def _create_pandas_data_frame_from_graph(graph, metrics='all'):
"""
Save on csv files the data in the graph.
Stores one csv per node of the graph
:param graph: (NetworkX Graph) Graph to be annotated with data
:param directory: (str) directory where to store csv files
:return: NetworkX Graph annotated with telemetry data
"""
result = pandas.DataFrame()
for node in graph.nodes(data=True):
node_name = InfoGraphNode.get_name(node)
node_layer = InfoGraphNode.get_layer(node)
node_type = InfoGraphNode.get_type(node)
# This method supports export of either normal metrics coming
# from telemetry agent or utilization type of metrics.
if metrics == 'all':
node_telemetry_data = InfoGraphNode.get_telemetry_data(node)
else:
node_telemetry_data = InfoGraphNode.get_utilization(node)
# df = node_telemetry_data.copy()
# LOG.info("Node Name: {} -- Telemetry: {}".format(
# InfoGraphNode.get_name(node),
# InfoGraphNode.get_telemetry_data(node).columns.values
# ))
node_telemetry_data['timestamp'] = node_telemetry_data[
'timestamp'].astype(float)
node_telemetry_data['timestamp'] = node_telemetry_data[
'timestamp'].round()
node_telemetry_data['timestamp'] = node_telemetry_data[
'timestamp'].astype(int)
for metric_name in node_telemetry_data.columns.values:
if metric_name == 'timestamp':
continue
col_name = "{}@{}@{}@{}".\
format(node_name, node_layer, node_type, metric_name)
col_name = col_name.replace(".", "_")
node_telemetry_data = node_telemetry_data.rename(
columns={metric_name: col_name})
# LOG.info("TELEMETRIA: {}".format(node_telemetry_data.columns.values))
if node_telemetry_data.empty or len(
node_telemetry_data.columns) <= 1:
continue
if result.empty:
result = node_telemetry_data.copy()
else:
node_telemetry_data = \
node_telemetry_data.drop_duplicates(subset='timestamp')
result = pandas.merge(result,
node_telemetry_data,
how='outer',
on='timestamp')
# TODO: Try with this removed
# result.set_index(['timestamp'])
return result
def _get_workload_subgraph(self, stack_name, ts_from=None, ts_to=None):
res = None
try:
# Get the node ID for the stack_name and query the landscape
properties = [("stack_name", stack_name)]
try:
time_window = ts_to - ts_from
except:
time_window = 600
landscape_res = landscape.get_node_by_properties(
properties, ts_from, time_window)
if not landscape_res:
LOG.info("No graph for a stack returned from analytics")
# try a service name
properties = [("service_name", stack_name)]
landscape_res = landscape.get_node_by_properties(
properties, ts_from, time_window)
if not landscape_res:
LOG.info("No graph for a service returned from analytics")
return None
res = landscape.get_subgraph(landscape_res.nodes()[0], ts_from,
time_window)
except Exception as e:
LOG.debug('Something went seriously wrong.')
LOG.error(e)
for node in res.nodes(data=True):
attrs = InfoGraphNode.get_attributes(node)
attrs = InfoGraphUtilities.str_to_dict(attrs)
InfoGraphNode.set_attributes(node, attrs)
return res
def get_metrics(graph, metrics='all'):
"""
Returns all the metrics associated with the input graph
:param graph: (NetworkX Graph) Graph to be annotated with data
:param metrics: metric type to be considered. default = all
:return: the list of metrics associated with the graph
"""
metric_list = []
for node in graph.nodes(data=True):
node_name = InfoGraphNode.get_name(node)
node_layer = InfoGraphNode.get_layer(node)
node_type = InfoGraphNode.get_type(node)
# This method supports export of either normal metrics coming
# from telemetry agent or utilization type of metrics.
if metrics == 'all':
node_telemetry_data = InfoGraphNode.get_telemetry_data(node)
else:
node_telemetry_data = InfoGraphNode.get_utilization(node)
metric_list.extend([
"{}@{}@{}@{}".format(node_name, node_layer, node_type,
metric_name).replace(".", "_")
for metric_name in node_telemetry_data.columns.values
if metric_name != 'timestamp'
])
return metric_list
def get_compute_node_view(self,
compute_node_hostnames,
ts_from=None,
ts_to=None,
name_filtering_support=False):
"""
Returns a view for the compute node.
