def test_memory_stress_replicas_group_load_balance(self, prepare_collection):
"""
target: test apply memory stress on replicas and load balance inside group
method: 1.Deploy milvus and limit querynode memory 6Gi
2.Insret 1000,000 entities (500Mb), load 2 replicas (memory usage 1.5Gb)
3.Apply memory stress 4Gi on querynode
expected: Verify that load balancing occurs
"""
collection_w = prepare_collection
utility_w = ApiUtilityWrapper()
release_name = "mic-memory"
# load and searchc
collection_w.load(replica_number=2)
progress, _ = utility_w.loading_progress(collection_w.name)
assert progress["loading_progress"] == "100%"
# get the replica and random chaos querynode
replicas, _ = collection_w.get_replicas()
chaos_querynode_id = replicas.groups[0].group_nodes[0]
label = f"app.kubernetes.io/instance={release_name}, app.kubernetes.io/component=querynode"
querynode_id_pod_pair = get_querynode_id_pod_pairs("chaos-testing", label)
chaos_querynode_pod = querynode_id_pod_pair[chaos_querynode_id]
# get the segment num before chaos
seg_info_before, _ = utility_w.get_query_segment_info(collection_w.name)
seg_distribution_before = cf.get_segment_distribution(seg_info_before)
segments_num_before = len(seg_distribution_before[chaos_querynode_id]["sealed"])
log.debug(segments_num_before)
log.debug(seg_distribution_before[chaos_querynode_id]["sealed"])
# apply memory stress
chaos_config = gen_experiment_config("./chaos_objects/memory_stress/chaos_replicas_memory_stress_pods.yaml")
chaos_config['spec']['selector']['pods']['chaos-testing'] = [chaos_querynode_pod]
log.debug(chaos_config)
chaos_res = CusResource(kind=chaos_config['kind'],
group=constants.CHAOS_GROUP,
version=constants.CHAOS_VERSION,
namespace=constants.CHAOS_NAMESPACE)
chaos_res.create(chaos_config)
log.debug(f"Apply memory stress on querynode {chaos_querynode_id}, pod {chaos_querynode_pod}")
duration = chaos_config.get('spec').get('duration')
duration = duration.replace('h', '*3600+').replace('m', '*60+').replace('s', '*1+') + '+0'
sleep(eval(duration))
chaos_res.delete(metadata_name=chaos_config.get('metadata', None).get('name', None))
# Verfiy auto load loadbalance
seg_info_after, _ = utility_w.get_query_segment_info(collection_w.name)
seg_distribution_after = cf.get_segment_distribution(seg_info_after)
segments_num_after = len(seg_distribution_after[chaos_querynode_id]["sealed"])
log.debug(segments_num_after)
log.debug(seg_distribution_after[chaos_querynode_id]["sealed"])
assert segments_num_after < segments_num_before
search_res, _ = collection_w.search(cf.gen_vectors(1, dim=self.dim),
ct.default_float_vec_field_name, ct.default_search_params,
ct.default_limit, timeout=120)
assert 1 == len(search_res) and ct.default_limit == len(search_res[0])
def test_chaos_memory_stress_indexnode(self, connection, chaos_yaml):
"""
target: test inject memory stress into indexnode
method: 1.Deploy milvus and limit indexnode memory resource 3 / 4Gi
2.Create collection and insert some data
3.Inject memory stress chaos 512Mi
4.Create index
expected:
"""
# init collection and insert
nb = 256000 # vector size: 512*4*nb about 512Mi and create index need 2.8Gi memory
dim = 512
# c_name = cf.gen_unique_str('chaos_memory')
c_name = 'chaos_memory_gKs8aSUu'
index_params = {"index_type": "IVF_SQ8", "metric_type": "L2", "params": {"nlist": 128}}
collection_w = ApiCollectionWrapper()
collection_w.init_collection(name=c_name,
schema=cf.gen_default_collection_schema(dim=dim), shards_num=1)
# insert 256000 512 dim entities, size 512Mi
for i in range(2):
t0_insert = datetime.datetime.now()
df = cf.gen_default_dataframe_data(nb=nb // 2, dim=dim)
res = collection_w.insert(df)[0]
assert res.insert_count == nb // 2
# log.info(f'After {i + 1} insert, num_entities: {collection_w.num_entities}')
tt_insert = datetime.datetime.now() - t0_insert
log.info(f"{i} insert data cost: {tt_insert}")
# flush
t0_flush = datetime.datetime.now()
assert collection_w.num_entities == nb
tt_flush = datetime.datetime.now() - t0_flush
log.info(f'flush {nb * 10} entities cost: {tt_flush}')
log.info(collection_w.indexes[0].params)
if collection_w.has_index()[0]:
collection_w.drop_index()
# indexNode start build index, inject chaos memory stress
chaos_config = gen_experiment_config(chaos_yaml)
log.debug(chaos_config)
chaos_res = CusResource(kind=chaos_config['kind'],
group=constants.CHAOS_GROUP,
version=constants.CHAOS_VERSION,
