def scale_up_milvus(release_name):
cus_configs = {'spec.components.queryNode.replicas': 2}
milvus_op = MilvusOperator()
log.info(f"scale up milvus with configs: {cus_configs}")
milvus_op.upgrade(release_name, cus_configs, namespace=namespace)
healthy = milvus_op.wait_for_healthy(release_name, namespace, timeout=1200)
log.info(f"milvus healthy: {healthy}")
if healthy:
endpoint = milvus_op.endpoint(release_name, namespace).split(':')
log.info(f"milvus endpoint: {endpoint}")
host = endpoint[0]
port = endpoint[1]
return release_name, host, port
else:
return release_name, None, None
def test_scale_proxy(self):
"""
target: test milvus operation after proxy expand
method: 1.deploy 1 proxy replicas
2.milvus e2e test in parallel
3.expand proxy pod from 1 to 5
4.milvus e2e test
5.shrink proxy from 5 to 2
expected: 1.verify data consistent and func work
"""
# deploy milvus cluster with one proxy
release_name = "scale-proxy"
image = f'{constants.IMAGE_REPOSITORY}:{constants.IMAGE_TAG}'
data_config = {
'metadata.namespace': constants.NAMESPACE,
'metadata.name': release_name,
'spec.components.image': image,
'spec.components.proxy.serviceType': 'LoadBalancer',
'spec.components.proxy.replicas': 1,
'spec.components.dataNode.replicas': 2,
'spec.config.dataCoord.enableCompaction': True,
'spec.config.dataCoord.enableGarbageCollection': True
}
mic = MilvusOperator()
mic.install(data_config)
healthy = mic.wait_for_healthy(release_name, constants.NAMESPACE, timeout=1200)
log.info(f"milvus healthy: {healthy}")
host = mic.endpoint(release_name, constants.NAMESPACE).split(':')[0]
# host = "10.98.0.7"
c_name = cf.gen_unique_str(prefix)
self.e2e_milvus_parallel(5, host, c_name)
log.info('Milvus test before expand')
# expand proxy replicas from 1 to 5
mic.upgrade(release_name, {'spec.components.proxy.replicas': 5}, constants.NAMESPACE)
wait_pods_ready(constants.NAMESPACE, f"app.kubernetes.io/instance={release_name}")
self.e2e_milvus_parallel(5, host, c_name)
log.info('Milvus test after expand')
# expand proxy replicas from 5 to 2
mic.upgrade(release_name, {'spec.components.proxy.replicas': 2}, constants.NAMESPACE)
wait_pods_ready(constants.NAMESPACE, f"app.kubernetes.io/instance={release_name}")
self.e2e_milvus_parallel(2, host, c_name)
log.info('Milvus test after shrink')
def install_milvus(release_name):
cus_configs = {
'spec.components.image': 'milvusdb/milvus-dev:master-20211206-b20a238',
'metadata.namespace': namespace,
'metadata.name': release_name,
'spec.components.proxy.serviceType': 'LoadBalancer'
}
milvus_op = MilvusOperator()
log.info(f"install milvus with configs: {cus_configs}")
milvus_op.install(cus_configs)
healthy = milvus_op.wait_for_healthy(release_name, namespace, timeout=1200)
log.info(f"milvus healthy: {healthy}")
if healthy:
endpoint = milvus_op.endpoint(release_name, namespace).split(':')
log.info(f"milvus endpoint: {endpoint}")
host = endpoint[0]
port = endpoint[1]
return release_name, host, port
else:
return release_name, None, None
def deploy_default_milvus(release_name, image_tag=None):
if image_tag is None:
image = f'{constants.IMAGE_REPO}:{constants.IMAGE_TAG}'
else:
image = f'{constants.IMAGE_REPO}:{image_tag}'
default_config = {
'metadata.namespace': constants.NAMESPACE,
'metadata.name': release_name,
'spec.components.image': image,
'spec.components.proxy.serviceType': 'LoadBalancer'
}
milvusOp = MilvusOperator()
milvusOp.install(default_config)
if milvusOp.wait_for_healthy(release_name, namespace=constants.NAMESPACE):
endpoint = milvusOp.endpoint(release_name, constants.NAMESPACE)
endpoint = endpoint.split(':')
host = endpoint[0]
port = int(endpoint[-1])
return milvusOp, host, port
else:
raise Exception(f"Failed to install {release_name}")
def test_scale_data_node(self):
"""
target: test scale dataNode
method: 1.deploy milvus cluster with 2 dataNode
2.create collection with shards_num=5
3.continuously insert new data (daemon thread)
4.expand dataNode from 2 to 5
5.create new collection with shards_num=2
6.continuously insert new collection new data (daemon thread)
7.shrink dataNode from 5 to 3
expected: Verify milvus remains healthy, Insert and flush successfully during scale
Average dataNode memory usage
"""
release_name = "scale-data"
image_tag = get_latest_tag()
image = f'{constants.IMAGE_REPOSITORY}:{image_tag}'
fail_count = 0
data_config = {
'metadata.namespace': constants.NAMESPACE,
'metadata.name': release_name,
'spec.components.image': image,
'spec.components.proxy.serviceType': 'LoadBalancer',
'spec.components.dataNode.replicas': 2,
'spec.config.dataCoord.enableCompaction': True,
'spec.config.dataCoord.enableGarbageCollection': True
}
mic = MilvusOperator()
mic.install(data_config)
if mic.wait_for_healthy(release_name,
constants.NAMESPACE,
timeout=1200):
host = mic.endpoint(release_name,
constants.NAMESPACE).split(':')[0]
else:
# log.warning(f'Deploy {release_name} timeout and ready to uninstall')
# mic.uninstall(release_name, namespace=constants.NAMESPACE)
raise BaseException(f'Milvus healthy timeout 1200s')
try:
# connect
connections.add_connection(default={"host": host, "port": 19530})
connections.connect(alias='default')
# create
c_name = cf.gen_unique_str("scale_query")
# c_name = 'scale_query_DymS7kI4'
collection_w = ApiCollectionWrapper()
collection_w.init_collection(
name=c_name,
schema=cf.gen_default_collection_schema(),
shards_num=5)
tmp_nb = 10000
def do_insert():
while True:
tmp_df = cf.gen_default_dataframe_data(tmp_nb)
collection_w.insert(tmp_df)
log.debug(collection_w.num_entities)
t_insert = threading.Thread(target=do_insert, args=(), daemon=True)
t_insert.start()
# scale dataNode to 5
mic.upgrade(release_name, {'spec.components.dataNode.replicas': 5},
constants.NAMESPACE)
mic.wait_for_healthy(release_name, constants.NAMESPACE)
wait_pods_ready(constants.NAMESPACE,
