SlideShare ist ein Scribd-Unternehmen logo
1 von 34
Using Splunk with SAP:
Planning for Performance
             and Capacity




      Shaun Butler and Luke Harris
About Corporate Express
Supplier of business essentials, established in 1995
Revenue $1.16 billion in 2009
E-Commerce sales currently account for 80% of all orders
Over 2300 staff in over 40 locations across Australia and New Zealand
Listed on the ASX with majority shareholder Staples Inc

                            Our mission:
“To provide a single source supply solution to make it easier and more
          cost-effective for our customers to do business.”

                                   2
About Shaun Butler
Senior Technology Specialist (Infrastructure Services)
RHCE, EMCPA
 Senior authority for planning, design, implementation and support in
relation to Tier One Infrastructure (including AIX, System P, Linux,
Oracle and Enterprise Storage)
Infrastructure Services is responsible for core infrastructure
components – datacentre, network, servers, storage, virtualisation,
monitoring, DNS/DHCP, email

                                 3
About Luke Harris
Senior Systems Engineer (Infrastructure Services)
Linux SOE Specialist, RHCE
EMC Storage Administrator
Splunk, Nagios, Cacti, and DNS Administrator
SplunkForNagios developer:
   http://www.splunkbase.com/apps/All/4.x/Add-On/app:SplunkForNagios




                                    4
Splunk At CE: Data Sources



                            Logfiles   Configs    Messages    Traps        Metrics   Scripts   Changes      Tickets
                                                              Alerts



Windows              Linux/Unix                  Virtualization             Applications            Cisco                      Storage
• Syslog (Snare)     •   Syslog                  • Hypervisor (ESX)         • Web logs              •    Firewalls, IPS, ACE   • EMC Symmetrix
• Event logs         •   DNS, DHCP               • VirtualCenter            • SAP                   •    Routers, Switches
• Active Directory   •   Nagios                                             • webMethods            •    Proxy, WAAS
• Altiris            •   Postfix                                            • netXpress             •    VPN, netflow




                                                                       5
Splunk At Corporate Express: Deployment
                  1 Production server (IBM Blade)
                  1 non-production server (VM)
                  Operating System: RHEL 5.5 64-bit
Infrastructure
                  Syslog – Linux, AIX, Windows (via Snare), ESX, Cisco
                     Switches, Routers, Firewalls, Load Balancers, WAAS, VPN
 Data Inputs        SNMP – Cisco IPS
                    rsync – SAP, webMethods, Nagios, Proxy, Apache, EMC
                    CIFS – Altiris
                    wget – netflow (StatSeeker)

                                   6
SAP at Corporate Express
    nXtgen Project – Business transformation and ERP replacement
    SAP applications implemented (5 out of 6)
   ERP Central Component (ECC)             Master Data Management (MDM)
   Customer Relationship Management (CRM)  Process Integration (PI)
   Business Intelligence (BI)              Portal
New Zealand go live April 2010
Australia go live 2011



                                    7
Splunk’s Value Proposition in a SAP World


 Powerful Trending + Data Accessibility + Data Augmentation
                             =
                  Operational Intelligence




                              8
SAP Data Sources
ECC, CRM, BI – Data retrieved from:
         ST03 - SAP Workload Monitor
         SM04 – SAP User List
         SM04/ST03 transactions are periodically called and output dumped into
    text files
MDM – Application logs
File replication/rsync




                                       9
SAP Use Cases At CE
Application Performance
Capacity/usage
Network analysis




                          10
SAP Use Case 1: Application Performance
ABAP SAP Applications (e.g. ECC, CRM, BI)
SAP Master Data Management (MDM)




                               11
Application Performance: Summary Dialog
           Step Response Time




                   12
Application Performance: Detailed Dialog Step
               Response Time




                      13
Application Performance: Detailed Dialog Step
    Response Time (Long Term Trending)




                      14
Application Performance: Checking Times




                   15
Application Performance: MDM Import Time
From This:
<Trace ts="2010/07/30 07:02:43.821 GMT" tid="1029" entry-no="18583">[MDS=syd1sap08 Repository=MDP ClientSystem=Code_Template
Port=Masterpack_Portal]:   Chunk size/parallel[50000/40]: Import Task Started.</Trace>
               <Timer ts="2010/07/30 07:02:47.426 GMT" tid="1029" entry-no="18584" name="GetInitializationInfoAllLanguages"
total="3.604439"/>
               <Timer ts="2010/07/30 07:02:47.707 GMT" tid="1029" entry-no="18585" name="Add User Dimensions" total="0.000006"/>
               <Timer ts="2010/07/30 07:02:48.199 GMT" tid="1029" entry-no="18586" name="Regular Table Load" total="0.492183"/>
               <Timer ts="2010/07/30 07:02:48.200 GMT" tid="1029" entry-no="18587" name="data Table Load " total="0.000095"/>


                                                ---*snip 30 lines*---
<Trace ts="2010/07/30 07:03:05.515 GMT" tid="1543" entry-no="18620">Import action:<LF/>--Skip: 0<LF/>--Create: 0<LF/>--Updated
(NULL fields only): 0<LF/>--Updated (all mapped fields): 36<LF/>--Replace: 0<LF/>--Delete [destination]: 0<LF/>--Value Exceptions:
0<LF/>--Import Exceptions: 0</Trace>
                <Trace ts="2010/07/30 07:03:05.516 GMT" tid="1543" entry-no="18621">xImporter: Total chunk import time:
77000.000000000 milli-seconds.</Trace>
                <Trace ts="2010/07/30 07:03:07.511 GMT" tid="1543" entry-no="18622">xImporter: : Start -&gt; End: 1083000.000000000
milli-seconds.</Trace>
<?xml version="1.0" encoding="utf-8"?>
<?xml-stylesheet type="text/xsl" href="MDM_Log.xsl"?>
                <Trace ts="2010/07/30 07:03:08.913 GMT" tid="1029" entry-no="18623">[MDS=syd1sap08 Repository=MDP
ClientSystem=Code_Template Port=Masterpack_Portal]:    Chunk size/parallel[50000/40]: Import Task Finished.</Trace>
        </Open>
</MDM_Log>