namespace=constants.CHAOS_NAMESPACE)
chaos_res.create(chaos_config)
log.debug("inject chaos")
# create index
t0_index = datetime.datetime.now()
index, _ = collection_w.create_index(field_name=ct.default_float_vec_field_name,
index_params=index_params)
tt_index = datetime.datetime.now() - t0_index
log.info(f"create index cost: {tt_index}")
log.info(collection_w.indexes[0].params)
def apply_memory_stress(chaos_yaml):
chaos_config = gen_experiment_config(chaos_yaml)
log.debug(chaos_config)
chaos_res = CusResource(kind=chaos_config['kind'],
group=constants.CHAOS_GROUP,
version=constants.CHAOS_VERSION,
namespace=constants.CHAOS_NAMESPACE)
chaos_res.create(chaos_config)
log.debug("chaos injected")
def test_chaos_memory_stress_querynode(self, connection, chaos_yaml):
"""
target: explore query node behavior after memory stress chaos injected and recovered
method: 1. Create a collection, insert some data
2. Inject memory stress chaos
3. Start a threas to load, search and query
4. After chaos duration, check query search success rate
5. Delete chaos or chaos finished finally
expected: 1.If memory is insufficient, querynode is OOMKilled and available after restart
2.If memory is sufficient, succ rate of query and search both are 1.0
"""
c_name = 'chaos_memory_nx6DNW4q'
collection_w = ApiCollectionWrapper()
collection_w.init_collection(c_name)
log.debug(collection_w.schema)
log.debug(collection_w._shards_num)
# apply memory stress chaos
chaos_config = gen_experiment_config(chaos_yaml)
log.debug(chaos_config)
chaos_res = CusResource(kind=chaos_config['kind'],
group=constants.CHAOS_GROUP,
version=constants.CHAOS_VERSION,
namespace=constants.CHAOS_NAMESPACE)
chaos_res.create(chaos_config)
log.debug("chaos injected")
duration = chaos_config.get('spec').get('duration')
duration = duration.replace('h', '*3600+').replace(
'm', '*60+').replace('s', '*1+') + '+0'
meta_name = chaos_config.get('metadata').get('name')
# wait memory stress
sleep(constants.WAIT_PER_OP * 2)
# try to do release, load, query and serach in a duration time loop
try:
start = time.time()
while time.time() - start < eval(duration):
collection_w.release()
collection_w.load()
term_expr = f'{ct.default_int64_field_name} in {[random.randint(0, 100)]}'
query_res, _ = collection_w.query(term_expr)
assert len(query_res) == 1
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
except Exception as e:
raise Exception(str(e))
finally:
chaos_res.delete(meta_name)
def test_memory_stress_replicas_group_insufficient(self, prepare_collection, mode):
"""
target: test apply stress memory on different number querynodes and the group failed to load,
bacause of the memory is insufficient
method: 1.Limit querynodes memory 5Gi
2.Create collection and insert 1000,000 entities
3.Apply memory stress on querynodes and it's memory is not enough to load replicas
expected: Verify load raise exception, and after delete chaos, load and search successfully
"""
collection_w = prepare_collection
utility_w = ApiUtilityWrapper()
chaos_config = gen_experiment_config("./chaos_objects/memory_stress/chaos_querynode_memory_stress.yaml")
# Update config
chaos_config['spec']['mode'] = mode
chaos_config['spec']['stressors']['memory']['size'] = '5Gi'
log.debug(chaos_config)
chaos_res = CusResource(kind=chaos_config['kind'],
group=constants.CHAOS_GROUP,
version=constants.CHAOS_VERSION,
namespace=constants.CHAOS_NAMESPACE)
chaos_res.create(chaos_config)
# chaos_start = time.time()
log.debug("chaos injected")
sleep(10)
try:
# load failed
err = {"err_code": 1, "err_msg": "shuffleSegmentsToQueryNodeV2: insufficient memory of available node"}
collection_w.load(replica_number=5, timeout=60, check_task=CheckTasks.err_res, check_items=err)
# query failed because not loaded
err = {"err_code": 1, "err_msg": "not loaded into memory"}
collection_w.query("int64 in [0]", check_task=CheckTasks.err_res, check_items=err)
# delete chaos
meta_name = chaos_config.get('metadata', None).get('name', None)
chaos_res.delete(metadata_name=meta_name)
sleep(10)
# after delete chaos load and query successfully
collection_w.load(replica_number=5, timeout=60)
progress, _ = utility_w.loading_progress(collection_w.name)
# assert progress["loading_progress"] == "100%"
query_res, _ = collection_w.query("int64 in [0]")
assert len(query_res) != 0
collection_w.release()
except Exception as e:
raise Exception(str(e))
finally:
log.debug("Test finished")
