15/06 - Aeris & Cassandra-An IOT Solution Helping Automakers Mak

About Aeris Communications and IOT market trends • The anatomy of an IOT PaaS • Customer challenges in delivering IOT/M2M solutions • The Aeris AerCloud PaaS offering • Evaluating database technologies • Case Study: How automotive OEMs leverage Aeris + Cassandra • Moving forward with Cassandra • Q&A
展开查看详情

1.Aeris + Cassandra: An IOT Solution Helping Automakers Make the Connected Car a Reality Drew Johnson, Vice President of Engineering, Aeris Communications Thank you for joining. We will begin shortly.

2.

3.Webinar Housekeeping All attendees Input questions at any time placed on mute using the online interface

4.Who Am I? Drew Johnson Vice President of Engineering • More than 20 years of experience at both large and small companies • Started career at Compaq Computer working on the first generations of mobile computing devices • Prior to Aeris, Director of Engineering at Austin mobile start-up SoloMio and VP of Engineering at mobile and messaging software company Openwave • Holds a Masters degree in Artificial Intelligence from the University of Illinois and has more than 20 patents Confidential 4

5.Agenda • About Aeris Communications and IOT market trends • The anatomy of an IOT PaaS • Customer challenges in delivering IOT/M2M solutions • The Aeris AerCloud PaaS offering • Evaluating database technologies • Case Study: How automotive OEMs leverage Aeris + Cassandra • Moving forward with Cassandra • Q&A Confidential 5

6.The Future is Here – IoT Trends 30 Connected IOT devices by 2020 billion 90 IOT data in the cloud by 2020 percent 400 Volume of IOT data by 2018 zettabytes Confidential 6

7.About Aeris Communications Enterprise/MNO Cloud-based IoT Automotive Connectivity-as-a- Applications and Applications/ Service Analytics PaaS Services Aeris IoT Platform

8.The General IOT PaaS Anatomy Requirements • Collect and store large amounts of data (time-series, location, sensor data) Location • Reliable / secure • Minimize data transfer Speed Business • Process in NRT for alerts Value • Handle batch/deep analytics Acceleration • Share data in a secure manner • Rapid prototype to production scale • Cost effective Traction Confidential 8

9.Customer Challenges w/o PaaS • Customer developers focused on infrastructure rather than differentiating features - suffering frequent downtimes • Data intake volume (Aeris: Grew from 1B transactions/year to almost 1B per day!) • HIPAA / Data location compliance • Need to derive more value from the data being captured • Wild Wild West on device protocols – have to adapt easily Confidential 9

10.How Aeris AerCloud Works Confidential 10

11.Aeris Technology Map Web Services Data Storage Location Geofence and Search Netty Cassandra Aeris Tomcat Indexing Aeris Queuing MQTT Analytics Netty RabbitMQ Aeris HTTP Push Aeris Confidential

12.Key Database Requirements Support high reliability and Flexible data model with security affordable scalability Structured & unstructured Strong real-time search and real-time data query capability Confidential 12

13.Why Not Relational Databases • Costly/Complex to scale – especially w/ HA • Manual sharding at scale is a pain • Inflexible data model – can’t handle IoT variety of data Confidential 13

14.Why NoSQL and Apache Cassandra • Purpose built for IOT & time-series data • Optimized for storage & retrieval of time-series data • Integrated analytics with Hadoop connector • Fantastic write performance (2B MQTT/day @ 8 nodes) • Simple to manage (No master/slave, shared storage, manual sharding) • Supports 100% uptime through masterless architecture & multi-datacenter replication • Flexible schema allows for faster time-to-market • Commodity storage/instance storage for linear & predictable scale • No lock-in to a specific cloud provider Confidential 14

15.Aeris Automotive Aeris has done especially well in Automotive Confidential 15

16.OEM Case Study • Aeris handling 1M+ vehicles for an OEM • Recently identified key anomaly due to software change • Same analytics engine could identify other vehicle system anomalies Confidential 16

17.Moving Forward Next up for Aeris – key customer areas: • Vehicle telematics – expanding use cases for both make-money and save-money • New verticals – avionics and fleet Our 2 cents: Plan for Big Data and Data Portability from the start! (Cassandra/AWS > AWS alone) Confidential 17

18.Q/A Input questions at any time using the online interface

19. Thank You! Confidential 19