                                                                  16
Application Performance: MDM Import Time
To This:




                   17
SAP Use Case 2: Throughput/Capacity
ABAP SAP Applications (e.g. ECC, CRM, BI)
   Dialog steps executed over time
   System activity expressed in SAPS
   Concurrent Users
SAP Master Data Management (MDM)
   Transaction throughput – Import/syndication




                                        18
Dialog Steps Executed Over Time
         (Business Day)




               19
Dialog Steps by Task Type




            20
Dialog Steps Since Go Live




            21
SAP Throughput as Represented by SAPS




                  22
Active vs. Inactive Concurrent Users




                 23
Active Users by Transaction Type




               24
Active Users By Location




           25
SAP Use Case 3: Network Analysis
WAN bandwidth consumption split by SAP application
SAP vs. Non-SAP WAN bandwidth consumption
Average WAN bandwidth footprint per SAP user




                             26
WAN Bandwidth Consumption
    by SAP Application




            27
WAN Bandwidth Consumption –
      SAP vs. Non-SAP




             28
Average WAN Footprint Per User




              29
Bringing It All Together...




             30
Bringing It Even More Together (SplunkForNagios)




                       31
Anticipated Challenges
Have a clear idea of what you are trying to achieve
Get your Basis/SAP administrator on board!




                                32
The Future
SAP Enterprise Portal
Auditing
Investigate implementing ST03/SM04 data output into database
and index from there




                              33
Questions?


    34

Weitere ähnliche Inhalte

Was ist angesagt?

EDBT 2013 - Near Realtime Analytics with IBM DB2 Analytics Accelerator
EDBT 2013 - Near Realtime Analytics with IBM DB2 Analytics AcceleratorEDBT 2013 - Near Realtime Analytics with IBM DB2 Analytics Accelerator
EDBT 2013 - Near Realtime Analytics with IBM DB2 Analytics AcceleratorDaniel Martin
 
SQL Server Reporting Services Disaster Recovery Webinar
SQL Server Reporting Services Disaster Recovery WebinarSQL Server Reporting Services Disaster Recovery Webinar
SQL Server Reporting Services Disaster Recovery WebinarDenny Lee
 
CCI2017 - Considerations for Migrating Databases to Azure - Gianluca Sartori
CCI2017 - Considerations for Migrating Databases to Azure - Gianluca SartoriCCI2017 - Considerations for Migrating Databases to Azure - Gianluca Sartori
CCI2017 - Considerations for Migrating Databases to Azure - Gianluca Sartoriwalk2talk srl
 
Databus: LinkedIn's Change Data Capture Pipeline SOCC 2012
Databus: LinkedIn's Change Data Capture Pipeline SOCC 2012Databus: LinkedIn's Change Data Capture Pipeline SOCC 2012
Databus: LinkedIn's Change Data Capture Pipeline SOCC 2012Shirshanka Das
 
Microsoft SQL server 2017 Level 300 technical deck
Microsoft SQL server 2017 Level 300 technical deckMicrosoft SQL server 2017 Level 300 technical deck
Microsoft SQL server 2017 Level 300 technical deckGeorge Walters
 
Feb 2013 HUG: A Visual Workbench for Big Data Analytics on Hadoop
Feb 2013 HUG: A Visual Workbench for Big Data Analytics on HadoopFeb 2013 HUG: A Visual Workbench for Big Data Analytics on Hadoop
Feb 2013 HUG: A Visual Workbench for Big Data Analytics on HadoopYahoo Developer Network
 
IBM World of Watson 2016 - DB2 Analytics Accelerator on Cloud
IBM World of Watson 2016 - DB2 Analytics Accelerator on CloudIBM World of Watson 2016 - DB2 Analytics Accelerator on Cloud
IBM World of Watson 2016 - DB2 Analytics Accelerator on CloudDaniel Martin
 
How Experian increased insights with Hadoop
How Experian increased insights with HadoopHow Experian increased insights with Hadoop
How Experian increased insights with HadoopPrecisely
 
Virtual Study Beta Exam 71-663 Exchange 2010 Designing And Deploying Messagin...
Virtual Study Beta Exam 71-663 Exchange 2010 Designing And Deploying Messagin...Virtual Study Beta Exam 71-663 Exchange 2010 Designing And Deploying Messagin...
Virtual Study Beta Exam 71-663 Exchange 2010 Designing And Deploying Messagin...Tobias Koprowski
 
Introduction to Databus
Introduction to DatabusIntroduction to Databus
Introduction to DatabusAmy W. Tang
 
Preventative Maintenance of Robots in Automotive Industry
Preventative Maintenance of Robots in Automotive IndustryPreventative Maintenance of Robots in Automotive Industry
Preventative Maintenance of Robots in Automotive IndustryDataWorks Summit/Hadoop Summit
 
Avanttic tech dates - de la monitorización a la 'observabilidad'
Avanttic tech dates - de la monitorización a la 'observabilidad'Avanttic tech dates - de la monitorización a la 'observabilidad'
Avanttic tech dates - de la monitorización a la 'observabilidad'avanttic Consultoría Tecnológica
 
Modernization sql server 2016
Modernization   sql server 2016Modernization   sql server 2016
Modernization sql server 2016Kiki Noviandi
 
Exadata x3 workshop
Exadata x3 workshopExadata x3 workshop
Exadata x3 workshopFran Navarro
 
Customer overview oracle solaris cluster, enterprise edition
Customer overview oracle solaris cluster, enterprise editionCustomer overview oracle solaris cluster, enterprise edition
Customer overview oracle solaris cluster, enterprise editionsolarisyougood
 
Capital One's Next Generation Decision in less than 2 ms
Capital One's Next Generation Decision in less than 2 msCapital One's Next Generation Decision in less than 2 ms
Capital One's Next Generation Decision in less than 2 msApache Apex
 