def test_memory_stress_replicas_cross_group_load_balance(self, prepare_collection):
"""
target: test apply memory stress on one group and no load balance cross replica groups
method: 1.Limit all querynodes memory 6Gi
2.Create and insert 1000,000 entities
3.Load collection with two replicas
4.Apply memory stress on one grooup 80%
expected: Verify that load balancing across groups is not occurring
"""
collection_w = prepare_collection
utility_w = ApiUtilityWrapper()
release_name = "mic-memory"
# load and searchc
collection_w.load(replica_number=2)
progress, _ = utility_w.loading_progress(collection_w.name)
assert progress["loading_progress"] == "100%"
seg_info_before, _ = utility_w.get_query_segment_info(collection_w.name)
# get the replica and random chaos querynode
replicas, _ = collection_w.get_replicas()
group_nodes = list(replicas.groups[0].group_nodes)
label = f"app.kubernetes.io/instance={release_name}, app.kubernetes.io/component=querynode"
querynode_id_pod_pair = get_querynode_id_pod_pairs("chaos-testing", label)
group_nodes_pod = [querynode_id_pod_pair[node_id] for node_id in group_nodes]
# apply memory stress
chaos_config = gen_experiment_config("./chaos_objects/memory_stress/chaos_replicas_memory_stress_pods.yaml")
chaos_config['spec']['selector']['pods']['chaos-testing'] = group_nodes_pod
log.debug(chaos_config)
chaos_res = CusResource(kind=chaos_config['kind'],
group=constants.CHAOS_GROUP,
version=constants.CHAOS_VERSION,
namespace=constants.CHAOS_NAMESPACE)
chaos_res.create(chaos_config)
log.debug(f"Apply memory stress on querynode {group_nodes}, pod {group_nodes_pod}")
duration = chaos_config.get('spec').get('duration')
duration = duration.replace('h', '*3600+').replace('m', '*60+').replace('s', '*1+') + '+0'
sleep(eval(duration))
chaos_res.delete(metadata_name=chaos_config.get('metadata', None).get('name', None))
# Verfiy auto load loadbalance
seg_info_after, _ = utility_w.get_query_segment_info(collection_w.name)
seg_distribution_before = cf.get_segment_distribution(seg_info_before)
seg_distribution_after = cf.get_segment_distribution(seg_info_after)
for node_id in group_nodes:
assert len(seg_distribution_before[node_id]) == len(seg_distribution_after[node_id])
search_res, _ = collection_w.search(cf.gen_vectors(1, dim=self.dim),
ct.default_float_vec_field_name, ct.default_search_params,
ct.default_limit, timeout=120)
assert 1 == len(search_res) and ct.default_limit == len(search_res[0])
def test_chaos_memory_stress_etcd(self, chaos_yaml):
"""
target: test inject memory stress into all etcd pods
method: 1.Deploy milvus and limit etcd memory resource 1Gi witl all mode
2.Continuously and concurrently do milvus operations
3.Inject memory stress chaos 51024Mi
4.After duration, delete chaos stress
expected: Verify milvus operation succ rate
"""
mic_checkers = {
Op.create: CreateChecker(),
Op.insert: InsertFlushChecker(),
Op.flush: InsertFlushChecker(flush=True),
Op.index: IndexChecker(),
Op.search: SearchChecker(),
Op.query: QueryChecker()
}
# start thread keep running milvus op
start_monitor_threads(mic_checkers)
# parse chaos object
chaos_config = cc.gen_experiment_config(chaos_yaml)
# duration = chaos_config["spec"]["duration"]
meta_name = chaos_config.get('metadata').get('name')
duration = chaos_config.get('spec').get('duration')
# apply chaos object
chaos_res = CusResource(kind=chaos_config['kind'],
group=constants.CHAOS_GROUP,
version=constants.CHAOS_VERSION,
namespace=constants.CHAOS_NAMESPACE)
chaos_res.create(chaos_config)
log.info("Chaos injected")
# convert string duration time to a int number in seconds
if isinstance(duration, str):
duration = duration.replace('h', '*3600+').replace(
'm', '*60+').replace('s', '*1+') + '+0'
else:
log.error("Duration must be string type")
# Delete experiment after it's over
timer = threading.Timer(interval=eval(duration),
function=chaos_res.delete,
args=(meta_name, False))
timer.start()
timer.join()
# output milvus op succ rate
for k, ch in mic_checkers.items():
log.debug(f'Succ rate of {k.value}: {ch.succ_rate()}')
assert ch.succ_rate() == 1.0
def reboot_pod(chaos_yaml):
# parse chaos object
chaos_config = gen_experiment_config(chaos_yaml)
log.debug(chaos_config)
# inject chaos
chaos_res = CusResource(kind=chaos_config['kind'],
group=constants.CHAOS_GROUP,
version=constants.CHAOS_VERSION,
namespace=constants.CHAOS_NAMESPACE)
chaos_res.create(chaos_config)
log.debug("chaos injected")
sleep(7)
