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Telediagnosis@Daimler powered by MongodDB
Madalin Broscaru, Daimler AG
IT Architect
Diagnostics and Connected Car Data
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
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
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
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
Telediagnosis@Daimler powered by MongodDB| Madalin Broscaru,
Daimler AG
Telediagnosis Data Overview
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
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
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
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
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
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
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
OPS.
Manager
MONGOD MONGOD MONGOD
RS-CFG
Mongo DB MVP - Architecture
Telediagnosis@Daimler powered by MongodDB| Madalin Broscaru,
Daimler AG
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
Conclusions
Telediagnosis@Daimler powered by MongodDB| Madalin Broscaru,
Daimler AG
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
Questions ?

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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

Editor's Notes

  1. Glad to be here with you today Few words about myself
  2. A quick overview of what I‘m going to show you today Before solution, what is specific to requirement is relevant
  3. Few words about context Auto industry Middle transformation
  4. From Future Mobility one lever deeper The telediagnosis usecase where MongoDB comes What happens beyound the scene
  5. 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
  6. This is how data is looking, oversimplified, human readable Diagnostic Trouble Code
  7. Saw the data but what about the access? Relevant for sharding, indexes + Cust. Assistance Center + Mercedes Me + Automated valet parking
  8. Beside all data and access we have also NFRS NFRs ware the triggers for MongoDB, Data and access are enablers
  9. Do the test drive before you buy Parenting books from people without children Why not as a service
  10. 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
  11. We like what we saw with POC so we move MVP
  12. Some things are reusable. Idea: Idea what is below is the productive env What is above is the operations
  13. Transition: What happens if we have multiple env? Idea: in our case, test = prod, only smaller. Why?
  14. You saw a little on the infrastructure and deployment archtecture What about Coniguration Specifics?
  15. 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
  16. Mongo DB is used to implement the future mobility @ Daimler
  17. 18