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 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)
InfoGraphNode.set_network_utilization(machine, pandas.DataFrame())
def utilization(internal_graph, node, telemetry):
# machine usage
telemetry_data = telemetry.get_data(node)
if 'intel/use/compute/utilization' in telemetry_data:
InfoGraphNode.set_compute_utilization(node,
pandas.DataFrame(telemetry_data['intel/use/compute/utilization'],
columns=['intel/use/compute/utilization']))
# pu usage
if 'intel/procfs/cpu/utilization_percentage' in telemetry_data:
InfoGraphNode.set_compute_utilization(node,
pandas.DataFrame(
telemetry_data['intel/procfs/cpu/utilization_percentage'],
columns=['intel/procfs/cpu/utilization_percentage']))
if 'intel/use/memory/utilization' in telemetry_data:
InfoGraphNode.set_memory_utilization(node, pandas.DataFrame(telemetry_data['intel/use/memory/utilization']))
if 'intel/use/disk/utilization' in telemetry_data:
InfoGraphNode.set_disk_utilization(node, pandas.DataFrame(telemetry_data['intel/use/disk/utilization']))
if 'intel/use/network/utilization' in telemetry_data:
InfoGraphNode.set_network_utilization(node,
pandas.DataFrame(telemetry_data['intel/use/network/utilization']))
# supporting not available /use/ metrics
if 'intel/procfs/meminfo/mem_total' in telemetry_data and 'intel/procfs/meminfo/mem_used' in telemetry_data:
# LOG.info('Found memory utilization procfs')
mem_used = telemetry_data['intel/procfs/meminfo/mem_used'].fillna(0)
mem_total = telemetry_data['intel/procfs/meminfo/mem_total'].fillna(0)
mem_util = mem_used * 100 / mem_total
mem_util.name = 'intel/procfs/memory/utilization_percentage'
InfoGraphNode.set_memory_utilization(node, pandas.DataFrame(mem_util))
if 'intel/procfs/disk/io_time' in telemetry_data:
io_time = telemetry_data['intel/procfs/disk/io_time'].fillna(0)
disk_util = io_time*100/1000
disk_util.name = 'intel/procfs/disk/utilization_percentage'
InfoGraphNode.set_disk_utilization(node, pandas.DataFrame(disk_util))
if 'intel/psutil/net/bytes_recv' in telemetry_data and 'intel/psutil/net/bytes_sent' in telemetry_data:
source=telemetry._source(node)
machine = InfoGraphNode.get_node(internal_graph, source)
nic_speed = InfoGraphNode.get_nic_speed_mbps(machine) * 1000000
net_data = telemetry_data.filter(['timestamp', 'intel/psutil/net/bytes_recv','intel/psutil/net/bytes_sent'], axis=1)
net_data.fillna(0)
net_data['intel/psutil/net/bytes_total'] = net_data['intel/psutil/net/bytes_recv']+net_data['intel/psutil/net/bytes_sent']
net_data_interval = net_data.set_index('timestamp').diff()
net_data_interval['intel/psutil/net/utilization_percentage'] = net_data_interval['intel/psutil/net/bytes_total'] * 100 /nic_speed
net_data_pct = pandas.DataFrame(net_data_interval['intel/psutil/net/utilization_percentage'])
InfoGraphNode.set_network_utilization(node, net_data_pct)
elif 'intel/procfs/iface/bytes_recv' in telemetry_data and 'intel/procfs/iface/bytes_recv' in telemetry_data:
source=telemetry._source(node)
machine = InfoGraphNode.get_node(internal_graph, source)
nic_speed = InfoGraphNode.get_nic_speed_mbps(machine) * 1000000
net_data = telemetry_data.filter(['timestamp', 'intel/procfs/iface/bytes_recv','intel/procfs/iface/bytes_sent'], axis=1)
net_data.fillna(0)