# delete chaos
meta_name = chaos_config.get('metadata', None).get('name', None)
chaos_res.delete(meta_name)
log.debug("chaos deleted")
def test_memory_stress_replicas_load_balance_single_node(self, prepare_collection):
"""
target: test apply memory stress on single node replica, and it OOMKilled
method: 1.Deploy 2 querynodes and limit memory 6Gi
2.Loading 1000,000 entities (data_size=500Mb) with 2 replicas (memory_usage=1.5Gb)
3.Apply memory stress on one querynode and make it OOMKilled
expected: After deleting chaos, querynode turns running, search successfully
"""
collection_w = prepare_collection
utility_w = ApiUtilityWrapper()
# load and searchc
collection_w.load(replica_number=2)
progress, _ = utility_w.loading_progress(collection_w.name)
assert progress["loading_progress"] == "100%"
query_res, _ = collection_w.query("int64 in [0]")
assert len(query_res) != 0
# apply memory stress
chaos_config = gen_experiment_config("./chaos_objects/memory_stress/chaos_querynode_memory_stress.yaml")
# Update config
chaos_config['spec']['mode'] = "one"
chaos_config['spec']['stressors']['memory']['size'] = '6Gi'
chaos_config['spec']['duration'] = "1m"
log.debug(chaos_config)
duration = chaos_config.get('spec').get('duration')
duration = duration.replace('h', '*3600+').replace('m', '*60+').replace('s', '*1+') + '+0'
chaos_res = CusResource(kind=chaos_config['kind'],
group=constants.CHAOS_GROUP,
version=constants.CHAOS_VERSION,
namespace=constants.CHAOS_NAMESPACE)
chaos_res.create(chaos_config)
sleep(eval(duration))
chaos_res.delete(metadata_name=chaos_config.get('metadata', None).get('name', None))
# release and load again
collection_w.release()
collection_w.load(replica_number=2)
progress, _ = utility_w.loading_progress(collection_w.name)
assert progress["loading_progress"] == "100%"
search_res, _ = collection_w.search(cf.gen_vectors(1, dim=self.dim),
ct.default_float_vec_field_name, ct.default_search_params,
ct.default_limit, timeout=120)
assert 1 == len(search_res) and ct.default_limit == len(search_res[0])
def test_chaos_memory_stress_datanode(self, chaos_yaml):
"""
target: test inject memory stress into dataNode
method: 1.Deploy milvus and limit datanode memory resource
2.Create collection and insert some data
3.Inject memory stress chaos
4.Continue to insert data
expected:
"""
# init collection and insert 250 nb
nb = 25000
dim = 512
c_name = cf.gen_unique_str('chaos_memory')
collection_w = ApiCollectionWrapper()
collection_w.init_collection(
name=c_name, schema=cf.gen_default_collection_schema(dim=dim))
for i in range(10):
t0 = datetime.datetime.now()
df = cf.gen_default_dataframe_data(nb=nb, dim=dim)
res = collection_w.insert(df)[0]
assert res.insert_count == nb
log.info(
f'After {i + 1} insert, num_entities: {collection_w.num_entities}'
)
tt = datetime.datetime.now() - t0
log.info(f"{i} insert and flush data cost: {tt}")
# inject memory stress
chaos_config = gen_experiment_config(chaos_yaml)
log.debug(chaos_config)
chaos_res = CusResource(kind=chaos_config['kind'],
group=constants.CHAOS_GROUP,
version=constants.CHAOS_VERSION,
namespace=constants.CHAOS_NAMESPACE)
chaos_res.create(chaos_config)
log.debug("chaos injected")
# Continue to insert data
collection_w.insert(df)
log.info(f'Total num entities: {collection_w.num_entities}')
# delete chaos
meta_name = chaos_config.get('metadata', None).get('name', None)
chaos_res.delete(metadata_name=meta_name)
def test_chaos_memory_stress_replicas_OOM(self, prepare_collection, mode):
"""
target: test apply memory stress during loading, and querynode OOMKilled
method: 1.Deploy and limit querynode memory limit 6Gi
2.Create collection and insert 1000,000 entities
3.Apply memory stress and querynode OOMKilled during loading replicas
expected: Verify the mic is available to load and search querynode restart
"""
collection_w = prepare_collection
utility_w = ApiUtilityWrapper()
chaos_config = gen_experiment_config("./chaos_objects/memory_stress/chaos_querynode_memory_stress.yaml")
chaos_config['spec']['mode'] = mode
chaos_config['spec']['duration'] = '3m'
chaos_config['spec']['stressors']['memory']['size'] = '6Gi'
log.debug(chaos_config)
chaos_res = CusResource(kind=chaos_config['kind'],
group=constants.CHAOS_GROUP,
version=constants.CHAOS_VERSION,
namespace=constants.CHAOS_NAMESPACE)
chaos_res.create(chaos_config)
log.debug("chaos injected")
collection_w.load(replica_number=2, timeout=60, _async=True)
