SAP-SuccessFactors Customer Presentation

1. Copyright © 2016 Splunk Inc.
SAP SuccessFactors
Alfred Wan
Director, Service Delivery Operations
HCM Suite Service Owner

2. 2
Agenda
• Splunk @ SAP SuccessFactors
• ITSI Proof of Concept
• Creative Projects w/ Splunk

3. Splunk @ SAP SuccessFactors

4. 4
About SAP SuccessFactors
• Market leader in cloud-based human resources application industry
• Supports 5000 customers and 50 million registered end users
• 10 global datacenters across US, Europe, APJ
• 10,000+ VMs/BMs in production

5. 5
About Me / Our Team
• HCM Suite Service Owner (Performance Engineering Background)
• Team of 90 people: San Francisco, Reston, Budapest, Bangalore, Shanghai
• Charter: application management for our HCM suite
• Focus: application troubleshooting, performance tuning, capacity management,
root cause analysis, long-term proactive measure
• Deal with everything that impacts applications (by involving responsible teams)

6. 6
Before Splunk: Manual, Inefficient
• Had to analyze logs manually
• Used various scripts (shell, perl, etc.)
• Could only view one server at a time
• No aggregated view
• Lack of visibility/analytics
• Heavily rely on experienced individual

7. 7
Choosing Splunk
• Initially purchased Splunk for log management
• Saved 100+ log request tickets per week
• Attending SplunkLive! expanded my perception of Splunk
• Dashboards and Reporting
• Various Visualization
• Correlation
• Started using it more extensively & gained multiple additional
advantages
• Reduce MTTR
• Business Analysis
• Environment Certification
“We still haven’t
unleashed the full
power of Splunk,
but we’re getting
better at it. We
now see it as
much more than
a log catching &
indexing tool.”

8. 8
Splunk Benefits
• Increased efficiency
– Automated previously manual processes
– Consolidated worthwhile tools, retired unnecessary tools
• Higher availability and performance
– Achieving 99.9% availability
– Better customer performance experience
• Gain of functional time
– Freed up engineering resources
– Eliminating redundancies in troubleshooting
• Information discovery, visibility
– Centralized, more precise log management
– Aggregated views help us understand navigation usage, outages, etc.
“Sharing clues and
our findings about
major activities
that we discover in
Splunk with
executives & peers
helps our business.”

9. 9
Splunk at SAP SuccessFactors
• Splunk Enterprise
• 5 TB license
• 10 data centers globally, multiple environments
• US Ashburn datacenter example:
– 8 indexers
– 2 syslogs, 1 job server, 1 search head
– 1500+ forwarders

10. 10
Logs indexed at SAP SuccessFactors
• Syslogs
• F5 load balancer logs
• Switch logs
• Firewall logs
• Blade logs
• OS level auditing logs
• Web server logs
• Application server logs
• Database logs
• Internal APM metrics
• …

11. 11
Day to Day Operations
• Centralize 90+ logs from various of tiers,
applications into Splunk
• Real-time troubleshooting capability
• Transparent view in one stop shop
• Connect the dots, reveal comprehensive status of
the application suite
• Monitoring the key components from dashboard
• Splunk Alerts via email or API
11

12. ITSI Proof of Concept

13. 13
New Site Availability Goals
• Reduce MTTR by 90%
• Optimize the troubleshooting/investigation process
• Leverage existing tools as much as possible
• All within 3 months!

14. 14
Challenges with existing solution
14
CHALLENGES
Multiple point solutions
Pingdom, Zabbix, Optier,
Solarwinds
Minimal indication of
root cause
Repeated escalations and
War Rooms
Rapid growth across
10 datacenters
PAIN POINTS
CONCERNED
Complexity, teams operating in
silos, massive infrastructure
ESCALATED
Long resolution times
STRESSED
Resource drain and
missed project deadlines

15. Splunk IT Service Intelligence
Machine Learning-Powered, Analytics-Driven IT Operations
Simplify service operations
Prioritize incidents with context Redefine the role of IT
Combine events & metrics
across silos with ease,
flexibility & scale in days
Unify siloed monitoring
Leverage machine learning to
detect anomalies & highlight
events that matter
Deliver business & service context to prioritize
incident investigation & action
Support decisions & communicate results
with powerful service-level insights

16. 16
Personalized visualizations of our HCM service
• Visualize contextual inter-relationships across
each layer of the stack from Web, Application
through Database and Network
• Illustrate business and service activity using
indicators aligned with strategic goals
• Once all the data was in Splunk we were able
to build the KPI’s and create glass tables
within a few days
• Goal is to create synthetic service health
scores with weighted KPI to facilitate early
alerting and fast resolution
16

17. 17
Organized View of Performance Indicators
17
Our Operations team will be able to:
• Build out Deep Dives to correlate critical
KPI’s for each layer of the stack
• Example: we can now track high load
on servers and tie it back to Java
Exceptions, long running SQL queries
• Compare performance over time and in
real time to understand trends and
identify systemic issues

18. 18
Real-Time View of Service and KPI Health Scores
Site Operations team will be able to:
• Get early warning of emerging incidents
with a heat map of service health and
KPI scores, metrics, sparklines and alerts
• Drill down into service and entity details
for in-depth triage
18

19. 19
Tweak KPI Weight for Health Score
19
Sliding bar approach makes the process
very intuitive
Simulated Severity helps user understand
how the weight impacts health score

20. 20
Learn What’s Normal and Abnormal
20
Baseline normal operations and alert on
anomalous conditions
Identify abnormal trends and patterns in
KPI data

21. 21
Baseline Trends to Adapt Thresholds
21
Use statistics to dynamically adapt KPI
thresholds by time
Maintain and preserve learned thresholds
to monitor KPI and service behavior

22. Creative Projects w/Splunk

23. 23
Long-term APM Data Retention
Integrated Splunk with our in house
APM solution for longer data retention
using the ODATA API’s.
• Identify usage patterns
• Capacity planning for “surge” periods
• Insights to improve overall business
• Proactively detect anomalies and
remediate
• Business analysis with historic data
• Machine learning with historic data to
project usage growth scientifically
23

24. 24
Log Verbosity Analysis & Log Fingerprinting
• Analyze where the most redundant logs are coming from
• Reduce the verbosity of top contributors
• Develop log fingerprint for highly redundant and heavy, but necessary log entries
• Replace heavy raw log entries with the light fingerprint entry
• Build Splunk lookup table to match the fingerprint with raw log entry
• Goal is to improve the logging efficiency so that we can do more with Splunk
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25. Thank You
y.wan@sap.com