from steelscript.appfwk.apps.report.models import Report
import steelscript.appfwk.apps.report.modules.tables as tables
from steelscript.appresponse.appfwk.datasources.appresponse import \
AppResponseTable, AppResponseScannerTable
report = Report.create("AppResponse Packets - Search Capture Jobs",
hidden_fields=[
'appresponse_device', 'appresponse_source',
'entire_pcap', 'granularity'
],
field_order=['endtime', 'duration'])
report.add_section()
# Create base table
base = AppResponseTable.create(name='ar_bytes', include_filter=True)
base.add_column('total_bytes',
label='Bytes',
iskey=False,
extractor='sum_traffic.total_bytes')
# Make
table = AppResponseScannerTable.create(name='ars', basetable=base)
table.add_column('name', "Name", datatype='string')
table.add_column('host', "Host", datatype='string')
table.add_column('capture_job', "Capture Job", datatype='string')
table.add_column('bytes', "Bytes")
report.add_widget(tables.TableWidget,
table,
"AppResponse Capture Jobs Found",
from steelscript.appfwk.apps.report.models import Report
import steelscript.appfwk.apps.report.modules.c3 as c3
import steelscript.appfwk.apps.report.modules.tables as tables
from steelscript.appresponse.appfwk.datasources.appresponse import \
AppResponseTable, AppResponseTimeSeriesTable, \
AppResponseTopNTimeSeriesTable, AppResponseLinkTable
topn = 10
report = Report.create("AppResponse SQL Overall")
report.add_section()
# t1 is used to derive the overall metrics over the duration
t1 = AppResponseTable.create('sql-overall', source='sql_summaries')
t1.add_column('db_process',
'Client Process Name',
datatype='string',
iskey=True,
extractor='db.process_name')
t1.add_column('sql_duration',
'Average Transaction Time',
datatype='float',
extractor='avg_sql.duration')
t1.add_column('sql_packets',
'Average SQL Packets',
datatype='float',
extractor='avg_sql.packets')
# t2 is used to derive the time series metrics values over the duration
import steelscript.appfwk.apps.report.modules.c3 as c3
import steelscript.appfwk.apps.report.modules.tables as tables
from steelscript.appresponse.appfwk.datasources.appresponse import \
AppResponseTable
report = Report.create("AppResponse Packets - TCP Errors",
field_order=[
'endtime', 'duration', 'appresponse_device',
'appresponse_source', 'entire_pcap', 'granularity'
])
report.add_section()
# TCP Errors
p = AppResponseTable.create('TCPErrors',
duration='1 min',
granularity='1s',
include_files=True)
p.add_column('error_type',
label='TCP Error Type',
iskey=True,
datatype='string',
extractor='tcp.error_type',
alias='tcp.error_type_name')
p.add_column('errors',
label='TCP Error Count',
datatype='integer',
sortdesc=True,
extractor='sum_tcp.errors')
report.add_widget(c3.BarWidget, p, 'TCP Errors', width=6, height=400)
from steelscript.appfwk.apps.report.models import Report
import steelscript.appfwk.apps.report.modules.c3 as c3
import steelscript.appfwk.apps.report.modules.tables as tables
from steelscript.appresponse.appfwk.datasources.appresponse import \
AppResponseTable, AppResponseTimeSeriesTable, \
AppResponseTopNTimeSeriesTable, AppResponseLinkTable
topn = 10
report = Report.create("AppResponse ASA Overall")
report.add_section()
# t1 is used to derive the overall metrics over the duration
t1 = AppResponseTable.create('applications-overall', source='aggregates')
t1.add_column('app_id', 'App ID', datatype='string', iskey=True,
extractor='app.id')
t1.add_column('app_name', 'App Name', datatype='string',
extractor='app.name')
t1.add_column('total_bytes', 'Average Bytes per Second', datatype='float',
extractor='avg_traffic.total_bytes_ps')
t1.add_column('srv_response_time', 'Average Server Response Time (seconds)',
datatype='float', extractor='avg_tcp.srv_response_time')
t1.add_column('usr_response_time', 'Average User Response Time (seconds)',
datatype='float', extractor='avg_tcp.user_response_time')
# t2 is used to derive the time series metrics values over the duration
t2 = AppResponseTable.create('applications-overall-ts', source='aggregates')