utility_w.wait_for_loading_complete(collection_w.name)
progress, _ = utility_w.loading_progress(collection_w.name)
assert progress["loading_progress"] == '100%'
sleep(180)
chaos_res.delete(metadata_name=chaos_config.get('metadata', None).get('name', None))
# TODO search failed
search_res, _ = collection_w.search(cf.gen_vectors(1, dim=self.dim),
ct.default_float_vec_field_name, ct.default_search_params,
ct.default_limit, timeout=120)
assert 1 == len(search_res) and ct.default_limit == len(search_res[0])
collection_w.release()
collection_w.load(replica_number=2)
search_res, _ = collection_w.search(cf.gen_vectors(1, dim=self.dim),
ct.default_float_vec_field_name, ct.default_search_params,
ct.default_limit, timeout=120)
assert 1 == len(search_res) and ct.default_limit == len(search_res[0])
def test_memory_stress_replicas_group_sufficient(self, prepare_collection, mode):
"""
target: test apply stress memory on one querynode and the memory is enough to load replicas
method: 1.Limit all querynodes memory 6Gi
2.Apply 3Gi memory stress on different number of querynodes (load whole collection need about 1.5GB)
expected: Verify load successfully and search result are correct
"""
collection_w = prepare_collection
utility_w = ApiUtilityWrapper()
# # apply memory stress chaos
chaos_config = gen_experiment_config("./chaos_objects/memory_stress/chaos_querynode_memory_stress.yaml")
chaos_config['spec']['mode'] = mode
chaos_config['spec']['duration'] = '3m'
chaos_config['spec']['stressors']['memory']['size'] = '3Gi'
log.debug(chaos_config)
chaos_res = CusResource(kind=chaos_config['kind'],
group=constants.CHAOS_GROUP,
version=constants.CHAOS_VERSION,
namespace=constants.CHAOS_NAMESPACE)
chaos_res.create(chaos_config)
log.debug("chaos injected")
sleep(20)
#
try:
collection_w.load(replica_number=2, timeout=60)
utility_w.loading_progress(collection_w.name)
replicas, _ = collection_w.get_replicas()
log.debug(replicas)
search_res, _ = collection_w.search(cf.gen_vectors(1, dim=self.dim),
ct.default_float_vec_field_name, ct.default_search_params,
ct.default_limit, timeout=120)
assert 1 == len(search_res) and ct.default_limit == len(search_res[0])
collection_w.release()
except Exception as e:
raise Exception(str(e))
finally:
# delete chaos
meta_name = chaos_config.get('metadata', None).get('name', None)
chaos_res.delete(metadata_name=meta_name)
log.debug("Test finished")
def install(self, configs, template=None):
"""
Method: apply a custom resource object to install milvus
Params:
configs: a dict type of configurations that describe the properties of milvus to be deployed
template: Optional. Pass the template file location if there is a template to apply
Return: custom resource object instance
"""
new_configs = self._update_configs(configs, template)
print(new_configs)
namespace = new_configs['metadata'].get('namespace', 'default')
# apply custom resource object to deploy milvus
cus_res = CusResource(kind=self.plural, group=self.group,
version=self.version, namespace=namespace)
log.info(f'install milvus with configs: {json.dumps(new_configs, indent=4)}')
return cus_res.create(new_configs)
def test_multi_replicas_with_only_one_group_available(
self, chaos_type, failed_node_type, failed_group_scope,
is_streaming):
# start the monitor threads to check the milvus ops
log.info("*********************Chaos Test Start**********************")
log.info("Test config")
log.info(cc.gen_experiment_config(config_file_name))
# log.info(f"chaos_yaml: {chaos_yaml}")
log.info(connections.get_connection_addr('default'))
if is_streaming is False:
del self.health_checkers[Op.insert]
cc.start_monitor_threads(self.health_checkers)
# get replicas info
release_name = self.instance_name
querynode_id_pod_pair = get_querynode_info(release_name)
log.info(querynode_id_pod_pair)
group_list = []
shard_leader_list = []
replicas_info, _ = self.health_checkers[
Op.search].c_wrap.get_replicas()
for g in replicas_info.groups:
group_list.append(list(g.group_nodes))
for shard in g.shards:
shard_leader_list.append(shard.shard_leader)
# keep only one group in healthy status, other groups will be unhealthy by injecting pod failure chaos,
# In the effected groups, each group has one pod is in pod failure status
target_pod_list = []
target_group = []
group_list = sorted(group_list, key=lambda x: -len(x))
if failed_group_scope == "one":
target_group = random.sample(group_list, 1)
