SlideShare a Scribd company logo
1 of 26
Download to read offline
Elisa	Oyj - Neo4j
April	30,	2019
Graph-based	real-time	
inventory	and	topology	
for	Network	Automation
Teemu Nykänen
Service Architect at Elisa
Jesús Barrasa
Director Telco Solutions at Neo4j
The	#1	Platform	for	
Connected	Data
Why	Graphs	in	Telco?
Challenges / Requirements
Capture Complexity
Allow Flexibility
High Performance
Rich, Dynamic, Flexible
Graph Model on a
Native Graph Platform
Adoption
Adoption Highlights
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
Use	Cases
Elisa Software Defined Networking
Graph based real-time inventory
• What Elisa does and why should you care
• Network automation (zero touch included, no added sugar)
• Beauty benefits of graph databases
• Your guide today:
• Teemu Nykänen, Service Architect (teemu.nykanen@elisa.fi)
Introduction
First in Finland and in the world
1882: 1929: 1936: 1950: 1991: 1993: 2007: 2010: 2011: 2015: 2019:
Daniel Wadén
brings the
telephone to
Finland.
The telephone
network in
Helsinki is
automated.
The speaking
clock service
is introduced.
The Helsinki
Telephone
Association
builds a
telephone
network with
four
switchboards
for the
Olympic
Games.
A GSM
telephone call
is made over
the Radiolinja
network.
A GSM data
call takes
place over the
Radiolinja
network.
Thanks to the
commercial
UMTS900
network, the
3G network
can be built
quickly all over
Finland.
The 4G
network taken
into pre-
commercial
use.
The Elisa
Viihde service
combines a
modern TV
service and
the ability to
watch
recordings
using a tablet.
Elisa Internet
of Things (IoT)
service
package
launched in
Finland and
Estonia
Commercial
5G
Elisa key figures
2.8 million
customers, Finland and Estonia
25.4 (21.1)
customer satisfaction (NPS) 2018
Approx. 185,000
shareholders
4,800 (4,700)
Elisa employees
#1 Finland, #2 Estonia
market position
€1.83 billion (1.79)
revenue 2018
€1.95 (1.86)
comparable earnings per share (EPS) 2018
€254 million (240)
capital expenditure investments 2018
4.66 million (4.68)
mobile subscriptions, Finland and Estonia 2018
696,500 (692,300)
fixed broadband subscriptions 2018
Leading market position in Finland
Mobile subscriptions Fixed network subscriptions
Elisa
40%
Telia
32%
DNA
28% Elisa
35%
Telia
29%
~20 Finnet
companies
8%
Others
2%
DNA
26%
Source: FICORA
Source: Company reports Q3/2018
Post-paid market shares: Elisa 40%, Telia 34% and DNA 26%
Digital services for international markets
Innovative managed
services and solution
provider for large enterpise
video conferencing
Providing automation
solutions to telcos for
zero-touch network
processes
Solution for
manufacturers to enable
better decisions, reduce
downtime and improve
quality
The best network, the best customer experience
• We offer fast broadband connections
implemented using the best possible
technologies
• Elisa’s 4G network covers 99.8% of Finland’s
population
• Connections up to 1 Gbit/s are available to more and
more households
• We are the first in world to build a 5G network,
and soon we will offer 5G services to all Finns
• We focus on quality and on continuously
improving our customers’ user experience
• We prevent disturbances
with the help of automation
• SDN with Elisa twist à Elisa
Software-defined Networking
• ”Facilitates network management
and enables programmatically
efficient network configuration in
order to improve network
performance and monitoring”
• Not just for fancy things
but also for devices à Hybrid
networks
Codename EDN
• Enables automation for network. From CLI towards Intent Driven network
• Service activation/provisioning
• ”Zero touch” functionality
• Telemetry collection
• Network optimization (closed loop with telemetry data and machine learning applied )
• Multivendor (and protocol) capable. (take the power back)
• Multiple domains. IP/MPLS currently under construction
• Building things for our own needs but also planning to make parts of it commercially available
• Available from your local dealer at later in time and space
• Situational awareness required
Codename EDN
• Nothing to see here. Just some:
• Nodes
• Edges
• Vertices
• Connections
• Required for true automation
• Essential piece in the EDN puzzle
• Graph database fits like a glove
Network topology view (in real-time please)
• It’s alive! We’re in production with few services released.
• Causal cluster filled with nodes and connections
• One microservice to kill rule em’ all
• Several data streams
• Element managers
• Network discovery
• Telemetry events
• Once more, automation.
• Most of the graph is not exposed via UI
• Sharing data for analytics, anomaly detection etc.
State of a nation
Supermodels
• Around 1.3 million nodes and 1.9 million connections
• To date, we have modelled:
• Physical layer (which can also be virtual)
• Part of the logical layer (portion of the services of IP/MPLS network)
• To be continued…
So far so good
• Other good graph databases in the market
• We even have in-house experience of some of them
• Querying and the power of Cypher
• Not just a graph but native labelled property graph.
• Maturity
• In-house deployment
Why neo4j?
• Elisa is awesome
• Finns are using loads of data. Also beware of angry 5G.
• Train it with automation instead of tight leash.
• We sell things
• SDN is nice EDN is nicer
• Cooler than being cool is ice cold.
• Did I already mention automation?
• Know your enemy network! Store it into graph, you won’t regret it.
• Make nodes not tables
Summary
Thank you!
Follow our journey on Facebook (@elisasuomi) and Twitter (@ElisaOyj)

