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quay/workers/test/test_logrotateworker.py
Jimmy Zelinskie 4bf4ce33c9 util/metrics: remove metricqueue abstraction
This change replaces the metricqueue library with a native Prometheus
client implementation with the intention to aggregated results with the
Prometheus PushGateway.

This change also adds instrumentation for greenlet context switches.
2019-11-21 12:53:09 -05:00

143 lines
4.6 KiB
Python

import os.path
from datetime import datetime, timedelta
from app import storage
from data import model
from data.database import LogEntry, LogEntry2, LogEntry3
from data.logs_model.elastic_logs import INDEX_NAME_PREFIX, INDEX_DATE_FORMAT
from data.logs_model.datatypes import AggregatedLogCount, LogEntriesPage, Log
from data.logs_model.document_logs_model import DocumentLogsModel
from data.logs_model.test.fake_elasticsearch import FAKE_ES_HOST, fake_elasticsearch
from data.logs_model.table_logs_model import TableLogsModel
from data.logs_model.combined_model import CombinedLogsModel
from data.logs_model.inmemory_model import InMemoryModel
from data.logs_model import LogsModelProxy
from util.timedeltastring import convert_to_timedelta
from workers.logrotateworker import LogRotateWorker, SAVE_PATH, SAVE_LOCATION
from test.fixtures import *
@pytest.fixture()
def clear_db_logs(initialized_db):
LogEntry.delete().execute()
LogEntry2.delete().execute()
LogEntry3.delete().execute()
def combined_model():
return CombinedLogsModel(TableLogsModel(), InMemoryModel())
def es_model():
return DocumentLogsModel(producer='elasticsearch', elasticsearch_config={
'host': FAKE_ES_HOST,
'port': 12345,
})
@pytest.fixture()
def fake_es():
with fake_elasticsearch():
yield
@pytest.fixture(params=[TableLogsModel, es_model, InMemoryModel, combined_model])
def logs_model(request, clear_db_logs, fake_es):
model = request.param()
with patch('data.logs_model.logs_model', model):
with patch('workers.logrotateworker.logs_model', model):
yield model
def _lookup_logs(logs_model, start_time, end_time, **kwargs):
logs_found = []
page_token = None
while True:
found = logs_model.lookup_logs(start_time, end_time, page_token=page_token, **kwargs)
logs_found.extend(found.logs)
page_token = found.next_page_token
if not found.logs or not page_token:
break
assert len(logs_found) == len(set(logs_found))
return logs_found
def test_logrotateworker(logs_model):
worker = LogRotateWorker()
days = 90
start_timestamp = datetime(2019, 1, 1)
# Make sure there are no existing logs
found = _lookup_logs(logs_model, start_timestamp - timedelta(days=1000), start_timestamp + timedelta(days=1000))
assert not found
# Create some logs
for day in range(0, days):
logs_model.log_action('push_repo', namespace_name='devtable', repository_name='simple',
ip='1.2.3.4', timestamp=start_timestamp-timedelta(days=day))
# Ensure there are logs.
logs = _lookup_logs(logs_model,
start_timestamp - timedelta(days=1000),
start_timestamp + timedelta(days=1000))
assert len(logs) == days
# Archive all the logs.
assert worker._perform_archiving(start_timestamp + timedelta(days=1))
# Ensure all the logs were archived.
found = _lookup_logs(logs_model, start_timestamp - timedelta(days=1000), start_timestamp + timedelta(days=1000))
assert not found
def test_logrotateworker_with_cutoff(logs_model):
days = 60
start_timestamp = datetime(2019, 1, 1)
# Make sure there are no existing logs
found = _lookup_logs(logs_model, start_timestamp - timedelta(days=365), start_timestamp + timedelta(days=365))
assert not found
# Create a new set of logs/indices.
for day in range(0, days):
logs_model.log_action('push_repo', namespace_name='devtable', repository_name='simple',
ip='1.2.3.4', timestamp=start_timestamp+timedelta(days=day))
# Get all logs
logs = _lookup_logs(logs_model,
start_timestamp - timedelta(days=days-1),
start_timestamp + timedelta(days=days+1))
assert len(logs) == days
# Set the cutoff datetime to be the midpoint of the logs
midpoint = logs[0:len(logs)/2]
assert midpoint
assert len(midpoint) < len(logs)
worker = LogRotateWorker()
cutoff_date = midpoint[-1].datetime
# Archive the indices at or older than the cutoff date
archived_files = worker._perform_archiving(cutoff_date)
# Ensure the eariler logs were archived
found = _lookup_logs(logs_model, start_timestamp, cutoff_date-timedelta(seconds=1))
assert not found
# Check that the files were written to storage
for archived_file in archived_files:
assert storage.exists([SAVE_LOCATION], os.path.join(SAVE_PATH, archived_file))
# If current model uses ES, check that the indices were also deleted
if isinstance(logs_model, DocumentLogsModel):
assert len(logs_model.list_indices()) == days - (len(logs) / 2)
for index in logs_model.list_indices():
dt = datetime.strptime(index[len(INDEX_NAME_PREFIX):], INDEX_DATE_FORMAT)
assert dt >= cutoff_date