#!/usr/bin/env python
'''
----------------------------------------------------------------------------
The contents of this file are subject to the "END USER LICENSE AGREEMENT FOR F5
Software Development Kit for iControl"; you may not use this file except in
compliance with the License. The License is included in the iControl
Software Development Kit.
Software distributed under the License is distributed on an "AS IS"
basis, WITHOUT WARRANTY OF ANY KIND, either express or implied. See
the License for the specific language governing rights and limitations
under the License.
The Original Code is iControl Code and related documentation
distributed by F5.
The Initial Developer of the Original Code is F5 Networks,
Inc. Seattle, WA, USA. Portions created by F5 are Copyright (C) 1996-2004 F5 Networks,
Inc. All Rights Reserved. iControl (TM) is a registered trademark of F5 Networks, Inc.
Alternatively, the contents of this file may be used under the terms
of the GNU General Public License (the "GPL"), in which case the
provisions of GPL are applicable instead of those above. If you wish
to allow use of your version of this file only under the terms of the
GPL and not to allow others to use your version of this file under the
License, indicate your decision by deleting the provisions above and
replace them with the notice and other provisions required by the GPL.
If you do not delete the provisions above, a recipient may use your
version of this file under either the License or the GPL.
----------------------------------------------------------------------------
Required Modules:
numpy
matplotlib
dateutil
pyparsing
suds
bigsuds
csv
time
base64
argparse
getpass
'''
__author__ = 'rahm'
def graph_memory(csvdata):
timestamp, total_mem, os_used, tmm_alloc, tmm_used, swap_used = np.genfromtxt(csvdata, delimiter=',',
skip_header=2, skip_footer=2, unpack=True,
converters= {0: mdates.strpdate2num('%Y-%m-%d %H:%M:%S')})
fig = plt.figure()
plt.plot_date(x=timestamp, y=total_mem, fmt='-')
plt.plot(timestamp, total_mem, 'k-', label="Total Memory")
plt.plot(timestamp, tmm_used, 'r-', label="TMM Used")
plt.plot(timestamp, tmm_alloc, 'c-', label="Tmm Allocated")
plt.plot(timestamp, os_used, 'g-', label="OS Used")
plt.plot(timestamp, swap_used, 'b-', label="OS Used Swap")
plt.legend(title="Context", loc='upper left', shadow=True)
plt.title('Global Memory')
plt.ylabel('GB')
plt.show()
def graph_cpu(csvdata):
timestamp, cpu_util = np.genfromtxt(csvdata, delimiter=',',
skip_header=2, skip_footer=2, unpack=True,
converters= {0: mdates.strpdate2num('%Y-%m-%d %H:%M:%S')})
fig = plt.figure()
plt.plot_date(x=timestamp, y=cpu_util, fmt='-')
plt.plot(timestamp, cpu_util, 'r-', label="CPU")
plt.title('CPU Utilization')
plt.ylabel('%')
plt.show()
def graph_active_connections(csvdata):
timestamp, conns = np.genfromtxt(csvdata, delimiter=',',
skip_header=2, skip_footer=2, unpack=True,
converters= {0: mdates.strpdate2num('%Y-%m-%d %H:%M:%S')})
fig = plt.figure()
plt.plot_date(x=timestamp, y=conns, fmt='-')
plt.plot(timestamp, conns, 'r-', label="conns")
plt.title('Active Connections')
plt.ylabel('conns')
plt.show()
def graph_new_connections(csvdata):
timestamp, client_conns, server_conns = np.genfromtxt(csvdata, delimiter=',',
skip_header=2, skip_footer=2, unpack=True,
converters= {0: mdates.strpdate2num('%Y-%m-%d %H:%M:%S')})
fig = plt.figure()
plt.plot_date(x=timestamp, y=client_conns, fmt='-')
plt.plot(timestamp, client_conns, 'g-', label="client")
plt.plot(timestamp, server_conns, 'r-', label="server")
plt.legend(title="Context", loc='best', shadow=True)
plt.title('New Connections')
plt.ylabel('conns/s')
plt.show()
def graph_throughput(csvdata):
timestamp, client, server, compression = np.genfromtxt(csvdata, delimiter=',',
skip_header=2, skip_footer=2, unpack=True,
converters= {0: mdates.strpdate2num('%Y-%m-%d %H:%M:%S')})
