+ = Vernetzte Fahrerassistenzsysteme (BMW + AWS ) Hazard Preview Andreas Winckler BMW EE-51 Location Based Services Walter Pernstecher AWS Enterprise Account Management
Gartner Magic Quadrant for Cloud Infrastructure as a Service, Worldwide *Gartner, Magic Quadrant for Cloud Infrastructure as a Service, Worldwide, Leong, Lydia, Petri, Gregor, Gill, Bob, Dorosh, Mike, August 32016 This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from AWS : http://www.gartner.com/doc/reprints?id=1-2g2o5fc&ct=150519&st=sb Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
AWS Global Footprint 1 of 12 AWS world-wide AWS regions Redundant path to transit centers Transit centers connect to: Private links to other AWS regions Private links to Direct Connect customers Internet through peering & paid transit Metro-area DWDM links between AZs 82,864 fiber strands in region AZs <2ms apart & usually < 1ms 25 Tbps peak inter-azs traffic 1 of 30 AZs world-wide All regions have 2 or more AZs Each AZ is 1 or more DC No data center is in two AZs Some AZs have as many as 6 DCs DCs in AZ less than ¼ ms apart Don t need inter-az independence Do require low latency & full B/W > 1 million customers in 190 countries 13 regions (Germany is one region) 35 availbility zones (AZs) 56 edge locations
Use the AWS Cloud as a part of your BMW IT Infrastructure Security, Rules Profiles Corporate Data Centers BMW On-Premises Resources Integration Cloud Resources secure Hybrid customer IT environment Global Cloud = BMW Cloud framework and governance model (supported by FG94)
AWS Portfolio TECHNICAL & BUSINESS SUPPORT Support Professional Services Partner Ecosystem Training & Certification Solutions Architects HYBRID ARCHITECTURE Integrated Networking Direct Connect Identity Federation Integrated App Deployments Business Apps ANALYTICS Data Warehousin g Business Intelligence Hadoop/ Spark Streaming Data Analysis Streaming Data Collection Machine Learning Elastic Searc h Identity Management Business Intelligenc e APP SERVICES Access Control Queuing & Notifications Workflow Search Email Transcoding DevOps Tools Key Management & Storage MOBILE SERVICES API Gateway Identity Sync Mobile Analytics Single Integrated Console Push Notifications MARKETPLACE Securit y DEVELOPMENT & OPERATIONS One-click App Deployment DevOps Resource Management Application Lifecycle Management Containers Triggers SECURITY & COMPLIANCE Monitoring & Logs Resource Templates Configuration Compliance Networking Web application firewall Databases IoT Rules Engine Device Shadows Device SDKs Device Gateway Registry Assessment and reporting Storage ENTERPRISE APPS Virtual Desktops Sharing & Collaboration Corporate Email Backup Resource & Usage Auditing Account Management Data Backups Compute VMs, Auto-scaling, & Load Balancing Storage Object, Blocks, Archival, Import/Export CORE SERVICES CDN Databases Relational, NoSQL, Caching, Migration Networking VPC, DX, DNS Security & Pricing Reports Integrated Resource Management Regions INFRASTRUCTURE Availability Zones Points of Presence
HAZARD PREVIEW PROJECT OVERVIEW & LESSONS LEARNED WITH AWS Andreas Winckler, EE-51
3 HAZARD PREVIEW 2016: A COOPERATIVE CLOUD BASED DRIVING ASSISTANCE SERVICE. Data processing and identification of affected vehicles Location Platform High-Precision Map Realtime Data 2 Transmission to Location Platform 4 Following car and driver is alerted 1 Upfront vehicle detects icy road Limited vehicle sensor range Hazard Preview 16.11.2016 Seite 8
HAZARD PREVIEW SYSTEM OVERVIEW. RTTI, existing data stream, enriched with hazard data. Traffic Service Providers HP Backend (this is where all the magic happens) ecall, accident events. Connected Drive Backend Digital map Campaign Mgmt Dynamic data, e.g. DSC events, precipitation, etc. Campaigns Anonymize ddata Collector Hazard Preview 16.11.2016 Seite 9
CONTENT ROLLOUT PLAN. Use case Q4/16 Q1/17 Q2/17 Breakdown (via sensor data) Accident (via automatic ecall) Heavy Rain Hazard Preview 16.11.2016 Page 10
COUNTRY ROLLOUT PLAN. 2016 Q3/16 Q4/16 Q1/17 Q2/17 2017 Hazard Preview Service Germany Switzerland France USA Canada Italy Belgium Netherlands Austria United Kingdom Anonymized data collection Germany Switzerland France USA Canada Italy Belgium Netherlands Austria United Kingdom Hazard Preview 16.11.2016 Page 11
HAZARD PREVIEW ARCHITECTURE OVERVIEW. Traffic Service Provider Hazard Preview 16.11.2016 Page 12
INTEGRATION WITH VEHICLES AND BMW CORPORATE NETWORK. Vehicle uses dedicated Proxy and Connected Navigation Gateway. Communication to AWS Ireland via Internet (no leased line). Connection secured with: o 2-way TLS (encryption terminates at the instance). o IP-Filtering. o End-to-end authentication. + Cheap, secure, scalable. No QoS due to standard internet connection. Hazard Preview 16.11.2016 Page 13
RECEIVER-WORKER DESIGN PATTERN. Based on Elastic Beanstalk Worker Environment Tier pattern. Receiver acts as https endpoint, quickly acknowledges incoming data. Asynchronous processing of ressource-heavy tasks in Worker. Receiver and Worker scale dynamically and independently. Pure Java. + Highly scalable, reacts quickly to load peaks. + Optimal ressource utilization, even under low load conditions. + Robust, loosely coupled system. o Might be replaced by a serverless solution in the future. Hazard Preview 16.11.2016 Page 14
LESSONS LEARNED WITH AWS. Rock solid. No serious issues so far. The AWS toolbox of cloud services fulfills all our needs in the project. Integration with BMW corporate network doable, optimized solution with QoS pending. Economical solution due to excellent scalability and dynamic ressource utilization. Perfectly supports agile development and devops model. Looking forward to IoT and serverless solutions with Lambda. Hazard Preview 16.11.2016 Page 15
Questions?
Thank you and further contact Walter Pernstecher Enterprise Account Management pernstec@amazon.de Twitter: @pernstecher Kontakt BMW Andreas Winckler : Andreas.Winckler@bmw.de