f"app.kubernetes.io/instance={release_name}")
log.debug("Expand dataNode test finished")
# create new collection and insert
new_c_name = cf.gen_unique_str("scale_query")
collection_w_new = ApiCollectionWrapper()
collection_w_new.init_collection(
name=new_c_name,
schema=cf.gen_default_collection_schema(),
shards_num=2)
def do_new_insert():
while True:
tmp_df = cf.gen_default_dataframe_data(tmp_nb)
collection_w_new.insert(tmp_df)
log.debug(collection_w_new.num_entities)
t_insert_new = threading.Thread(target=do_new_insert,
args=(),
daemon=True)
t_insert_new.start()
# scale dataNode to 3
mic.upgrade(release_name, {'spec.components.dataNode.replicas': 3},
constants.NAMESPACE)
mic.wait_for_healthy(release_name, constants.NAMESPACE)
wait_pods_ready(constants.NAMESPACE,
f"app.kubernetes.io/instance={release_name}")
log.debug(collection_w.num_entities)
time.sleep(300)
log.debug("Shrink dataNode test finished")
except Exception as e:
log.error(str(e))
fail_count += 1
# raise Exception(str(e))
finally:
log.info(f'Test finished with {fail_count} fail request')
assert fail_count <= 1
label = f"app.kubernetes.io/instance={release_name}"
log.info('Start to export milvus pod logs')
read_pod_log(namespace=constants.NAMESPACE,
label_selector=label,
release_name=release_name)
mic.uninstall(release_name, namespace=constants.NAMESPACE)
def test_shrink_index_node(self):
"""
target: test shrink indexNode from 2 to 1
method: 1.deploy two indexNode
2.create index with two indexNode
3.shrink indexNode from 2 to 1
4.create index with 1 indexNode
expected: The cost of one indexNode is about twice that of two indexNodes
"""
release_name = "shrink-index"
image_tag = get_latest_tag()
image = f'{constants.IMAGE_REPOSITORY}:{image_tag}'
data_config = {
'metadata.namespace': constants.NAMESPACE,
'metadata.name': release_name,
'spec.components.image': image,
'spec.components.proxy.serviceType': 'LoadBalancer',
'spec.components.indexNode.replicas': 2,
'spec.components.dataNode.replicas': 2,
'spec.config.dataCoord.enableCompaction': True,
'spec.config.dataCoord.enableGarbageCollection': True
}
mic = MilvusOperator()
mic.install(data_config)
if mic.wait_for_healthy(release_name,
constants.NAMESPACE,
timeout=1800):
host = mic.endpoint(release_name,
constants.NAMESPACE).split(':')[0]
else:
raise MilvusException(message=f'Milvus healthy timeout 1800s')
try:
# connect
connections.add_connection(default={"host": host, "port": 19530})
connections.connect(alias='default')
data = cf.gen_default_dataframe_data(nb)
# create
c_name = "index_scale_one"
collection_w = ApiCollectionWrapper()
# collection_w.init_collection(name=c_name)
collection_w.init_collection(
name=c_name, schema=cf.gen_default_collection_schema())
# insert
loop = 10
for i in range(loop):
collection_w.insert(data)
assert collection_w.num_entities == nb * loop
# create index on collection one and two
start = datetime.datetime.now()
collection_w.create_index(ct.default_float_vec_field_name,
default_index_params)
assert collection_w.has_index()[0]
t0 = datetime.datetime.now() - start
log.info(f'Create index on 2 indexNode cost t0: {t0}')
collection_w.drop_index()
assert not collection_w.has_index()[0]
# shrink indexNode from 2 to 1
mic.upgrade(release_name,
{'spec.components.indexNode.replicas': 1},
constants.NAMESPACE)
mic.wait_for_healthy(release_name, constants.NAMESPACE)
wait_pods_ready(constants.NAMESPACE,
f"app.kubernetes.io/instance={release_name}")
start = datetime.datetime.now()
collection_w.create_index(ct.default_float_vec_field_name,
default_index_params)
assert collection_w.has_index()[0]
t1 = datetime.datetime.now() - start
log.info(f'Create index on 1 indexNode cost t1: {t1}')
collection_w.drop_index()
start = datetime.datetime.now()
collection_w.create_index(ct.default_float_vec_field_name,
default_index_params)
assert collection_w.has_index()[0]
t2 = datetime.datetime.now() - start
log.info(f'Create index on 1 indexNode cost t2: {t2}')
log.debug(f'one indexNode: {t2}')
log.debug(f't2 is {t2}, t0 is {t0}, t2/t0 is {t2 / t0}')
# assert round(t2 / t0) == 2
except Exception as e:
raise Exception(str(e))
finally:
label = f"app.kubernetes.io/instance={release_name}"
log.info('Start to export milvus pod logs')
read_pod_log(namespace=constants.NAMESPACE,
label_selector=label,
release_name=release_name)
mic.uninstall(release_name, namespace=constants.NAMESPACE)
def test_scale_query_node(self):
"""
target: test scale queryNode
method: 1.deploy milvus cluster with 1 queryNode
2.prepare work (connect, create, insert, index and load)
3.continuously search (daemon thread)
4.expand queryNode from 2 to 5
5.continuously insert new data (daemon thread)
6.shrink queryNode from 5 to 3
expected: Verify milvus remains healthy and search successfully during scale
"""
release_name = "scale-query"
query_config = {
'metadata.namespace': constants.NAMESPACE,
'metadata.name': release_name,
'spec.components.image': 'harbor.zilliz.cc/milvus/milvus:master-20211202-ed546d0',
'spec.components.proxy.serviceType': 'LoadBalancer',
'spec.components.queryNode.replicas': 1,
'spec.config.dataCoord.enableCompaction': True,
'spec.config.dataCoord.enableGarbageCollection': True
}
mic = MilvusOperator()
mic.install(query_config)
healthy = mic.wait_for_healthy(release_name, constants.NAMESPACE, timeout=1200)
log.info(f"milvus healthy: {healthy}")
host = mic.endpoint(release_name, constants.NAMESPACE).split(':')[0]
# host = "10.98.0.8"
# connect
connections.add_connection(default={"host": host, "port": 19530})
connections.connect(alias='default')
# create
c_name = cf.gen_unique_str("scale_query")
# c_name = 'scale_query_DymS7kI4'
collection_w = ApiCollectionWrapper()
collection_w.init_collection(name=c_name, schema=cf.gen_default_collection_schema(), shards_num=2)
# insert two segments
for i in range(3):