"""
res = None
if isinstance(compute_node_hostnames, str):
res = self._get_compute_node_subgraph(compute_node_hostnames,
ts_from, ts_to)
elif isinstance(compute_node_hostnames, list):
res = self._get_network_subgraph(ts_from, ts_to)
for hostname in compute_node_hostnames:
if isinstance(hostname, str):
graph = self._get_compute_node_subgraph(
hostname, ts_from, ts_to)
if len(graph.nodes()) > 0:
graphs.merge_graph(res, graph)
if name_filtering_support:
for node in res.nodes(data=True):
name = InfoGraphNode.get_name(node)
InfoGraphNode.set_attribute(node, 'node_name', name)
return res
def _nic(self, node):
nic = None
if InfoGraphNode.get_type(node) == NODE_TYPE.PHYSICAL_NIC:
attrs = InfoGraphNode.get_attributes(node)
if 'osdev_network-name' in attrs:
nic = attrs["osdev_network-name"]
# if InfoGraphNode.get_type(node) == NODE_TYPE.PHYSICAL_MACHINE:
# LOG.info('NODEEEEE: {}'.format(node))
return nic
def _nova_uuid(self, node):
if InfoGraphNode.get_type(node) == NODE_TYPE.INSTANCE_DISK:
disk_name = InfoGraphNode.get_name(node)
vm = self.landscape.get_neighbour_by_type(disk_name, "vm")
return vm
if InfoGraphNode.get_type(node) == NODE_TYPE.PHYSICAL_MACHINE:
vm = self.vms.pop()
return vm
return None
def _disk(self, node):
disk = None
if (InfoGraphNode.get_type(node) == NODE_TYPE.PHYSICAL_DISK
or InfoGraphNode.get_type(node) == NODE_TYPE.PHYSICAL_MACHINE):
attrs = InfoGraphNode.get_attributes(node)
if 'osdev_storage-name' in attrs:
disk = attrs["osdev_storage-name"]
elif InfoGraphNode.get_type(node) == NODE_TYPE.INSTANCE_DISK:
disk = InfoGraphNode.get_name(node).split("_")[1]
return disk
def _stack(self, node):
if InfoGraphNode.get_type(node) == NODE_TYPE.VIRTUAL_MACHINE:
# Taking service node to which the VM is connected
predecessors = self.landscape.predecessors(
InfoGraphNode.get_name(node))
for predecessor in predecessors:
predecessor_node = self.landscape.node[predecessor]
if predecessor_node['type'] == NODE_TYPE.SERVICE_COMPUTE:
if 'stack_name' in predecessor_node:
return predecessor_node["stack_name"]
return None
def _pu(self, node, metric):
pu = None
if (InfoGraphNode.get_type(node) == NODE_TYPE.PHYSICAL_PU
or InfoGraphNode.get_type(node) == NODE_TYPE.PHYSICAL_MACHINE):
attrs = InfoGraphNode.get_attributes(node)
if 'os_index' in attrs:
pu = attrs["os_index"]
