Data Science for Effective Network Operations

1. © 2017 TM Forum | 1
Data Science for Effective
Network Operations
Kiran Inampudi,Cisco

2. © 2017 TM Forum | 2
Who am I ?
Kiran Inampudi
Kiran Inampudi currently focuses on Service Provider Automation-­
strategy, innovation, new services incubation & launch, strategic
partnerships, Business Plans, Sales enablement, GTM etc
Network Web 2.0 Cloud SDN/NFV
Two decades ago….My initial foray into “AI”
Thesis : Finding faults in power transmission networks using AI

3. © 2017 TM Forum | 3
What is Data Science ?
Data science involves using automated
methods to analyze massive amounts of
data and to extract knowledge from them.
Data science is a broad discipline that
includes
• Statistics
• Computer science
• Applied mathematics
• Machine learning/AI
• Visualization
Data Science is a methodology, not a feature!

4. © 2017 TM Forum | 4
SP Automation Journey
Current: Hardware Centric
Complex/Legacy OSS
Physical , Multi-­Vendor
CLI/ Manual
Siloed, Slow
Future: Software Centric
Cloud Native/Modular
Programmable, Virtual
DevOps, Automation
Agile, Innovative
Tools
Infra
Process
Culture
Tools
Infra
Process
Culture
Adopting Automation is a broad proposition, requiring investment in
technology, tooling, people and process change.

5. © 2017 TM Forum | 5
Raw
Data
Cleaned
Data
Standard
Reports
Data Exploration &
Metrics Reporting
Predictive
Analytics
Prescriptive
Analytics
Path towards Automated future
Why did it happen
What will happen
What is the best
way to do this
Statistics & Data
Visualization
What happened
Sense & Respond Predict & Act
Competitive Advantage
Current Network Management Platforms Smart Network Management
Cognitive
Analytics
Machine tells humans
what to do!
Source : SAP

6. © 2017 TM Forum | 6
Data Science for Telco Ops
Advanced Security
Optimization
Predictive
Maintenance
Forecasting
Reduce Alerts
Why Now?
NFV/SDN
Data ,
Real-time
Telemetry
Cloud

7. © 2017 TM Forum | 7
Machine Learning Methods
ML Algorithms
Supervised
Regression
Naïve Bayes
Decision Trees
kNN, SVM
Un Supervised
Artificial neural
networks
k-­Means
Hierarchical
Clustering
Principal
Components
Analysis (PCA)

8. © 2017 TM Forum | 8
Use Case #1 : Alert Reduction
Unsupervised Machine Learning Enables “Significance”
Filtering of >98% Noise
Source: EVANIOS

9. © 2017 TM Forum | 9
Supervised Learning
Use Case #2 Network Health
Neural Network
Data
Collection
Infrastructure
Recognized
Patterns
e.g. Control
plane
disconnect
Real time
streaming

10. © 2017 TM Forum | 10
Use Case #3 Proactive Network Maintenance
Device
Reboots
Errors
Session
Failures
CPU
Process
Uptime
Memory
Metrics
Unsupervised Learning Algorithms(Ex-PCA)
Identify the
root
cause
of
various
network
problems
§ CPE
Reboots
§ IPv6
session
failures
§ Performance
Degradation
§ Etc

11. © 2017 TM Forum | 11
Workflow
Remediation
AI/ML Engine
Data Collection
Service
Use Case #4 Auto Remediation
• Network Change & Verification
• Auto QOS
• Intelligent Routing
• MOP Automation

12. © 2017 TM Forum | 12
What skills are required to succeed?
SP Operations
Transformation
SP Domain
Expertise
Software
Automation
Data Science
Expertise
Math & Software
Background
SP Ops Workflow
Algorithms & Models
Software Dev
Expertise
Open Source Tools
Identify use cases

13. © 2017 TM Forum | 13
Summary
Ø Data Science is a Methodology, Not a feature!
Ø SDN/NFV & Data Science is a powerful new approach for making
networks more reliable and secure
Ø Data science capabilities should synergize, empower network
Operations teams
Ø Recommended Approach-­ Crawl, Walk & Run