df = cf.gen_default_dataframe_data(nb)
collection_w.insert(df)
log.debug(collection_w.num_entities)
# create index
collection_w.create_index(ct.default_float_vec_field_name, default_index_params)
assert collection_w.has_index()[0]
assert collection_w.index()[0] == Index(collection_w.collection, ct.default_float_vec_field_name,
default_index_params)
# load
collection_w.load()
# scale queryNode to 5
mic.upgrade(release_name, {'spec.components.queryNode.replicas': 5}, constants.NAMESPACE)
# continuously search
def do_search():
while True:
search_res, _ = collection_w.search(cf.gen_vectors(1, ct.default_dim),
ct.default_float_vec_field_name,
ct.default_search_params, ct.default_limit)
log.debug(search_res[0].ids)
assert len(search_res[0].ids) == ct.default_limit
t_search = threading.Thread(target=do_search, args=(), daemon=True)
t_search.start()
# wait new QN running, continuously insert
# time.sleep(10)
healthy = mic.wait_for_healthy(release_name, constants.NAMESPACE, timeout=1200)
log.info(f"milvus healthy after scale up: {healthy}")
# wait_pods_ready(constants.NAMESPACE, f"app.kubernetes.io/instance={release_name}")
def do_insert():
while True:
tmp_df = cf.gen_default_dataframe_data(1000)
collection_w.insert(tmp_df)
t_insert = threading.Thread(target=do_insert, args=(), daemon=True)
t_insert.start()
log.debug(collection_w.num_entities)
time.sleep(20)
log.debug("Expand querynode test finished")
mic.upgrade(release_name, {'spec.components.queryNode.replicas': 3}, constants.NAMESPACE)
time.sleep(60)
wait_pods_ready(constants.NAMESPACE, f"app.kubernetes.io/instance={release_name}")
log.debug(collection_w.num_entities)
time.sleep(60)
log.debug("Shrink querynode test finished")
def test_expand_index_node(self):
"""
target: test expand indexNode from 1 to 2
method: 1.deploy two indexNode
2.create index with two indexNode
3.expand indexNode from 1 to 2
4.create index with one indexNode
expected: The cost of one indexNode is about twice that of two indexNodes
"""
release_name = "scale-index"
image = f'{constants.IMAGE_REPOSITORY}:{constants.IMAGE_TAG}'
data_config = {
'metadata.namespace': constants.NAMESPACE,
'metadata.name': release_name,
'spec.components.image': image,
'spec.components.proxy.serviceType': 'LoadBalancer',
'spec.components.indexNode.replicas': 1,
'spec.components.dataNode.replicas': 2,
'spec.config.dataCoord.enableCompaction': True,
'spec.config.dataCoord.enableGarbageCollection': True
}
mic = MilvusOperator()
mic.install(data_config)
healthy = mic.wait_for_healthy(release_name,
constants.NAMESPACE,
timeout=1200)
log.info(f"milvus healthy: {healthy}")
host = mic.endpoint(release_name, constants.NAMESPACE).split(':')[0]
# host = '10.98.0.8'
# connect
connections.add_connection(default={"host": host, "port": 19530})
connections.connect(alias='default')
data = cf.gen_default_dataframe_data(nb)
# create
c_name = "index_scale_one"
collection_w = ApiCollectionWrapper()
# collection_w.init_collection(name=c_name)
collection_w.init_collection(name=c_name,
schema=cf.gen_default_collection_schema())
# insert
loop = 100
for i in range(loop):
collection_w.insert(data, timeout=60)
assert collection_w.num_entities == nb * loop
# create index on collection
# note that the num of segments and the num of indexNode are related to indexing time
collection_w.drop_index()
start = datetime.datetime.now()
collection_w.create_index(ct.default_float_vec_field_name,
default_index_params)
assert collection_w.has_index()[0]
t0 = datetime.datetime.now() - start
log.debug(f't0: {t0}')
collection_w.drop_index()
assert not collection_w.has_index()[0]
# expand indexNode from 1 to 2
mic.upgrade(release_name, {'spec.components.indexNode.replicas': 2},
constants.NAMESPACE)
time.sleep(60)
mic.wait_for_healthy(release_name, constants.NAMESPACE)
start = datetime.datetime.now()
collection_w.create_index(ct.default_float_vec_field_name,
default_index_params)
assert collection_w.has_index()[0]
t1 = datetime.datetime.now() - start
log.debug(f't1: {t1}')
assert round(t0 / t1) == 2
def test_scale_data_node(self):
"""
target: test scale dataNode
method: 1.deploy milvus cluster with 2 dataNode
2.create collection with shards_num=5
3.continuously insert new data (daemon thread)
4.expand dataNode from 2 to 5
5.create new collection with shards_num=2
6.continuously insert new collection new data (daemon thread)
7.shrink dataNode from 5 to 3
expected: Verify milvus remains healthy, Insert and flush successfully during scale
Average dataNode memory usage
"""
release_name = "scale-data"
image = f'{constants.IMAGE_REPOSITORY}:{constants.IMAGE_TAG}'
data_config = {
'metadata.namespace': constants.NAMESPACE,
'metadata.name': release_name,
'spec.components.image': image,
'spec.components.proxy.serviceType': 'LoadBalancer',
'spec.components.dataNode.replicas': 2,
'spec.config.dataCoord.enableCompaction': True,
'spec.config.dataCoord.enableGarbageCollection': True
}
mic = MilvusOperator()
mic.install(data_config)
healthy = mic.wait_for_healthy(release_name,
constants.NAMESPACE,
timeout=1200)
log.info(f"milvus healthy: {healthy}")
host = mic.endpoint(release_name, constants.NAMESPACE).split(':')[0]
# host = '10.98.0.4'
# connect
connections.add_connection(default={"host": host, "port": 19530})
connections.connect(alias='default')
# create
c_name = cf.gen_unique_str("scale_query")
# c_name = 'scale_query_DymS7kI4'
collection_w = ApiCollectionWrapper()
collection_w.init_collection(name=c_name,
schema=cf.gen_default_collection_schema(),
shards_num=5)
tmp_nb = 10000
def do_insert():
while True:
tmp_df = cf.gen_default_dataframe_data(tmp_nb)
collection_w.insert(tmp_df)
log.debug(collection_w.num_entities)
t_insert = threading.Thread(target=do_insert, args=(), daemon=True)
t_insert.start()
