openstack/cloudkitty
Code Issues Proposed changes

Add OpenSearch as a v2 storage backend

Browse Source 
To facilitate the switch from Elasticsearch to OpenSearch, the ES
backend has been duplicated and renamed where appropriate to OpenSearch.

The OpenSearch implementation was modified in places for compatibility
with OpenSearch 2.x, for example:

- remove mapping name from bulk API URL
- replace put_mapping by post_mapping

This will allow for the future removal of the Elasticsearch backend.

Change-Id: I88b0a30f66af13dad1bd75cde412d2880b4ead30
Co-Authored-By: Pierre Riteau <pierre@stackhpc.com>
(cherry picked from commit 964c6704a2)
This commit is contained in:
Matt Crees 2023-04-18 13:39:07 +01:00 committed by Pierre Riteau
parent 74462f0ade
commit 7b1cd3aee0
14 changed files with 1349 additions and 18 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

13
.zuul.yaml
View File

@ -94,6 +94,17 @@
CLOUDKITTY_STORAGE_BACKEND: elasticsearch
CLOUDKITTY_STORAGE_VERSION: 2
- job:
name: cloudkitty-tempest-full-v2-storage-opensearch
parent: base-cloudkitty-v2-api-tempest-job
description: |
Job testing cloudkitty installation on devstack with python 3 and the
OpenSearch v2 storage driver and running tempest tests
vars:
devstack_localrc:
CLOUDKITTY_STORAGE_BACKEND: opensearch
CLOUDKITTY_STORAGE_VERSION: 2
- job:
name: cloudkitty-tox-bandit
parent: openstack-tox
@ -130,6 +141,8 @@
- cloudkitty-tempest-full-v2-storage-influxdb
- cloudkitty-tempest-full-v2-storage-elasticsearch:
voting: false
- cloudkitty-tempest-full-v2-storage-opensearch:
voting: false
- cloudkitty-tempest-full-v1-storage-sqlalchemy
- cloudkitty-tempest-full-ipv6-only
- cloudkitty-tox-bandit:

3
cloudkitty/common/config.py
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@ -32,6 +32,7 @@ import cloudkitty.storage
import cloudkitty.storage.v1.hybrid.backends.gnocchi
import cloudkitty.storage.v2.elasticsearch
import cloudkitty.storage.v2.influx
import cloudkitty.storage.v2.opensearch
import cloudkitty.utils
__all__ = ['list_opts']
@ -70,6 +71,8 @@ _opts = [
cloudkitty.storage.v2.influx.influx_storage_opts))),
('storage_elasticsearch', list(itertools.chain(
cloudkitty.storage.v2.elasticsearch.elasticsearch_storage_opts))),
('storage_opensearch', list(itertools.chain(
cloudkitty.storage.v2.opensearch.opensearch_storage_opts))),
('storage_gnocchi', list(itertools.chain(
cloudkitty.storage.v1.hybrid.backends.gnocchi.gnocchi_storage_opts))),
(None, list(itertools.chain(

205
cloudkitty/storage/v2/opensearch/__init__.py Normal file
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@ -0,0 +1,205 @@
# Copyright 2019 Objectif Libre
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
#
import datetime
from oslo_config import cfg
from oslo_log import log
from cloudkitty import dataframe
from cloudkitty.storage import v2 as v2_storage
from cloudkitty.storage.v2.opensearch import client as os_client
from cloudkitty.storage.v2.opensearch import exceptions
from cloudkitty.utils import tz as tzutils
LOG = log.getLogger(__name__)
CONF = cfg.CONF
OPENSEARCH_STORAGE_GROUP = 'storage_opensearch'
opensearch_storage_opts = [
cfg.StrOpt(
'host',
help='OpenSearch host, along with port and protocol. '
'Defaults to http://localhost:9200',
default='http://localhost:9200'),
cfg.StrOpt(
'index_name',
help='OpenSearch index to use. Defaults to "cloudkitty".',
default='cloudkitty'),
cfg.BoolOpt('insecure',
help='Set to true to allow insecure HTTPS '
'connections to OpenSearch',
default=False),
cfg.StrOpt('cafile',
help='Path of the CA certificate to trust for '
'HTTPS connections.',
default=None),
cfg.IntOpt('scroll_duration',
help="Duration (in seconds) for which the OpenSearch scroll "
"contexts should be kept alive.",
advanced=True,
default=30, min=0, max=300),
]
CONF.register_opts(opensearch_storage_opts, OPENSEARCH_STORAGE_GROUP)
CLOUDKITTY_INDEX_MAPPING = {
"dynamic_templates": [
{
"strings_as_keywords": {
"match_mapping_type": "string",
"mapping": {
"type": "keyword"
}
}
}
],
"dynamic": False,
"properties": {
"start": {"type": "date"},
"end": {"type": "date"},
"type": {"type": "keyword"},
"unit": {"type": "keyword"},
"qty": {"type": "double"},
"price": {"type": "double"},
"groupby": {"dynamic": True, "type": "object"},
"metadata": {"dynamic": True, "type": "object"}
},
}
class OpenSearchStorage(v2_storage.BaseStorage):
def __init__(self, *args, **kwargs):
super(OpenSearchStorage, self).__init__(*args, **kwargs)
LOG.warning('The OpenSearch storage driver is experimental. '
'DO NOT USE IT IN PRODUCTION.')
verify = not CONF.storage_opensearch.insecure
if verify and CONF.storage_opensearch.cafile:
verify = CONF.storage_opensearch.cafile
self._conn = os_client.OpenSearchClient(
CONF.storage_opensearch.host,
CONF.storage_opensearch.index_name,
"_doc",
verify=verify)
def init(self):
r = self._conn.get_index()
if r.status_code != 200:
raise exceptions.IndexDoesNotExist(
CONF.storage_opensearch.index_name)
LOG.info('Creating mapping "_doc" on index {}...'.format(
CONF.storage_opensearch.index_name))
self._conn.post_mapping(CLOUDKITTY_INDEX_MAPPING)
LOG.info('Mapping created.')
def push(self, dataframes, scope_id=None):
for frame in dataframes:
for type_, point in frame.iterpoints():
start, end = self._local_to_utc(frame.start, frame.end)
self._conn.add_point(point, type_, start, end)
self._conn.commit()
@staticmethod
def _local_to_utc(*args):
return [tzutils.local_to_utc(arg) for arg in args]
@staticmethod
def _doc_to_datapoint(doc):
return dataframe.DataPoint(
doc['unit'],
doc['qty'],
doc['price'],
doc['groupby'],
doc['metadata'],
)
def _build_dataframes(self, docs):
dataframes = {}
nb_points = 0
for doc in docs:
source = doc['_source']
start = tzutils.dt_from_iso(source['start'])
end = tzutils.dt_from_iso(source['end'])
key = (start, end)
if key not in dataframes.keys():
dataframes[key] = dataframe.DataFrame(start=start, end=end)
dataframes[key].add_point(
self._doc_to_datapoint(source), source['type'])
nb_points += 1
output = list(dataframes.values())
output.sort(key=lambda frame: (frame.start, frame.end))
return output
def retrieve(self, begin=None, end=None,
filters=None,
metric_types=None,
offset=0, limit=1000, paginate=True):
begin, end = self._local_to_utc(begin or tzutils.get_month_start(),
end or tzutils.get_next_month())
total, docs = self._conn.retrieve(
begin, end, filters, metric_types,
offset=offset, limit=limit, paginate=paginate)
return {
'total': total,
'dataframes': self._build_dataframes(docs),
}
def delete(self, begin=None, end=None, filters=None):
self._conn.delete_by_query(begin, end, filters)
@staticmethod
def _normalize_time(t):
if isinstance(t, datetime.datetime):
return tzutils.utc_to_local(t)
return tzutils.dt_from_iso(t)
def _doc_to_total_result(self, doc, start, end):
output = {
'begin': self._normalize_time(doc.get('start', start)),
'end': self._normalize_time(doc.get('end', end)),
'qty': doc['sum_qty']['value'],
'rate': doc['sum_price']['value'],
}
# Means we had a composite aggregation
if 'key' in doc.keys():
for key, value in doc['key'].items():
if key == 'begin' or key == 'end':
# OpenSearch returns ts in milliseconds
value = tzutils.dt_from_ts(value // 1000)
output[key] = value
return output
def total(self, groupby=None, begin=None, end=None, metric_types=None,
filters=None, custom_fields=None, offset=0, limit=1000,
paginate=True):
begin, end = self._local_to_utc(begin or tzutils.get_month_start(),
end or tzutils.get_next_month())
total, docs = self._conn.total(begin, end, metric_types, filters,
groupby, custom_fields=custom_fields,
offset=offset, limit=limit,
paginate=paginate)
return {
'total': total,
'results': [self._doc_to_total_result(doc, begin, end)
for doc in docs],
}