# Add this time key column is the main differentiator between t2 and t1
t2.copy_columns(t1)
from steelscript.appresponse.appfwk.datasources.appresponse import \
AppResponseTable
from steelscript.appfwk.apps.datasource.modules.analysis import \
FocusedAnalysisTable
report = Report.create("AppResponse Packets - Microburst and TCP Errors",
field_order=[
'endtime', 'duration', 'appresponse_device',
'appresponse_source', 'entire_pcap', 'granularity'
])
report.add_section()
# summary microbursts
p = AppResponseTable.create('MicroburstsTime',
duration='1 min',
granularity='1s',
include_files=True)
p.add_column('time',
label='Time',
iskey=True,
datatype='time',
extractor='start_time',
formatter='formatDateTimeMs')
p.add_column('max_microburst_1ms_bytes',
label='uBurst 1ms',
extractor='max_traffic.microburst_1ms_bytes',
units='B')
p.add_column('max_microburst_10ms_bytes',
from steelscript.appfwk.apps.report.models import Report
import steelscript.appfwk.apps.report.modules.c3 as c3
import steelscript.appfwk.apps.report.modules.tables as tables
from steelscript.appresponse.appfwk.datasources.appresponse import \
AppResponseTable, AppResponseTimeSeriesTable, \
AppResponseTopNTimeSeriesTable, AppResponseLinkTable
topn = 10
report = Report.create("AppResponse UC Overall")
report.add_section()
# t1 is used to derive the overall metrics over the duration
t1 = AppResponseTable.create('uc-overall', source='aggregates')
t1.add_column('media_type', 'Media Type ID', datatype='string', iskey=True,
extractor='rtp.media_type')
t1.add_column('media_type_name', 'Media Type Name', datatype='string',
extractor='rtp.media_type_name')
t1.add_column('packets', 'Number of RTP Packets', datatype='integer',
extractor='sum_rtp.packets')
t1.add_column('bytes', 'Number of RTP Bytes',
datatype='integer', extractor='sum_rtp.traffic_bytes')
# t2 is used to derive the time series metrics values over the duration
t2 = AppResponseTable.create('uc-overall-ts', source='aggregates')
# Add this time key column is the main differentiator between t2 and t1
t2.copy_columns(t1)
t2.add_column('start_time', 'Time', datatype='time', iskey=True,
extractor='start_time')
import steelscript.appfwk.apps.report.modules.c3 as c3
import steelscript.appfwk.apps.report.modules.tables as tables
from steelscript.appresponse.appfwk.datasources.appresponse import \
AppResponseTable
report = Report.create("AppResponse Packets - DNS",
field_order=[
'endtime', 'duration', 'appresponse_device',
'appresponse_source', 'entire_pcap', 'granularity'
])
report.add_section()
# DNS Queries Over time
name = 'DNS Queries and Response Time Over Time'
p = AppResponseTable.create(name, include_files=True)
p.add_column('time',
label='Time',
iskey=True,
datatype='time',
extractor='start_time',
formatter='formatDateTimeMs')
p.add_column('dns_count',
label='DNS Query Count',
datatype='integer',
extractor='sum_dns.query.count')
p.add_column('dns_response_time',
label='Avg DNS Response Time (ns)',
units='ms',
extractor='avg_dns.response_time')
#
# This software is licensed under the terms and conditions of the MIT License
# accompanying the software ("License"). This software is distributed "AS IS"
# as set forth in the License.
from steelscript.appfwk.apps.report.models import Report
import steelscript.appfwk.apps.report.modules.yui3 as yui3
from steelscript.appresponse.appfwk.datasources.appresponse import \
AppResponseTable, AppResponseTimeSeriesTable
report = Report.create("AppResponse WTA Time Series")
report.add_section()
t = AppResponseTable.create('wta-base', source='aggregates')
t.add_column('start_time',
'Time',
datatype='time',
iskey=True,
extractor='start_time')
t.add_column('page_family_id',
'Web Page Family ID',
datatype='string',
iskey=True,
extractor='web.page.family.id')
t.add_column('page_family_name',
'Web Page Family Name',
datatype='string',
extractor='web.page.family.name')
