Opportunities in the digital economy Plamen Nedeltchev, Ph.D., Cisco IT Distinguished Engineer Skolkovo, Russia October 27, 2016
Cloud Infrastructure Challenges Agenda 1
Evolution of the revolutions
2
Internet of things
3
“Every successful business will be digital”
4
Cisco leading the way
Evolution of the revolutions Revolution
Year
Outcome
1st
1784
Steam, water, mechanical production equipment
2nd
1870
Division of labor, electricity, mass production
3rd
1969
Electronics, IT, automated production
4th
?
Digital, Cyber-physical, Cyber-bio systems
The pace is exponential – why and why now? The Laws
The Enablers “Fixed” Computing
Mobility/BYOD
go to the device) BW(The device goes with you) IPv6,(You Storage,
Internet of Things
Internet of Things
(Age of Devices)
(People, Process, Data, Things)
50B things 200M
Doubled every 1.4 years
10B
Doubles every ? years
Renewable, Doubled everydistributed energy 1.3 years
1995 2000 Driverless cars, drones
2011
2020
Global Food Waste
Region
Waste (tons)
North Africa
36M
North America/Oceania
113M
Latin America
134M
Sub-Sahara Africa
137M
Europe
207M
East Asia
381M
West/South/Southeast/Central Asia
449M
Global Water Waste Brazil
USA
8,233 Gm /year 3
FAO More Code
Country
Avg precipitation 1961-1990 (km3 /year)
Internal Resources: surface (km3 /year)
than 2.8 billion people in 48 countries will face water stress or scarcity Brazil conditions by15236 2025. By the5418 21 middle of the century, this will have reachedRussian almost 7 billion. 185 7855 4037 Source: WaterFootprint.org and WWF Federation
Russia
4,507 Gm /year 3
Internal resources: groundwater (km3 /year)
Internal resources: overlap (km3 /year)
Internal resources: total (km3 /year)
1874
1874
788
China
3,069 Gm /year 3
Indonesia
2,896 Gm /year
2,838 Gm 3/year
3
External resources: natural (km3 /year)
External resources: actual (km3 /year)
Total resources: natural (km3 /year)
Total resources: actual (km3 /year)
IRWR/ inhab. (m3 /year)
5418
2815
2815
8233
8233
31795
512
4313
195
195
4507
4507
29642
33
Canada
5352
2840
370
360
2850
52
52
2902
2902
96662
101
Indonesia
5147
2793
455
410
2838
0
0
2838
2838
13381
41
China, mainland
5995
2712
829
728
2812
17
17
2830
2830
2245
44
Colombia
2975
2112
510
510
2112
20
20
2132
2132
50160
231
Continental USA
5800
1862
1300
1162
2000
71
71
2071
2071
7153
170
Peru
1919
1616
303
303
1616
297
297
1913
1913
62973
100
India
3559
1222
419
380
1261
647
636
1908
1897
1249
Inching toward Utopia…
A harvest alert could let vintners know precisely when grapes are perfectly ripened?
Factories could produce better goods more efficiently?
We could bring healthcare to where there is none and better scale existing resources?
We could eliminate food waste and feed millions more people?
We could track any device – virtual or physical – and eliminate theft and loss?
We could track and better conserve our essential natural resources?