Powering Interactive BI Analytics with Presto and Delta Lake
Powering Interactive BI Analytics with Presto and Delta LakePowering Interactive BI Analytics with Presto and Delta Lake
Powering Interactive BI Analytics with Presto and Delta LakeDatabricks
 
[Pulsar summit na 21] Change Data Capture To Data Lakes Using Apache Pulsar/Hudi
[Pulsar summit na 21] Change Data Capture To Data Lakes Using Apache Pulsar/Hudi[Pulsar summit na 21] Change Data Capture To Data Lakes Using Apache Pulsar/Hudi
[Pulsar summit na 21] Change Data Capture To Data Lakes Using Apache Pulsar/HudiVinoth Chandar
 
Denver Big Data Analytics Day
Denver Big Data Analytics DayDenver Big Data Analytics Day
Denver Big Data Analytics DayZivaro Inc
 
Spark as part of a Hybrid RDBMS Architecture-John Leach Cofounder Splice Machine
Spark as part of a Hybrid RDBMS Architecture-John Leach Cofounder Splice MachineSpark as part of a Hybrid RDBMS Architecture-John Leach Cofounder Splice Machine
Spark as part of a Hybrid RDBMS Architecture-John Leach Cofounder Splice MachineData Con LA
 

Was ist angesagt? (20)

EDBT 2013 - Near Realtime Analytics with IBM DB2 Analytics Accelerator
EDBT 2013 - Near Realtime Analytics with IBM DB2 Analytics AcceleratorEDBT 2013 - Near Realtime Analytics with IBM DB2 Analytics Accelerator
EDBT 2013 - Near Realtime Analytics with IBM DB2 Analytics Accelerator
 
SQL Server Reporting Services Disaster Recovery Webinar
SQL Server Reporting Services Disaster Recovery WebinarSQL Server Reporting Services Disaster Recovery Webinar
SQL Server Reporting Services Disaster Recovery Webinar
 
CCI2017 - Considerations for Migrating Databases to Azure - Gianluca Sartori
CCI2017 - Considerations for Migrating Databases to Azure - Gianluca SartoriCCI2017 - Considerations for Migrating Databases to Azure - Gianluca Sartori
CCI2017 - Considerations for Migrating Databases to Azure - Gianluca Sartori
 
Databus: LinkedIn's Change Data Capture Pipeline SOCC 2012
Databus: LinkedIn's Change Data Capture Pipeline SOCC 2012Databus: LinkedIn's Change Data Capture Pipeline SOCC 2012
Databus: LinkedIn's Change Data Capture Pipeline SOCC 2012
 
Microsoft SQL server 2017 Level 300 technical deck
Microsoft SQL server 2017 Level 300 technical deckMicrosoft SQL server 2017 Level 300 technical deck
Microsoft SQL server 2017 Level 300 technical deck
 
Feb 2013 HUG: A Visual Workbench for Big Data Analytics on Hadoop
Feb 2013 HUG: A Visual Workbench for Big Data Analytics on HadoopFeb 2013 HUG: A Visual Workbench for Big Data Analytics on Hadoop
Feb 2013 HUG: A Visual Workbench for Big Data Analytics on Hadoop
 
IBM World of Watson 2016 - DB2 Analytics Accelerator on Cloud
IBM World of Watson 2016 - DB2 Analytics Accelerator on CloudIBM World of Watson 2016 - DB2 Analytics Accelerator on Cloud
IBM World of Watson 2016 - DB2 Analytics Accelerator on Cloud
 
How Experian increased insights with Hadoop
How Experian increased insights with HadoopHow Experian increased insights with Hadoop
How Experian increased insights with Hadoop
 
Virtual Study Beta Exam 71-663 Exchange 2010 Designing And Deploying Messagin...
Virtual Study Beta Exam 71-663 Exchange 2010 Designing And Deploying Messagin...Virtual Study Beta Exam 71-663 Exchange 2010 Designing And Deploying Messagin...
Virtual Study Beta Exam 71-663 Exchange 2010 Designing And Deploying Messagin...
 
Introduction to Databus
Introduction to DatabusIntroduction to Databus
Introduction to Databus
 
Preventative Maintenance of Robots in Automotive Industry
Preventative Maintenance of Robots in Automotive IndustryPreventative Maintenance of Robots in Automotive Industry
Preventative Maintenance of Robots in Automotive Industry
 
Avanttic tech dates - de la monitorización a la 'observabilidad'
Avanttic tech dates - de la monitorización a la 'observabilidad'Avanttic tech dates - de la monitorización a la 'observabilidad'
Avanttic tech dates - de la monitorización a la 'observabilidad'
 
Modernization sql server 2016
Modernization   sql server 2016Modernization   sql server 2016
Modernization sql server 2016
 
Exadata x3 workshop
Exadata x3 workshopExadata x3 workshop
Exadata x3 workshop
 
Customer overview oracle solaris cluster, enterprise edition
Customer overview oracle solaris cluster, enterprise editionCustomer overview oracle solaris cluster, enterprise edition
Customer overview oracle solaris cluster, enterprise edition
 
Capital One's Next Generation Decision in less than 2 ms
Capital One's Next Generation Decision in less than 2 msCapital One's Next Generation Decision in less than 2 ms
Capital One's Next Generation Decision in less than 2 ms
 
Powering Interactive BI Analytics with Presto and Delta Lake
Powering Interactive BI Analytics with Presto and Delta LakePowering Interactive BI Analytics with Presto and Delta Lake
Powering Interactive BI Analytics with Presto and Delta Lake
 
[Pulsar summit na 21] Change Data Capture To Data Lakes Using Apache Pulsar/Hudi
[Pulsar summit na 21] Change Data Capture To Data Lakes Using Apache Pulsar/Hudi[Pulsar summit na 21] Change Data Capture To Data Lakes Using Apache Pulsar/Hudi
[Pulsar summit na 21] Change Data Capture To Data Lakes Using Apache Pulsar/Hudi
 
Denver Big Data Analytics Day
Denver Big Data Analytics DayDenver Big Data Analytics Day
Denver Big Data Analytics Day
 
