The document discusses using graphs and Neo4j to improve network and IT operations. It describes how networks can be modeled as graphs and how this allows for more effective proactive dependency analysis and reactive root cause analysis when issues arise. Examples of specific scenarios and use cases are provided, as well as a discussion of the types of organizations that are using Neo4j for these purposes.

1. Taming the Complexity
of Network & IT Ops
Improving Network Operations With Neo4j & Graphs
Stefan Kolmar"
Vice President Field Engineering

2. Agenda
• Networks are Graphs!
• Network & IT-Operations with Graphs !
• Network Upgrade and Helpdesk Scenarios!
• Why Neo4j!
• References and Resources!
• Q&A!

3. Networks are Graphs

4. network topology

6. Mesh
Router
Gatew
ay
Router
Router
Router
Mesh
Router
Router
Router
Mesh
Router
Gatew
ay
Access
Point
CPU
CPU CPU
CPU
Mobile
Mobile Mobile
Mobile
Base
Station
CPU
CPU
CPU
CPU
Access
Point

7. Relational
Database

8. This is data modelled as graph!
Graph
Database

9. Network & IT-Operations
with Graphs

10. Typical IT organization

11. Sys Admins
Servers, on-premise virtual machines,
cloud virtual machines, etc.
Network Admins
Switches, Routers, Egress Points
App Admins
I.e. Salesforce, Marketo, SAP, Oracle
Apps, Tableau, SharePoint, DBA’s
etc.
Internal Users
HR, Sales, Marketing, Data Analysts,
E-staff etc.
Numerous Customers & Partners

12. Router
Servers
Servers
Apps
FirewallCloud
Switch
Apps
Network Admins
Switches, Routers, Egress Points
Sys Admins
Servers, on-premise virtual machines,
cloud virtual machines, etc.
App Admins
I.e. Salesforce, Marketo, SAP, Oracle
Apps, Tableau, SharePoint, DBA’s
etc.
Internal Users
HR, Sales, Marketing, Data Analysts,
E-staff etc.

13. Router
Servers
Servers
Apps
FirewallCloud
Switch
Apps
Network Admins
Switches, Routers, Egress Points
Sys Admins
Servers, on-premise virtual machines,
cloud virtual machines, etc.
App Admins
I.e. Salesforce, Marketo, SAP, Oracle
Apps, Tableau, SharePoint, DBA’s
etc.
Internal Users
HR, Sales, Marketing, Data Analysts,
E-staff etc.

14. Router
Servers
Servers
Apps
FirewallCloud
Switch
Apps
Network Admins
Switches, Routers, Egress Points
Sys Admins
Servers, on-premise virtual machines,
cloud virtual machines, etc.
App Admins
I.e. Salesforce, Marketo, SAP, Oracle
Apps, Tableau, SharePoint, DBA’s
etc.
Internal Users
HR, Sales, Marketing, Data Analysts,
E-staff etc.

15. Router
Servers
Servers
Apps
FirewallCloud
Switch
Apps
Network Admins
Switches, Routers, Egress Points
Sys Admins
Servers, on-premise virtual machines,
cloud virtual machines, etc.
App Admins
I.e. Salesforce, Marketo, SAP, Oracle
Apps, Tableau, SharePoint, DBA’s
etc.
Internal Users
HR, Sales, Marketing, Data Analysts,
E-staff etc.

16. Router
Servers
Servers
Apps
FirewallCloud
Switch
Apps
Network Admins
Switches, Routers, Egress Points
Sys Admins
Servers, on-premise virtual machines,
cloud virtual machines, etc.
App Admins
I.e. Salesforce, Marketo, SAP, Oracle
Apps, Tableau, SharePoint, DBA’s
etc.
Internal Users
HR, Sales, Marketing, Data Analysts,
E-staff etc.

17. Network & IT operations
Proactive! Reactive!

18. Proactive Scenario:!
Dependency Analysis

19. Best,
John Lewis
Network Administrator
Email
#newyork
#london
#funstuff
#graphicdesign
#product_team
#marketing
#staff_info
#IT_maintenance
Slack
Premise:
We are the Network admins at the company ACME and we’re
planning on doing maintenance on a switch on a Friday afternoon.
Network Admins
Sys Admins
Notify! Hi, maintenance scheduled for Switch IP 10.2.5 on Rack 5 on
Friday, May 28 @ 3-4pm.
@channel Hi, maintenance scheduled for
Switch IP 10.2.5 on Rack 5 on Friday,
May 28 @ 3-4pm.

20. Premise:
We are the Network admins at the company ACME and we’re
planning on doing maintenance on a switch on a Friday afternoon.
Sys Admins
(Servers & Other Hardware)!
Network Admins
(In Charge of Switch)!
The Telephone Game

21. Premise:
We are the Network admins at the company ACME and we’re
planning on doing maintenance on a switch on a Friday afternoon.
Network Admins
Sys Admins
App Admins 10+
(Marketo, SalesForce, Publishing Tools etc.)!
(Servers & Other Hardware)!
(In Charge of Switch)!
The Telephone Game

22. Premise:
We are the Network admins at the company ACME and we’re
planning on doing maintenance on a switch on a Friday afternoon.
Network Admins
Sys Admins
App Admins
Internal Users
10+
(Marketo, SalesForce, Publishing Tools etc.)!
(Employees in Sales, Marketing, Legal, HR, etc)!
(Servers & Other Hardware)!
(In Charge of Switch)!
500+
The Telephone Game

23. Network Admins
Sys Admins
App Admins
Customers
Internal Users
10+
(Marketo, SalesForce, Publishing Tools etc.)!
(Employees in Sales, Marketing, Legal, HR, etc)!
(Servers & Other Hardware)!
(In Charge of Switch)!
500+
10’000+
The Telephone Game
Premise:
We are the Network admins at the company ACME and we’re
planning on doing maintenance on a switch on a Friday afternoon.