10 emerging technologies will lead the way
INTERNET of
THINGS
IoT Value at stake
$4.6T
$19T
$14.4T
Cisco estimates for VAS of IoT = $19T PROCESS
People to People (P2P)
PEOPLE People to Things (P2T)
Architectures Cloud / Mobile / Secure Big Data / Analytics THINGS
Network value = #Connections2 200M à 10B à 50B à 500B2
Data to Process (D2P)
DATA
Machine to Machine (M2M)
What is the value? IoT – Fast Innovation Manufacturing
Retail
Oil + Gas
$3.9T
$1.5T
$504B
Finance
Healthcare
$1.3T
$1.1T
Manufacturing
Retail
Oil + Gas
Finance
Healthcare
• • • • •
• • • • • •
• • • •
• NG Business Models • Service Profitability • Cloud and ACI à Deploy with Speed • Cross Selling
• • • • •
Productivity + Efficiency Improved Security Improved Visibility and Control Optimized Operations Decreased Downtime
Mobile/BYOD Video/Social/Voice Change Customer Experience Connected Marketing Increase Sales, Productivity Lower Operating Costs
Reduced TCO of IT Reduced Downtime Improved IT, Asset Utilization Enhanced Security
Improved Productivity Operational Efficiency Resource Utilization Compliance Improved Outcome
IoT Country by Country Value at Stake (VAS) Country
VAS-Public ($B)
VAS-Private ($B)
Total ($B)
India
$116.2
$23.5
$139.7
Africa
$128
$362
$490
Middle East
$210
$442
$652
Russia
$57.1
$216
$273.1
UAE
$6.9
$46.0
$52.9
Germany
$177.8
$736
$913.8
Netherlands
$49.7
$188
$237.7
USA
$585
$585
Japan
$109.2
$109.2
China
$291.5
$1757.2
$2,048.7
South Korea
$45.7
$204.8
$250.5
France
$182.6
$537.4
$720
UK
$173.4
$537.4
$710.8
Australia
$25.9
$241.7
$267.6
Mexico
$34.3
$163
$197.3
Canada
$92.8
$92.8
Russia: $57.1B VAS Public Sector $4.6T
$7.1B
Citizens • Chronic Disease • Telework • Smart Payments • Counterfeit Drugs
$57.1B
$50B
Cities • Cyber Security • Mobile Collaboration • Transmission Grid • BYOD
Implementing an IoT for the Public Sector in Russia could generate an estimated $57.1B of value
Russia: $57.1B VAS Public Sector Detailed public sector use case values ($M) Video Surveillance
$540
Disaster Response
$148
Smart Parking
$380
Smart Buildings
$1,082
Smart Street Lighting
$0
Correction Visits
$145
Waste Management
$89
Bridge Maintenance
$21
Road Pricing
$162
Wildfire Suppression
$25
Public Transport
$235
Fleet Management
$141
Offender Transport
$25
Local Metro
$160
Telework
$2,029
Travel
$3,584
BYOD
$4,605
Payments
$1,922
Connected Museum
$2
Smart Tollbooths
$10
Connected Learning
$771
Chronic Disease
$4,191
Gas Monitoring
$1,320
Inpatient Monitoring
$61
Water Management
$431
Counterfeit Drugs
$1,620
Smart Xmission Grid
$12,575
Cybersecurity
$9,871
Mobile Collaboration
$10,438
Drug Compliance
$239
Smart Lotteries
$85
Virtual Desktop
$206
Russia: $216B VAS Private Sector $14.4T
$157B
Vertical • Connected Marketing/Advertisement • Smart Factories • Connected Gaming/Entertainment • Innovative Payments
$216B
$59B
Cross-Vertical • Future of Work • Time-to-Market • Supply Chain Efficiency • Travel Avoidance
Implementing an IoT for the Private Sector in Russia could generate an estimated $216B of value
Russia: $216B VAS Private Sector Detailed private sector use case values ($B) Connected Commercial Vehicles
$7.8
Smart Buildings
$5.7
Smart Farming
$4.3
Wealth Management
$7.3
Physical/Logical Security
$17.8
Next-Gen Retail Bank Branches
$0.3
Smart Factories
$26.7
Next-Gen Vending Machines/Digital Malls
$1.5
Business Process Outsourcing
$12.1
Connected Gaming/Entertainment
$19.2
Innovative Payments
$18.6
Connected Marketing/Advertising
$31.9
Future of Work
$18.5
Digital Signage
$1.2
Travel Avoidance
$8.4
Virtual Attendants
$2.7
Supply Chain Efficiency
$15.6
Time-to-Market
$16.9
Every successful business will be digital
Why Companies Are Focused on Digitization Top of Mind OPERATIONAL EFFICIENCY
46% 34%
CUSTOMER SERVICE INTRAORGANIZATIONAL COLLABORATION
31%