Spark as part of a Hybrid RDBMS Architecture-John Leach Cofounder Splice Machine
Spark as part of a Hybrid RDBMS Architecture-John Leach Cofounder Splice MachineSpark as part of a Hybrid RDBMS Architecture-John Leach Cofounder Splice Machine
Spark as part of a Hybrid RDBMS Architecture-John Leach Cofounder Splice Machine
 

Ähnlich wie Splunk Conf2010: Corporate Express presents Splunk with SAP

Best practices and lessons learnt from Running Apache NiFi at Renault
Best practices and lessons learnt from Running Apache NiFi at RenaultBest practices and lessons learnt from Running Apache NiFi at Renault
Best practices and lessons learnt from Running Apache NiFi at RenaultDataWorks Summit
 
PLNOG 8: Kazimierz Jantas - Innowacyjne rozwiązania dla IT
PLNOG 8: Kazimierz Jantas - Innowacyjne rozwiązania dla IT PLNOG 8: Kazimierz Jantas - Innowacyjne rozwiązania dla IT
PLNOG 8: Kazimierz Jantas - Innowacyjne rozwiązania dla IT PROIDEA
 
Scale Your Load Balancer from 0 to 1 million TPS on Azure
Scale Your Load Balancer from 0 to 1 million TPS on AzureScale Your Load Balancer from 0 to 1 million TPS on Azure
Scale Your Load Balancer from 0 to 1 million TPS on AzureAvi Networks
 
Spark Streaming the Industrial IoT
Spark Streaming the Industrial IoTSpark Streaming the Industrial IoT
Spark Streaming the Industrial IoTJim Haughwout
 
Smack Stack and Beyond—Building Fast Data Pipelines with Jorg Schad
Smack Stack and Beyond—Building Fast Data Pipelines with Jorg SchadSmack Stack and Beyond—Building Fast Data Pipelines with Jorg Schad
Smack Stack and Beyond—Building Fast Data Pipelines with Jorg SchadSpark Summit
 
Splunk App for Stream
Splunk App for StreamSplunk App for Stream
Splunk App for StreamSplunk
 
SnapLogic- iPaaS (Elastic Integration Cloud and Data Integration)
SnapLogic- iPaaS (Elastic Integration Cloud and Data Integration) SnapLogic- iPaaS (Elastic Integration Cloud and Data Integration)
SnapLogic- iPaaS (Elastic Integration Cloud and Data Integration) Surendar S
 
PayPal datalake journey | teradata - edge of next | san diego | 2017 october ...
PayPal datalake journey | teradata - edge of next | san diego | 2017 october ...PayPal datalake journey | teradata - edge of next | san diego | 2017 october ...
PayPal datalake journey | teradata - edge of next | san diego | 2017 october ...Deepak Chandramouli
 
Sybase Global Infrastructure
Sybase Global InfrastructureSybase Global Infrastructure
Sybase Global InfrastructureRobert Mobley
 
Nagios Conference 2007 | Nagios in very large Environments by Werner Neunteufl
Nagios Conference 2007 | Nagios in very large Environments by Werner NeunteuflNagios Conference 2007 | Nagios in very large Environments by Werner Neunteufl
Nagios Conference 2007 | Nagios in very large Environments by Werner NeunteuflNETWAYS
 
Io t world_2016_iot_smart_gateways_moe
Io t world_2016_iot_smart_gateways_moeIo t world_2016_iot_smart_gateways_moe
Io t world_2016_iot_smart_gateways_moeShawn Moe
 
Pivotal Real Time Data Stream Analytics
Pivotal Real Time Data Stream AnalyticsPivotal Real Time Data Stream Analytics
Pivotal Real Time Data Stream Analyticskgshukla
 
A Big Data Lake Based on Spark for BBVA Bank-(Oscar Mendez, STRATIO)
A Big Data Lake Based on Spark for BBVA Bank-(Oscar Mendez, STRATIO)A Big Data Lake Based on Spark for BBVA Bank-(Oscar Mendez, STRATIO)
A Big Data Lake Based on Spark for BBVA Bank-(Oscar Mendez, STRATIO)Spark Summit
 
DEVNET-1166 Open SDN Controller APIs
DEVNET-1166	Open SDN Controller APIsDEVNET-1166	Open SDN Controller APIs
DEVNET-1166 Open SDN Controller APIsCisco DevNet
 
Crypt tech technical-presales
Crypt tech technical-presalesCrypt tech technical-presales
Crypt tech technical-presalesMustafa Kuğu
 
Attacking SAP Mobile
Attacking SAP MobileAttacking SAP Mobile
Attacking SAP MobileERPScan
 
Lenovo Servers and Microsoft Azure: the future of the stack
Lenovo Servers and Microsoft Azure: the future of the stackLenovo Servers and Microsoft Azure: the future of the stack
Lenovo Servers and Microsoft Azure: the future of the stackLenovo Data Center
 

Ähnlich wie Splunk Conf2010: Corporate Express presents Splunk with SAP (20)

Best practices and lessons learnt from Running Apache NiFi at Renault
Best practices and lessons learnt from Running Apache NiFi at RenaultBest practices and lessons learnt from Running Apache NiFi at Renault
Best practices and lessons learnt from Running Apache NiFi at Renault
 
PLNOG 8: Kazimierz Jantas - Innowacyjne rozwiązania dla IT
PLNOG 8: Kazimierz Jantas - Innowacyjne rozwiązania dla IT PLNOG 8: Kazimierz Jantas - Innowacyjne rozwiązania dla IT
PLNOG 8: Kazimierz Jantas - Innowacyjne rozwiązania dla IT
 
Scale Your Load Balancer from 0 to 1 million TPS on Azure
Scale Your Load Balancer from 0 to 1 million TPS on AzureScale Your Load Balancer from 0 to 1 million TPS on Azure
Scale Your Load Balancer from 0 to 1 million TPS on Azure
 