# scale dataNode to 5
mic.upgrade(release_name, {'spec.components.dataNode.replicas': 5},
constants.NAMESPACE)
time.sleep(300)
log.debug("Expand dataNode test finished")
# create new collection and insert
new_c_name = cf.gen_unique_str("scale_query")
collection_w_new = ApiCollectionWrapper()
collection_w_new.init_collection(
name=new_c_name,
schema=cf.gen_default_collection_schema(),
shards_num=2)
def do_new_insert():
while True:
tmp_df = cf.gen_default_dataframe_data(tmp_nb)
collection_w_new.insert(tmp_df)
log.debug(collection_w_new.num_entities)
t_insert_new = threading.Thread(target=do_new_insert,
args=(),
daemon=True)
t_insert_new.start()
# scale dataNode to 3
mic.upgrade(release_name, {'spec.components.dataNode.replicas': 3},
constants.NAMESPACE)
wait_pods_ready(constants.NAMESPACE,
f"app.kubernetes.io/instance={release_name}")
log.debug(collection_w.num_entities)
time.sleep(300)
log.debug("Shrink dataNode test finished")
def test_scale_query_node(self):
"""
target: test scale queryNode
method: 1.deploy milvus cluster with 1 queryNode
2.prepare work (connect, create, insert, index and load)
3.continuously search (daemon thread)
4.expand queryNode from 2 to 5
5.continuously insert new data (daemon thread)
6.shrink queryNode from 5 to 3
expected: Verify milvus remains healthy and search successfully during scale
"""
fail_count = 0
release_name = "scale-query"
image_tag = get_latest_tag()
image = f'{constants.IMAGE_REPOSITORY}:{image_tag}'
query_config = {
'metadata.namespace': constants.NAMESPACE,
'metadata.name': release_name,
'spec.components.image': image,
'spec.components.proxy.serviceType': 'LoadBalancer',
'spec.components.queryNode.replicas': 1,
'spec.config.dataCoord.enableCompaction': True,
'spec.config.dataCoord.enableGarbageCollection': True
}
mic = MilvusOperator()
mic.install(query_config)
if mic.wait_for_healthy(release_name, constants.NAMESPACE, timeout=1200):
host = mic.endpoint(release_name, constants.NAMESPACE).split(':')[0]
else:
# log.warning(f'Deploy {release_name} timeout and ready to uninstall')
# mic.uninstall(release_name, namespace=constants.NAMESPACE)
raise BaseException(f'Milvus healthy timeout 1200s')
try:
# connect
connections.add_connection(default={"host": host, "port": 19530})
connections.connect(alias='default')
# create
c_name = cf.gen_unique_str("scale_query")
# c_name = 'scale_query_DymS7kI4'
collection_w = ApiCollectionWrapper()
collection_w.init_collection(name=c_name, schema=cf.gen_default_collection_schema(), shards_num=2)
# insert two segments
for i in range(3):
df = cf.gen_default_dataframe_data(nb)
collection_w.insert(df)
log.debug(collection_w.num_entities)
# create index
collection_w.create_index(ct.default_float_vec_field_name, default_index_params)
assert collection_w.has_index()[0]
assert collection_w.index()[0] == Index(collection_w.collection, ct.default_float_vec_field_name,
default_index_params)
# load
collection_w.load()
# scale queryNode to 5
mic.upgrade(release_name, {'spec.components.queryNode.replicas': 5}, constants.NAMESPACE)
# continuously search
def do_search():
while True:
search_res, _ = collection_w.search(cf.gen_vectors(1, ct.default_dim),
ct.default_float_vec_field_name,
ct.default_search_params, ct.default_limit)
log.debug(search_res[0].ids)
assert len(search_res[0].ids) == ct.default_limit
t_search = threading.Thread(target=do_search, args=(), daemon=True)
t_search.start()
# wait new QN running, continuously insert
mic.wait_for_healthy(release_name, constants.NAMESPACE)
wait_pods_ready(constants.NAMESPACE, f"app.kubernetes.io/instance={release_name}")
def do_insert():
while True:
tmp_df = cf.gen_default_dataframe_data(1000)
collection_w.insert(tmp_df)
t_insert = threading.Thread(target=do_insert, args=(), daemon=True)
t_insert.start()
log.debug(collection_w.num_entities)
time.sleep(20)
log.debug("Expand querynode test finished")
mic.upgrade(release_name, {'spec.components.queryNode.replicas': 3}, constants.NAMESPACE)
mic.wait_for_healthy(release_name, constants.NAMESPACE)
wait_pods_ready(constants.NAMESPACE, f"app.kubernetes.io/instance={release_name}")
log.debug(collection_w.num_entities)
time.sleep(60)
log.debug("Shrink querynode test finished")
except Exception as e:
log.error(str(e))
fail_count += 1
# raise Exception(str(e))
finally:
log.info(f'Test finished with {fail_count} fail request')
assert fail_count <= 1
label = f"app.kubernetes.io/instance={release_name}"
log.info('Start to export milvus pod logs')
read_pod_log(namespace=constants.NAMESPACE, label_selector=label, release_name=release_name)
mic.uninstall(release_name, namespace=constants.NAMESPACE)
def test_scale_proxy(self):
"""
target: test milvus operation after proxy expand
method: 1.deploy 1 proxy replicas
2.milvus e2e test in parallel
3.expand proxy pod from 1 to 5
4.milvus e2e test
5.shrink proxy from 5 to 2
expected: 1.verify data consistent and func work
"""
# deploy milvus cluster with one proxy
fail_count = 0
release_name = "scale-proxy"
image_tag = get_latest_tag()
image = f'{constants.IMAGE_REPOSITORY}:{image_tag}'
data_config = {
'metadata.namespace': constants.NAMESPACE,
'metadata.name': release_name,
'spec.components.image': image,
'spec.components.proxy.serviceType': 'LoadBalancer',
'spec.components.proxy.replicas': 1,
'spec.components.dataNode.replicas': 2,
'spec.config.dataCoord.enableCompaction': True,
'spec.config.dataCoord.enableGarbageCollection': True
}
mic = MilvusOperator()
mic.install(data_config)
if mic.wait_for_healthy(release_name,
constants.NAMESPACE,
timeout=1200):
host = mic.endpoint(release_name,
constants.NAMESPACE).split(':')[0]
else:
# log.warning(f'Deploy {release_name} timeout and ready to uninstall')
# mic.uninstall(release_name, namespace=constants.NAMESPACE)
raise BaseException(f'Milvus healthy timeout 1200s')
try:
c_name = cf.gen_unique_str(prefix)
