MongoDB .local Munich 2019: Telediagnosis@Daimler powered by MongoDB
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The document outlines the implementation of MongoDB for telediagnosis at Daimler, detailing the use case, architecture, and data access strategies. It highlights the importance of seamless integrated mobility platforms and the transformation of data into business opportunities for connected vehicles. Key sections cover scaling requirements, performance metrics, and the technology's advantages for future mobility services.
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Mongo DB Data - Vehicle Telediagnosis Msg
{
.............
"schema": "3.1.0"
"createdAt": {..},
.............
"vehicleIdentData": {
"chassisNumber": "WDD24708A5432J63",
"countryCode": "4f3490b14e238a5f",
"modelSeries": "f16ad22d42064811",
"modelType": "2196868af1c70d74",
"modelYear": "5e01ac15d73c3e4a",
"steering": "4a3424fe6411461c"
},
"basicData": {
"mileage": {..},
"batteries": [..],
"tanks": [..],
"tiresPressure": [..],
},
"controlUnits": [..],
"affectedFunctions": [..],
"vehicleClusterMessagesData": [..],
"maintenanceData": {...},
..............
}
"controlUnits": [
{
"ecuId": {..}
"name": "a927e49b0549f00f71",
"detailsHardware": {},
"detailsSoftware": {},
"dtc": [
{
"code": "B214F73",
...
"failureText": "81957650ea",
"environmentalData": {...}
},
...
]
},
...
]
Telediagnosis@Daimler powered by MongodDB| Madalin Broscaru,
Daimler AG](https://image.slidesharecdn.com/455pmvds-mongodb-191021133426/85/MongoDB-local-Munich-2019-Telediagnosis-Daimler-powered-by-MongoDB-7-320.jpg)
MongoDB .local Munich 2019: Telediagnosis@Daimler powered by MongoDB
- 1. Telediagnosis@Daimler powered by MongodDB Madalin Broscaru, Daimler AG IT Architect Diagnostics and Connected Car Data
- 2. Telediagnosis@Daimler powered by MongodDB| Madalin Broscaru, Daimler AG 2 About Myself Name: Mădălin Broscaru Role: IT Architect - Diagnostics and Connected Car Data/ Daimler Aftersales Topics: Vehicle Diagnosis / Telediagnosis Aftersales Connected Services Connected Cars
- 3. 3 Agenda • Present our MongoDB use case: Telediagnosis @Daimler • Why Daimler has chosen MongoDB • Data specifics • How data is accessed • Data storage requirements • Our Mongo DB journey • How we started with MongoDB (sizing) • How our Architecture looks like (Sharding, Replicas, Indexes) Telediagnosis@Daimler powered by MongodDB| Madalin Broscaru, Daimler AG
- 4. Seamless integrated mobility platforms will be game changer for future mobility services Connected Vehicles: Digital Transformation requires Game Changers in IT-Support and Operations of Mercedes Benz Cars | Ruediger Schmid, Daimler AG 4 Mercedes me connect E-Mobility Parking Services Car 2 X Communication Autonomous Driving Car Sharing Smart Home User Device Connectivity Mobility Services me CASE
- 5. 5 Telematics as Core Process in the future Mercedes Services Transforming data into business opportunities (e.g. Mercedes connect services, data driven business models, autonomous driving) … the Vehicle Data Conditioning (VDC) where these technical vehicle events are processed … CAC Retail Customer … and the follow-up processes are triggered with real-time recommendations for actions. VDC Vehicles are transmitting regularly status and health data into ... Agregated Quality Analisys Telediagnosis@Daimler powered by MongodDB| Madalin Broscaru, Daimler AG
- 6. 6 Telediagnosis@Daimler powered by MongodDB| Madalin Broscaru, Daimler AG Telediagnosis Data Overview
- 7. 7 Mongo DB Data - Vehicle Telediagnosis Msg { ............. "schema": "3.1.0" "createdAt": {..}, ............. "vehicleIdentData": { "chassisNumber": "WDD24708A5432J63", "countryCode": "4f3490b14e238a5f", "modelSeries": "f16ad22d42064811", "modelType": "2196868af1c70d74", "modelYear": "5e01ac15d73c3e4a", "steering": "4a3424fe6411461c" }, "basicData": { "mileage": {..}, "batteries": [..], "tanks": [..], "tiresPressure": [..], }, "controlUnits": [..], "affectedFunctions": [..], "vehicleClusterMessagesData": [..], "maintenanceData": {...}, .............. } "controlUnits": [ { "ecuId": {..} "name": "a927e49b0549f00f71", "detailsHardware": {}, "detailsSoftware": {}, "dtc": [ { "code": "B214F73", ... "failureText": "81957650ea", "environmentalData": {...} }, ... ] }, ... ] Telediagnosis@Daimler powered by MongodDB| Madalin Broscaru, Daimler AG
- 8. 8 How Data is accessed Controlling Units Failures WDD176039 j540918A84 N10-Signal acquisition module (SAM) MPC-Multifunction Camera Water fluid level too low Today 22 October 2019 9:40 WDD176039 j540918A84 Today 22 October 2019 9:40 MPC-Multifunction Camera Error Frequency: Counter: 3 Ignition Cycle: Counter: 9 Software Version: 15/0930 Hardware Revision:13/0930 Telediagnosis@Daimler powered by MongodDB| Madalin Broscaru, Daimler AG
- 9. 9 Top Requirements • Horizontal Scaling • Support HA • Speed / Fast Response Time • Mature technology, good community • Cost Telediagnosis@Daimler powered by MongodDB| Madalin Broscaru, Daimler AG