Spark Streaming the Industrial IoT
Spark Streaming the Industrial IoTSpark Streaming the Industrial IoT
Spark Streaming the Industrial IoT
 
Smack Stack and Beyond—Building Fast Data Pipelines with Jorg Schad
Smack Stack and Beyond—Building Fast Data Pipelines with Jorg SchadSmack Stack and Beyond—Building Fast Data Pipelines with Jorg Schad
Smack Stack and Beyond—Building Fast Data Pipelines with Jorg Schad
 
Splunk App for Stream
Splunk App for StreamSplunk App for Stream
Splunk App for Stream
 
SnapLogic- iPaaS (Elastic Integration Cloud and Data Integration)
SnapLogic- iPaaS (Elastic Integration Cloud and Data Integration) SnapLogic- iPaaS (Elastic Integration Cloud and Data Integration)
SnapLogic- iPaaS (Elastic Integration Cloud and Data Integration)
 
PayPal datalake journey | teradata - edge of next | san diego | 2017 october ...
PayPal datalake journey | teradata - edge of next | san diego | 2017 october ...PayPal datalake journey | teradata - edge of next | san diego | 2017 october ...
PayPal datalake journey | teradata - edge of next | san diego | 2017 october ...
 
Sybase Global Infrastructure
Sybase Global InfrastructureSybase Global Infrastructure
Sybase Global Infrastructure
 
Nagios Conference 2007 | Nagios in very large Environments by Werner Neunteufl
Nagios Conference 2007 | Nagios in very large Environments by Werner NeunteuflNagios Conference 2007 | Nagios in very large Environments by Werner Neunteufl
Nagios Conference 2007 | Nagios in very large Environments by Werner Neunteufl
 
Io t world_2016_iot_smart_gateways_moe
Io t world_2016_iot_smart_gateways_moeIo t world_2016_iot_smart_gateways_moe
Io t world_2016_iot_smart_gateways_moe
 
Javantura v3 - Real-time BigData ingestion and querying of aggregated data – ...
Javantura v3 - Real-time BigData ingestion and querying of aggregated data – ...Javantura v3 - Real-time BigData ingestion and querying of aggregated data – ...
Javantura v3 - Real-time BigData ingestion and querying of aggregated data – ...
 
Pivotal Real Time Data Stream Analytics
Pivotal Real Time Data Stream AnalyticsPivotal Real Time Data Stream Analytics
Pivotal Real Time Data Stream Analytics
 
A Big Data Lake Based on Spark for BBVA Bank-(Oscar Mendez, STRATIO)
A Big Data Lake Based on Spark for BBVA Bank-(Oscar Mendez, STRATIO)A Big Data Lake Based on Spark for BBVA Bank-(Oscar Mendez, STRATIO)
A Big Data Lake Based on Spark for BBVA Bank-(Oscar Mendez, STRATIO)
 
DEVNET-1166 Open SDN Controller APIs
DEVNET-1166	Open SDN Controller APIsDEVNET-1166	Open SDN Controller APIs
DEVNET-1166 Open SDN Controller APIs
 
The CDO Agenda: how data architecture can help?
The CDO Agenda: how data architecture can help?The CDO Agenda: how data architecture can help?
The CDO Agenda: how data architecture can help?
 
Dev Ops Training
Dev Ops TrainingDev Ops Training
Dev Ops Training
 
Crypt tech technical-presales
Crypt tech technical-presalesCrypt tech technical-presales
Crypt tech technical-presales
 
Attacking SAP Mobile
Attacking SAP MobileAttacking SAP Mobile
Attacking SAP Mobile
 
Lenovo Servers and Microsoft Azure: the future of the stack
Lenovo Servers and Microsoft Azure: the future of the stackLenovo Servers and Microsoft Azure: the future of the stack
Lenovo Servers and Microsoft Azure: the future of the stack
 

Mehr von Splunk

.conf Go 2023 - Data analysis as a routine
.conf Go 2023 - Data analysis as a routine.conf Go 2023 - Data analysis as a routine
.conf Go 2023 - Data analysis as a routineSplunk
 
.conf Go 2023 - How KPN drives Customer Satisfaction on IPTV
.conf Go 2023 - How KPN drives Customer Satisfaction on IPTV.conf Go 2023 - How KPN drives Customer Satisfaction on IPTV
.conf Go 2023 - How KPN drives Customer Satisfaction on IPTVSplunk
 
.conf Go 2023 - Navegando la normativa SOX (Telefónica)
.conf Go 2023 - Navegando la normativa SOX (Telefónica).conf Go 2023 - Navegando la normativa SOX (Telefónica)
.conf Go 2023 - Navegando la normativa SOX (Telefónica)Splunk
 
.conf Go 2023 - Raiffeisen Bank International
.conf Go 2023 - Raiffeisen Bank International.conf Go 2023 - Raiffeisen Bank International
.conf Go 2023 - Raiffeisen Bank InternationalSplunk
 
.conf Go 2023 - På liv og død Om sikkerhetsarbeid i Norsk helsenett
.conf Go 2023 - På liv og død Om sikkerhetsarbeid i Norsk helsenett .conf Go 2023 - På liv og død Om sikkerhetsarbeid i Norsk helsenett
.conf Go 2023 - På liv og død Om sikkerhetsarbeid i Norsk helsenett Splunk
 
.conf Go 2023 - Many roads lead to Rome - this was our journey (Julius Bär)
.conf Go 2023 - Many roads lead to Rome - this was our journey (Julius Bär).conf Go 2023 - Many roads lead to Rome - this was our journey (Julius Bär)
.conf Go 2023 - Many roads lead to Rome - this was our journey (Julius Bär)Splunk
 
.conf Go 2023 - Das passende Rezept für die digitale (Security) Revolution zu...
.conf Go 2023 - Das passende Rezept für die digitale (Security) Revolution zu....conf Go 2023 - Das passende Rezept für die digitale (Security) Revolution zu...
.conf Go 2023 - Das passende Rezept für die digitale (Security) Revolution zu...Splunk
 
