IoT and Edge Computing

Satyam VaghaniVP & GM, IOT & AI

Where is everybody?

N O T P U B L I C C L O U D P U B L I C C L O U D

Private DCs 201732 million nodes

Top-3 providers 20173.5 million nodes

Enterprise IoT 20173.135 billion devices

Enterprise IoT 20207.5 billion devices

Sources: Gartner, IDC

A New Paradigm Needs a New OS

HUMANS DATACENTERS THINGS

DESKTOPWindowsMac OS

MOBILEiOS

Android

PRIVATE CLOUDvSphereAcropolis

PUBLIC CLOUDAWSGCE

?

No, Not That OS

Scope of an IoT OS

2017 2020

Cloud traffic

8.6 ZB 15.3 ZB

2017 2020

IoT data

256 ZB

600 ZB

Key Change: Edge Trumps Cloud

Sources: Cisco Global Cloud Index, Memoori

AFTER

AFTER

BEFORE

Data IngestionReal-time

ProcessingLong-termProcessing

Real-timeProcessing

Long-termProcessingData Ingestion

Key Consequence: The Intelligent Edge

SENSORS

SENSORS

CLOUD

CLOUD

EDGE COMPUTING

IoT GATEWAY

The Intelligent Edge is Not Ready

TWO PROBLEMS PREVENT WIDESPREAD ADOPTION• Distributed infrastructure burden• Domain expertise burden

A Smart Airport ExampleTOPOLOGY

Airport 1 (of 10)

2000 x

100 x

250 x

A Smart Airport Use CaseOBJECT OF INTERESTLook for a red car at airport(s)

SFO AIRPORT (EDGE) CLOUD

...10:41AM: redcar=010:42AM: redcar=110:43AM: redcar=010:44AM: redcar=0...

...10:41AM: SFO, redcar=010:42AM: SFO, redcar=110:43AM: SFO, redcar=010:44AM: SFO, redcar=0...

EXPLICIT DISTRIBUTED SYSTEMS, MACHINE LEARNING, IMAGE RECOGNITION, SECURITY, STORAGE, NETWORK PROGRAMMING, AND MORE

IoT Infrastructure Burden: Apps Span Edge and Cloud

Train model to recognize red car

Deploy model to selected edges

Runtime for car recognition model

Persistence for surveillance feed

Sampling surveillance feed to match model

input requirements

Persistence of image recognition time series output Data mover to

move time series output to cloud

Persistence for time series data in cloud

App runtime in cloud

Security

business logic

infrastructure madness

IoT Development Burden: Domain Knowledge

IoT APP CREATION REQUIRES DOMAIN EXPERTISE IN MULTIPLE AREAS

Analytics Machine Learning Security

Data Pipelining Cloud Services …etc.

Don’t try this at home

Machine Learning

Reduce infrastructureburden

Reduce developmentburden

An Ideal IoT “OS”: Hyperconvergence 3.0

EDGE CLOUD

Sensor services

Data services

App services

App services

Data services

ENABLE RAPID DEVELOPMENT OF IoT APPS

MAKE IoT INFRASTRUCTURE SEAMLESS + INVISIBLE

2

1

DemoHIGHLIGHTS

• Multi-tenant application runtime across Edge and Cloud• 1-click data pipelines across Edge and Cloud

MAKE IoT INFRASTRUCTURE SEAMLESS + INVISIBLE 1

• Modular functions for rapid development of IoT apps

ENABLE RAPID DEVELOPMENT OF IoT APPS2

Global time

series in cloud

Time

series

Modular Functions for Rapid Development of IoT Apps

FUNCTIONDatastream

in

Datastream

out

Parameters

VIDEOPROCESSING

OBJECTRECOGNITION

DATAMOVER

Image

stream

Live video

sample, crop redcar, presence Google, structured

person, count

Persistence

Runtime

High level IoT OS Architecture

Data Ingestion

Sensor Actuation

Real-time Data Service

Unstructured Data Service

Structured Data Service

Data Bus

Machine Training

Streaming Analytics

Custom Code

Control Plane

Operations Console

Developer Console

SENSORS

Machine Training

Long term Analytics

Custom Code

Streaming Data Service

Unstructured Data Service

Structured Data Service

EDGE CLOUD

LONG TERM PROCESSINGREAL TIME PROCESSINGINGRESS

MUCH BIGGER THAN IoT

Persistence

Runtime

The Long View: A Data and Code Hypervisor for Hybrid Apps

Data Ingestion

Data Archival

Streaming Data Service

Unstructured Data Service

Structured Data Service

Data Bus

Machine Learning

Streaming Analytics

Custom Code

Control Plane

Operations Console

Developer Console

DATA LAKE

Machine Training

Long term Analytics

Custom Code

Streaming Data Service

Unstructured Data Service

Structured Data Service

LOCAL CLOUD OTHER CLOUDS

REMOTE PROCESSINGLOCAL PROCESSINGINGRESS

Use casesA RANDOM WALK• Your doctor’s office• At Great Mall• The airline. And the government. And an airport authority• ONG services• The car company• The county

GTM experiences

Thank YouSatyam Vaghani | @SatyamVaghani