# metric prefix 'cpu' on to the front of the cpu number.
if pu and ('intel/proc/schedstat/cpu/' in metric
or 'intel/psutil/cpu/' in metric):
pu = "cpu{}".format(pu)
return pu
def _nic(self, node, tag_key):
nic = None
if InfoGraphNode.get_type(node) == NODE_TYPE.PHYSICAL_NIC:
attrs = InfoGraphNode.get_attributes(node)
if tag_key == "hardware_addr":
nic = attrs["address"]
elif 'osdev_network-name' in attrs:
nic = attrs["osdev_network-name"]
elif 'name' in attrs:
nic = attrs["name"]
# if InfoGraphNode.get_type(node) == NODE_TYPE.PHYSICAL_MACHINE:
# LOG.info('NODEEEEE: {}'.format(node))
return nic
def _get_compute_node_subgraph(self,
compute_node,
ts_from=None,
ts_to=None):
res = self.db.\
get_subgraph('type', 'machine', timestamp=ts_to)
for node in res.nodes(data=True):
attrs = InfoGraphNode.get_attributes(node)
attrs = InfoGraphUtilities.str_to_dict(attrs)
InfoGraphNode.set_attributes(node, attrs)
return res
def get_node_subgraph(self, node_id, ts_from=None, ts_to=None):
try:
time_window = ts_to - ts_from
except:
time_window = 600
landscape_res = landscape.get_subgraph(node_id, ts_from, time_window)
for node in landscape_res.nodes(data=True):
attrs = InfoGraphNode.get_attributes(node)
attrs = InfoGraphUtilities.str_to_dict(attrs)
InfoGraphNode.set_attributes(node, attrs)
return landscape_res
def extract_infrastructure_graph(workload_name, ts_from, ts_to):
"""
Returns the entire landscape at the current time
:return:
"""
landscape_ip = ConfigHelper.get("LANDSCAPE", "host")
landscape_port = ConfigHelper.get("LANDSCAPE", "port")
subgraph_extraction = SubGraphExtraction(landscape_ip=landscape_ip,
landscape_port=landscape_port)
# res = subgraph_extraction.get_workload_view_graph(
# workload_name, int(ts_from), int(ts_to),
# name_filtering_support=True)
res = landscape.get_graph()
#PARALLEL = True
if PARALLEL:
i = 0
threads = []
cpu_count = multiprocessing.cpu_count()
all_node = res.nodes(data=True)
no_node_thread = len(res.nodes()) / cpu_count
node_pool = []
for node in all_node:
if i < no_node_thread:
node_pool.append(node)
i = i + 1
else:
thread1 = ParallelLandscape(
i, "Thread-{}".format(InfoGraphNode.get_name(node)), i,
node_pool)
# thread1 = ParallelTelemetryAnnotation(i, "Thread-{}".format(InfoGraphNode.get_name(node)), i,
# node_pool, internal_graph, self.telemetry, ts_to, ts_from)
thread1.start()
threads.append(thread1)
i = 0
node_pool = []
if len(node_pool) != 0:
thread1 = ParallelLandscape(
i, "Thread-{}".format(InfoGraphNode.get_name(node)), i,
node_pool)
thread1.start()
threads.append(thread1)
[t.join() for t in threads]
else:
for node in res.nodes(data=True):
attrs = InfoGraphNode.get_attributes(node)
attrs = InfoGraphUtilities.str_to_dict(attrs)
InfoGraphNode.set_attributes(node, attrs)
return res
def _source(self, node):
attrs = InfoGraphNode.get_attributes(node)
if InfoGraphNode.get_layer(node) == GRAPH_LAYER.PHYSICAL:
if 'allocation' in attrs:
return attrs['allocation']
# fix due to the landscape
else:
while attrs.get('attributes', None):
attrs = attrs['attributes']
if 'allocation' in attrs:
return attrs['allocation']
if InfoGraphNode.get_type(node) == NODE_TYPE.VIRTUAL_MACHINE:
if 'vm_name' in attrs:
return attrs['vm_name']
if InfoGraphNode.get_type(node) == NODE_TYPE.INSTANCE_DISK:
# The machine is the source as this is a libvirt disk.
disk_name = InfoGraphNode.get_name(node)
vm = self.landscape.get_neighbour_by_type(
disk_name, NODE_TYPE.VIRTUAL_MACHINE)
machine = self.landscape.get_neighbour_by_type(
vm, NODE_TYPE.PHYSICAL_MACHINE)
return machine
if InfoGraphNode.get_type(node) == NODE_TYPE.PHYSICAL_MACHINE:
if 'name' in attrs:
return attrs['name']
if InfoGraphNode.get_type(node) == NODE_TYPE.DOCKER_CONTAINER:
docker_node = self.landscape.get_neighbour_by_type(
InfoGraphNode.get_name(node), 'docker_node')
if docker_node:
machine = self.landscape.get_neighbour_by_type(
docker_node, 'machine')
return machine
return None
def _source_metrics(self, node):
"""
Retrieves metrics associated with a source/host. The source is
identified by the node and then all metrics types are collected for
that source. If the node is physical then the metric types are
retrieved using just the machine name as the source, if the node is
virtual then the source (the vm hostname) and the stack name are
required.
"""
metric_types = []
node_layer = InfoGraphNode.get_layer(node)
node_type = InfoGraphNode.get_type(node)
if node_layer == GRAPH_LAYER.PHYSICAL \
or node_type == NODE_TYPE.INSTANCE_DISK:
try:
source = self._source(node)
identifier = source
query_tags = {"source": source}
metric_types = self._cached_metrics(identifier, query_tags)
except Exception as ex:
LOG.error('Malformed graph: {}'.format(
InfoGraphNode.get_name(node)))
LOG.error(ex)
elif node_layer == GRAPH_LAYER.VIRTUAL:
source = self._source(node)
stack = self._stack(node)
#LOG.info("SOURCE: {}".format(source))
#LOG.info("STACK: {}".format(stack))
if stack is not None:
identifier = "{}-{}".format(source, stack)
# query_tags = {"source": source, "stack": stack}
query_tags = {"stack_name": stack}
metric_types = self._cached_metrics(identifier, query_tags)
elif node_type == NODE_TYPE.DOCKER_CONTAINER:
source = self._source(node)
docker_id = InfoGraphNode.get_docker_id(node)
if docker_id is not None and source is not None:
identifier = "{}-{}".format(source, docker_id)
query_tags = {"docker_id": docker_id, "source": source}
metric_types = self._cached_metrics(identifier, query_tags)
return metric_types
def _get_metrics(self, node):
"""
Retrieves the metrics for a node based on its type. This is done by
checking if the node is in the NODE_METRICS dictionary and then pulling
out a list of metric heads for that node type. If the metric head
matches the metric retrieved from the host then we attach it.
"""
metrics = []
node_type = InfoGraphNode.get_type(node)
if node_type in NODE_METRICS:
source_metrics = self._source_metrics(node)
for metric in source_metrics:
for metric_start in NODE_METRICS[node_type]:
if metric.startswith(metric_start) \
and not self._exception(node, metric):
if metric.startswith("intel/net/"):
nic_id = self._nic(node)
if nic_id in metric:
metrics.append(metric)
if metric.startswith('intel/libvirt/'):
self._get_nova_uuids(node)
for x in range(0, len(self.vms)):
#LOG.info('Adding {}'.format(metric))
metrics.append(metric)
else:
metrics.append(metric)
return metrics
def _tag_value(self, tag_key, node, metric):
# TODO: fully qualify this with metric name, if metric is this and tag
tag_value = None
if tag_key == "source":
tag_value = self._source(node)
elif tag_key in set(["device_id", "disk", "device_name"]):
tag_value = self._disk(node)
elif tag_key in set(["cpu_id", "cpuID", "core_id"]):
tag_value = self._pu(node, metric)
elif tag_key in set([
"nic_id", "interface", "network_interface", "interface_name",
"hardware_addr"
]):
tag_value = self._nic(node, tag_key)
elif tag_key == "nova_uuid":
tag_value = self._nova_uuid(node)
elif tag_key == "stack_name":
tag_value = self._stack(node)
elif tag_key == "dev_id":
if "intel/use/network" in metric:
tag_value = self._nic(node)
elif "intel/use/disk" in metric:
tag_value = self._disk(node)
elif tag_key == "docker_id":
tag_value = InfoGraphNode.get_docker_id(node)
return tag_value
def get_queries(self, landscape, node, ts_from, ts_to):
"""
Return queries to use for telemetry for the specific node.