.conf go 2023 - Cyber Resilienz – Herausforderungen und Ansatz für Energiever...
.conf go 2023 - Cyber Resilienz – Herausforderungen und Ansatz für Energiever....conf go 2023 - Cyber Resilienz – Herausforderungen und Ansatz für Energiever...
.conf go 2023 - Cyber Resilienz – Herausforderungen und Ansatz für Energiever...Splunk
 
.conf go 2023 - De NOC a CSIRT (Cellnex)
.conf go 2023 - De NOC a CSIRT (Cellnex).conf go 2023 - De NOC a CSIRT (Cellnex)
.conf go 2023 - De NOC a CSIRT (Cellnex)Splunk
 
conf go 2023 - El camino hacia la ciberseguridad (ABANCA)
conf go 2023 - El camino hacia la ciberseguridad (ABANCA)conf go 2023 - El camino hacia la ciberseguridad (ABANCA)
conf go 2023 - El camino hacia la ciberseguridad (ABANCA)Splunk
 
Splunk - BMW connects business and IT with data driven operations SRE and O11y
Splunk - BMW connects business and IT with data driven operations SRE and O11ySplunk - BMW connects business and IT with data driven operations SRE and O11y
Splunk - BMW connects business and IT with data driven operations SRE and O11ySplunk
 
Splunk x Freenet - .conf Go Köln
Splunk x Freenet - .conf Go KölnSplunk x Freenet - .conf Go Köln
Splunk x Freenet - .conf Go KölnSplunk
 
Splunk Security Session - .conf Go Köln
Splunk Security Session - .conf Go KölnSplunk Security Session - .conf Go Köln
Splunk Security Session - .conf Go KölnSplunk
 
Data foundations building success, at city scale – Imperial College London
 Data foundations building success, at city scale – Imperial College London Data foundations building success, at city scale – Imperial College London
Data foundations building success, at city scale – Imperial College LondonSplunk
 
Splunk: How Vodafone established Operational Analytics in a Hybrid Environmen...
Splunk: How Vodafone established Operational Analytics in a Hybrid Environmen...Splunk: How Vodafone established Operational Analytics in a Hybrid Environmen...
Splunk: How Vodafone established Operational Analytics in a Hybrid Environmen...Splunk
 
SOC, Amore Mio! | Security Webinar
SOC, Amore Mio! | Security WebinarSOC, Amore Mio! | Security Webinar
SOC, Amore Mio! | Security WebinarSplunk
 
.conf Go 2022 - Observability Session
.conf Go 2022 - Observability Session.conf Go 2022 - Observability Session
.conf Go 2022 - Observability SessionSplunk
 
.conf Go Zurich 2022 - Keynote
.conf Go Zurich 2022 - Keynote.conf Go Zurich 2022 - Keynote
.conf Go Zurich 2022 - KeynoteSplunk
 
.conf Go Zurich 2022 - Platform Session
.conf Go Zurich 2022 - Platform Session.conf Go Zurich 2022 - Platform Session
.conf Go Zurich 2022 - Platform SessionSplunk
 
.conf Go Zurich 2022 - Security Session
.conf Go Zurich 2022 - Security Session.conf Go Zurich 2022 - Security Session
.conf Go Zurich 2022 - Security SessionSplunk
 

Mehr von Splunk (20)

.conf Go 2023 - Data analysis as a routine
.conf Go 2023 - Data analysis as a routine.conf Go 2023 - Data analysis as a routine
.conf Go 2023 - Data analysis as a routine
 
.conf Go 2023 - How KPN drives Customer Satisfaction on IPTV
.conf Go 2023 - How KPN drives Customer Satisfaction on IPTV.conf Go 2023 - How KPN drives Customer Satisfaction on IPTV
.conf Go 2023 - How KPN drives Customer Satisfaction on IPTV
 
.conf Go 2023 - Navegando la normativa SOX (Telefónica)
.conf Go 2023 - Navegando la normativa SOX (Telefónica).conf Go 2023 - Navegando la normativa SOX (Telefónica)
.conf Go 2023 - Navegando la normativa SOX (Telefónica)
 
.conf Go 2023 - Raiffeisen Bank International
.conf Go 2023 - Raiffeisen Bank International.conf Go 2023 - Raiffeisen Bank International
.conf Go 2023 - Raiffeisen Bank International
 
.conf Go 2023 - På liv og død Om sikkerhetsarbeid i Norsk helsenett
.conf Go 2023 - På liv og død Om sikkerhetsarbeid i Norsk helsenett .conf Go 2023 - På liv og død Om sikkerhetsarbeid i Norsk helsenett
.conf Go 2023 - På liv og død Om sikkerhetsarbeid i Norsk helsenett
 
.conf Go 2023 - Many roads lead to Rome - this was our journey (Julius Bär)
.conf Go 2023 - Many roads lead to Rome - this was our journey (Julius Bär).conf Go 2023 - Many roads lead to Rome - this was our journey (Julius Bär)
.conf Go 2023 - Many roads lead to Rome - this was our journey (Julius Bär)
 
.conf Go 2023 - Das passende Rezept für die digitale (Security) Revolution zu...
.conf Go 2023 - Das passende Rezept für die digitale (Security) Revolution zu....conf Go 2023 - Das passende Rezept für die digitale (Security) Revolution zu...
.conf Go 2023 - Das passende Rezept für die digitale (Security) Revolution zu...
 
.conf go 2023 - Cyber Resilienz – Herausforderungen und Ansatz für Energiever...
.conf go 2023 - Cyber Resilienz – Herausforderungen und Ansatz für Energiever....conf go 2023 - Cyber Resilienz – Herausforderungen und Ansatz für Energiever...
.conf go 2023 - Cyber Resilienz – Herausforderungen und Ansatz für Energiever...
 