if failed_group_scope == "except_one":
target_group = random.sample(group_list, len(group_list) - 1)
if failed_group_scope == "all":
target_group = group_list[:]
for g in target_group:
target_nodes = []
if failed_node_type == "shard_leader":
target_nodes = list(set(g) & set(shard_leader_list))
if failed_node_type == "non_shard_leader":
target_nodes = list(set(g) - set(shard_leader_list))
if len(target_nodes) == 0:
log.info("there is no node satisfied, chose one randomly")
target_nodes = [random.choice(g)]
for target_node in target_nodes:
pod = querynode_id_pod_pair[target_node]
target_pod_list.append(pod)
log.info(f"target_pod_list: {target_pod_list}")
chaos_config = cc.gen_experiment_config(
f"{str(Path(__file__).absolute().parent)}/chaos_objects/template/{chaos_type}-by-pod-list.yaml"
)
chaos_config['metadata'][
'name'] = f"test-multi-replicase-{int(time.time())}"
meta_name = chaos_config.get('metadata', None).get('name', None)
chaos_config['spec']['selector']['pods'][
'chaos-testing'] = target_pod_list
self._chaos_config = chaos_config # cache the chaos config for tear down
log.info(f"chaos_config: {chaos_config}")
# wait 20s
sleep(constants.WAIT_PER_OP * 2)
# replicas info
replicas_info, _ = self.health_checkers[
Op.search].c_wrap.get_replicas()
log.info(
f"replicas_info for search collection {self.health_checkers[Op.search].c_wrap.name}: {replicas_info}"
)
# assert statistic:all ops 100% succ
log.info("******1st assert before chaos: ")
assert_statistic(self.health_checkers)
# apply chaos object
chaos_res = CusResource(kind=chaos_config['kind'],
group=constants.CHAOS_GROUP,
version=constants.CHAOS_VERSION,
namespace=constants.CHAOS_NAMESPACE)
chaos_res.create(chaos_config)
log.info("chaos injected")
sleep(constants.WAIT_PER_OP * 2)
# reset counting
cc.reset_counting(self.health_checkers)
# wait 120s
sleep(constants.CHAOS_DURATION)
log.info(f'Alive threads: {threading.enumerate()}')
# node info
querynode_id_pod_pair = get_querynode_info(release_name)
log.info(querynode_id_pod_pair)
# replicas info
replicas_info, _ = self.health_checkers[
Op.search].c_wrap.get_replicas()
log.info(
f"replicas_info for search collection {self.health_checkers[Op.search].c_wrap.name}: {replicas_info}"
)
replicas_info, _ = self.health_checkers[Op.query].c_wrap.get_replicas()
log.info(
f"replicas_info for query collection {self.health_checkers[Op.query].c_wrap.name}: {replicas_info}"
)
# assert statistic
log.info("******2nd assert after chaos injected: ")
expectations = {Op.search: constants.SUCC, Op.query: constants.SUCC}
if failed_group_scope == "all":
expectations = {
Op.search: constants.FAIL,
Op.query: constants.FAIL
}
assert_statistic(self.health_checkers, expectations=expectations)
# delete chaos
chaos_res.delete(meta_name)
log.info("chaos deleted")
sleep(2)
# wait all pods ready
log.info(
f"wait for pods in namespace {constants.CHAOS_NAMESPACE} with label app.kubernetes.io/instance={release_name}"
)
ready_1 = wait_pods_ready(
constants.CHAOS_NAMESPACE,
f"app.kubernetes.io/instance={release_name}")
log.info(
f"wait for pods in namespace {constants.CHAOS_NAMESPACE} with label release={release_name}"
)
ready_2 = wait_pods_ready(constants.CHAOS_NAMESPACE,
f"release={release_name}")
if ready_1 and ready_2:
log.info("all pods are ready")
# reconnect if needed
sleep(constants.WAIT_PER_OP * 2)
# cc.reconnect(connections, alias='default')
# reset counting again
cc.reset_counting(self.health_checkers)
# wait 50s (varies by feature)
sleep(constants.WAIT_PER_OP * 5)
# node info
querynode_id_pod_pair = get_querynode_info(release_name)
log.info(querynode_id_pod_pair)
sleep(30)
# replicas info
replicas_info, _ = self.health_checkers[
Op.search].c_wrap.get_replicas()
log.info(
f"replicas_info for collection {self.health_checkers[Op.search].c_wrap.name}: {replicas_info}"
)
replicas_info, _ = self.health_checkers[Op.query].c_wrap.get_replicas()
log.info(
f"replicas_info for collection {self.health_checkers[Op.query].c_wrap.name}: {replicas_info}"
)
# assert statistic: all ops success again
log.info("******3rd assert after chaos deleted: ")
assert_statistic(self.health_checkers)
# assert all expectations
assert_expectations()
log.info(
"*********************Chaos Test Completed**********************")
def test_chaos(self, chaos_yaml):
# start the monitor threads to check the milvus ops
log.info("*********************Chaos Test Start**********************")