self.e2e_milvus_parallel(5, host, c_name)
log.info('Milvus test before expand')
# expand proxy replicas from 1 to 5
mic.upgrade(release_name, {'spec.components.proxy.replicas': 5},
constants.NAMESPACE)
mic.wait_for_healthy(release_name, constants.NAMESPACE)
wait_pods_ready(constants.NAMESPACE,
f"app.kubernetes.io/instance={release_name}")
self.e2e_milvus_parallel(5, host, c_name)
log.info('Milvus test after expand')
# expand proxy replicas from 5 to 2
mic.upgrade(release_name, {'spec.components.proxy.replicas': 2},
constants.NAMESPACE)
mic.wait_for_healthy(release_name, constants.NAMESPACE)
wait_pods_ready(constants.NAMESPACE,
f"app.kubernetes.io/instance={release_name}")
self.e2e_milvus_parallel(2, host, c_name)
log.info('Milvus test after shrink')
except Exception as e:
log.error(str(e))
fail_count += 1
# raise Exception(str(e))
finally:
log.info(f'Test finished with {fail_count} fail request')
assert fail_count <= 1
label = f"app.kubernetes.io/instance={release_name}"
log.info('Start to export milvus pod logs')
read_pod_log(namespace=constants.NAMESPACE,
label_selector=label,
release_name=release_name)
mic.uninstall(release_name, namespace=constants.NAMESPACE)
def test_scale_query_node(self):
"""
target: test scale queryNode
method: 1.deploy milvus cluster with 1 queryNode
2.prepare work (connect, create, insert, index and load)
3.continuously search (daemon thread)
4.expand queryNode from 2 to 5
5.continuously insert new data (daemon thread)
6.shrink queryNode from 5 to 3
expected: Verify milvus remains healthy and search successfully during scale
"""
release_name = "scale-query"
image_tag = get_latest_tag()
image = f'{constants.IMAGE_REPOSITORY}:{image_tag}'
query_config = {
'metadata.namespace': constants.NAMESPACE,
'spec.mode': 'cluster',
'metadata.name': release_name,
'spec.components.image': image,
'spec.components.proxy.serviceType': 'LoadBalancer',
'spec.components.queryNode.replicas': 1,
'spec.config.common.retentionDuration': 60
}
mic = MilvusOperator()
mic.install(query_config)
if mic.wait_for_healthy(release_name,
constants.NAMESPACE,
timeout=1800):
host = mic.endpoint(release_name,
constants.NAMESPACE).split(':')[0]
else:
raise MilvusException(message=f'Milvus healthy timeout 1800s')
try:
# connect
connections.add_connection(default={"host": host, "port": 19530})
connections.connect(alias='default')
# create
c_name = cf.gen_unique_str("scale_query")
# c_name = 'scale_query_DymS7kI4'
collection_w = ApiCollectionWrapper()
collection_w.init_collection(
name=c_name,
schema=cf.gen_default_collection_schema(),
shards_num=2)
# insert two segments
for i in range(3):
df = cf.gen_default_dataframe_data(nb)
collection_w.insert(df)
log.debug(collection_w.num_entities)
# create index
collection_w.create_index(ct.default_float_vec_field_name,
default_index_params)
assert collection_w.has_index()[0]
assert collection_w.index()[0] == Index(
collection_w.collection, ct.default_float_vec_field_name,
default_index_params)
# load
collection_w.load()
# scale queryNode to 5
mic.upgrade(release_name,
{'spec.components.queryNode.replicas': 5},
constants.NAMESPACE)
@counter
def do_search():
""" do search """
search_res, is_succ = collection_w.search(
cf.gen_vectors(1, ct.default_dim),
ct.default_float_vec_field_name,
ct.default_search_params,
ct.default_limit,
check_task=CheckTasks.check_nothing)
assert len(search_res) == 1
return search_res, is_succ
def loop_search():
""" continuously search """
while True:
do_search()
threading.Thread(target=loop_search, args=(), daemon=True).start()
# wait new QN running, continuously insert
mic.wait_for_healthy(release_name, constants.NAMESPACE)
wait_pods_ready(constants.NAMESPACE,
f"app.kubernetes.io/instance={release_name}")
@counter
def do_insert():
""" do insert """
return collection_w.insert(cf.gen_default_dataframe_data(1000),
check_task=CheckTasks.check_nothing)
def loop_insert():
""" loop insert """
while True:
do_insert()
threading.Thread(target=loop_insert, args=(), daemon=True).start()
log.debug(collection_w.num_entities)
time.sleep(20)
log.debug("Expand querynode test finished")
mic.upgrade(release_name,
{'spec.components.queryNode.replicas': 3},
constants.NAMESPACE)
mic.wait_for_healthy(release_name, constants.NAMESPACE)
wait_pods_ready(constants.NAMESPACE,
f"app.kubernetes.io/instance={release_name}")
log.debug(collection_w.num_entities)
time.sleep(60)
scale_common.check_succ_rate(do_search)
scale_common.check_succ_rate(do_insert)
log.debug("Shrink querynode test finished")
except Exception as e:
raise Exception(str(e))
finally:
label = f"app.kubernetes.io/instance={release_name}"
log.info('Start to export milvus pod logs')
read_pod_log(namespace=constants.NAMESPACE,
label_selector=label,
release_name=release_name)
mic.uninstall(release_name, namespace=constants.NAMESPACE)
def test_scale_in_query_node_less_than_replicas(self):
"""
target: test scale in cluster and querynode < replica
method: 1.Deploy cluster with 3 querynodes
2.Create and insert data, flush
3.Load collection with 2 replica number
4.Scale in querynode from 3 to 1 and query
5.Scale out querynode from 1 back to 3
expected: Verify search successfully after scale out
"""
release_name = "scale-in-query"
image_tag = get_latest_tag()
image = f'{constants.IMAGE_REPOSITORY}:{image_tag}'
query_config = {
'metadata.namespace': constants.NAMESPACE,
'metadata.name': release_name,
'spec.mode': 'cluster',
'spec.components.image': image,
'spec.components.proxy.serviceType': 'LoadBalancer',
'spec.components.queryNode.replicas': 2,
'spec.config.common.retentionDuration': 60
}
mic = MilvusOperator()
mic.install(query_config)
if mic.wait_for_healthy(release_name,
constants.NAMESPACE,
timeout=1800):
host = mic.endpoint(release_name,
constants.NAMESPACE).split(':')[0]
else:
raise MilvusException(message=f'Milvus healthy timeout 1800s')