STRATEGIC DECISION MAKING
29%
PROFITABILITY
25%
REVENUE GROWTH
24%
INNOVATIVENESS
23%
EMPLOYEE SATISFACTION
22% 15%
DATA AND PHYSICAL SECURITY INTERORGANIZATIONAL COLLABORATION
13%
TIME TO MARKET
12%
DO NOT KNOW
1% 0
Source: Business Insider/Cisco (global survey of 7000 executives)
0,05
0,1
0,15
0,2
0,25
0,3
0,35
0,4
0,45
0,5
“Digitizing” the Operating Model
Simplification
Monitor & Adapt
Automation
Continuous Innovation
Security Strategic Outcomes Reengineered
Flexible Assets E2E Policy-Based Architecture
Federated Analytics Measurable Insights (Machine Learning)
Collaboration (People & Machine)
IT and OT integration
Remote Access
Industrial Router
Local Access
Industrial Switch
WAN
Industrial Access Point
Data Center
Industrial Video
Cloud
Industrial Sensor 22
The Data Grows Exponentially Big Data is the New Normal
30
Data Center
Cloud Data: 64% will be in the Cloud (UP from 40% in 2012); Only 36% will be in traditional DCs (DOWN from 60% in 2012)
25
Global Mobile Traffic reached 190 EB/year by 2008 and will reach 25 EB/year by 2020
20
16,1
15
10,7
10 5
24,3
57% CAGR 2014-2019
2,5
4,2
6,8
0 2014 2015 2016 2017 2018 2019
Exabytes per Month
Mobile
Cloud Major consumers / generators of traffic will be M2M, wearables, smartphones, tablets and laptops
Mobile Video will be 70% of all the traffic. Cloud will host 90% of all the mobile traffic
Smart Home
Big Data is the new normal – the triple “V” The “N” dimension – the N data is the Big Data
What do I do with all this IoT data? Corp. Traffic 60%
90% Unstructured
On the edge
40% 80% of traffic will be inside the Data Center; 7% DC to DC; 13% DC to Users
Widely-distributed, short shelf life, too big to move
Streaming data at massive scale Store and analyze Analyze before you store Replicate, Parse
New Skill Set in IT Cisco Data Preparation
Clean and change
Business Analysts Data Engineers
Data Virtualization Files Databases SaaS Apps
Combine
Explore
Data Scientists
Share & Govern DBaaS
AnswerSet
Add data
XML Docs Hadoop NoSQL
Publish Desktops
Shape
Enrich
The IT professionals Hownew do you prepare? Techniques § § § §
A/B Testing Crowdsourcing Data fusion and integration – Data integration. Genetic Algorithms – In the field of artificial intelligence, a genetic algorithm (GA) is a search heuristic that mimics the process of natural selection
New Skill set • • • • • •
Machine Learning Natural Language Processing Signal Processing Simulation Time series analysis Visualization
Languages and Solutions: • • • • • •
PIG, Go, R, Python MapReduce Column-oriented databases Schema-less database (NoSQL databases) Hadoop Hive 26
Cisco’s IoT Architecture and Control Point Distributed Platform … Computing, Storage, Networking Data Center Cloud Core Networking and Services
Multi-Service Edge
Embedded Systems, Machine-to-Machine Sensors
Centralized Intelligence
Distributed Intelligence
Distributed Intelligence: Fog Computing
IP/MPLS Core
Field Area Network
Smart Things Smart Things NetworkNetwork
Big Data challenge in Security Today, in DNS and TCP/IP queries alone, • What’s on the Cisco Network? about 0.5 TB of raw data is collected daily; with new architecture, that number will increase to 4TB • • • • • •
1.1M public IPv4* addresses plus 1.7M private addresses 125,000 Windows, 72,000 Linux, 50,000 Cisco devices, 43,000 “other” 120,000 IP phones 30,000 Data Center hosts 1820 labs, 100,000+ devices 2400+ IT applications supporting 835 service offerings
• 16 major Internet connections, ~32 TB bandwidth used daily • 66k employees + 33K contractors in 165+ countries (475+ offices) • 294 partners using 547 IT extranet connections into Cisco • 400+ cloud/ASP providers used (officially) *Most users do not have IPv6 dual-stack support; the transition to IPv6 is in progress
28
Types of Analytics
How can we make it happen?
