Contenu connexe Similaire à Building A Cloud-Native Advanced Logistics Ecosystem (20) Plus de Christian Deger (17) Building A Cloud-Native Advanced Logistics Ecosystem1. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
BuildingACloud-NativeAdvanced
Logistics Ecosystem
Christian Deger
Chief Architect
RIO The Logistics Flow | TRATON Group
2. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Agenda
What is RIO
10.000ft architecture
100ft use cases
Lessons learned
Next steps
3. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
4. RIO'S VISION
RIO's vision is to make the
complete transport and
logistics ecosystem more
transparent – across all
manufacturers, and open to
all. The centralizing platform
creates the foundations for a
wide range of new business
and service models.
5. Digitization
of trucks with
the RIO Box
RIO DIGITIZES THE
LOGISTICS SUPPLY CHAIN.
Integration
of producer
platforms
System connection of
the receivers
TMS connection
of logistics service
providers
6. Fleet customers
registered at
RIO Platform
MORE THAN
4,500Vehicles
equipped with
RIO Box
MORE THAN
80,00027Participating
countries
OUR CUSTOMERS
ON THE RIO PLATFORM.
7. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
8. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Vehicleconnectivity
9. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Vehicleconnectivity
AWS Account Connectivity
Private APN
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Vehicleconnectivity
AWS Account Connectivity
Private APN
MQTT Broker
HiveMQ
11. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Vehicleconnectivity
AWS Account Connectivity
Private APN
MQTT Broker
HiveMQ
AWS Account Services
Peering
12. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Vehicleconnectivity
AWS Account Connectivity
Private APN
MQTT Broker
HiveMQ
Kafka
Event Bus
AWS Account Services
Peering
13. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Vehicleconnectivity
AWS Account Connectivity
Private APN
MQTT Broker
HiveMQ
Kafka
Event Bus
AWS Account Services
Peering
MQTT
Gateway
14. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Vehicleconnectivity
AWS Account Connectivity
Private APN
MQTT
Gateway
MQTT Broker
HiveMQ
Kafka
Event Bus
AWS Account Services
Peering
15. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Vehicleconnectivity
AWS Account Connectivity
Private APN
MQTT
Gateway
MQTT Broker
HiveMQ
Kafka
Event Bus
Receiver:
Decodes
Enriches
Routes
AWS Account Services
Peering
16. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Vehicleconnectivity
AWS Account Connectivity
Private APN
MQTT
Gateway
MQTT Broker
HiveMQ
Kafka
Event Bus
Receiver:
Decodes
Enriches
Routes
Microservices
AWS Account Services
Peering
17. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Vehicleconnectivity
AWS Account Connectivity
Private APN
MQTT
Gateway
MQTT Broker
HiveMQ
Kafka
Event Bus
Receiver:
Decodes
Enriches
Routes
Sender:
Routes
Microservices
AWS Account Services
Peering
18. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Vehicleconnectivity
AWS Account Connectivity
Private APN
MQTT
Gateway
MQTT Broker
HiveMQ
Proxy
NGINX
Kafka
Event Bus
Proxy
NGINX
Mobile Device
Management
Receiver:
Decodes
Enriches
Routes
Sender:
Routes
Microservices
AWS Account Services
Peering
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Telematicshardware – RIO box
AWS CloudCloud
Connect
Gateway
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Telematicshardware – RIO box
AWS CloudCloud
Connect
Gateway
• Over the air update of base software
• Over the air updates of individual apps
• End-to-end responsibility for teams
• Middleware includes MQTT broker
• App config changes via MQTT
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Dataarchitecture
Connectivity
Gateway
Connectivity
Gateway
Data or event flow
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Dataarchitecture
Event Bus
Connectivity
Gateway
Connectivity
Gateway
Kafka
Data or event flow
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Dataarchitecture
Event Bus
Connectivity
Gateway
Connectivity
Gateway
Microservice Microservice Microservice
Other sources
Kafka
Data or event flow
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Dataarchitecture
Event Bus
Connectivity
Gateway
Connectivity
Gateway
Microservice Microservice Microservice
Other sources
Kafka
Connect S3
Kafka Raw Data
Data or event flow
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Dataarchitecture
Event Bus
Connectivity
Gateway
Connectivity
Gateway
Microservice Microservice Microservice
Other sources
Data Lake
Kafka
Connect S3
Kafka Raw Data Data Hub
Data or event flow
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Dataarchitecture
Event Bus
Connectivity
Gateway
Connectivity
Gateway
Microservice Microservice Microservice
Other sources
Data Lake
Kafka
Connect S3
Kafka Raw Data Data Hub
Data or event flow
Analytics
27. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Dataarchitecture
Event Bus
Connectivity
Gateway
Connectivity
Gateway
Microservice Microservice Microservice
Other sources
Data Lake
Kafka
Connect S3
Kafka Raw Data Data Hub
Data or event flow
Analytics
Use case
data
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Bounded contexts
Event Bus
Microservices
Microservices
Microservice
Storage
API Gateway
Microservices
Microservices
Microservice
Storage
Bounded Context Bounded Context
A bounded context delimits
the applicability of a particular
model so that team members
have a clear and shared
understanding of what has to
be consistent and how it
relates to other contexts.