try:
# prepare collection
connections.connect("scale-in", host=host, port=19530)
utility_w = ApiUtilityWrapper()
collection_w = ApiCollectionWrapper()
collection_w.init_collection(
name=cf.gen_unique_str("scale_in"),
schema=cf.gen_default_collection_schema(),
using="scale-in")
collection_w.insert(cf.gen_default_dataframe_data())
assert collection_w.num_entities == ct.default_nb
# load multi replicas and search success
collection_w.load(replica_number=2)
search_res, is_succ = collection_w.search(
cf.gen_vectors(1, ct.default_dim),
ct.default_float_vec_field_name, ct.default_search_params,
ct.default_limit)
assert len(search_res[0].ids) == ct.default_limit
log.info("Search successfully after load with 2 replicas")
log.debug(collection_w.get_replicas()[0])
log.debug(
utility_w.get_query_segment_info(collection_w.name,
using="scale-in"))
# scale in querynode from 2 to 1, less than replica number
log.debug("Scale in querynode from 2 to 1")
mic.upgrade(release_name,
{'spec.components.queryNode.replicas': 1},
constants.NAMESPACE)
mic.wait_for_healthy(release_name, constants.NAMESPACE)
wait_pods_ready(constants.NAMESPACE,
f"app.kubernetes.io/instance={release_name}")
# search and not assure success
collection_w.search(cf.gen_vectors(1, ct.default_dim),
ct.default_float_vec_field_name,
ct.default_search_params,
ct.default_limit,
check_task=CheckTasks.check_nothing)
log.debug(
collection_w.get_replicas(
check_task=CheckTasks.check_nothing)[0])
# scale querynode from 1 back to 2
mic.upgrade(release_name,
{'spec.components.queryNode.replicas': 2},
constants.NAMESPACE)
mic.wait_for_healthy(release_name, constants.NAMESPACE)
wait_pods_ready(constants.NAMESPACE,
f"app.kubernetes.io/instance={release_name}")
# verify search success
collection_w.search(cf.gen_vectors(1, ct.default_dim),
ct.default_float_vec_field_name,
ct.default_search_params, ct.default_limit)
# Verify replica info is correct
replicas = collection_w.get_replicas()[0]
assert len(replicas.groups) == 2
for group in replicas.groups:
assert len(group.group_nodes) == 1
# Verify loaded segment info is correct
seg_info = utility_w.get_query_segment_info(collection_w.name,
using="scale-in")[0]
num_entities = 0
for seg in seg_info:
assert len(seg.nodeIds) == 2
num_entities += seg.num_rows
assert num_entities == ct.default_nb
except Exception as e:
raise Exception(str(e))
finally:
label = f"app.kubernetes.io/instance={release_name}"
log.info('Start to export milvus pod logs')
read_pod_log(namespace=constants.NAMESPACE,
label_selector=label,
release_name=release_name)
mic.uninstall(release_name, namespace=constants.NAMESPACE)
def test_scale_query_node_replicas(self):
"""
target: test scale out querynode when load multi replicas
method: 1.Deploy cluster with 5 querynodes
2.Create collection with 2 shards
3.Insert 10 segments and flushed
4.Load collection with 2 replicas
5.Scale out querynode from 5 to 6 while search and insert growing data
expected: Verify search succ rate is 100%
"""
release_name = "scale-replica"
image_tag = get_latest_tag()
image = f'{constants.IMAGE_REPOSITORY}:{image_tag}'
query_config = {
'metadata.namespace': constants.NAMESPACE,
'metadata.name': release_name,
'spec.mode': 'cluster',
'spec.components.image': image,
'spec.components.proxy.serviceType': 'LoadBalancer',
'spec.components.queryNode.replicas': 5,
'spec.config.common.retentionDuration': 60
}
mic = MilvusOperator()
mic.install(query_config)
if mic.wait_for_healthy(release_name,
constants.NAMESPACE,
timeout=1800):
host = mic.endpoint(release_name,
constants.NAMESPACE).split(':')[0]
else:
raise MilvusException(message=f'Milvus healthy timeout 1800s')
try:
scale_querynode = random.choice([6, 7, 4, 3])
connections.connect("scale-replica", host=host, port=19530)
collection_w = ApiCollectionWrapper()
collection_w.init_collection(
name=cf.gen_unique_str("scale_out"),
schema=cf.gen_default_collection_schema(),
using='scale-replica',
shards_num=3)
# insert 10 sealed segments
for i in range(5):
df = cf.gen_default_dataframe_data(nb=nb, start=i * nb)
collection_w.insert(df)
assert collection_w.num_entities == (i + 1) * nb
collection_w.load(replica_number=2)
@counter
def do_search():
""" do search """
search_res, is_succ = collection_w.search(
cf.gen_vectors(1, ct.default_dim),
ct.default_float_vec_field_name,
ct.default_search_params,
ct.default_limit,
check_task=CheckTasks.check_nothing)
assert len(search_res) == 1
return search_res, is_succ
def loop_search():
""" continuously search """
while True:
do_search()
threading.Thread(target=loop_search, args=(), daemon=True).start()
# scale out
mic.upgrade(
release_name,
{'spec.components.queryNode.replicas': scale_querynode},
constants.NAMESPACE)
mic.wait_for_healthy(release_name, constants.NAMESPACE)
wait_pods_ready(constants.NAMESPACE,
f"app.kubernetes.io/instance={release_name}")
log.debug("Scale out querynode success")
time.sleep(100)
scale_common.check_succ_rate(do_search)
log.debug("Scale out test finished")
except Exception as e:
raise Exception(str(e))
finally:
label = f"app.kubernetes.io/instance={release_name}"
log.info('Start to export milvus pod logs')
read_pod_log(namespace=constants.NAMESPACE,
label_selector=label,
release_name=release_name)
mic.uninstall(release_name, namespace=constants.NAMESPACE)
def test_expand_data_node(self):
"""
target: test create and insert api after expand dataNode pod
method: 1.create collection a and insert df
2.expand dataNode pod from 1 to 2
3.verify collection a property and verify create and insert of new collection
expected: two collection create and insert op are both correctly
"""
# deploy all nodes one pod cluster milvus with helm
release_name = "scale-data"
# env = HelmEnv(release_name=release_name)
# host = env.helm_install_cluster_milvus()
# deploy cluster milvus with dataNode 1 replicas
default_config = {