:param landscape:
:param node:
:param ts_from:
:param ts_to:
:return:
"""
queries = []
self.landscape = landscape
node_layer = InfoGraphNode.get_layer(node)
# Service Layer metrics are not required
#if node_layer == GRAPH_LAYER.SERVICE:
# return []
for metric in self._get_metrics(node):
try:
query = self._build_query(metric, node, ts_from, ts_to)
queries.append(query)
except Exception as e:
LOG.error('Exception for metric: {}'.format(metric))
return queries
def run(self, workload, service_type="stack", telemetry_system='snap'):
# Extract data from Info Core
service_subgraphs = list()
try:
LOG.debug("Workload: {}".format(workload.get_workload_name()))
landscape_ip = ConfigHelper.get("LANDSCAPE", "host")
landscape_port = ConfigHelper.get("LANDSCAPE", "port")
landscape.set_landscape_server(host=landscape_ip,
port=landscape_port)
sge = SubGraphExtraction(landscape_ip, landscape_port)
res = sge.get_hist_service_nodes(service_type,
workload.get_workload_name())
nodes = [(node[0], InfoGraphNode.get_attributes(node).get('from'),
InfoGraphNode.get_attributes(node).get('to'))
for node in res.nodes(data=True)]
nodes.sort(reverse=True, key=self.node_sort)
#pr = cProfile.Profile()
counter = 0
for node in nodes:
#pr.enable()
node_id = node[0]
from_ts = int(time.time())
# to_ts = int(attrs['to'])
tf = from_ts * -1
subgraph = landscape.get_subgraph(node_id, from_ts, tf)
if len(subgraph.nodes()) > 0:
annotated_subgraph = SubgraphUtilities.graph_telemetry_annotation(
subgraph, node[1], node[2], telemetry_system)
service_subgraphs.append(annotated_subgraph)
#print "cProfile Stats"+node_id
#print "=============="
#pr.print_stats(sort='time')
#print "=============="
#pr.disable()
counter = counter + 1
if counter == SUBGRAPH_LIMIT:
break
except Exception as e:
LOG.error(e)
LOG.error("No topology data has been found for the selected "
"workload.")
import traceback
traceback.print_exc()
exit()
workload.save_results(self.__filter_name__, service_subgraphs)
return service_subgraphs
def _node_is_nic_on_management_net(node, graph, mng_net_name):
node_name = InfoGraphNode.get_name(node)
node_type = InfoGraphNode.get_type(node)
if node_type == InfoGraphNodeType.VIRTUAL_NIC or \
node_type == InfoGraphNodeType.VIRTUAL_NIC_2:
neighs = graph.neighbors(node_name)
for n in neighs:
neighbor = InfoGraphNode.\
get_node(graph, n)
if InfoGraphNode.get_type(neighbor) == \
InfoGraphNodeType.VIRTUAL_NETWORK:
network_name = \
InfoGraphNode.get_attributes(
neighbor)['name']
if network_name == mng_net_name:
return True
return False
def _tags(self, metric, node):
tags = {}
attrs = InfoGraphNode.get_attributes(node)
tag_keys = self._tag_keys(metric, node)
for tag_key in tag_keys:
tag_value = self._tag_value(tag_key, node, metric)
tags[tag_key] = tag_value
return tags
def machine_capacity_usage(annotated_subgraph):
"""
This is a type of fingerprint from the infrastructure perspective
"""
# TODO: Validate graph
categories = list()
categories.append(InfoGraphNodeCategory.COMPUTE)
categories.append(InfoGraphNodeCategory.NETWORK)
# TODO: Add a Volume to the workloads to get HD usage
categories.append(InfoGraphNodeCategory.STORAGE)
# TODO: Get telemetry for Memory
categories.append(InfoGraphNodeCategory.MEMORY)