- 10. 10 Our Journey with MongoDB: First POC - 1 MongoDB – primary • Ubuntu • 4 Cores • 32 GB • 500 GB SSD 3000 IOPS MongoDB – secondary • Ubuntu • 4 Cores • 32 GB • 500 GB SSD 3000 IOPS JSON Producer MongoDB – secondary • Ubuntu • 4 Cores • 32 GB • 500 GB SSD 3000 IOPS Data Reader • How easy it is ? • Storage requirements for 500 mil EES • Test MongoDB performance • Insight on scaling Telediagnosis@Daimler powered by MongodDB| Madalin Broscaru, Daimler AG
- 11. 11 Our Journey with MongoDB: First POC - 2 rs0:PRIMARY> db.ees.count() 62544261 (62 mil) rs0:PRIMARY> rs0:PRIMARY> db.ees.totalIndexSize() 1404067840 (1,4GB) rs0:PRIMARY> ubuntu@ip-172-31-36-140:~$ : df -h Filesystem Size Used Avail Use% Mounted on udev 126G 8.0K 126G 1% /dev tmpfs 126G 12K 126G 1% /dev/shm /dev/xdva1 41G 7.8G 32G 20% / /dev/xdvb 500G 251G 249G 51% /data/db ubuntu@ip-172-31-36-140:~$ mongostat insert query update delete getmore command dirty used flushes vsize res qrw arw net_in net_out conn 991 432 *0 *0 0 2|0 3.4% 4.5% 0 2.90G 297M 0|0 0|0 12.9m 84.2k 12 989 482 *0 *0 0 2|0 3.6% 4.7% 0 2.91G 310M 0|0 0|0 12.9m 84.1k 12 988 419 *0 *0 0 1|0 3.7% 4.8% 0 2.92G 323M 0|0 0|0 12.8m 83.8k 12 • How easy it is ? • Sizing • Insight on scaling • Performance Telediagnosis@Daimler powered by MongodDB| Madalin Broscaru, Daimler AG
- 12. 12 Mongo DB MVP - Architecture MONGOD MONGOD MONGOD MONGOS MONGOS OPS. Manager MONGOD MONGOD MONGOD MONGOD MONGOD MONGOD MONGOD MONGOD MONGOD MONGOD MONGOD MONGOD SHRD-1 SHRD-2 SHRD-3RS-CFG RS-OPS Telediagnosis@Daimler powered by MongodDB| Madalin Broscaru, Daimler AG
- 13. 13 MONGOD MONGOD MONGOD MONGOS MONGOS OPS. Manager MONGOD MONGOD MONGOD MONGOD MONGOD MONGOD MONGOD MONGOD MONGOD MONGOD MONGOD MONGOD SHRD-1 SHRD-2 SHRD-3RS-CFG RS-CFG Mongo DB MVP - Architecture Telediagnosis@Daimler powered by MongodDB| Madalin Broscaru, Daimler AG
- 14. 14 OPS. Manager MONGOD MONGOD MONGOD RS-CFG Mongo DB MVP - Architecture Telediagnosis@Daimler powered by MongodDB| Madalin Broscaru, Daimler AG
- 15. 15 • Sharding • Using 3 shards from the begining. • Expecting to store up to 2 TB per shard • 3 Replica set node per shard • Using the VIN (chassisNumber) as the shard key • Indexing • VIN (chassisNumber), ECU, DTC Mongo DB - Project Specifics • Collections • Data Migration • Backup • Cloud vs On-Premise • Monitoring • Operations Telediagnosis@Daimler powered by MongodDB| Madalin Broscaru, Daimler AG
- 16. 16 Conclusions Telediagnosis@Daimler powered by MongodDB| Madalin Broscaru, Daimler AG
- 17. Seamless integrated mobility platforms will be game changer for future mobility services Connected Vehicles: Digital Transformation requires Game Changers in IT-Support and Operations of Mercedes Benz Cars | Ruediger Schmid, Daimler AG 17 @Daimler
- 18. Questions ?
Editor's Notes
- #3: Glad to be here with you today Few words about myself
- #4: A quick overview of what I‘m going to show you today Before solution, what is specific to requirement is relevant
- #5: Few words about context Auto industry Middle transformation
- #6: From Future Mobility one lever deeper The telediagnosis usecase where MongoDB comes What happens beyound the scene
- #7: You saw the domain, but how the data looks like? What kind of data a car has Car as a mini datacenter up to > 100 ECUs Engine Control Module, Brake Control Module, Suspension Control Module, Clima, Inteligent Lighting, Clima, Adaptative Driv
- #8: This is how data is looking, oversimplified, human readable Diagnostic Trouble Code
- #9: Saw the data but what about the access? Relevant for sharding, indexes + Cust. Assistance Center + Mercedes Me + Automated valet parking
- #10: Beside all data and access we have also NFRS NFRs ware the triggers for MongoDB, Data and access are enablers
- #11: Do the test drive before you buy Parenting books from people without children Why not as a service
- #12: Transition: And base on the POC we got our own insights. Inserted 62 mil (20 h) W -7-10. R-3-6 Indexes best practices: in memory, serch by index compression 50% W I R E D Tiger Not so many deletes and updates Cloud watch, see Bootleneck: CPU, RAM, NETWORK, IO My advice, make your own experience with it, it helps you understand better the product
- #13: We like what we saw with POC so we move MVP
- #14: Some things are reusable. Idea: Idea what is below is the productive env What is above is the operations
- #15: Transition: What happens if we have multiple env? Idea: in our case, test = prod, only smaller. Why?
- #16: You saw a little on the infrastructure and deployment archtecture What about Coniguration Specifics?
- #17: This is where we are and what worked for us We are at the beginning (no so much aggregation, relations) It will come more and more requirement
- #18: Mongo DB is used to implement the future mobility @ Daimler
- #19: 18