'metadata.namespace': constants.NAMESPACE,
'metadata.name': release_name,
'spec.components.image':
'milvusdb/milvus-dev:master-20211020-b40513b',
'spec.components.proxy.serviceType': 'LoadBalancer',
'dependencies.etcd.inCluster.deletionPolicy': 'Delete',
'dependencies.etcd.inCluster.pvcDeletion': 'true',
'dependencies.pulsar.inCluster.deletionPolicy': 'Delete',
'dependencies.pulsar.inCluster.pvcDeletion': 'true',
'dependencies.storage.inCluster.deletionPolicy': 'Delete',
'dependencies.storage.inCluster.pvcDeletion': 'true',
}
milvusOp = MilvusOperator()
milvusOp.install(default_config)
if milvusOp.wait_for_healthy(release_name,
namespace=constants.NAMESPACE):
endpoint = milvusOp.endpoint(release_name, constants.NAMESPACE)
endpoint = endpoint.split(':')
host = endpoint[0]
port = int(endpoint[-1])
else:
raise Exception(f"Failed to install {release_name}")
# connect
connections.add_connection(default={"host": host, "port": port})
connections.connect(alias='default')
# create
c_name = cf.gen_unique_str(prefix)
collection_w = ApiCollectionWrapper()
collection_w.init_collection(name=c_name,
schema=cf.gen_default_collection_schema())
# # insert
data = cf.gen_default_list_data(ct.default_nb)
mutation_res, _ = collection_w.insert(data)
assert mutation_res.insert_count == ct.default_nb
# scale dataNode to 2 pods
milvusOp.upgrade(release_name,
{'spec.components.dataNode.replicas': 2},
constants.NAMESPACE)
# env.helm_upgrade_cluster_milvus(dataNode=2)
# after scale, assert data consistent
assert utility.has_collection(c_name)
assert collection_w.num_entities == ct.default_nb
# assert new operations
new_cname = cf.gen_unique_str(prefix)
new_collection_w = ApiCollectionWrapper()
new_collection_w.init_collection(
name=new_cname, schema=cf.gen_default_collection_schema())
new_mutation_res, _ = new_collection_w.insert(data)
assert new_mutation_res.insert_count == ct.default_nb
assert new_collection_w.num_entities == ct.default_nb
# assert old collection ddl
mutation_res_2, _ = collection_w.insert(data)
assert mutation_res.insert_count == ct.default_nb
assert collection_w.num_entities == ct.default_nb * 2
collection_w.drop()
new_collection_w.drop()
def test_scale_proxy(self):
"""
target: test milvus operation after proxy expand
method: 1.deploy 1 proxy replicas
2.milvus e2e test in parallel
3.expand proxy pod from 1 to 5
4.milvus e2e test
5.shrink proxy from 5 to 2
expected: 1.verify data consistent and func work
"""
# deploy milvus cluster with one proxy
fail_count = 0
release_name = "scale-proxy"
image_tag = get_latest_tag()
image = f'{constants.IMAGE_REPOSITORY}:{image_tag}'
data_config = {
'metadata.namespace': constants.NAMESPACE,
'metadata.name': release_name,
'spec.mode': 'cluster',
'spec.components.image': image,
'spec.components.proxy.serviceType': 'LoadBalancer',
'spec.components.proxy.replicas': 1,
'spec.components.dataNode.replicas': 2,
'spec.config.common.retentionDuration': 60
}
mic = MilvusOperator()
mic.install(data_config)
if mic.wait_for_healthy(release_name, constants.NAMESPACE, timeout=1800):
host = mic.endpoint(release_name, constants.NAMESPACE).split(':')[0]
else:
raise MilvusException(message=f'Milvus healthy timeout 1800s')
try:
c_name = cf.gen_unique_str("proxy_scale")
e2e_milvus_parallel(2, host, c_name)
log.info('Milvus test before expand')
# expand proxy replicas from 1 to 5
mic.upgrade(release_name, {'spec.components.proxy.replicas': 5}, constants.NAMESPACE)
mic.wait_for_healthy(release_name, constants.NAMESPACE)
wait_pods_ready(constants.NAMESPACE, f"app.kubernetes.io/instance={release_name}")
e2e_milvus_parallel(5, host, c_name)
log.info('Milvus test after expand')
# expand proxy replicas from 5 to 2
mic.upgrade(release_name, {'spec.components.proxy.replicas': 2}, constants.NAMESPACE)
mic.wait_for_healthy(release_name, constants.NAMESPACE)
wait_pods_ready(constants.NAMESPACE, f"app.kubernetes.io/instance={release_name}")
e2e_milvus_parallel(2, host, c_name)
log.info('Milvus test after shrink')
connections.connect('default', host=host, port=19530)
collection_w = ApiCollectionWrapper()
collection_w.init_collection(name=c_name)
"""
total start 2+5+2 process to run e2e, each time insert default_nb data, But one of the 2 processes started
for the first time did not insert due to collection creation exception. So actually insert eight times
"""
assert collection_w.num_entities == 8 * default_nb
except Exception as e:
log.error(str(e))
fail_count += 1
# raise Exception(str(e))
finally:
log.info(f'Test finished with {fail_count} fail request')
assert fail_count <= 1
label = f"app.kubernetes.io/instance={release_name}"
log.info('Start to export milvus pod logs')
read_pod_log(namespace=constants.NAMESPACE, label_selector=label, release_name=release_name)
mic.uninstall(release_name, namespace=constants.NAMESPACE)
def test_expand_index_node(self):
"""
target: test expand indexNode from 1 to 2
method: 1.deploy two indexNode
2.create index with two indexNode
3.expand indexNode from 1 to 2
4.create index with one indexNode
expected: The cost of one indexNode is about twice that of two indexNodes
"""
release_name = "expand-index"
image_tag = get_latest_tag()
image = f'{constants.IMAGE_REPOSITORY}:{image_tag}'
init_replicas = 1
expand_replicas = 2
data_config = {
'metadata.namespace': constants.NAMESPACE,
'spec.mode': 'cluster',
'metadata.name': release_name,
'spec.components.image': image,
'spec.components.proxy.serviceType': 'LoadBalancer',
'spec.components.indexNode.replicas': init_replicas,
'spec.components.dataNode.replicas': 2,
'spec.config.common.retentionDuration': 60
}
mic = MilvusOperator()
mic.install(data_config)
if mic.wait_for_healthy(release_name, constants.NAMESPACE, timeout=1800):
host = mic.endpoint(release_name, constants.NAMESPACE).split(':')[0]