More Related Content

What's hot

Data Mesh Part 4 Monolith to Mesh
Data Mesh Part 4 Monolith to MeshData Mesh Part 4 Monolith to Mesh
Data Mesh Part 4 Monolith to Mesh
Jeffrey T. Pollock
 
Kappa vs Lambda Architectures and Technology Comparison
Kappa vs Lambda Architectures and Technology ComparisonKappa vs Lambda Architectures and Technology Comparison
Kappa vs Lambda Architectures and Technology Comparison
Kai Wähner
 

What's hot (20)

Scaling up uber's real time data analytics
Scaling up uber's real time data analyticsScaling up uber's real time data analytics
Scaling up uber's real time data analytics
 
Intro to Delta Lake
Intro to Delta LakeIntro to Delta Lake
Intro to Delta Lake
 
Databricks Delta Lake and Its Benefits
Databricks Delta Lake and Its BenefitsDatabricks Delta Lake and Its Benefits
Databricks Delta Lake and Its Benefits
 
Data Quality Strategies
Data Quality StrategiesData Quality Strategies
Data Quality Strategies
 
Introduction SQL Analytics on Lakehouse Architecture
Introduction SQL Analytics on Lakehouse ArchitectureIntroduction SQL Analytics on Lakehouse Architecture
Introduction SQL Analytics on Lakehouse Architecture
 
Data Observability Best Pracices
Data Observability Best PracicesData Observability Best Pracices
Data Observability Best Pracices
 
Data Modeling with Neo4j
Data Modeling with Neo4jData Modeling with Neo4j
Data Modeling with Neo4j
 
Optimizing the Supply Chain with Knowledge Graphs, IoT and Digital Twins_Moor...
Optimizing the Supply Chain with Knowledge Graphs, IoT and Digital Twins_Moor...Optimizing the Supply Chain with Knowledge Graphs, IoT and Digital Twins_Moor...
Optimizing the Supply Chain with Knowledge Graphs, IoT and Digital Twins_Moor...
 
Graph database Use Cases
Graph database Use CasesGraph database Use Cases
Graph database Use Cases
 
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...Data Architecture, Solution Architecture, Platform Architecture — What’s the ...
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...
 