412
cloudkitty/storage/v2/opensearch/client.py Normal file
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@ -0,0 +1,412 @@
# Copyright 2019 Objectif Libre
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
#
import itertools
from oslo_log import log
import requests
from cloudkitty.storage.v2.opensearch import exceptions
from cloudkitty.utils import json
LOG = log.getLogger(__name__)
class OpenSearchClient(object):
"""Class used to ease interaction with OpenSearch.
:param autocommit: Defaults to True. Automatically push documents to
OpenSearch once chunk_size has been reached.
:type autocommit: bool
:param chunk_size: Maximal number of documents to commit/retrieve at once.
:type chunk_size: int
:param scroll_duration: Defaults to 60. Duration, in seconds, for which
search contexts should be kept alive
:type scroll_duration: int
"""
def __init__(self, url, index_name, mapping_name,
verify=True,
autocommit=True,
chunk_size=5000,
scroll_duration=60):
self._url = url.strip('/')
self._index_name = index_name.strip('/')
self._mapping_name = mapping_name.strip('/')
self._autocommit = autocommit
self._chunk_size = chunk_size
self._scroll_duration = str(scroll_duration) + 's'
self._scroll_params = {'scroll': self._scroll_duration}
self._docs = []
self._scroll_ids = set()
self._sess = requests.Session()
self._verify = self._sess.verify = verify
self._sess.headers = {'Content-Type': 'application/json'}
@staticmethod
def _log_query(url, query, response):
message = 'Query on {} with body "{}" took {}ms'.format(
url, query, response['took'])
if 'hits' in response.keys():
message += ' for {} hits'.format(response['hits']['total'])
LOG.debug(message)
@staticmethod
def _build_must(start, end, metric_types, filters):
must = []
if start:
must.append({"range": {"start": {"gte": start.isoformat()}}})
if end:
must.append({"range": {"end": {"lte": end.isoformat()}}})
if filters and 'type' in filters.keys():
must.append({'term': {'type': filters['type']}})
if metric_types:
must.append({"terms": {"type": metric_types}})
return must
@staticmethod
def _build_should(filters):
if not filters:
return []
should = []
for k, v in filters.items():
if k != 'type':
should += [{'term': {'groupby.' + k: v}},
{'term': {'metadata.' + k: v}}]
return should
def _build_composite(self, groupby):
if not groupby:
return []
sources = []
for elem in groupby:
if elem == 'type':
sources.append({'type': {'terms': {'field': 'type'}}})
elif elem == 'time':
# Not doing a date_histogram aggregation because we don't know
# the period
sources.append({'begin': {'terms': {'field': 'start'}}})
sources.append({'end': {'terms': {'field': 'end'}}})
else:
sources.append({elem: {'terms': {'field': 'groupby.' + elem}}})
return {"sources": sources}
@staticmethod
def _build_query(must, should, composite):
query = {}
if must or should:
query["query"] = {"bool": {}}
if must:
query["query"]["bool"]["must"] = must
if should:
query["query"]["bool"]["should"] = should
# We want each term to match exactly once, and each term introduces
# two "term" aggregations: one for "groupby" and one for "metadata"
query["query"]["bool"]["minimum_should_match"] = len(should) // 2
if composite:
query["aggs"] = {"sum_and_price": {
"composite": composite,
"aggregations": {
"sum_price": {"sum": {"field": "price"}},
"sum_qty": {"sum": {"field": "qty"}},
}
}}
return query
def _req(self, method, url, data, params, deserialize=True):
r = method(url, data=data, params=params)
if r.status_code < 200 or r.status_code >= 300:
raise exceptions.InvalidStatusCode(
200, r.status_code, r.text, data)
if not deserialize:
return r
output = r.json()
self._log_query(url, data, output)
return output
def post_mapping(self, mapping):
"""Does a POST request against OpenSearch's mapping API.
The POST request will be done against
`/<index_name>/<mapping_name>`
:mapping: body of the request
:type mapping: dict
:rtype: requests.models.Response
"""
url = '/'.join(
(self._url, self._index_name, self._mapping_name))
return self._req(
self._sess.post, url, json.dumps(mapping), {}, deserialize=False)
def get_index(self):
"""Does a GET request against OpenSearch's index API.
The GET request will be done against `/<index_name>`
:rtype: requests.models.Response
"""
url = '/'.join((self._url, self._index_name))
return self._req(self._sess.get, url, None, None, deserialize=False)
def search(self, body, scroll=True):
"""Does a GET request against OpenSearch's search API.
The GET request will be done against `/<index_name>/_search`
:param body: body of the request
:type body: dict
:rtype: dict
"""
url = '/'.join((self._url, self._index_name, '_search'))
params = self._scroll_params if scroll else None
return self._req(
self._sess.get, url, json.dumps(body), params)
def scroll(self, body):
"""Does a GET request against OpenSearch's scroll API.
The GET request will be done against `/_search/scroll`
:param body: body of the request
:type body: dict
:rtype: dict
"""
url = '/'.join((self._url, '_search/scroll'))
return self._req(self._sess.get, url, json.dumps(body), None)
def close_scroll(self, body):
"""Does a DELETE request against OpenSearch's scroll API.
The DELETE request will be done against `/_search/scroll`
:param body: body of the request
:type body: dict
:rtype: dict
"""
url = '/'.join((self._url, '_search/scroll'))
resp = self._req(
self._sess.delete, url, json.dumps(body), None, deserialize=False)
body = resp.json()
LOG.debug('Freed {} scrolls contexts'.format(body['num_freed']))
return body
def close_scrolls(self):
"""Closes all scroll contexts opened by this client."""
ids = list(self._scroll_ids)
LOG.debug('Closing {} scroll contexts: {}'.format(len(ids), ids))