fingerprint = dict()
counter = dict()
for category in categories:
fingerprint[category] = 0
counter[category] = 0
# calculation of the fingerprint on top of the virtual resources
local_subgraph = annotated_subgraph.copy()
local_subgraph.filter_nodes('layer', "virtual")
local_subgraph.filter_nodes('layer', "service")
local_subgraph.filter_nodes('type', 'machine')
for node in local_subgraph.nodes(data=True):
# if Fingerprint._node_is_nic_on_management_net(
# node, annotated_subgraph, mng_net_name):
# continue
name = InfoGraphNode.get_name(node)
category = InfoGraphNode.get_category(node)
utilization = InfoGraphNode.get_utilization(node)
if 'utilization' in utilization.columns.values:
# LOG.info("NODE: {} - CATEGORY: {}".format(name, category))
mean = utilization['utilization'].mean()
fingerprint[category] += mean
counter[category] += 1
# This is just an average
# TODO: Improve the average
for category in categories:
if counter[category] > 0:
fingerprint[category] = \
fingerprint[category] / counter[category]
return fingerprint
def _pu(self, node, metric):
pu = None
if (InfoGraphNode.get_type(node) == NODE_TYPE.PHYSICAL_PU
or InfoGraphNode.get_type(node) == NODE_TYPE.PHYSICAL_MACHINE):
attrs = InfoGraphNode.get_attributes(node)
# fix attributes from landscaper - fixing
# permanently on the fly if needed
while attrs.get('attributes', None):
attrs = attrs['attributes']
if 'os_index' in attrs:
pu = attrs["os_index"]
# metric prefix 'cpu' on to the front of the cpu number.
if pu and ('intel/proc/schedstat/cpu/' in metric
or 'intel/psutil/cpu/' in metric):
pu = "cpu{}".format(pu)
return pu
def saturation(internal_graph, node, telemetry):
telemetry_data = telemetry.get_data(node)
if 'intel/use/compute/saturation' in telemetry_data:
InfoGraphNode.set_compute_saturation(node,
pandas.DataFrame(telemetry_data['intel/use/compute/saturation']))
if 'intel/use/memory/saturation' in telemetry_data:
InfoGraphNode.set_memory_saturation(node, pandas.DataFrame(telemetry_data['intel/use/memory/saturation']))
if 'intel/use/disk/saturation' in telemetry_data:
InfoGraphNode.set_disk_saturation(node, pandas.DataFrame(telemetry_data['intel/use/disk/saturation']))
if 'intel/use/network/saturation' in telemetry_data:
InfoGraphNode.set_network_saturation(node,
pandas.DataFrame(telemetry_data['intel/use/network/saturation']))
def get_annotated_graph(self,
graph,
ts_from,
ts_to,
utilization=True,
saturation=True):
internal_graph = graph.copy()
i = 0
threads = []
cpu_count = multiprocessing.cpu_count()
no_node_thread = len(internal_graph.nodes()) / (cpu_count)
node_pool = []
node_pools = []
for node in internal_graph.nodes(data=True):
if i < no_node_thread:
node_pool.append(node)
i = i + 1
else:
thread1 = ParallelTelemetryAnnotation(
i, "Thread-{}".format(InfoGraphNode.get_name(node)), i,
node_pool, internal_graph, self.telemetry, ts_to, ts_from)
threads.append(thread1)
node_pools.append(node_pool)
i = 1
node_pool = [node]
if len(node_pool) != 0:
node_pools.append(node_pool)
thread1 = ParallelTelemetryAnnotation(
i, "Thread-{}".format(InfoGraphNode.get_name(node)), i,
node_pool, internal_graph, self.telemetry, ts_to, ts_from)
threads.append(thread1)
[t.start() for t in threads]