Value
What will happen?
What happened?
Why did it happen?
Predictive Analytics
Diagnostic Analytics
Descriptive Analytics
Difficulty
Prescriptive Analytics
Cisco leading the way
Digital IT and Technologies of Digital Economy The top 10 IoT Technologies for 2017-2018 IoT Security
IoT Analytics
IoT Device Management
Low-Power, Short-Range IoT Networks
Low-Power, Wide-Area Networks
IoT Processors
IoT Operating Systems
Event Stream Processing
IoT Platforms
Standards and Ecosystems
The top 12 IoT Common Services for 2017-2018 Location
Virtual Reality
Haptics, ZUI, Voice, Vision
Presence
Contextual Services
Gesture Recognition
Behavior
Artificial Intelligence
Voice Recognition
Image Recognition
Proximity
Reality Augmentation
Cisco IT Digital Architecture Business Intelligence
Advanced Threat Defense and Risk Mitigation
Business Process Management
Application-Centric IT/IoT SDN Controller
Policy Management
Distributed Fast Data Processing
Infrastructure Data Foundation
Foundational Network
Domain Management and Orchestration
Predictive Analytics Data Science
Emerging Technologies of the Digital Economy Artificial Intelligence
Robotics
Internet of Things
Autonomous Vehicles
3D Printing
Nanotechnology
Biotechnology
Material Science
Energy Storage
Quantum Computing
Who is who in IoT The opportunities of the technological companies in the new world – June 2016 Business and Technology Consulting
IoT Apps/Sls
OT Services/ Edge OEMs
IoT Platforms
CSPs
Infrastructure/ Semiconductors
Digital Operations Management
Boston Consulting Group
Accenture
Black & Veatch
Ayla Networks
AT&T
Amazon Web Services
Genpact
Deloitte
Atos
Bosch
IBM
Deutsche Telekom
Cisco
HCL Tech
EY
Capgemini
GE
Microsoft
Sigfox
Fujitsu
HPE
KPMG
Cognizant
Hitachi
Oracle
Telefónica
Google
IBM
PwC
IBM GBS
L&T Infotech
SAP
Vodafone
Intel
Taleris
McKinsey & Co.