self.close_scroll({'scroll_id': ids})
self._scroll_ids = set()
def bulk_with_instruction(self, instruction, terms):
"""Does a POST request against OpenSearch's bulk API
The POST request will be done against
`/<index_name>/_bulk`
The instruction will be appended before each term. For example,
bulk_with_instruction('instr', ['one', 'two']) will produce::
instr
one
instr
two
:param instruction: instruction to execute for each term
:type instruction: dict
:param terms: list of terms for which instruction should be executed
:type terms: collections.abc.Iterable
:rtype: requests.models.Response
"""
instruction = json.dumps(instruction)
data = '\n'.join(itertools.chain(
*[(instruction, json.dumps(term)) for term in terms]
)) + '\n'
url = '/'.join(
(self._url, self._index_name, '_bulk'))
return self._req(self._sess.post, url, data, None, deserialize=False)
def bulk_index(self, terms):
"""Indexes each of the documents in 'terms'
:param terms: list of documents to index
:type terms: collections.abc.Iterable
"""
LOG.debug("Indexing {} documents".format(len(terms)))
return self.bulk_with_instruction({"index": {}}, terms)
def commit(self):
"""Index all documents"""
while self._docs:
self.bulk_index(self._docs[:self._chunk_size])
self._docs = self._docs[self._chunk_size:]
def add_point(self, point, type_, start, end):
"""Append a point to the client.
:param point: DataPoint to append
:type point: cloudkitty.dataframe.DataPoint
:param type_: type of the DataPoint
:type type_: str
"""
self._docs.append({
'start': start,
'end': end,
'type': type_,
'unit': point.unit,
'qty': point.qty,
'price': point.price,
'groupby': point.groupby,
'metadata': point.metadata,
})
if self._autocommit and len(self._docs) >= self._chunk_size:
self.commit()
def _get_chunk_size(self, offset, limit, paginate):
if paginate and offset + limit < self._chunk_size:
return offset + limit
return self._chunk_size
def retrieve(self, begin, end, filters, metric_types,
offset=0, limit=1000, paginate=True):
"""Retrieves a paginated list of documents from OpenSearch."""
if not paginate:
offset = 0
query = self._build_query(
self._build_must(begin, end, metric_types, filters),
self._build_should(filters), None)
query['size'] = self._get_chunk_size(offset, limit, paginate)
resp = self.search(query)
scroll_id = resp['_scroll_id']
self._scroll_ids.add(scroll_id)
total_hits = resp['hits']['total']
if isinstance(total_hits, dict):
LOG.debug("Total hits [%s] is a dict. Therefore, we only extract "
"the 'value' attribute as the total option.", total_hits)
total_hits = total_hits.get("value")
total = total_hits
chunk = resp['hits']['hits']
output = chunk[offset:offset+limit if paginate else len(chunk)]
offset = 0 if len(chunk) > offset else offset - len(chunk)
while (not paginate) or len(output) < limit:
resp = self.scroll({
'scroll_id': scroll_id,
'scroll': self._scroll_duration,
})
scroll_id, chunk = resp['_scroll_id'], resp['hits']['hits']
self._scroll_ids.add(scroll_id)
# Means we've scrolled until the end
if not chunk:
break
output += chunk[offset:offset+limit if paginate else len(chunk)]
offset = 0 if len(chunk) > offset else offset - len(chunk)
self.close_scrolls()
return total, output
def delete_by_query(self, begin=None, end=None, filters=None):
"""Does a POST request against ES's Delete By Query API.
The POST request will be done against
`/<index_name>/_delete_by_query`
:param filters: Optional filters for documents to delete
:type filters: list of dicts
:rtype: requests.models.Response
"""
url = '/'.join((self._url, self._index_name, '_delete_by_query'))
must = self._build_must(begin, end, None, filters)
data = (json.dumps({"query": {"bool": {"must": must}}})
if must else None)
return self._req(self._sess.post, url, data, None)
def total(self, begin, end, metric_types, filters, groupby,
custom_fields=None, offset=0, limit=1000, paginate=True):
if custom_fields:
LOG.warning("'custom_fields' are not implemented yet for "
"OpenSearch. Therefore, the custom fields [%s] "
"informed by the user will be ignored.", custom_fields)
if not paginate:
offset = 0
must = self._build_must(begin, end, metric_types, filters)
should = self._build_should(filters)
composite = self._build_composite(groupby) if groupby else None
if composite:
composite['size'] = self._chunk_size
query = self._build_query(must, should, composite)
if "aggs" not in query.keys():
query["aggs"] = {
"sum_price": {"sum": {"field": "price"}},
"sum_qty": {"sum": {"field": "qty"}},
}
query['size'] = 0
resp = self.search(query, scroll=False)
# Means we didn't group, so length is 1
if not composite:
return 1, [resp["aggregations"]]
after = resp["aggregations"]["sum_and_price"].get("after_key")
chunk = resp["aggregations"]["sum_and_price"]["buckets"]
total = len(chunk)
output = chunk[offset:offset+limit if paginate else len(chunk)]
offset = 0 if len(chunk) > offset else offset - len(chunk)
# FIXME(peschk_l): We have to iterate over ALL buckets in order to get
# the total length. If there is a way for composite aggregations to get
# the total amount of buckets, please fix this
while after:
composite_query = query["aggs"]["sum_and_price"]["composite"]
composite_query["size"] = self._chunk_size
composite_query["after"] = after
resp = self.search(query, scroll=False)
after = resp["aggregations"]["sum_and_price"].get("after_key")
chunk = resp["aggregations"]["sum_and_price"]["buckets"]
if not chunk:
break
output += chunk[offset:offset+limit if paginate else len(chunk)]
offset = 0 if len(chunk) > offset else offset - len(chunk)
total += len(chunk)
if paginate:
output = output[offset:offset+limit]
return total, output