log.info(connections.get_connection_addr('default'))
self.checker_threads = cc.start_monitor_threads(self.health_checkers)
# parse chaos object
chaos_config = cc.gen_experiment_config(chaos_yaml)
self._chaos_config = chaos_config # cache the chaos config for tear down
log.info(f"chaos_config: {chaos_config}")
# parse the test expectations in testcases.yaml
if self.parser_testcase_config(chaos_yaml) is False:
log.error("Fail to get the testcase info in testcases.yaml")
assert False
# init report
meta_name = chaos_config.get('metadata', None).get('name', None)
dir_name = "./reports"
file_name = f"./reports/{meta_name}.log"
if not os.path.exists(dir_name):
os.makedirs(dir_name)
# wait 20s
sleep(constants.WAIT_PER_OP * 2)
# assert statistic:all ops 100% succ
log.info("******1st assert before chaos: ")
assert_statistic(self.health_checkers)
with open(file_name, "a+") as f:
f.write("1st assert before chaos: ")
f.write(f"{self.health_checkers}\n")
# apply chaos object
chaos_res = CusResource(kind=chaos_config['kind'],
group=constants.CHAOS_GROUP,
version=constants.CHAOS_VERSION,
namespace=constants.CHAOS_NAMESPACE)
chaos_res.create(chaos_config)
log.info("chaos injected")
log.info(f"chaos information: {chaos_res.get(meta_name)}")
sleep(constants.WAIT_PER_OP * 2.1)
# reset counting
cc.reset_counting(self.health_checkers)
# wait 40s
sleep(constants.CHAOS_DURATION)
for k, t in self.checker_threads.items():
log.info(f"10s later: Thread {k} is_alive(): {t.is_alive()}")
# assert statistic
log.info("******2nd assert after chaos injected: ")
assert_statistic(self.health_checkers,
expectations={
Op.create: self.expect_create,
Op.insert: self.expect_insert,
Op.flush: self.expect_flush,
Op.index: self.expect_index,
Op.search: self.expect_search,
Op.query: self.expect_query
})
with open(file_name, "a+") as f:
f.write("2nd assert after chaos injected:")
f.write(f"{self.health_checkers}\n")
# delete chaos
chaos_res.delete(meta_name)
log.info("chaos deleted")
for k, t in self.checker_threads.items():
log.info(f"Thread {k} is_alive(): {t.is_alive()}")
sleep(2)
# reconnect if needed
sleep(constants.WAIT_PER_OP * 2)
cc.reconnect(connections, alias='default')
# reset counting again
cc.reset_counting(self.health_checkers)
# wait 50s (varies by feature)
sleep(constants.WAIT_PER_OP * 5)
# assert statistic: all ops success again
log.info("******3rd assert after chaos deleted: ")
assert_statistic(self.health_checkers)
with open(file_name, "a+") as f:
f.write("3rd assert after chaos deleted:")
f.write(f"{self.health_checkers}\n")
# assert all expectations
assert_expectations()
log.info(
"*********************Chaos Test Completed**********************")
def test_chaos(self, chaos_yaml):
# start the monitor threads to check the milvus ops
log.info("*********************Chaos Test Start**********************")
log.info(connections.get_connection_addr('default'))
cc.start_monitor_threads(self.health_checkers)
# parse chaos object
chaos_config = cc.gen_experiment_config(chaos_yaml)
meta_name = chaos_config.get('metadata', None).get('name', None)
release_name = meta_name
chaos_config_str = json.dumps(chaos_config)
chaos_config_str = chaos_config_str.replace("milvus-chaos", release_name)
chaos_config = json.loads(chaos_config_str)
self._chaos_config = chaos_config # cache the chaos config for tear down
log.info(f"chaos_config: {chaos_config}")
# parse the test expectations in testcases.yaml
if self.parser_testcase_config(chaos_yaml, chaos_config) is False:
log.error("Fail to get the testcase info in testcases.yaml")
assert False
# init report
dir_name = "./reports"
file_name = f"./reports/{meta_name}.log"
if not os.path.exists(dir_name):
os.makedirs(dir_name)
# wait 20s
sleep(constants.WAIT_PER_OP * 2)
# assert statistic:all ops 100% succ
log.info("******1st assert before chaos: ")
assert_statistic(self.health_checkers)
with open(file_name, "a+") as f:
ts = time.strftime("%Y-%m-%d %H:%M:%S")
f.write(f"{meta_name}-{ts}\n")
f.write("1st assert before chaos:\n")
f.write(record_results(self.health_checkers))
# apply chaos object
chaos_res = CusResource(kind=chaos_config['kind'],
group=constants.CHAOS_GROUP,
version=constants.CHAOS_VERSION,
namespace=constants.CHAOS_NAMESPACE)
chaos_res.create(chaos_config)
log.info("chaos injected")
log.info(f"chaos information: {chaos_res.get(meta_name)}")
sleep(constants.WAIT_PER_OP * 2)
# reset counting
cc.reset_counting(self.health_checkers)