BT Group: Use of Graph in VENA (a smart broadcast network)
BT Group: Use of Graph in VENA (a smart broadcast network)BT Group: Use of Graph in VENA (a smart broadcast network)
BT Group: Use of Graph in VENA (a smart broadcast network)
 
Informatica MDM Presentation
Informatica MDM PresentationInformatica MDM Presentation
Informatica MDM Presentation
 
Data Mesh Part 4 Monolith to Mesh
Data Mesh Part 4 Monolith to MeshData Mesh Part 4 Monolith to Mesh
Data Mesh Part 4 Monolith to Mesh
 
Applying Network Analytics in KYC
Applying Network Analytics in KYCApplying Network Analytics in KYC
Applying Network Analytics in KYC
 
Data Modeling with Neo4j
Data Modeling with Neo4jData Modeling with Neo4j
Data Modeling with Neo4j
 
Enterprise Data Architecture Deliverables
Enterprise Data Architecture DeliverablesEnterprise Data Architecture Deliverables
Enterprise Data Architecture Deliverables
 
Introducing Neo4j
Introducing Neo4jIntroducing Neo4j
Introducing Neo4j
 
Snowflake Data Science and AI/ML at Scale
Snowflake Data Science and AI/ML at ScaleSnowflake Data Science and AI/ML at Scale
Snowflake Data Science and AI/ML at Scale
 
Free Training: How to Build a Lakehouse
Free Training: How to Build a LakehouseFree Training: How to Build a Lakehouse
Free Training: How to Build a Lakehouse
 
Kappa vs Lambda Architectures and Technology Comparison
Kappa vs Lambda Architectures and Technology ComparisonKappa vs Lambda Architectures and Technology Comparison
Kappa vs Lambda Architectures and Technology Comparison
 

Similar to Graph based real-time inventory and topology for network automation - webinar 30 apr 2019

5g Mobile Technology
5g Mobile Technology5g Mobile Technology
5g Mobile Technology
vineetkathan
 
Connecting_Things_2.01_Instructor Supplemental Materials_Chapter4.pptx
Connecting_Things_2.01_Instructor Supplemental Materials_Chapter4.pptxConnecting_Things_2.01_Instructor Supplemental Materials_Chapter4.pptx
Connecting_Things_2.01_Instructor Supplemental Materials_Chapter4.pptx
ssuser52b751
 
Network Architecture of 5G Mobile Tecnology
Network Architecture of 5G Mobile TecnologyNetwork Architecture of 5G Mobile Tecnology
Network Architecture of 5G Mobile Tecnology
vineetkathan
 
Devising a practical approach to the Internet of Things
Devising a practical approach to the Internet of ThingsDevising a practical approach to the Internet of Things
Devising a practical approach to the Internet of Things
Gordon Haff
 
Auto id-labs-kaist-research-2014
Auto id-labs-kaist-research-2014Auto id-labs-kaist-research-2014
Auto id-labs-kaist-research-2014
Daeyoung Kim
 

Similar to Graph based real-time inventory and topology for network automation - webinar 30 apr 2019 (20)

Neo4j @ elisa, Teemu Nykänen, Elisa
Neo4j @ elisa, Teemu Nykänen, ElisaNeo4j @ elisa, Teemu Nykänen, Elisa
Neo4j @ elisa, Teemu Nykänen, Elisa
 
Verso IoT experience – What have we learned from implementations all over the...
Verso IoT experience – What have we learned from implementations all over the...Verso IoT experience – What have we learned from implementations all over the...
Verso IoT experience – What have we learned from implementations all over the...
 