32
cloudkitty/storage/v2/opensearch/exceptions.py Normal file
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@ -0,0 +1,32 @@
# Copyright 2019 Objectif Libre
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
#
class BaseOpenSearchException(Exception):
"""Base exception raised by the OpenSearch v2 storage driver"""
class InvalidStatusCode(BaseOpenSearchException):
def __init__(self, expected, actual, msg, query):
super(InvalidStatusCode, self).__init__(
"Expected {} status code, got {}: {}. Query was {}".format(
expected, actual, msg, query))
class IndexDoesNotExist(BaseOpenSearchException):
def __init__(self, index_name):
super(IndexDoesNotExist, self).__init__(
"OpenSearch index {} does not exist".format(index_name)
)

0
cloudkitty/tests/storage/v2/opensearch/__init__.py Normal file
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482
cloudkitty/tests/storage/v2/opensearch/test_client.py Normal file
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@ -0,0 +1,482 @@
# Copyright 2019 Objectif Libre
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
#
import collections
import datetime
import unittest
from unittest import mock
from dateutil import tz
from cloudkitty import dataframe
from cloudkitty.storage.v2.opensearch import client
from cloudkitty.storage.v2.opensearch import exceptions
class TestOpenSearchClient(unittest.TestCase):
def setUp(self):
super(TestOpenSearchClient, self).setUp()
self.client = client.OpenSearchClient(
'http://opensearch:9200',
'index_name',
'test_mapping',
autocommit=False)
def test_build_must_no_params(self):
self.assertEqual(self.client._build_must(None, None, None, None), [])
def test_build_must_with_start_end(self):
start = datetime.datetime(2019, 8, 30, tzinfo=tz.tzutc())
end = datetime.datetime(2019, 8, 31, tzinfo=tz.tzutc())
self.assertEqual(
self.client._build_must(start, end, None, None),
[{'range': {'start': {'gte': '2019-08-30T00:00:00+00:00'}}},
{'range': {'end': {'lte': '2019-08-31T00:00:00+00:00'}}}],
)
def test_build_must_with_filters(self):
filters = {'one': '1', 'two': '2', 'type': 'awesome'}
self.assertEqual(
self.client._build_must(None, None, None, filters),
[{'term': {'type': 'awesome'}}],
)
def test_build_must_with_metric_types(self):
types = ['awesome', 'amazing']
self.assertEqual(
self.client._build_must(None, None, types, None),
[{'terms': {'type': ['awesome', 'amazing']}}],
)
def test_build_should_no_filters(self):
self.assertEqual(
self.client._build_should(None),
[],
)
def test_build_should_with_filters(self):
filters = collections.OrderedDict([
('one', '1'), ('two', '2'), ('type', 'awesome')])
self.assertEqual(
self.client._build_should(filters),
[
{'term': {'groupby.one': '1'}},
{'term': {'metadata.one': '1'}},
{'term': {'groupby.two': '2'}},
{'term': {'metadata.two': '2'}},
],
)
def test_build_composite_no_groupby(self):
self.assertEqual(self.client._build_composite(None), [])
def test_build_composite(self):
self.assertEqual(
self.client._build_composite(['one', 'type', 'two']),
{'sources': [
{'one': {'terms': {'field': 'groupby.one'}}},
{'type': {'terms': {'field': 'type'}}},
{'two': {'terms': {'field': 'groupby.two'}}},
]},
)
def test_build_query_no_args(self):
self.assertEqual(self.client._build_query(None, None, None), {})
def test_build_query(self):
must = [{'range': {'start': {'gte': '2019-08-30T00:00:00+00:00'}}},
{'range': {'start': {'lt': '2019-08-31T00:00:00+00:00'}}}]
should = [
{'term': {'groupby.one': '1'}},
{'term': {'metadata.one': '1'}},
{'term': {'groupby.two': '2'}},
{'term': {'metadata.two': '2'}},
]
composite = {'sources': [
{'one': {'terms': {'field': 'groupby.one'}}},
{'type': {'terms': {'field': 'type'}}},
{'two': {'terms': {'field': 'groupby.two'}}},
]}
expected = {
'query': {
'bool': {
'must': must,
'should': should,
'minimum_should_match': 2,
},
},
'aggs': {
'sum_and_price': {
'composite': composite,
'aggregations': {
"sum_price": {"sum": {"field": "price"}},
"sum_qty": {"sum": {"field": "qty"}},
},
},
},
}
self.assertEqual(
self.client._build_query(must, should, composite), expected)
def test_log_query_no_hits(self):
url = '/endpoint'
body = {'1': 'one'}
response = {'took': 42}
expected = """Query on /endpoint with body "{'1': 'one'}" took 42ms"""
with mock.patch.object(client.LOG, 'debug') as debug_mock:
self.client._log_query(url, body, response)
debug_mock.assert_called_once_with(expected)
def test_log_query_with_hits(self):
url = '/endpoint'
body = {'1': 'one'}
response = {'took': 42, 'hits': {'total': 1337}}
expected = """Query on /endpoint with body "{'1': 'one'}" took 42ms"""
expected += " for 1337 hits"
with mock.patch.object(client.LOG, 'debug') as debug_mock:
self.client._log_query(url, body, response)
debug_mock.assert_called_once_with(expected)
def test_req_valid_status_code_no_deserialize(self):
resp_mock = mock.MagicMock()
resp_mock.status_code = 200
method_mock = mock.MagicMock()
method_mock.return_value = resp_mock