24. Dependency Analysis
Demo

25. Reactive Scenario:!
Root Cause Analysis

26. Helpdesk
Customers
App Admins
Internal Users
Sys Admins
Network Admins
Organization Hierarchy

27. Premise:
It’s 5 pm on a Friday in the summer. Most staff have left for the day, but the
Helpdesk remain on call. The staff starts receiving numerous complaints.

28. Premise:
It’s 5 pm on a Friday in the summer. Most staff have left for the day, but the
Helpdesk remain on call. The staff starts receiving numerous complaints.
CRM system
Oracle Financials
Tableau

29. Premise:
App Admins
6-6.45pm
Starts
investigating
8pm
Oracle App
Admin
On-call Sys
Admin
Slow fiber connection
to the SAN detected
5pm
Complaints
begin
Helpdesk Network
Admin
9pm
Issue is a bad
fiber connector
10pm
System
operational
Helpdesk
It’s 5 pm on a Friday in the summer. Most staff have left for the day, but the
Helpdesk remain on call. The staff starts receiving numerous complaints.

30. Premise:
Impact:
• Outage lasted 5 hours
• 3 helpdesk staff involved
• 3 on-call app admins
• 3 on-call sysadmins
• 2 on-call network admins return to the office
• Total people time until resolution: 55 hours
It’s 5 pm on a Friday in the summer. Most staff have left for the day, but the
Helpdesk remain on call. The staff starts receiving numerous complaints.

31. Helpdesk Root Cause
Demo

32. Premise:
Impact after switching to graph:
• Outage lasts 45 min
• 3 helpdesk staff involved
• 2 on-call network admins are involved
• Total people time until resolution: 3.75 hours
It’s 5 pm on a Friday in the summer. Most staff have left for the day, but the
Helpdesk remain on call. The staff starts receiving numerous complaints.

33. Exploring the Graph

34. Data Model!

35. Who’s using Neo4j?

36. Government Commercial clients
Who’s Using Neo4j?
Institutions
Local Governments
Law Enforcement
Military & Intelligence

37. !
Background
• World’s largest provider of IT infrastructure,
software and services
• Unified Correlation Analyzer (UCA) helps
comms operators manage large networks !
with carrier-class resource and service
management, root cause and impact analysis
Business Problem
• Use network topology to identify root problems
causes on the network
• Simplify and speed alarm handling by operators
• Automate handling of certain types of alarms
• Filter/group/eliminate redundant alarms via
event correlation
Solution and Benefits
• Accelerated product development time
• Extremely fast network-topology queries
• Graph representation a perfect domain fit
• 24x7 carrier-grade reliability with Neo4j
High Availability clustering
• Met objective in under six months
Hewlett Packard WEB/ISV COMMUNICATIONS!
Network and IT Operations !37!

38. !Internet of Things!
Business Problem
• Support complex operational infrastructure
collects, records and manages weather data
across a wide network
• Integrate with Splunk system that monitors
remote instruments
• Use graphs to query instrument network
Solution and Benefits
• Neo4j analyzes dependency graphs to produce
exception reports
• Neo4j and SPLUNK integrated tightly
• Solution has enabled KNMI to re-architect and
rebuild their entire operational infrastructure
Background
• The Royal Netherlands Meteorological
Institute (KNMI)
• Dutch national service with 1100+ weather
measurement locations
• Monitors and forecasts weather, climate,
air quality and seismic activity
Royal Netherlands Meteorological Institute
SCIENCES!
38!

39. !
Background!
• Leaders in model-driven engineering!
• Founded in 2004 in France!
• Source code cartography software used at over
100 sites!
Business Problem!
• Reaching the limits of legacy OODB technology!
• Find new data platform well suited for storing
software dependency graph!
• Perform rapid,efficient dependency mapping and
impact analysis across Java, .NET, Flex, HTML,
COBOL, DB2, Oracle and more!
Solution and Benefits!
• Moved to modern graph platform with more readily-
available skills and expertise!
• Strong domain fit has accelerated development!
• Enabled new impact analysis features not possible
in the previous technology!
Sodifrance SOFTWARE!
Impact Analysis!39!

40. !
Background!
• One of the world’s oldest and largest banks!
• 100+ year-old bank with more than 1000
predecessor institutions!
• 500,000 employees and contractors!
• Needed to manage and visualize ~50,000
Unix servers in its network!
Business Problem!
• Original RDBMS solution could handle only
5,000 servers!
• Improve net performance company-wide!
• Leverage M&A legacy systems with no
room !
for error!
Solution and Benefits!
• Store UNIX server and network config in
Neo4j!
• Combine Splunk log data into an application !
that visualizes events on the network!
• Neo4j vastly improved app performance!
• New apps built much faster with Neo4j than
SQL!
Large Investment Bank FINANCIAL
SERVICES!
Network and IT Operations!40!

41. Neo4j Adoption by Selected Verticals
SOFTWARE
FINANCIAL
SERVICES
RETAIL
MEDIA & OTHER
SOCIAL
NETWORKS
TELECOM
HEALTHCAR
E

42. Thank you!