t.add_column('pages',
# Copyright (c) 2017 Riverbed Technology, Inc.
#
# This software is licensed under the terms and conditions of the MIT License
# accompanying the software ("License"). This software is distributed "AS IS"
# as set forth in the License.
from steelscript.appfwk.apps.report.models import Report
import steelscript.appfwk.apps.report.modules.c3 as c3
from steelscript.appresponse.appfwk.datasources.appresponse import \
AppResponseTable, AppResponseTimeSeriesTable
report = Report.create("AppResponse DB Sessions TimeSeries")
report.add_section()
t = AppResponseTable.create('db-session-overall', source='dbsession_summaries')
t.add_column('start_time',
'Time',
datatype='time',
iskey=True,
extractor='start_time')
t.add_column('db_instance',
'DB Instance',
datatype='string',
iskey=True,
extractor='db.instance')
t.add_column('active_sessions',
'Concurrent Active DB Sessions',
datatype='float',
extractor='avg_db.active_sessions')
t.add_column('active_time',
# Copyright (c) 2017 Riverbed Technology, Inc.
#
# This software is licensed under the terms and conditions of the MIT License
# accompanying the software ("License"). This software is distributed "AS IS"
# as set forth in the License.
from steelscript.appfwk.apps.report.models import Report
import steelscript.appfwk.apps.report.modules.c3 as c3
from steelscript.appresponse.appfwk.datasources.appresponse import \
AppResponseTable, AppResponseTimeSeriesTable
report = Report.create("AppResponse SQL TimeSeries")
report.add_section()
t = AppResponseTable.create('SQL-overall', source='sql_summaries')
t.add_column('start_time',
'Time',
datatype='time',
iskey=True,
extractor='start_time')
t.add_column('db_process',
'Client Process Name',
datatype='string',
iskey=True,
extractor='db.process_name')
t.add_column('sql_duration',
'Transaction Time',
datatype='float',
extractor='avg_sql.duration')
t.add_column('sql_packets',
from steelscript.appfwk.apps.report.models import Report
import steelscript.appfwk.apps.report.modules.c3 as c3
import steelscript.appfwk.apps.report.modules.tables as tables
from steelscript.appresponse.appfwk.datasources.appresponse import \
AppResponseTable
report = Report.create("AppResponse Packets",
field_order=[
'endtime', 'duration', 'appresponse_device',
'appresponse_source', 'entire_pcap', 'granularity'
])
report.add_section()
p = AppResponseTable.create('network_traffic', include_files=True)
p.add_column('time',
'Time',
datatype='time',
iskey=True,
extractor='start_time')
p.add_column('network_traffic',
'Network Traffic',
datatype='integer',
extractor='sum_traffic.network_bytes')
report.add_widget(c3.TimeSeriesWidget, p, "Network Traffic (Bytes)", width=12)
p = AppResponseTable.create('Traffic by TCP/UDP', include_files=True)
p.add_column('time',
'Time',
datatype='time',
from steelscript.appfwk.apps.report.models import Report
import steelscript.appfwk.apps.report.modules.c3 as c3
import steelscript.appfwk.apps.report.modules.tables as tables
from steelscript.appresponse.appfwk.datasources.appresponse import \
AppResponseTable, AppResponseTimeSeriesTable, \
AppResponseTopNTimeSeriesTable, AppResponseLinkTable
topn = 10
report = Report.create("AppResponse WTA Overall")
report.add_section()
# t1 is used to derive the overall metrics over the duration
t1 = AppResponseTable.create('wta-overall',
source='aggregates',
sort_col_name='pages',
ascending=False)
t1.add_column('page_family_id',
'Web Page Family ID',
datatype='string',
iskey=True,
extractor='web.page.family.id')
t1.add_column('page_family_name',
'Web Page Family Name',
datatype='string',
extractor='web.page.family.name')
t1.add_column('pages',
'Number of Pages Viewed',
datatype='integer',
extractor='sum_web.pages')
t1.add_column('page_bps',
# Copyright (c) 2017 Riverbed Technology, Inc.
#
# This software is licensed under the terms and conditions of the MIT License
# accompanying the software ("License"). This software is distributed "AS IS"
# as set forth in the License.
from steelscript.appfwk.apps.report.models import Report
import steelscript.appfwk.apps.report.modules.c3 as c3
from steelscript.appresponse.appfwk.datasources.appresponse import \
AppResponseTable, AppResponseTimeSeriesTable
report = Report.create("AppResponse ASA Time Series")
report.add_section()
t = AppResponseTable.create('timeseries-base', source='aggregates')
t.add_column('start_time',
'Time',
datatype='time',
iskey=True,
extractor='start_time')
t.add_column('app_id',
'App ID',
datatype='string',
iskey=True,
extractor='app.id')
t.add_column('app_name', 'App Name', datatype='string', extractor='app.name')
t.add_column('srv_response_time',
'Average Server Response Time (seconds)',
datatype='float',
extractor='avg_tcp.srv_response_time')