req_resp = self.client._req(
method_mock, None, None, None, deserialize=False)
method_mock.assert_called_once_with(None, data=None, params=None)
self.assertEqual(req_resp, resp_mock)
def test_req_valid_status_code_deserialize(self):
resp_mock = mock.MagicMock()
resp_mock.status_code = 200
resp_mock.json.return_value = 'output'
method_mock = mock.MagicMock()
method_mock.return_value = resp_mock
with mock.patch.object(self.client, '_log_query') as log_mock:
req_resp = self.client._req(
method_mock, None, None, None, deserialize=True)
method_mock.assert_called_once_with(None, data=None, params=None)
self.assertEqual(req_resp, 'output')
log_mock.assert_called_once_with(None, None, 'output')
def test_req_invalid_status_code(self):
resp_mock = mock.MagicMock()
resp_mock.status_code = 400
method_mock = mock.MagicMock()
method_mock.return_value = resp_mock
self.assertRaises(exceptions.InvalidStatusCode,
self.client._req,
method_mock, None, None, None)
def test_post_mapping(self):
mapping = {'a': 'b'}
with mock.patch.object(self.client, '_req') as rmock:
self.client.post_mapping(mapping)
rmock.assert_called_once_with(
self.client._sess.post,
'http://opensearch:9200/index_name/test_mapping',
'{"a": "b"}', {}, deserialize=False)
def test_get_index(self):
with mock.patch.object(self.client, '_req') as rmock:
self.client.get_index()
rmock.assert_called_once_with(
self.client._sess.get,
'http://opensearch:9200/index_name',
None, None, deserialize=False)
def test_search_without_scroll(self):
mapping = {'a': 'b'}
with mock.patch.object(self.client, '_req') as rmock:
self.client.search(mapping, scroll=False)
rmock.assert_called_once_with(
self.client._sess.get,
'http://opensearch:9200/index_name/_search',
'{"a": "b"}', None)
def test_search_with_scroll(self):
mapping = {'a': 'b'}
with mock.patch.object(self.client, '_req') as rmock:
self.client.search(mapping, scroll=True)
rmock.assert_called_once_with(
self.client._sess.get,
'http://opensearch:9200/index_name/_search',
'{"a": "b"}', {'scroll': '60s'})
def test_scroll(self):
body = {'a': 'b'}
with mock.patch.object(self.client, '_req') as rmock:
self.client.scroll(body)
rmock.assert_called_once_with(
self.client._sess.get,
'http://opensearch:9200/_search/scroll',
'{"a": "b"}', None)
def test_close_scroll(self):
body = {'a': 'b'}
with mock.patch.object(self.client, '_req') as rmock:
self.client.close_scroll(body)
rmock.assert_called_once_with(
self.client._sess.delete,
'http://opensearch:9200/_search/scroll',
'{"a": "b"}', None, deserialize=False)
def test_close_scrolls(self):
with mock.patch.object(self.client, 'close_scroll') as func_mock:
with mock.patch.object(self.client, '_scroll_ids',
new=['a', 'b', 'c']):
self.client.close_scrolls()
func_mock.assert_called_once_with(
{'scroll_id': ['a', 'b', 'c']})
self.assertSetEqual(set(), self.client._scroll_ids)
def test_bulk_with_instruction(self):
instruction = {'instruction': {}}
terms = ('one', 'two', 'three')
expected_data = ''.join([
'{"instruction": {}}\n'
'"one"\n'
'{"instruction": {}}\n'
'"two"\n'
'{"instruction": {}}\n'
'"three"\n',
])
with mock.patch.object(self.client, '_req') as rmock:
self.client.bulk_with_instruction(instruction, terms)
rmock.assert_called_once_with(
self.client._sess.post,
'http://opensearch:9200/index_name/_bulk',
expected_data, None, deserialize=False)
def test_bulk_index(self):
terms = ('one', 'two', 'three')
with mock.patch.object(self.client, 'bulk_with_instruction') as fmock:
self.client.bulk_index(terms)
fmock.assert_called_once_with({'index': {}}, terms)
def test_commit(self):
docs = ['one', 'two', 'three', 'four', 'five', 'six', 'seven']
size = 3
with mock.patch.object(self.client, 'bulk_index') as bulk_mock:
with mock.patch.object(self.client, '_docs', new=docs):
with mock.patch.object(self.client, '_chunk_size', new=size):
self.client.commit()
bulk_mock.assert_has_calls([
mock.call(['one', 'two', 'three']),
mock.call(['four', 'five', 'six']),
mock.call(['seven']),
])
def test_add_point_no_autocommit(self):
point = dataframe.DataPoint(
'unit', '0.42', '0.1337', {}, {})
start = datetime.datetime(2019, 1, 1)
end = datetime.datetime(2019, 1, 1, 1)
with mock.patch.object(self.client, 'commit') as func_mock:
with mock.patch.object(self.client, '_autocommit', new=False):
with mock.patch.object(self.client, '_chunk_size', new=3):
self.client._docs = []
for _ in range(5):
self.client.add_point(
point, 'awesome_type', start, end)
func_mock.assert_not_called()
self.assertEqual(self.client._docs, [{
'start': start,
'end': end,
'type': 'awesome_type',
'unit': point.unit,
'qty': point.qty,
'price': point.price,
'groupby': point.groupby,
'metadata': point.metadata,
} for _ in range(5)])
self.client._docs = []
def test_add_point_with_autocommit(self):
point = dataframe.DataPoint(
'unit', '0.42', '0.1337', {}, {})
start = datetime.datetime(2019, 1, 1)
end = datetime.datetime(2019, 1, 1, 1)