5g Mobile Technology
5g Mobile Technology5g Mobile Technology
5g Mobile Technology
 
Unveiling the Sydney IoT Landscape
Unveiling the Sydney IoT LandscapeUnveiling the Sydney IoT Landscape
Unveiling the Sydney IoT Landscape
 
Connecting_Things_2.01_Instructor Supplemental Materials_Chapter4.pptx
Connecting_Things_2.01_Instructor Supplemental Materials_Chapter4.pptxConnecting_Things_2.01_Instructor Supplemental Materials_Chapter4.pptx
Connecting_Things_2.01_Instructor Supplemental Materials_Chapter4.pptx
 
seminar on 5g Technology
seminar on 5g Technologyseminar on 5g Technology
seminar on 5g Technology
 
Bulding a modern infrastructure & data center
Bulding a modern infrastructure & data centerBulding a modern infrastructure & data center
Bulding a modern infrastructure & data center
 
Digital Global Systems Inc.
Digital Global Systems Inc. Digital Global Systems Inc.
Digital Global Systems Inc.
 
5G Wireless
5G Wireless5G Wireless
5G Wireless
 
5G Technology
5G Technology5G Technology
5G Technology
 
Network technology in mobile
Network technology in mobileNetwork technology in mobile
Network technology in mobile
 
5 g
5 g5 g
5 g
 
IOT_module_3.pdf
IOT_module_3.pdfIOT_module_3.pdf
IOT_module_3.pdf
 
5G and Internet of Things (IoT)
5G and Internet of Things (IoT)5G and Internet of Things (IoT)
5G and Internet of Things (IoT)
 
Network Architecture of 5G Mobile Tecnology
Network Architecture of 5G Mobile TecnologyNetwork Architecture of 5G Mobile Tecnology
Network Architecture of 5G Mobile Tecnology
 
Devising a practical approach to the Internet of Things
Devising a practical approach to the Internet of ThingsDevising a practical approach to the Internet of Things
Devising a practical approach to the Internet of Things
 
5g
5g5g
5g
 
Auto id-labs-kaist-research-2014
Auto id-labs-kaist-research-2014Auto id-labs-kaist-research-2014
Auto id-labs-kaist-research-2014
 
Evolving to a Software Defined Carrier Network
Evolving to a Software Defined Carrier NetworkEvolving to a Software Defined Carrier Network
Evolving to a Software Defined Carrier Network
 
Chap006
Chap006Chap006
Chap006
 

More from Neo4j

More from Neo4j (20)

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 - 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 ...
 
QIAGEN: Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
QIAGEN: Biomedical Knowledge Graphs for Data Scientists and BioinformaticiansQIAGEN: Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
QIAGEN: Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
 
EY_Graph Database Powered Sustainability
EY_Graph Database Powered SustainabilityEY_Graph Database Powered Sustainability
EY_Graph Database Powered Sustainability
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
 
Build your next Gen AI Breakthrough - April 2024
Build your next Gen AI Breakthrough - April 2024Build your next Gen AI Breakthrough - April 2024
Build your next Gen AI Breakthrough - April 2024
 
Connecting the Dots for Information Discovery.pdf
Connecting the Dots for Information Discovery.pdfConnecting the Dots for Information Discovery.pdf
Connecting the Dots for Information Discovery.pdf
 
ISDEFE - GraphSummit Madrid - ARETA: Aviation Real-Time Emissions Token Accre...
ISDEFE - GraphSummit Madrid - ARETA: Aviation Real-Time Emissions Token Accre...ISDEFE - GraphSummit Madrid - ARETA: Aviation Real-Time Emissions Token Accre...
ISDEFE - GraphSummit Madrid - ARETA: Aviation Real-Time Emissions Token Accre...
 
BBVA - GraphSummit Madrid - Caso de éxito en BBVA: Optimizando con grafos
BBVA - GraphSummit Madrid - Caso de éxito en BBVA: Optimizando con grafosBBVA - GraphSummit Madrid - Caso de éxito en BBVA: Optimizando con grafos
BBVA - GraphSummit Madrid - Caso de éxito en BBVA: Optimizando con grafos
 
Graph Everywhere - Josep Taruella - Por qué Graph Data Science en tus modelos...
Graph Everywhere - Josep Taruella - Por qué Graph Data Science en tus modelos...Graph Everywhere - Josep Taruella - Por qué Graph Data Science en tus modelos...
Graph Everywhere - Josep Taruella - Por qué Graph Data Science en tus modelos...
 
GraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4j
GraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4jGraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4j
GraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4j
 
Neo4j_Exploring the Impact of Graph Technology on Financial Services.pdf
Neo4j_Exploring the Impact of Graph Technology on Financial Services.pdfNeo4j_Exploring the Impact of Graph Technology on Financial Services.pdf
Neo4j_Exploring the Impact of Graph Technology on Financial Services.pdf
 
Rabobank_Exploring the Impact of Graph Technology on Financial Services.pdf
Rabobank_Exploring the Impact of Graph Technology on Financial Services.pdfRabobank_Exploring the Impact of Graph Technology on Financial Services.pdf
Rabobank_Exploring the Impact of Graph Technology on Financial Services.pdf
 
Webinar - IA generativa e grafi Neo4j: RAG time!
Webinar - IA generativa e grafi Neo4j: RAG time!Webinar - IA generativa e grafi Neo4j: RAG time!
Webinar - IA generativa e grafi Neo4j: RAG time!
 
IA Generativa y Grafos de Neo4j: RAG time
IA Generativa y Grafos de Neo4j: RAG timeIA Generativa y Grafos de Neo4j: RAG time
IA Generativa y Grafos de Neo4j: RAG time
 
Neo4j: Data Engineering for RAG (retrieval augmented generation)
Neo4j: Data Engineering for RAG (retrieval augmented generation)Neo4j: Data Engineering for RAG (retrieval augmented generation)
Neo4j: Data Engineering for RAG (retrieval augmented generation)
 
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdf
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdfNeo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdf
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdf
 
Enabling GenAI Breakthroughs with Knowledge Graphs
Enabling GenAI Breakthroughs with Knowledge GraphsEnabling GenAI Breakthroughs with Knowledge Graphs
Enabling GenAI Breakthroughs with Knowledge Graphs
 
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdf
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdfNeo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdf
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdf
 
Neo4j Jesus Barrasa The Art of the Possible with Graph
Neo4j Jesus Barrasa The Art of the Possible with GraphNeo4j Jesus Barrasa The Art of the Possible with Graph
Neo4j Jesus Barrasa The Art of the Possible with Graph
 

Recently uploaded

Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
panagenda
 
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
?#DUbAI#??##{{(☎️+971_581248768%)**%*]'#abortion pills for sale in dubai@
 

Recently uploaded (20)

AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of Terraform
 
Ransomware_Q4_2023. The report. [EN].pdf
Ransomware_Q4_2023. The report. [EN].pdfRansomware_Q4_2023. The report. [EN].pdf
Ransomware_Q4_2023. The report. [EN].pdf
 
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin WoodPolkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
 
Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptx
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
 
[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf
 
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
 
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsMS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectors
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
 
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challenges
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
 
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor Presentation
 

Graph based real-time inventory and topology for network automation - webinar 30 apr 2019