.conf go 2023 - De NOC a CSIRT (Cellnex)
.conf go 2023 - De NOC a CSIRT (Cellnex).conf go 2023 - De NOC a CSIRT (Cellnex)
.conf go 2023 - De NOC a CSIRT (Cellnex)
 
conf go 2023 - El camino hacia la ciberseguridad (ABANCA)
conf go 2023 - El camino hacia la ciberseguridad (ABANCA)conf go 2023 - El camino hacia la ciberseguridad (ABANCA)
conf go 2023 - El camino hacia la ciberseguridad (ABANCA)
 
Splunk - BMW connects business and IT with data driven operations SRE and O11y
Splunk - BMW connects business and IT with data driven operations SRE and O11ySplunk - BMW connects business and IT with data driven operations SRE and O11y
Splunk - BMW connects business and IT with data driven operations SRE and O11y
 
Splunk x Freenet - .conf Go Köln
Splunk x Freenet - .conf Go KölnSplunk x Freenet - .conf Go Köln
Splunk x Freenet - .conf Go Köln
 
Splunk Security Session - .conf Go Köln
Splunk Security Session - .conf Go KölnSplunk Security Session - .conf Go Köln
Splunk Security Session - .conf Go Köln
 
Data foundations building success, at city scale – Imperial College London
 Data foundations building success, at city scale – Imperial College London Data foundations building success, at city scale – Imperial College London
Data foundations building success, at city scale – Imperial College London
 
Splunk: How Vodafone established Operational Analytics in a Hybrid Environmen...
Splunk: How Vodafone established Operational Analytics in a Hybrid Environmen...Splunk: How Vodafone established Operational Analytics in a Hybrid Environmen...
Splunk: How Vodafone established Operational Analytics in a Hybrid Environmen...
 
SOC, Amore Mio! | Security Webinar
SOC, Amore Mio! | Security WebinarSOC, Amore Mio! | Security Webinar
SOC, Amore Mio! | Security Webinar
 
.conf Go 2022 - Observability Session
.conf Go 2022 - Observability Session.conf Go 2022 - Observability Session
.conf Go 2022 - Observability Session
 
.conf Go Zurich 2022 - Keynote
.conf Go Zurich 2022 - Keynote.conf Go Zurich 2022 - Keynote
.conf Go Zurich 2022 - Keynote
 
.conf Go Zurich 2022 - Platform Session
.conf Go Zurich 2022 - Platform Session.conf Go Zurich 2022 - Platform Session
.conf Go Zurich 2022 - Platform Session
 
.conf Go Zurich 2022 - Security Session
.conf Go Zurich 2022 - Security Session.conf Go Zurich 2022 - Security Session
.conf Go Zurich 2022 - Security Session
 

Kürzlich hochgeladen

Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonAnna Loughnan Colquhoun
 
Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Allon Mureinik
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsEnterprise Knowledge
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)Gabriella Davis
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxMalak Abu Hammad
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...Neo4j
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsMaria Levchenko
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024The Digital Insurer
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking MenDelhi Call girls
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityPrincipled Technologies
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Servicegiselly40
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slidevu2urc
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Scriptwesley chun
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfEnterprise Knowledge
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processorsdebabhi2
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘RTylerCroy
 

Kürzlich hochgeladen (20)

Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI Solutions
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
 