[t.join() for t in threads]
for node in internal_graph.nodes(data=True):
if InfoGraphNode.get_type(node) == InfoGraphNodeType.PHYSICAL_PU:
self.utils.annotate_machine_pu_util(internal_graph, node)
elif InfoGraphNode.node_is_disk(node):
self.utils.annotate_machine_disk_util(internal_graph, node)
elif InfoGraphNode.node_is_nic(node):
self.utils.annotate_machine_network_util(internal_graph, node)
return internal_graph
def annotate_machine_disk_util(internal_graph, node):
source = InfoGraphNode.get_attributes(node)['allocation']
machine = InfoGraphNode.get_node(internal_graph, source)
machine_util = InfoGraphNode.get_disk_utilization(machine)
if 'intel/use/disk/utilization' not in machine_util.columns:
disk_metric = 'intel/procfs/disk/utilization_percentage'
disk_util_df = InfoGraphNode.get_disk_utilization(node)
if disk_metric in disk_util_df.columns:
disk_util = disk_util_df[disk_metric]
disk_util = disk_util.fillna(0)
machine_util[InfoGraphNode.get_attributes(node)['name']] = disk_util
InfoGraphNode.set_disk_utilization(machine, machine_util)
else:
LOG.info('Disk util not Found use for node {}'.format(InfoGraphNode.get_name(node)))
else:
LOG.debug('Found use disk for node {}'.format(InfoGraphNode.get_name(node)))
def annotate_machine_network_util(internal_graph, node):
source = InfoGraphNode.get_attributes(node)['allocation']
machine = InfoGraphNode.get_node(internal_graph, source)
machine_util = InfoGraphNode.get_network_utilization(machine)
if 'intel/use/network/utilization' not in machine_util.columns:
net_metric = 'intel/psutil/net/utilization_percentage'
net_util_df = InfoGraphNode.get_network_utilization(node)
if net_metric in net_util_df.columns:
net_util = net_util_df[net_metric]
net_util = net_util.fillna(0)
machine_util[InfoGraphNode.get_attributes(node)['name']] = net_util
InfoGraphNode.set_network_utilization(machine, machine_util)
else:
LOG.info('Net util not Found use for node {}'.format(InfoGraphNode.get_name(node)))
else:
LOG.debug('Found use network for node {}'.format(InfoGraphNode.get_name(node)))
def get_data(self, node):
"""
Return telemetry data for the specified node
:param node: InfoGraph node
:return: pandas.DataFrame
"""
queries = InfoGraphNode.get_queries(node)
ret_val = pandas.DataFrame()
try:
ret_val = self._get_data(queries)
except Exception as ex:
LOG.debug("Exception in user code: \n{} {} {}".format('-' * 60),
traceback.print_exc(file=sys.stdout), '-' * 60)
#ret_val.set_index(keys='timestamp')
if InfoGraphNode.node_is_vm(node):
if not ret_val.empty:
ret_val.columns = tm_utils.clean_vm_telemetry_colnames(
ret_val.columns)
return ret_val
def _get_data(self, node):
# TODO: Create here the object SnapQuery from the string
results = {}
for query_vars in InfoGraphNode.get_queries(node):
query = SnapQuery(self.snap, query_vars['metric'],
query_vars['tags'], query_vars['ts_from'],
query_vars['ts_to'])
res = query.run()
results[query.metric] = res
results_dataframe = self._to_dataframe(results)
return results_dataframe
def _tag_keys(self, metric, node):
tag_keys = []
# always put in instance
tag_keys += ["instance"]
node_type = InfoGraphNode.get_type(node)
if node_type in NODE_TO_METRIC_TAGS:
tag_keys = NODE_TO_METRIC_TAGS[node_type]
return tag_keys