# wait 40s
sleep(constants.CHAOS_DURATION)
log.info(f'Alive threads: {threading.enumerate()}')
# assert statistic
log.info("******2nd assert after chaos injected: ")
assert_statistic(self.health_checkers,
expectations={Op.create: self.expect_create,
Op.insert: self.expect_insert,
Op.flush: self.expect_flush,
Op.index: self.expect_index,
Op.search: self.expect_search,
Op.query: self.expect_query
})
with open(file_name, "a+") as f:
f.write("2nd assert after chaos injected:\n")
f.write(record_results(self.health_checkers))
# delete chaos
chaos_res.delete(meta_name)
log.info("chaos deleted")
log.info(f'Alive threads: {threading.enumerate()}')
sleep(2)
# wait all pods ready
log.info(f"wait for pods in namespace {constants.CHAOS_NAMESPACE} with label app.kubernetes.io/instance={meta_name}")
wait_pods_ready(constants.CHAOS_NAMESPACE, f"app.kubernetes.io/instance={meta_name}")
log.info(f"wait for pods in namespace {constants.CHAOS_NAMESPACE} with label release={meta_name}")
wait_pods_ready(constants.CHAOS_NAMESPACE, f"release={meta_name}")
log.info("all pods are ready")
# reconnect if needed
sleep(constants.WAIT_PER_OP * 2)
cc.reconnect(connections, alias='default')
# reset counting again
cc.reset_counting(self.health_checkers)
# wait 50s (varies by feature)
sleep(constants.WAIT_PER_OP * 5)
# assert statistic: all ops success again
log.info("******3rd assert after chaos deleted: ")
assert_statistic(self.health_checkers)
with open(file_name, "a+") as f:
f.write("3rd assert after chaos deleted:\n")
f.write(record_results(self.health_checkers))
# assert all expectations
assert_expectations()
log.info("*********************Chaos Test Completed**********************")
def test_bulk_load(self, chaos_type, target_component):
# start the monitor threads to check the milvus ops
log.info("*********************Chaos Test Start**********************")
log.info(connections.get_connection_addr('default'))
release_name = self.instance_name
cc.start_monitor_threads(self.health_checkers)
chaos_config = cc.gen_experiment_config(
f"{str(Path(__file__).absolute().parent)}/chaos_objects/{chaos_type}/chaos_{target_component}_{chaos_type}.yaml"
)
chaos_config['metadata']['name'] = f"test-bulk-load-{int(time.time())}"
kind = chaos_config['kind']
meta_name = chaos_config.get('metadata', None).get('name', None)
update_key_value(chaos_config, "release", release_name)
update_key_value(chaos_config, "app.kubernetes.io/instance",
release_name)
self._chaos_config = chaos_config # cache the chaos config for tear down
log.info(f"chaos_config: {chaos_config}")
# wait 20s
sleep(constants.WAIT_PER_OP * 10)
# assert statistic:all ops 100% succ
log.info("******1st assert before chaos: ")
assert_statistic(self.health_checkers)
# apply chaos object
chaos_res = CusResource(kind=chaos_config['kind'],
group=constants.CHAOS_GROUP,
version=constants.CHAOS_VERSION,
namespace=constants.CHAOS_NAMESPACE)
chaos_res.create(chaos_config)
log.info("chaos injected")
sleep(constants.WAIT_PER_OP * 10)
# reset counting
cc.reset_counting(self.health_checkers)
# wait 120s
sleep(constants.CHAOS_DURATION)
log.info(f'Alive threads: {threading.enumerate()}')
# assert statistic
log.info("******2nd assert after chaos injected: ")
assert_statistic(self.health_checkers,
expectations={
Op.bulk_load: constants.FAIL,
})
# delete chaos
chaos_res.delete(meta_name)
log.info("chaos deleted")
sleep(2)
# wait all pods ready
log.info(
f"wait for pods in namespace {constants.CHAOS_NAMESPACE} with label app.kubernetes.io/instance={release_name}"
)
wait_pods_ready(constants.CHAOS_NAMESPACE,
f"app.kubernetes.io/instance={release_name}")
log.info(
f"wait for pods in namespace {constants.CHAOS_NAMESPACE} with label release={release_name}"
)
wait_pods_ready(constants.CHAOS_NAMESPACE, f"release={release_name}")
log.info("all pods are ready")
# reconnect if needed
sleep(constants.WAIT_PER_OP * 2)
cc.reconnect(connections, alias='default')
# recheck failed tasks in third assert
self.health_checkers[Op.bulk_load].recheck_failed_task = True
# reset counting again
cc.reset_counting(self.health_checkers)
# wait 50s (varies by feature)
sleep(constants.WAIT_PER_OP * 10)
# assert statistic: all ops success again
log.info("******3rd assert after chaos deleted: ")
assert_statistic(self.health_checkers)
# assert all expectations
assert_expectations()
log.info(
"*********************Chaos Test Completed**********************")