Splunk Conf2010: Corporate Express presents Splunk with SAP

  • 1. Using Splunk with SAP: Planning for Performance and Capacity Shaun Butler and Luke Harris
  • 2. About Corporate Express Supplier of business essentials, established in 1995 Revenue $1.16 billion in 2009 E-Commerce sales currently account for 80% of all orders Over 2300 staff in over 40 locations across Australia and New Zealand Listed on the ASX with majority shareholder Staples Inc Our mission: “To provide a single source supply solution to make it easier and more cost-effective for our customers to do business.” 2
  • 3. About Shaun Butler Senior Technology Specialist (Infrastructure Services) RHCE, EMCPA Senior authority for planning, design, implementation and support in relation to Tier One Infrastructure (including AIX, System P, Linux, Oracle and Enterprise Storage) Infrastructure Services is responsible for core infrastructure components – datacentre, network, servers, storage, virtualisation, monitoring, DNS/DHCP, email 3
  • 4. About Luke Harris Senior Systems Engineer (Infrastructure Services) Linux SOE Specialist, RHCE EMC Storage Administrator Splunk, Nagios, Cacti, and DNS Administrator SplunkForNagios developer:  http://www.splunkbase.com/apps/All/4.x/Add-On/app:SplunkForNagios 4
  • 5. Splunk At CE: Data Sources Logfiles Configs Messages Traps Metrics Scripts Changes Tickets Alerts Windows Linux/Unix Virtualization Applications Cisco Storage • Syslog (Snare) • Syslog • Hypervisor (ESX) • Web logs • Firewalls, IPS, ACE • EMC Symmetrix • Event logs • DNS, DHCP • VirtualCenter • SAP • Routers, Switches • Active Directory • Nagios • webMethods • Proxy, WAAS • Altiris • Postfix • netXpress • VPN, netflow 5
  • 6. Splunk At Corporate Express: Deployment  1 Production server (IBM Blade)  1 non-production server (VM)  Operating System: RHEL 5.5 64-bit Infrastructure  Syslog – Linux, AIX, Windows (via Snare), ESX, Cisco Switches, Routers, Firewalls, Load Balancers, WAAS, VPN Data Inputs  SNMP – Cisco IPS  rsync – SAP, webMethods, Nagios, Proxy, Apache, EMC  CIFS – Altiris  wget – netflow (StatSeeker) 6
  • 7. SAP at Corporate Express nXtgen Project – Business transformation and ERP replacement SAP applications implemented (5 out of 6)  ERP Central Component (ECC)  Master Data Management (MDM)  Customer Relationship Management (CRM)  Process Integration (PI)  Business Intelligence (BI)  Portal New Zealand go live April 2010 Australia go live 2011 7
  • 8. Splunk’s Value Proposition in a SAP World Powerful Trending + Data Accessibility + Data Augmentation = Operational Intelligence 8
  • 9. SAP Data Sources ECC, CRM, BI – Data retrieved from:  ST03 - SAP Workload Monitor  SM04 – SAP User List  SM04/ST03 transactions are periodically called and output dumped into text files MDM – Application logs File replication/rsync 9
  • 10. SAP Use Cases At CE Application Performance Capacity/usage Network analysis 10
  • 11. SAP Use Case 1: Application Performance ABAP SAP Applications (e.g. ECC, CRM, BI) SAP Master Data Management (MDM) 11
  • 12. Application Performance: Summary Dialog Step Response Time 12
  • 13. Application Performance: Detailed Dialog Step Response Time 13
  • 14. Application Performance: Detailed Dialog Step Response Time (Long Term Trending) 14
  • 16. Application Performance: MDM Import Time From This: <Trace ts="2010/07/30 07:02:43.821 GMT" tid="1029" entry-no="18583">[MDS=syd1sap08 Repository=MDP ClientSystem=Code_Template Port=Masterpack_Portal]: Chunk size/parallel[50000/40]: Import Task Started.</Trace> <Timer ts="2010/07/30 07:02:47.426 GMT" tid="1029" entry-no="18584" name="GetInitializationInfoAllLanguages" total="3.604439"/> <Timer ts="2010/07/30 07:02:47.707 GMT" tid="1029" entry-no="18585" name="Add User Dimensions" total="0.000006"/> <Timer ts="2010/07/30 07:02:48.199 GMT" tid="1029" entry-no="18586" name="Regular Table Load" total="0.492183"/> <Timer ts="2010/07/30 07:02:48.200 GMT" tid="1029" entry-no="18587" name="data Table Load " total="0.000095"/> ---*snip 30 lines*--- <Trace ts="2010/07/30 07:03:05.515 GMT" tid="1543" entry-no="18620">Import action:<LF/>--Skip: 0<LF/>--Create: 0<LF/>--Updated (NULL fields only): 0<LF/>--Updated (all mapped fields): 36<LF/>--Replace: 0<LF/>--Delete [destination]: 0<LF/>--Value Exceptions: 0<LF/>--Import Exceptions: 0</Trace> <Trace ts="2010/07/30 07:03:05.516 GMT" tid="1543" entry-no="18621">xImporter: Total chunk import time: 77000.000000000 milli-seconds.</Trace> <Trace ts="2010/07/30 07:03:07.511 GMT" tid="1543" entry-no="18622">xImporter: : Start -&gt; End: 1083000.000000000 milli-seconds.</Trace> <?xml version="1.0" encoding="utf-8"?> <?xml-stylesheet type="text/xsl" href="MDM_Log.xsl"?> <Trace ts="2010/07/30 07:03:08.913 GMT" tid="1029" entry-no="18623">[MDS=syd1sap08 Repository=MDP ClientSystem=Code_Template Port=Masterpack_Portal]: Chunk size/parallel[50000/40]: Import Task Finished.</Trace> </Open> </MDM_Log> 16
  • 17. Application Performance: MDM Import Time To This: 17
  • 18. SAP Use Case 2: Throughput/Capacity ABAP SAP Applications (e.g. ECC, CRM, BI)  Dialog steps executed over time  System activity expressed in SAPS  Concurrent Users SAP Master Data Management (MDM)  Transaction throughput – Import/syndication 18
  • 19. Dialog Steps Executed Over Time (Business Day) 19
  • 20. Dialog Steps by Task Type 20
  • 21. Dialog Steps Since Go Live 21
  • 22. SAP Throughput as Represented by SAPS 22
  • 23. Active vs. Inactive Concurrent Users 23
  • 24. Active Users by Transaction Type 24
  • 25. Active Users By Location 25
  • 26. SAP Use Case 3: Network Analysis WAN bandwidth consumption split by SAP application SAP vs. Non-SAP WAN bandwidth consumption Average WAN bandwidth footprint per SAP user 26
  • 27. WAN Bandwidth Consumption by SAP Application 27
  • 28. WAN Bandwidth Consumption – SAP vs. Non-SAP 28
  • 29. Average WAN Footprint Per User 29
  • 30. Bringing It All Together... 30
  • 31. Bringing It Even More Together (SplunkForNagios) 31
  • 32. Anticipated Challenges Have a clear idea of what you are trying to achieve Get your Basis/SAP administrator on board! 32
  • 33. The Future SAP Enterprise Portal Auditing Investigate implementing ST03/SM04 data output into database and index from there 33

Hinweis der Redaktion

  1. We capture system logs from all of our AIX, Linux and Windows servers We capture Active Directory events for auditing We capture power savings from Altiris a daily snapshot of our VMware ESX servers and Virtual Machines and also: task log every 10 minutes syslog of ESX logs splunk light weight forwarder on VirtualCenter server* logs from all of our Cisco devices including Firewalls, IPS, ACE Load Balancers, Routers, Switches, VPN, WAAS and Proxy server hourly snapshots of disk usage on our Symmetrix Storage Array (shell script - symcli) we rsync the nagios log every five minutes to assist with event correlation and troubleshooting* we syslog our external and internal DNS/DHCP servers, and the postfix email gateway servers* we rsync our S.A.P., webMethods (Middleware), and netXpress (Web Portal) logs* and we use wget for Netflow logs to capture bandwidth utilization
  2. Dialog Step (Official SAP Definition) - User action that provokes a change of a user&apos;s state by requesting a new screen. Fundamental transaction component of an ABAP based SAP application.
  3. Dialog Step (Official SAP Definition) - User action that provokes a change of a user&apos;s state by requesting a new screen. Fundamental transaction component of an ABAP based SAP application.
  4. Dialog Step (Official SAP Definition) - User action that provokes a change of a user&apos;s state by requesting a new screen. Fundamental transaction component of an ABAP based SAP application.
  5. Warning Alerts - Last 60 Minutes Number of Host &amp; Service alerts with status Warning Critical Alerts - Last 60 Minutes Number of Host &amp; Service alerts with status Critical Warning and Critical Alerts Top 5 Host &amp; Service alerts with status Warning &amp; Critical Top 10 Service Notifications with status Warning Chart of recent service notifications Top 10 Service Notifications with status Critical Chart of recent service notifications