API Gateway
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Bounded contexts – Interfaces
Event Bus
Microservices
Microservices
Microservice
Storage
API Gateway
Microservices
Microservices
Microservice
Storage
Bounded Context Bounded Context
Bounded contexts interact
only via their interfaces
API Gateway
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Bounded contexts –AWSAccounts
Event Bus
Microservices
Microservices
Microservice
Storage
API Gateway
Microservices
Microservices
Microservice
Storage
AWS Account AWS Account
Strengthen the architecture
with AWS account as explicit
boundary
API Gateway
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Stereotypicalcontext account
AWS Account
Bounded Context
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Stereotypicalcontext account
AWS Account
Bounded Context
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Stereotypicalcontext account
AWS Account
Delivery
Bounded Context
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Stereotypicalcontext account
AWS Account
Delivery
Bounded Context
Hosted zone
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Stereotypicalcontext account
AWS Account
Delivery
Bounded Context
Hosted zone
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Stereotypicalcontext account
AWS Account
Parameter
Store
Delivery
Bounded Context
Hosted zone
37. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Stereotypicalcontext account
AWS Account
Parameter
Store
or or
Delivery
Bounded Context
MongoDB
Atlas
Hosted zone
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Stereotypicalcontext account
AWS Account
Hosted zone
Parameter
Store
or or
Delivery
Bounded Context
Kafka
MongoDB
Atlas
39. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Stereotypicalcontext account
AWS Account
Hosted zone
Parameter
Store
or or
Delivery
Bounded Context
Kafka
MongoDB
Atlas
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Stereotypicalcontext account
AWS Account
Hosted zone
Parameter
Store
or or
Delivery
Bounded Context
Kafka
MongoDB
Atlas
41. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Stereotypicalcontext account
AWS Account
Hosted zone
Parameter
Store
or or
Delivery
Bounded Context
Kafka
MongoDB
Atlas
React App
42. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Stereotypicalcontext account
AWS Account
Hosted zone
Parameter
Store
or or
Delivery
Bounded Context
Kafka
MongoDB
Atlas
React App
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Foster
autonomy
You build it, You run it teams…
• own one or more bounded contexts
• decide on micro architecture
• deploy and operate services in their
context accounts
• have end-to-end responsibility for
their services
• are cross-functional
Autonomy and alignment
45. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
You build it, You run it teams…
• own one or more bounded contexts
• decide on micro architecture
• deploy and operate services in their
context accounts
• have end-to-end responsibility for
their services
• are cross-functional
• Objectives and key results (OKR)
• Technology Radar
• Transparent decisions via
Macro Architecture Guild
Autonomy and alignment
Enable
alignment
Foster
autonomy
46. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
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Usecases
Fleet Monitor
End-to-end responsibility and
device configuration
Performance Analysis
Stream processing with higher
data volume
Tachograph Services
Polyglot microservices and
personal data
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Fleetmonitor
49. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Fleetmonitor – architecture
Async events
via Kafka
Vehicle
connectivity
HTTP calls
50. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Fleetmonitor – architecture
Location
MongoDB
Atlas
Async events
via Kafka
Vehicle
connectivity
HTTP calls
Location reports
51. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Fleetmonitor – architecture
Location
MongoDB
Atlas
Async events
via Kafka
Vehicle
connectivity
HTTP calls
Location reports
52. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Fleetmonitor – architecture
Location
MongoDB
Atlas
React App
Fleet monitor
Async events
via Kafka
Vehicle
connectivity
HTTP calls
Location reports
53. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Fleetmonitor – architecture
Location
MongoDB
Atlas
Here Maps
API
Map Service
React App
Fleet monitor
Async events
via Kafka
Vehicle
connectivity
HTTP calls
Location reports
54. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Fleetmonitor – architecture
Location
MongoDB
Atlas
Here Maps
API
Map Service
React App
Fleet monitor
Async events
via Kafka
Vehicle
connectivity
HTTP calls
Location reports
55. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Fleetmonitor – architecture
Location
RIO
Marketplace
MongoDB
Atlas
Here Maps
API
Map Service
React App
Fleet monitor
Async events
via Kafka
Vehicle
connectivity
HTTP calls
Location reports
56. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Fleetmonitor – architecture
Location
RIO
Marketplace
MongoDB
Atlas
Here Maps
API
Map Service
React App
Fleet monitor
MongoDB
Atlas
Async events
via Kafka
Vehicle
connectivity
HTTP calls
Product activated
Map
Activation
Location reports
57. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Fleetmonitor – architecture
