_time = g['timestamp']
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if repo not in self.repos:
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self.repos[repo] = {}
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self.repos[repo]['total'] = 0.0
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node_time = nodes * secs
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self.total_usage += node_time
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self.repos[repo]['total'] += node_time
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if job not in self.jobs:
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self.jobs[job] = 0.0
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if job not in self.repos[repo]:
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self.repos[repo][job] = 0.0
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self.jobs[job] += node_time
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self.repos[repo][job] += node_time
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def list_log_files(self, path='/var/log/zuul'):
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ret = []
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entries = os.listdir(path)
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prefix = os.path.join(path, 'zuul.log')
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for entry in entries:
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entry = os.path.join(path, entry)
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if os.path.isfile(entry) and entry.startswith(prefix):
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ret.append(entry)
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ret.sort(key=get_log_age, reverse=True)
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return ret
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def sort_repos(self):
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for repo in self.repos:
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self.sorted_repos.append((repo, self.repos[repo]['total']))
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self.sorted_repos.sort(key=lambda x: x[1], reverse=True)
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def sort_jobs(self):
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for job, usage in self.jobs.items():
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self.sorted_jobs.append((job, usage))
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self.sorted_jobs.sort(key=lambda x: x[1], reverse=True)
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def calculate_project_usage(self):
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'''Group usage by logical project/effort
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It is often the case that a single repo doesn't capture the work
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of a logical project or effort. If this is the case in your situation
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you can create a projects.yaml file that groups together repos
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under logical project names to report usage by that logical grouping.
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The projects.yaml should be in your current directory and have this
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format:
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project_name:
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deliverables:
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logical_deliverable_name:
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repos:
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- repo1
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- repo2
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project_name2:
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deliverables:
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logical_deliverable_name2:
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repos:
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- repo3
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- repo4
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'''
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if not os.path.exists('projects.yaml'):
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return self.sorted_projects
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with open('projects.yaml') as f:
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y = yaml.load(f)
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for name, v in y.items():
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self.projects[name] = 0.0
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for deliverable in v['deliverables'].values():
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for repo in deliverable['repos']:
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if repo in self.repos:
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self.projects[name] += self.repos[repo]['total']
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for project, usage in self.projects.items():
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self.sorted_projects.append((project, usage))
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self.sorted_projects.sort(key=lambda x: x[1], reverse=True)
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scraper = LogScraper()
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for fn in scraper.list_log_files():
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scraper.scrape_file(fn)
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print('For period from %s to %s' % (scraper.start_time, scraper.end_time))
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print('Total node time used: %.2fs' % scraper.total_usage)
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print()
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scraper.calculate_project_usage()
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if scraper.sorted_projects:
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print('Top 20 logical projects by resource usage:')
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for project, total in scraper.sorted_projects[:20]:
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percentage = (total / scraper.total_usage) * 100
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print('%s: %.2fs, %.2f%%' % (project, total, percentage))
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print()
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scraper.sort_repos()
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print('Top 20 repos by resource usage:')
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for repo, total in scraper.sorted_repos[:20]:
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percentage = (total / scraper.total_usage) * 100
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print('%s: %.2fs, %.2f%%' % (repo, total, percentage))
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print()
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scraper.sort_jobs()
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print('Top 20 jobs by resource usage:')
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for job, total in scraper.sorted_jobs[:20]:
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percentage = (total / scraper.total_usage) * 100
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print('%s: %.2fs, %.2f%%' % (job, total, percentage))
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print()
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