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![MATCH (a:Element { id: “A”})
MATCH p = (a)-[:DEPENDS_ON*]->(n { id: “N”})
RETURN p
SELECT
d1.ElementId, d2.ElementId, d3.ElementId
FROM dpndncs AS d1
INNER JOIN dpndncs AS d2
ON d1.dependsOnElemId = d2.ElemId
INNER JOIN dpndncs AS d3
ON d2.dependsOnElemId = d3.ElemId
… <arbitrary number of joins>…
WHERE d1.ElementId = “A”
AND d3.ElementId = “N”
Element Depends On
A B
A C
A D
C H
D J
E F
E G
F J
G L
H I
J N
J M
L M
Does X depend on Y ?](https://image.slidesharecdn.com/totaltelecom-neo4j-jbarrasa-191104164231/75/Graph-enabled-network-automation-solutions-with-Neo4j-25-2048.jpg)
![MATCH (fe:Link { linkId: $id})<-[:DEPENDS_ON*]-(s:Service)
RETURN max(s.priority) AS severity
{ alarmType: “LOS”,
notifyingEntity: “IF/AX/0/3”, …}
Service Assurance
IA/RCA
GET http://localhost:11001/engine/ia/s1_361_sdh
{"severitySummaryCode": 4,
"severitySummaryDesc": "MAJOR",
"detail": [{"elem":"2217/ol",
"impact" : 1,](https://image.slidesharecdn.com/totaltelecom-neo4j-jbarrasa-191104164231/75/Graph-enabled-network-automation-solutions-with-Neo4j-32-2048.jpg)
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Graph-enabled network automation solutions with Neo4j
1) Graph databases like Neo4j are well-suited for network automation solutions because they can flexibly model complex network dependencies and relationships. 2) Key benefits of using Neo4j include flexibility to dynamically change schemas, developer productivity through an intuitive query language, and improved performance over traditional databases. 3) Common use cases for graph databases in telecommunications include assurance, orchestration, customer experience management, identity and access management, and smart home/city applications.
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Graph-enabled network automation solutions with Neo4j
- 1. Graph-Enabled Network Automation Solutionswith Neo4j Dr. Jesús Barrasa - @BarrasaDV Director Telco&Media - Neo4j London - 29th October 2019
- 2. The #1 Platformfor Connected Data
- 4. Not this typeof graphs!
- 5. The Property GraphModel Optical MUX Filter Card
- 7. Are you stillNOT using Graphs? Here are a few reasons why you should
- 8. ”Graph analysis ispossibly the single most effective competitive differentiator for organisations pursuing data-driven operations and decisions“
- 9.
- 10. Adoption Highlights Top MVPD 2of the Top 5 US multichannel video service providers have chosen Neo4j Leading OSS Vendors Half of the leaders in the 2018 Gartner MQ for OSS embed Neo4j in their products 2 of the 3 world’s largest CSP use Neo4j in mission critical solutions Largest Telcos
- 11. IoT OSS/BSS Governance & MetadataMgmnt IAM & Fraud Analysis Common Graph Use Cases in Telco • Assurance • Orchestration • CRM/Support • Planning & Optimisation • Regulatory compliance • Data Lineage • Consent Mgmnt • Identity & Access Mgmnt • Smart Home • Smart Cities • Industrial /Manufacturing Customer Experience Mgmt • Personalisation/Rec ommendation • Customer Journey Analysis • Customer 360 - KYC
- 12. 2. Key BusinessBenefits
- 13. • Flexibility: DynamicSchema • Developer Productivity: Agility, Declarative query language Faster Time-To-Market (Solution/Production) • New data paradigm • Graph representation of data Innovation Enabler • Timeliness • Accuracy Better decisions drive better business outcomes • 10x less CPU with index-free adjacency • 10x less hardware than other platforms Hardware efficiency Neo4j: Graph Platform Benefits
- 14.
- 15. Need to capturecomplexity Flexibility Performance
- 16. Need to capturecomplexity Flexibility Performance
- 17.
- 18. Need to capturecomplexity Flexibility Performance
- 19. Need to capturecomplexity Flexibility Performance
- 20.
- 21. Look at thisdata… Element Depends On A B A C A D C H D J E F E G F J G L H I J N J M L M
- 22. Element Depends On AB A C A D C H D J E F E G F J G L H I J N J M L M Time challenge #1: Does A depend on F ? ?
- 23. Look at thisdata again…
- 24. Time challenge #2:Does E depend on M ? ? M E
- 25. MATCH (a:Element {id: “A”}) MATCH p = (a)-[:DEPENDS_ON*]->(n { id: “N”}) RETURN p SELECT d1.ElementId, d2.ElementId, d3.ElementId FROM dpndncs AS d1 INNER JOIN dpndncs AS d2 ON d1.dependsOnElemId = d2.ElemId INNER JOIN dpndncs AS d3 ON d2.dependsOnElemId = d3.ElemId … <arbitrary number of joins>… WHERE d1.ElementId = “A” AND d3.ElementId = “N” Element Depends On A B A C A D C H D J E F E G F J G L H I J N J M L M Does X depend on Y ?
- 26. Things get morecomplicated: Route diversity, SPOF detection…
- 27.
- 28.
- 29. Graph-Based Network DualModel Route Oriented Model Least cost path from A to B Diverse routes + Dependency Oriented Model No shared underlying resources IA/RCA
- 30.
- 31. 🏦 :DEPENDS_ON :DEPENDS_ON :DEPENDS_ON IF/AX2431 💥 Customer Event Correlation EventPrioritisation Service Assurance IA/RCA
- 32. MATCH (fe:Link {linkId: $id})<-[:DEPENDS_ON*]-(s:Service) RETURN max(s.priority) AS severity { alarmType: “LOS”, notifyingEntity: “IF/AX/0/3”, …} Service Assurance IA/RCA GET http://localhost:11001/engine/ia/s1_361_sdh {"severitySummaryCode": 4, "severitySummaryDesc": "MAJOR", "detail": [{"elem":"2217/ol", "impact" : 1,
- 33. Graph Size: ~50Mnodes (avg depth: 6)Graph Size: ~1K nodes (avg depth: 5) Simulation: 128 clients, synchronous requests with1ms wait between requests AT SCALE 50000x increase in size of dataset -> 1.14x impact in query performance Graph Native Matters!!! (Deep) Impact/Root Cause Analysis
- 34.
- 37. 100 requests/day x11 devices/zone x 1.3 Mill Zones = 1.43 Bill w/req to Neo4j/day
- 38.
- 39.
- 41. Come meet usat Stand 30 in the Exhibition Area to see Neo4j in action Join us at 12:50 for the Data Driven Technologies roundtable on “How to bring Graph Analytics into your projects: From Network Operations to Customer Journey Analysis” Thank you!