Infosys
Rockwell
Telit
Verizon
Microsoft
UPS
Mindtree
Schneider
ThingWorx
Salesforce
Zerox
TCS
Tech Mahindra
Xively
SAP
Wipro
Source: Gartner (June 2016)
Cisco opportunities by Gartner Security
Data Management and Analytics e.g. Big Data, Data Mining, Analytics, Machine Learning
Enterprise Systems
Business Systems e.g. ERP, Custom Applications, Industrial Control Systems, Websites
IoT Middleware and Platforms IoT Cloud Services Telco M2M Platform
Gateway/Aggregation
“Things” On-Device Functions
Source: Gartner (June 2016)
On-Device Agents
External Devices and Apps (e.g. Mobile, PC)
IoT Technology Stack Cloud and Fog
Applications
Analytics
Software Platform IoT Software IoT Platform Applications
Security and Identity Management
Things Open and Infrastructure Infrastructure Programmability (APIs) Ease of use and Management
Things
From Raw Data to Better Business Outcomes Cisco Data Preparation Clean and change
Business Analysts Data Engineers
Data Virtualization Files Databases SaaS Apps
Combine
Explore
Data Scientists
Share & Govern DBaaS
AnswerSet
Add data
XML Docs Hadoop NoSQL
Publish Desktops
Shape
Enrich
35
Databases ALL other Sources
Conventional Data Platform Architecture Sources
Storage and Processing
Consumption
Cisco Data Virtualization (Composite)
Integration Toolkit
Logical Data Abstraction Layer across transactional, SaaS, Big Data & DW B2B
Relational Databases
Agile Analytics
Golden Gate
SAP HANA on UCS
NoSQL Databases
Hadoop & Spark on UCS
SaaS Applications • • •
Unstructured Data, IoT
• •
Big Data Platform
•
In-Memory Columnar DB Fast Agile Development
Network of Truth Mission Critical Reporting
Enterprise Data Lake Data Archive Warehouse Expansion Multiple frameworks for Processing
Legacy EDW • • •
Financial SSOTs Stable core Controlled Change
Partner / Customer Integration
APIs & ESB
CIS Web Services
Cisco Data Virtualization (Composite)
Ingestion
(Mobile / Browser / Data Service)
Experience Toolkit
Rapid Prototyping / Logical Warehouse Self Service (Exploration & Dashboards) High Value / Fast response Real time Predictive
Large scale data processing + Self Service Machine Learning, Statistical Analysis Structured + Unstructured Data Analysis Advanced Analytics HANA
Mission Critical Operational Reports
Mahout, Spark SAS IT App & System Logs & Config.
Operational Intelligence
Index & Search
H2O
Financial Reporting & Extract Ops Intelligence & Data Acceleration
IoT Data Collection and Distributed Processing Edge / DC
real-time
(network/ computer/storage, domain managers, 3rd party monitoring apps)
OSS/NMS apps
IoT
Policy and Autoscale Manager
Publish/subscribe
Analytics
Telemetry (netflow)
Logs (app, web)
IoT Stream Data (mobile devices, sensors, processes, people)
Data Source
Cloud/DC
Data Collection Platform (DCP)
Events
Metrics (local data aggregation)
Collectors w/ Protocol Adaptors (Netflow, Syslog, HTTP, MQTT, DDS, CoAP, etc.)
Fog (IoT)
Data Transformer (data clean and repurpose)
Large Data Downloader
Data Aggregation
Distribution
37
Operations Dashboards
Network Analytics (SDN, SLN)
Business Reports
Log Analysis (Clap, Splunk)
Service Assurance Analytics Short term, transactional data
Local Analytics
Sensor Telemetry
Data Lake
(location, sensors, etc.)
(Perf, Fault, Change, Capacity, Dependency)
Orchestration
(SLA, Fulfillment)
Remedy Ticketing
…
Long term, historical data
Security and Threat Analytics
IoT BI Apps
Data Store
Analytics
Applications
Stealthwatch Stealthwatch Learning and Positioning Summary • • • •
We can sell both , and be clear on SLNL unique Cisco embed features Multiple AD Engines used in different places is not a bad thing, and it’s actually a good thing Machine Learning in SLNL is a new technology showing Cisco innovation in the NBAD Space Roadmap does call for phasing SCA into SMC, and preserving unique feature like PCAP Stealthwatch Learning Agent Manager (SCA)
Stealthwatch Management Console (SMC)
ISE Manager
Best of Breed Portfolio
Private / Public Network
• PCAP Packet Analysis • Mitigation ACL
Branch Network
Any Routers with Netflow
ISR4K with Stealthwatch DLA Agent
Unique Architecture Choices
Contextual Services Deliverables Distribution platform for continuous delivery
Self-learning Contextual Services Engine and Personalization Services Engine Cross-platform real-time contextual services clients
Business Benefits / ROI Seamless Workflow
Insights for more focused and relevant customer interactions Real-time information to help close deals
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