commit_calls = {'count': 0}
def commit():
# We can't re-assign nonlocal variables in python2
commit_calls['count'] += 1
self.client._docs = []
with mock.patch.object(self.client, 'commit', new=commit):
with mock.patch.object(self.client, '_autocommit', new=True):
with mock.patch.object(self.client, '_chunk_size', new=3):
self.client._docs = []
for i in range(5):
self.client.add_point(
point, 'awesome_type', start, end)
self.assertEqual(commit_calls['count'], 1)
self.assertEqual(self.client._docs, [{
'start': start,
'end': end,
'type': 'awesome_type',
'unit': point.unit,
'qty': point.qty,
'price': point.price,
'groupby': point.groupby,
'metadata': point.metadata,
} for _ in range(2)])
# cleanup
self.client._docs = []
def test_delete_by_query_with_must(self):
with mock.patch.object(self.client, '_req') as rmock:
with mock.patch.object(self.client, '_build_must') as func_mock:
func_mock.return_value = {'a': 'b'}
self.client.delete_by_query()
rmock.assert_called_once_with(
self.client._sess.post,
'http://opensearch:9200/index_name/_delete_by_query',
'{"query": {"bool": {"must": {"a": "b"}}}}', None)
def test_delete_by_query_no_must(self):
with mock.patch.object(self.client, '_req') as rmock:
with mock.patch.object(self.client, '_build_must') as func_mock:
func_mock.return_value = {}
self.client.delete_by_query()
rmock.assert_called_once_with(
self.client._sess.post,
'http://opensearch:9200/index_name/_delete_by_query',
None, None)
def test_retrieve_no_pagination(self):
search_resp = {
'_scroll_id': '000',
'hits': {'hits': ['one', 'two', 'three'], 'total': 12},
}
scroll_resps = [{
'_scroll_id': str(i + 1) * 3,
'hits': {'hits': ['one', 'two', 'three']},
} for i in range(3)]
scroll_resps.append({'_scroll_id': '444', 'hits': {'hits': []}})
self.client._scroll_ids = set()
with mock.patch.object(self.client, 'search') as search_mock:
with mock.patch.object(self.client, 'scroll') as scroll_mock:
with mock.patch.object(self.client, 'close_scrolls') as close:
search_mock.return_value = search_resp
scroll_mock.side_effect = scroll_resps
total, resp = self.client.retrieve(
None, None, None, None, paginate=False)
search_mock.assert_called_once()
scroll_mock.assert_has_calls([
mock.call({
'scroll_id': str(i) * 3,
'scroll': '60s',
}) for i in range(4)
])
self.assertEqual(total, 12)
self.assertEqual(resp, ['one', 'two', 'three'] * 4)
self.assertSetEqual(self.client._scroll_ids,
set(str(i) * 3 for i in range(5)))
close.assert_called_once()
self.client._scroll_ids = set()
def test_retrieve_with_pagination(self):
search_resp = {
'_scroll_id': '000',
'hits': {'hits': ['one', 'two', 'three'], 'total': 12},
}
scroll_resps = [{
'_scroll_id': str(i + 1) * 3,
'hits': {'hits': ['one', 'two', 'three']},
} for i in range(3)]
scroll_resps.append({'_scroll_id': '444', 'hits': {'hits': []}})
self.client._scroll_ids = set()
with mock.patch.object(self.client, 'search') as search_mock:
with mock.patch.object(self.client, 'scroll') as scroll_mock:
with mock.patch.object(self.client, 'close_scrolls') as close:
search_mock.return_value = search_resp
scroll_mock.side_effect = scroll_resps
total, resp = self.client.retrieve(
None, None, None, None,
offset=2, limit=4, paginate=True)
search_mock.assert_called_once()
scroll_mock.assert_called_once_with({
'scroll_id': '000',
'scroll': '60s',
})
self.assertEqual(total, 12)
self.assertEqual(resp, ['three', 'one', 'two', 'three'])
self.assertSetEqual(self.client._scroll_ids,
set(str(i) * 3 for i in range(2)))
close.assert_called_once()
self.client._scroll_ids = set()
def _do_test_total(self, groupby, paginate):
with mock.patch.object(self.client, 'search') as search_mock:
if groupby:
search_resps = [{
'aggregations': {
'sum_and_price': {
'buckets': ['one', 'two', 'three'],
'after_key': str(i),
}
}
} for i in range(3)]
last_resp_aggs = search_resps[2]['aggregations']
last_resp_aggs['sum_and_price'].pop('after_key')
last_resp_aggs['sum_and_price']['buckets'] = []
search_mock.side_effect = search_resps
else:
search_mock.return_value = {
'aggregations': ['one', 'two', 'three'],
}
resp = self.client.total(None, None, None, None, groupby,
offset=2, limit=4, paginate=paginate)
if not groupby:
search_mock.assert_called_once()
return resp
def test_total_no_groupby_no_pagination(self):
total, aggs = self._do_test_total(None, False)
self.assertEqual(total, 1)
self.assertEqual(aggs, [['one', 'two', 'three']])
def test_total_no_groupby_with_pagination(self):
total, aggs = self._do_test_total(None, True)
self.assertEqual(total, 1)
self.assertEqual(aggs, [['one', 'two', 'three']])
def test_total_with_groupby_no_pagination(self):
total, aggs = self._do_test_total(['x'], False)
self.assertEqual(total, 6)
self.assertEqual(aggs, ['one', 'two', 'three'] * 2)
def test_total_with_groupby_with_pagination(self):
total, aggs = self._do_test_total(['x'], True)
self.assertEqual(total, 6)
self.assertEqual(aggs, ['three', 'one', 'two', 'three'])