else:
# If deploy failed and want to uninsatll mic
# log.warning(f'Deploy {release_name} timeout and ready to uninstall')
# mic.uninstall(release_name, namespace=constants.NAMESPACE)
raise MilvusException(message=f'Milvus healthy timeout 1800s')
try:
# connect
connections.add_connection(default={"host": host, "port": 19530})
connections.connect(alias='default')
# create collection
c_name = "index_scale_one"
collection_w = ApiCollectionWrapper()
collection_w.init_collection(name=c_name, schema=cf.gen_default_collection_schema())
# insert data
data = cf.gen_default_dataframe_data(nb)
loop = 100
for i in range(loop):
collection_w.insert(data, timeout=60)
assert collection_w.num_entities == nb * loop
# create index
# Note that the num of segments and the num of indexNode are related to indexing time
start = datetime.datetime.now()
collection_w.create_index(ct.default_float_vec_field_name, default_index_params)
assert collection_w.has_index()[0]
t0 = datetime.datetime.now() - start
log.info(f'Create index on {init_replicas} indexNode cost t0: {t0}')
# drop index
collection_w.drop_index()
assert not collection_w.has_index()[0]
# expand indexNode
mic.upgrade(release_name, {'spec.components.indexNode.replicas': expand_replicas}, constants.NAMESPACE)
mic.wait_for_healthy(release_name, constants.NAMESPACE)
wait_pods_ready(constants.NAMESPACE, f"app.kubernetes.io/instance={release_name}")
# create index again
start = datetime.datetime.now()
collection_w.create_index(ct.default_float_vec_field_name, default_index_params)
assert collection_w.has_index()[0]
t1 = datetime.datetime.now() - start
log.info(f'Create index on {expand_replicas} indexNode cost t1: {t1}')
collection_w.drop_index()
start = datetime.datetime.now()
collection_w.create_index(ct.default_float_vec_field_name, default_index_params)
assert collection_w.has_index()[0]
t2 = datetime.datetime.now() - start
log.info(f'Create index on {expand_replicas} indexNode cost t2: {t2}')
log.debug(f't2 is {t2}, t0 is {t0}, t0/t2 is {t0 / t2}')
# assert round(t0 / t2) == 2
except Exception as e:
raise Exception(str(e))
finally:
label = f"app.kubernetes.io/instance={release_name}"
log.info('Start to export milvus pod logs')
read_pod_log(namespace=constants.NAMESPACE, label_selector=label, release_name=release_name)
mic.uninstall(release_name, namespace=constants.NAMESPACE)
def test_scale_data_node(self):
"""
target: test scale dataNode
method: 1.deploy milvus cluster with 2 dataNode
2.create collection with shards_num=5
3.continuously insert new data (daemon thread)
4.expand dataNode from 2 to 5
5.create new collection with shards_num=2
6.continuously insert new collection new data (daemon thread)
7.shrink dataNode from 5 to 3
expected: Verify milvus remains healthy, Insert and flush successfully during scale
Average dataNode memory usage
"""
release_name = "scale-data"
image_tag = get_latest_tag()
image = f'{constants.IMAGE_REPOSITORY}:{image_tag}'
data_config = {
'metadata.namespace': constants.NAMESPACE,
'spec.mode': 'cluster',
'metadata.name': release_name,
'spec.components.image': image,
'spec.components.proxy.serviceType': 'LoadBalancer',
'spec.components.dataNode.replicas': 2,
'spec.config.common.retentionDuration': 60
}
mic = MilvusOperator()
mic.install(data_config)
if mic.wait_for_healthy(release_name,
constants.NAMESPACE,
timeout=1800):
host = mic.endpoint(release_name,
constants.NAMESPACE).split(':')[0]
else:
raise MilvusException(message=f'Milvus healthy timeout 1800s')
try:
# connect
connections.add_connection(default={"host": host, "port": 19530})
connections.connect(alias='default')
# create
c_name = cf.gen_unique_str("scale_data")
collection_w = ApiCollectionWrapper()
collection_w.init_collection(
name=c_name,
schema=cf.gen_default_collection_schema(),
shards_num=4)
tmp_nb = 10000
@counter
def do_insert():
""" do insert and flush """
insert_res, is_succ = collection_w.insert(
cf.gen_default_dataframe_data(tmp_nb))
log.debug(collection_w.num_entities)
return insert_res, is_succ
def loop_insert():
""" loop do insert """
while True:
do_insert()
threading.Thread(target=loop_insert, args=(), daemon=True).start()
# scale dataNode to 5
mic.upgrade(release_name, {'spec.components.dataNode.replicas': 5},
constants.NAMESPACE)
mic.wait_for_healthy(release_name, constants.NAMESPACE)
wait_pods_ready(constants.NAMESPACE,
f"app.kubernetes.io/instance={release_name}")
log.debug("Expand dataNode test finished")
# create new collection and insert
new_c_name = cf.gen_unique_str("scale_data")
collection_w_new = ApiCollectionWrapper()
collection_w_new.init_collection(
name=new_c_name,
schema=cf.gen_default_collection_schema(),
shards_num=3)
@counter
def do_new_insert():
""" do new insert """
insert_res, is_succ = collection_w_new.insert(
cf.gen_default_dataframe_data(tmp_nb))
log.debug(collection_w_new.num_entities)
return insert_res, is_succ
def loop_new_insert():
""" loop new insert """
while True:
do_new_insert()
threading.Thread(target=loop_new_insert, args=(),
daemon=True).start()
# scale dataNode to 3
mic.upgrade(release_name, {'spec.components.dataNode.replicas': 3},
constants.NAMESPACE)
mic.wait_for_healthy(release_name, constants.NAMESPACE)
wait_pods_ready(constants.NAMESPACE,
f"app.kubernetes.io/instance={release_name}")
log.debug(collection_w.num_entities)
time.sleep(300)
scale_common.check_succ_rate(do_insert)
scale_common.check_succ_rate(do_new_insert)
log.debug("Shrink dataNode test finished")
except Exception as e:
log.error(str(e))
# raise Exception(str(e))
finally:
label = f"app.kubernetes.io/instance={release_name}"
log.info('Start to export milvus pod logs')
read_pod_log(namespace=constants.NAMESPACE,
label_selector=label,
release_name=release_name)
mic.uninstall(release_name, namespace=constants.NAMESPACE)