  • 2. Teemu Nykänen Service Architect at Elisa Jesús Barrasa Director Telco Solutions at Neo4j
  • 4.
  • 6. Challenges / Requirements Capture Complexity Allow Flexibility High Performance Rich, Dynamic, Flexible Graph Model on a Native Graph Platform
  • 8. Adoption Highlights 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
  • 10.
  • 11. Elisa Software Defined Networking Graph based real-time inventory
  • 12. • What Elisa does and why should you care • Network automation (zero touch included, no added sugar) • Beauty benefits of graph databases • Your guide today: • Teemu Nykänen, Service Architect (teemu.nykanen@elisa.fi) Introduction
  • 13. First in Finland and in the world 1882: 1929: 1936: 1950: 1991: 1993: 2007: 2010: 2011: 2015: 2019: Daniel Wadén brings the telephone to Finland. The telephone network in Helsinki is automated. The speaking clock service is introduced. The Helsinki Telephone Association builds a telephone network with four switchboards for the Olympic Games. A GSM telephone call is made over the Radiolinja network. A GSM data call takes place over the Radiolinja network. Thanks to the commercial UMTS900 network, the 3G network can be built quickly all over Finland. The 4G network taken into pre- commercial use. The Elisa Viihde service combines a modern TV service and the ability to watch recordings using a tablet. Elisa Internet of Things (IoT) service package launched in Finland and Estonia Commercial 5G
  • 14. Elisa key figures 2.8 million customers, Finland and Estonia 25.4 (21.1) customer satisfaction (NPS) 2018 Approx. 185,000 shareholders 4,800 (4,700) Elisa employees #1 Finland, #2 Estonia market position €1.83 billion (1.79) revenue 2018 €1.95 (1.86) comparable earnings per share (EPS) 2018 €254 million (240) capital expenditure investments 2018 4.66 million (4.68) mobile subscriptions, Finland and Estonia 2018 696,500 (692,300) fixed broadband subscriptions 2018
  • 15. Leading market position in Finland Mobile subscriptions Fixed network subscriptions Elisa 40% Telia 32% DNA 28% Elisa 35% Telia 29% ~20 Finnet companies 8% Others 2% DNA 26% Source: FICORA Source: Company reports Q3/2018 Post-paid market shares: Elisa 40%, Telia 34% and DNA 26%
  • 16. Digital services for international markets Innovative managed services and solution provider for large enterpise video conferencing Providing automation solutions to telcos for zero-touch network processes Solution for manufacturers to enable better decisions, reduce downtime and improve quality
  • 17. The best network, the best customer experience • We offer fast broadband connections implemented using the best possible technologies • Elisa’s 4G network covers 99.8% of Finland’s population • Connections up to 1 Gbit/s are available to more and more households • We are the first in world to build a 5G network, and soon we will offer 5G services to all Finns • We focus on quality and on continuously improving our customers’ user experience • We prevent disturbances with the help of automation
  • 18. • SDN with Elisa twist à Elisa Software-defined Networking • ”Facilitates network management and enables programmatically efficient network configuration in order to improve network performance and monitoring” • Not just for fancy things but also for devices à Hybrid networks Codename EDN
  • 19. • Enables automation for network. From CLI towards Intent Driven network • Service activation/provisioning • ”Zero touch” functionality • Telemetry collection • Network optimization (closed loop with telemetry data and machine learning applied ) • Multivendor (and protocol) capable. (take the power back) • Multiple domains. IP/MPLS currently under construction • Building things for our own needs but also planning to make parts of it commercially available • Available from your local dealer at later in time and space • Situational awareness required Codename EDN
  • 20. • Nothing to see here. Just some: • Nodes • Edges • Vertices • Connections • Required for true automation • Essential piece in the EDN puzzle • Graph database fits like a glove Network topology view (in real-time please)
  • 21. • It’s alive! We’re in production with few services released. • Causal cluster filled with nodes and connections • One microservice to kill rule em’ all • Several data streams • Element managers • Network discovery • Telemetry events • Once more, automation. • Most of the graph is not exposed via UI • Sharing data for analytics, anomaly detection etc. State of a nation
  • 23. • Around 1.3 million nodes and 1.9 million connections • To date, we have modelled: • Physical layer (which can also be virtual) • Part of the logical layer (portion of the services of IP/MPLS network) • To be continued… So far so good
  • 24. • Other good graph databases in the market • We even have in-house experience of some of them • Querying and the power of Cypher • Not just a graph but native labelled property graph. • Maturity • In-house deployment Why neo4j?
  • 25. • Elisa is awesome • Finns are using loads of data. Also beware of angry 5G. • Train it with automation instead of tight leash. • We sell things • SDN is nice EDN is nicer • Cooler than being cool is ice cold. • Did I already mention automation? • Know your enemy network! Store it into graph, you won’t regret it. • Make nodes not tables Summary
  • 26. Thank you! Follow our journey on Facebook (@elisasuomi) and Twitter (@ElisaOyj)