97
cloudkitty/tests/storage/v2/opensearch_utils.py Normal file
View File

@ -0,0 +1,97 @@
# Copyright 2019 Objectif Libre
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
#
import copy
import functools
import itertools
import requests
from cloudkitty.storage.v2.opensearch import client
class FakeOpenSearchClient(client.OpenSearchClient):
def __init__(self, *args, **kwargs):
kwargs["autocommit"] = False
super(FakeOpenSearchClient, self).__init__(*args, **kwargs)
for method in ('get_index', 'post_mapping'):
setattr(self, method, self.__base_response)
@staticmethod
def __base_response(*args, **kwargs):
r = requests.Response()
r.status_code = 200
return r
def commit(self):
pass
@staticmethod
def __filter_func(begin, end, filters, mtypes, doc):
type_filter = lambda doc: ( # noqa: E731
doc['type'] in mtypes if mtypes else True)
time_filter = lambda doc: ( # noqa: E731
(doc['start'] >= begin if begin else True)
and (doc['start'] < end if end else True))
def filter_(doc):
return all((doc['groupby'].get(k) == v
or (doc['metadata'].get(k) == v)
for k, v in filters.items())) if filters else True
return type_filter(doc) and time_filter(doc) and filter_(doc)
def retrieve(self, begin, end, filters, metric_types,
offset=0, limit=1000, paginate=True):
filter_func = functools.partial(
self.__filter_func, begin, end, filters, metric_types)
output = list(filter(filter_func, self._docs))[offset:offset+limit]
for doc in output:
doc["start"] = doc["start"].isoformat()
doc["end"] = doc["end"].isoformat()
doc["_source"] = copy.deepcopy(doc)
return len(output), output
def total(self, begin, end, metric_types, filters, groupby,
custom_fields=None, offset=0, limit=1000, paginate=True):
filter_func = functools.partial(
self.__filter_func, begin, end, filters, metric_types)
docs = list(filter(filter_func, self._docs))
if not groupby:
return 1, [{
'sum_qty': {'value': sum(doc['qty'] for doc in docs)},
'sum_price': {'value': sum(doc['price'] for doc in docs)},
'begin': begin,
'end': end,
}]
output = []
key_func = lambda d: tuple( # noqa: E731
d['type'] if g == 'type' else d['groupby'][g] for g in groupby)
docs.sort(key=key_func)
for groups, values in itertools.groupby(docs, key_func):
val_list = list(values)
output.append({
'begin': begin,
'end': end,
'sum_qty': {'value': sum(doc['qty'] for doc in val_list)},
'sum_price': {'value': sum(doc['price'] for doc in val_list)},
'key': dict(zip(groupby, groups)),
})
return len(output), output[offset:offset+limit]
def _req(self, method, url, data, params, deserialize=True):
pass

12
cloudkitty/tests/storage/v2/test_storage_unit.py
View File

@ -21,6 +21,7 @@ from cloudkitty import storage
from cloudkitty.tests import samples
from cloudkitty.tests.storage.v2 import es_utils
from cloudkitty.tests.storage.v2 import influx_utils
from cloudkitty.tests.storage.v2 import opensearch_utils
from cloudkitty.tests import TestCase
from cloudkitty.tests import utils as test_utils
from cloudkitty.utils import tz as tzutils
@ -32,11 +33,16 @@ _ES_CLIENT_PATH = ('cloudkitty.storage.v2.elasticsearch'
_INFLUX_CLIENT_PATH = 'cloudkitty.storage.v2.influx.InfluxClient'
_OS_CLIENT_PATH = ('cloudkitty.storage.v2.opensearch'
'.client.OpenSearchClient')
class StorageUnitTest(TestCase):
storage_scenarios = [
('influx', dict(storage_backend='influxdb')),
('elastic', dict(storage_backend='elasticsearch'))]
('influxdb', dict(storage_backend='influxdb')),
('elasticsearch', dict(storage_backend='elasticsearch')),
('opensearch', dict(storage_backend='opensearch'))]
@classmethod
def generate_scenarios(cls):
@ -48,6 +54,8 @@ class StorageUnitTest(TestCase):
new=es_utils.FakeElasticsearchClient)
@mock.patch(_INFLUX_CLIENT_PATH,
new=influx_utils.FakeInfluxClient)
@mock.patch(_OS_CLIENT_PATH,
new=opensearch_utils.FakeOpenSearchClient)
@mock.patch('cloudkitty.utils.load_conf', new=test_utils.load_conf)
def setUp(self):
super(StorageUnitTest, self).setUp()

