architecting iot for the cloud - a case study

dreamfactoryBen Busse@benbusse

benbusse@dreamfactory.com

Architecting IoT for the CloudA Case Study

About DreamFactory

Open Source Software Apache licenseQ4 2013 - Version 1.0 Q1 2015 - Version 2.0 Strong developer and cloud vendor adoption

REST API PlatformRun-time server softwareAuto-generates APIs for SQL, NoSQL, file storage

Use CasesREST APIs and server-side security for enterprise mobile apps REST APIs for IoT data

Development Process

DreamFactory provides REST API Services to your

data

Build apps for phone, tablet, desktop or IoT

device

Install Connect Develop

+ =Install

DreamFactory on IaaS cloud, PaaS cloud, or server

Unified REST Interface

SQ

LN

oS

QL

Files

SQL

NoSQL

Files

Fragmented APIsDreamFactory

FramTack IoT Case Study

Software Vendor

Solution Family Product for IoT Solution Engine for processing IoT dataSolution Builder for configuring data collectors,

rules, and statistics Reduces cost and time required to build IoT engine

yourself

Building Automation Use Case

6

Solution Family Suite

Edge

SolutionEngine®

Data Model

Clouds

Storage

Analytics

Appliances

IoT Data Flow

2. Analyze Data

Solution Builder®

1. Get Data

3. Send Data to/from Cloud

4. Control the Appliance5. Build Dashboards

Building Automation Example

Intel Gateway

Intel Gateway + PLC

Temperatures Pressures

Solution Engine®

Steam Room

Intel Gateway + PLC

Temperatures Pressures

APT1 Lobby

Pump Room Space Temps

Electric Meter

Analytics

From Sensor to End User

Solution Builder

Solution Engine

Mobile App Dashboard

DreamFactory Admin Console

Service Platform

Solution Family Products

IOT Data to Cloud via REST

Alerts and Analytics via RESTDB Connection, Schema, Data

10

Dashboard Builder

7/10/13

Discussion

Data explosionWhat data is actually useful for end users?

• Transactional vs aggregated data• Tolerance thresholds for alerts• Learning from false positives and false negatives

Where does data processing occur (e.g. gateway vs cloud)?• Complexity of analysis• How transient is the data (e.g. one day vs one month)?

IoT trade-offs Business Requirements – e.g. what data matters, what

frequency?Cost – e.g. API calls, bandwidth, storageSpeed – e.g. how “real-time” must the data be?Scalability – related to data explosion considerations

above

Thank You!

QUESTIONS

benbusse@dreamfactory.comnat.frampton@solution-family.com