net_data['intel/psutil/net/bytes_total'] = net_data['intel/procfs/iface/bytes_recv']+net_data['intel/procfs/iface/bytes_sent']
net_data_interval = net_data.set_index('timestamp').diff()
net_data_interval['intel/psutil/net/utilization_percentage'] = net_data_interval['intel/psutil/net/bytes_total'] * 100 /nic_speed
net_data_pct = pandas.DataFrame(net_data_interval['intel/psutil/net/utilization_percentage'])
InfoGraphNode.set_network_utilization(node, net_data_pct)
if 'intel/docker/stats/cgroups/cpu_stats/cpu_usage/total' in telemetry_data:
# Container node
#cpu util
cpu_data = telemetry_data.filter(['timestamp', 'intel/docker/stats/cgroups/cpu_stats/cpu_usage/total'], axis=1)
cpu_data_interval = cpu_data.set_index('timestamp').diff()
#util data in nanoseconds
cpu_data_interval['intel/docker/stats/cgroups/cpu_stats/cpu_usage/percentage'] = cpu_data_interval['intel/docker/stats/cgroups/cpu_stats/cpu_usage/total'] / 10000000
cpu_data_pct = pandas.DataFrame(cpu_data_interval['intel/docker/stats/cgroups/cpu_stats/cpu_usage/percentage'])
InfoGraphNode.set_compute_utilization(node, cpu_data_pct)
if "intel/docker/stats/cgroups/memory_stats/usage/usage" in telemetry_data:
#container mem util
source=telemetry._source(node)
machine = InfoGraphNode.get_node(internal_graph, source)
local_mem = int(InfoGraphNode.get_attributes(machine).get("local_memory"))
mem_data = telemetry_data.filter(['timestamp', "intel/docker/stats/cgroups/memory_stats/usage/usage"], axis=1)
mem_data["intel/docker/stats/cgroups/memory_stats/usage/percentage"] = mem_data["intel/docker/stats/cgroups/memory_stats/usage/usage"]/local_mem * 100
mem_data_pct = pandas.DataFrame(mem_data["intel/docker/stats/cgroups/memory_stats/usage/percentage"])
InfoGraphNode.set_memory_utilization(node, mem_data_pct)
if "intel/docker/stats/network/tx_bytes" in telemetry_data:
#container network util
source=telemetry._source(node)
machine = InfoGraphNode.get_node(internal_graph, source)
nic_speed = InfoGraphNode.get_nic_speed_mbps(machine) * 1000000
net_data = telemetry_data.filter(['timestamp', "intel/docker/stats/network/tx_bytes","intel/docker/stats/network/rx_bytes"], axis=1)
net_data.fillna(0)
net_data['intel/docker/stats/network/bytes_total'] = net_data["intel/docker/stats/network/tx_bytes"]+net_data["intel/docker/stats/network/rx_bytes"]
net_data_interval = net_data.set_index('timestamp').diff()
net_data_interval['intel/docker/stats/network/utilization_percentage'] = net_data_interval['intel/docker/stats/network/bytes_total'] * 100 /nic_speed
net_data_pct = pandas.DataFrame(net_data_interval['intel/docker/stats/network/utilization_percentage'])
InfoGraphNode.set_network_utilization(node, net_data_pct)
if "intel/docker/stats/cgroups/blkio_stats/io_time_recursive/value" in telemetry_data:
#container disk util
disk_data = telemetry_data.filter(['timestamp', "intel/docker/stats/cgroups/blkio_stats/io_time_recursive/value"], axis=1)
disk_data_interval = disk_data.set_index('timestamp').diff()
#util data in milliseconds
disk_data_interval["intel/docker/stats/cgroups/blkio_stats/io_time_recursive/percentage"] = \
disk_data_interval["intel/docker/stats/cgroups/blkio_stats/io_time_recursive/value"] / 1000000
disk_data_pct = pandas.DataFrame(disk_data_interval["intel/docker/stats/cgroups/blkio_stats/io_time_recursive/percentage"])
InfoGraphNode.set_disk_utilization(node, disk_data_pct)