74
devstack/plugin.sh
View File

@ -178,6 +178,11 @@ function configure_cloudkitty {
iniset $CLOUDKITTY_CONF storage_${CLOUDKITTY_STORAGE_BACKEND} index_name ${CLOUDKITTY_ELASTICSEARCH_INDEX}
fi
if [ "$CLOUDKITTY_STORAGE_BACKEND" == "opensearch" ]; then
iniset $CLOUDKITTY_CONF storage_${CLOUDKITTY_STORAGE_BACKEND} host ${CLOUDKITTY_OPENSEARCH_HOST}
iniset $CLOUDKITTY_CONF storage_${CLOUDKITTY_STORAGE_BACKEND} index_name ${CLOUDKITTY_OPENSEARCH_INDEX}
fi
# collect
iniset $CLOUDKITTY_CONF collect collector $CLOUDKITTY_COLLECTOR
iniset $CLOUDKITTY_CONF "collector_${CLOUDKITTY_COLLECTOR}" auth_section authinfos
@ -248,6 +253,12 @@ function create_elasticsearch_index {
fi
}
function create_opensearch_index {
if [ "$CLOUDKITTY_STORAGE_BACKEND" == "opensearch" ]; then
curl -XPUT "${CLOUDKITTY_OPENSEARCH_HOST}/${CLOUDKITTY_OPENSEARCH_INDEX}"
fi
}
# init_cloudkitty() - Initialize CloudKitty database
function init_cloudkitty {
# Delete existing cache
@ -265,6 +276,7 @@ function init_cloudkitty {
create_influxdb_database
create_elasticsearch_index
create_opensearch_index
# Migrate cloudkitty database
$CLOUDKITTY_BIN_DIR/cloudkitty-dbsync upgrade
@ -301,20 +313,54 @@ function install_influx {
sudo systemctl start influxdb || sudo systemctl restart influxdb
}
function install_elasticsearch_ubuntu {
local opensearch_file=$(get_extra_file https://artifacts.opensearch.org/releases/bundle/opensearch/1.3.9/opensearch-1.3.9-linux-x64.deb)
sudo dpkg -i --skip-same-version ${opensearch_file}
}
function install_elasticsearch_fedora {
local opensearch_file=$(get_extra_file https://artifacts.opensearch.org/releases/bundle/opensearch/1.3.9/opensearch-1.3.9-linux-x64.rpm)
sudo yum localinstall -y ${opensearch_file}
}
function install_elasticsearch {
if is_ubuntu; then
install_elasticsearch_ubuntu
elif is_fedora; then
install_elasticsearch_fedora
else
die $LINENO "Distribution must be Debian or Fedora-based"
fi
if ! sudo grep plugins.security.disabled /etc/opensearch/opensearch.yml >/dev/null; then
echo "plugins.security.disabled: true" | sudo tee -a /etc/opensearch/opensearch.yml >/dev/null
fi
sudo systemctl enable opensearch
sudo systemctl start opensearch || sudo systemctl restart opensearch
}
function install_opensearch_ubuntu {
local opensearch_file=$(get_extra_file https://artifacts.opensearch.org/releases/bundle/opensearch/2.11.0/opensearch-2.11.0-linux-x64.deb)
sudo dpkg -i --skip-same-version ${opensearch_file}
}
function install_opensearch_fedora {
local opensearch_file=$(get_extra_file https://artifacts.opensearch.org/releases/bundle/opensearch/2.11.0/opensearch-2.11.0-linux-x64.rpm)
sudo yum localinstall -y ${opensearch_file}
}
function install_opensearch {
OPENSEARCH_HOME=/usr/share/opensearch
local opensearch_file=$(get_extra_file "https://artifacts.opensearch.org/releases/bundle/opensearch/1.3.6/opensearch-1.3.6-linux-x64.tar.gz")
sudo mkdir -p $OPENSEARCH_HOME
sudo tar -xzpf ${opensearch_file} -C $OPENSEARCH_HOME --strip-components=1
sudo mkdir -p $OPENSEARCH_HOME/data /var/log/opensearch
sudo chown -R $STACK_USER $OPENSEARCH_HOME /var/log/opensearch
cat - <<EOF | sudo tee $OPENSEARCH_HOME/config/opensearch.yml >/dev/null
discovery.type: single-node
path.data: /usr/share/opensearch/data
path.logs: /var/log/opensearch
plugins.security.disabled: true
EOF
_run_under_systemd opensearch "$OPENSEARCH_HOME/bin/opensearch"
if is_ubuntu; then
install_opensearch_ubuntu
elif is_fedora; then
install_opensearch_fedora
else
die $LINENO "Distribution must be Debian or Fedora-based"
fi
if ! sudo grep plugins.security.disabled /etc/opensearch/opensearch.yml >/dev/null; then
echo "plugins.security.disabled: true" | sudo tee -a /etc/opensearch/opensearch.yml >/dev/null
fi
sudo systemctl enable opensearch
sudo systemctl start opensearch || sudo systemctl restart opensearch
}
# install_cloudkitty() - Collect source and prepare
@ -325,6 +371,8 @@ function install_cloudkitty {
if [ $CLOUDKITTY_STORAGE_BACKEND == 'influxdb' ]; then
install_influx
elif [ $CLOUDKITTY_STORAGE_BACKEND == 'elasticsearch' ]; then
install_elasticsearch
elif [ $CLOUDKITTY_STORAGE_BACKEND == 'opensearch' ]; then
install_opensearch
fi
}

4
devstack/settings
View File

@ -76,3 +76,7 @@ CLOUDKITTY_INFLUXDB_DATABASE=${CLOUDKITTY_INFLUXDB_DATABASE:-"cloudkitty"}
# Set elasticsearch info
CLOUDKITTY_ELASTICSEARCH_HOST=${CLOUDKITTY_ELASTICSEARCH_HOST:-"http://localhost:9200"}
CLOUDKITTY_ELASTICSEARCH_INDEX=${CLOUDKITTY_ELASTICSEARCH_INDEX:-"cloudkitty"}
# Set opensearch info
CLOUDKITTY_OPENSEARCH_HOST=${CLOUDKITTY_OPENSEARCH_HOST:-"http://localhost:9200"}
CLOUDKITTY_OPENSEARCH_INDEX=${CLOUDKITTY_OPENSEARCH_INDEX:-"cloudkitty"}

25
doc/source/admin/configuration/storage.rst
View File

@ -27,6 +27,7 @@ the configuration file. The following options are available:
- ``influxdb``
- ``elasticsearch``
- ``opensearch``
Driver-specific options
=======================
@ -75,7 +76,7 @@ Section: ``storage_influxdb``.
regular exports of your data and create a custom retention policy on
cloudkitty's database.
ElasticSearch (v2)
Elasticsearch (v2)
------------------
Section ``storage_elasticsearch``:
@ -90,5 +91,23 @@ Section ``storage_elasticsearch``:
* ``cafile``: Path of the CA certificate to trust for HTTPS connections.
* ``scroll_duration``: Defaults to 30. Duration (in seconds) for which the ES
scroll contexts should be kept alive.
* ``scroll_duration``: Defaults to 30. Duration (in seconds) for which the
Elasticsearch scroll contexts should be kept alive.
OpenSearch 2.x (v2)
-------------------
Section ``storage_opensearch``:
* ``host``: Defaults to ``http://localhost:9200``. OpenSearch 2.x host, along
with port and protocol.
* ``index_name``: Defaults to ``cloudkitty``. OpenSearch index to use.
* ``insecure``: Defaults to ``false``. Set to true to allow insecure HTTPS
connections to OpenSearch.
* ``cafile``: Path of the CA certificate to trust for HTTPS connections.
* ``scroll_duration``: Defaults to 30. Duration (in seconds) for which the
OpenSearch scroll contexts should be kept alive.

7
releasenotes/notes/add-opensearch-as-v2-storage-backend-ff4080d6d32d8a2a.yaml Normal file
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@ -0,0 +1,7 @@
---
features:
- |
OpenSearch has been added as an alternative v2 storage backend. It is a
duplicate of the ElasticSearch backend, with the naming changed where
appropriate. This change is in support of the deprecation of ElasticSearch
as a backend.

1
setup.cfg
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@ -71,6 +71,7 @@ cloudkitty.storage.v1.backends =
cloudkitty.storage.v2.backends =
influxdb = cloudkitty.storage.v2.influx:InfluxStorage
elasticsearch = cloudkitty.storage.v2.elasticsearch:ElasticsearchStorage
opensearch = cloudkitty.storage.v2.opensearch:OpenSearchStorage
cloudkitty.storage.hybrid.backends =
gnocchi = cloudkitty.storage.v1.hybrid.backends.gnocchi:GnocchiStorage