fig = plt.figure()
plt.plot_date(x=timestamp, y=client, fmt='-')
plt.plot(timestamp, client, 'g-', label="client")
plt.plot(timestamp, server, 'r-', label="server")
plt.plot(timestamp, compression, 'c-', label="compression")
plt.legend(title="Context", loc='upper center', ncol=3, shadow=True)
plt.title('Global Throughput')
plt.ylabel('Mb/s')
plt.show()
def graph_http_requests(csvdata):
timestamp, requests = np.genfromtxt(csvdata, delimiter=',',
skip_header=2, skip_footer=2, unpack=True,
converters= {0: mdates.strpdate2num('%Y-%m-%d %H:%M:%S')})
fig = plt.figure()
plt.plot_date(x=timestamp, y=requests, fmt='-')
plt.plot(timestamp, requests, 'r-', label="requests")
plt.title('HTTP Requests')
plt.ylabel('req/s')
plt.show()
def graph_ramcache_util(csvdata):
timestamp, hit_rate, byte_rate, eviction_rate = np.genfromtxt(csvdata, delimiter=',',
skip_header=2, skip_footer=2, unpack=True,
converters= {0: mdates.strpdate2num('%Y-%m-%d %H:%M:%S')})
fig = plt.figure()
plt.plot_date(x=timestamp, y=hit_rate, fmt='-')
plt.plot(timestamp, hit_rate, 'k-', label="Hit Rate")
plt.plot(timestamp, byte_rate, 'c-', label="Byte Rate")
plt.plot(timestamp, eviction_rate, 'r-', label="Evict Rate")
plt.legend(title="Context", loc='best', shadow=True)
plt.title('Ramcache')
plt.ylabel('%')
plt.show()
def graph_active_ssl(csvdata):
timestamp, client_ssl, server_ssl = np.genfromtxt(csvdata, delimiter=',',
skip_header=2, skip_footer=2, unpack=True,
converters= {0: mdates.strpdate2num('%Y-%m-%d %H:%M:%S')})
fig = plt.figure()
plt.plot_date(x=timestamp, y=client_ssl, fmt='-')
plt.plot(timestamp, client_ssl, 'g-', label="client")
plt.plot(timestamp, server_ssl, 'r-', label="server")
plt.legend(title="Context", loc='best', shadow=True)
plt.title('Active SSL Connections')
plt.ylabel('conns')
plt.show()
if __name__ == "__main__":
import bigsuds as pc
import getpass
import argparse
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import numpy as np
import csv, time, base64
parser = argparse.ArgumentParser()
parser.add_argument("-s", "--system", required=True)
parser.add_argument("-u", "--username", required=True)
args = vars(parser.parse_args())
print "%s, enter your " % args['username'],
upass = getpass.getpass()
b = pc.BIGIP(args['system'], args['username'], upass)
stats = b.System.Statistics
graphs = stats.get_performance_graph_list()
graph_obj_name = []
count = 1
print "\n\nGraph Options. Not all options supported at this time, please select only 1, 2, 3, 4, 5, 7, 8, or 12.\n\n"
for x in graphs:
graph_obj_name.append(x['graph_name'])
print "%d> %s, %s" % (count, x['graph_description'], x['graph_name'])
count +=1
num_select = int(raw_input("\n\nPlease select the number for the desired graph data: "))
print "\n\n"
graphstats = stats.get_performance_graph_csv_statistics(
[{'object_name': graph_obj_name[num_select - 1],
'start_time': 0,
'end_time': 0,
'interval': 0,
'maximum_rows': 0}])
statsFile = "%s_rawStats.csv" % graph_obj_name[num_select-1]
f = open(statsFile, "w")
f.write(base64.b64decode(graphstats[0]['statistic_data']))
f.close()
outputFile = "%s_modStats.csv" % graph_obj_name[num_select-1]
with open(statsFile) as infile, open(outputFile, "w") as outfile:
r = csv.reader(infile)
w = csv.writer(outfile)
w.writerow(next(r))
for row in r:
fl = float(row[0])
row[0] = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(fl))
w.writerow(row)
if num_select == 1:
graph_memory(outputFile)
elif num_select == 2:
graph_cpu(outputFile)
elif num_select == 3:
graph_active_connections(outputFile)
elif num_select == 4:
graph_new_connections(outputFile)
elif num_select == 5:
graph_throughput(outputFile)
elif num_select == 7:
graph_http_requests(outputFile)
elif num_select == 8:
graph_ramcache_util(outputFile)
elif num_select == 12:
graph_active_ssl(outputFile)
else:
print "graph function not yet defined, please select 1, 2, 3, 4, 5, 7, 8, or 12."