Location
RIO
Marketplace
MongoDB
Atlas
Here Maps
API
Map Service
React App
Fleet monitor
MongoDB
Atlas
Async events
via Kafka
Vehicle
connectivity
HTTP calls
Product activated
Map
Activation
Change configuration
Location reports
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Performance analysis
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Performance analysis– architecture
Async events
via Kafka
Vehicle
connectivity
HTTP calls
60. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Performance analysis– architecture
Async events
via Kafka
Vehicle
connectivity
HTTP calls
Performance data
Kafka
Streaming
Performance
Kafka Streams
61. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Performance analysis– architecture
Async events
via Kafka
Vehicle
connectivity
HTTP calls
Performance data
Kafka
Streaming
Performance
Kafka Streams
Driver changed
62. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Performance analysis– architecture
Async events
via Kafka
Vehicle
connectivity
HTTP calls
Performance data
Kafka
Streaming
Performance
Kafka Streams
Driver changed
• Deserialization, Deduplication, Filtering,
Repartitioning
• Group by fleet and vehicle
• Create 15 minute windows of snapshots
• Join vehicle snapshots with drivers
• Combine aggregates within windows
63. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Performance analysis– architecture
MongoDB
Atlas
Async events
via Kafka
Vehicle
connectivity
HTTP calls
Performance data
Kafka
Streaming
Performance
Kafka Streams
Driver changed
15 min aggregates
64. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Performance analysis– architecture
Performance
History
MongoDB
Atlas
Async events
via Kafka
Vehicle
connectivity
HTTP calls
Performance data
Kafka
Streaming
Performance
Kafka Streams
Driver changed
15 min aggregates
65. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Performance analysis– architecture
Performance
History
MongoDB
Atlas
React App
Performance
Async events
via Kafka
Vehicle
connectivity
HTTP calls
Performance data
Kafka
Streaming
Performance
Kafka Streams
Driver changed
15 min aggregates
66. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Performance analysis– architecture
Performance
History
RIO
Marketplace
MongoDB
Atlas
React App
Performance
Async events
via Kafka
Vehicle
connectivity
HTTP calls
Product activated
Product
Config
Change configuration,
including data reduction
Performance data
Kafka
Streaming
Performance
Kafka Streams
Driver changed
15 min aggregates
67. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Performance analysis– architecture
Performance
History
RIO
Marketplace
MongoDB
Atlas
React App
Performance
Async events
via Kafka
Vehicle
connectivity
HTTP calls
Product activated
Product
Config
Change configuration,
including data reduction
Performance data
Kafka
Streaming
Performance
Kafka Streams
Driver changed
15 min aggregates
IoT throughput:
~4KB per truck per minute
68. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Performance analysis– architecture
Performance
History
RIO
Marketplace
MongoDB
Atlas
React App
Performance
Async events
via Kafka
Vehicle
connectivity
HTTP calls
Product activated
Product
Config
Change configuration,
including data reduction
Performance data
Kafka
Streaming
Performance
Kafka Streams
Driver changed
15 min aggregates
IoT throughput:
~4KB per truck per minute Retention: 60 days
69. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Performance analysis– architecture
Performance
History
RIO
Marketplace
MongoDB
Atlas
React App
Performance
Async events
via Kafka
Vehicle
connectivity
HTTP calls
Product activated
Product
Config
Change configuration,
including data reduction
Performance data
Kafka
Streaming
Performance
Kafka Streams
Driver changed
15 min aggregates
Write amplification
factor 12
IoT throughput:
~4KB per truck per minute Retention: 60 days
70. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Performance analysis– architecture
Performance
History
RIO
Marketplace
MongoDB
Atlas
React App
Performance
Async events
via Kafka
Vehicle
connectivity
HTTP calls
Product activated
Product
Config
Change configuration,
including data reduction
Performance data
Kafka
Streaming
Performance
Kafka Streams
Driver changed
15 min aggregates
Write amplification
factor 12
IoT throughput:
~4KB per truck per minute Retention: 60 days
Reprocessing of ~45 million
truck messages in
~14 hours, with 7 instances,
each 4 GB RAM, 1 vCPU
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KafkaStreamsalternatives
Kafka and Apache Flink
• Apache Flink is not so deeply integrated with Kafka
• Apache Flink is deployed as cluster, Kafka Streams is included as library
• Kafka Stream applications can be deployed to ECS
Amazon Kinesis and Apache Flink
• Deployment managed by AWS
• Amazon Kinesis Data Analytics for Java was not available yet
72. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Performance analysis– Keypoints
End-to-end responsibility from device to application allows fast iteration and
control
• Payload definition
• Various trigger for data collection
• Remote configurable aggregation on device
Stream processing
• Near real-time access to results
• Reprocessing of truck events possible
Elastic adjustment of capacity between reprocessing and normal operation
73. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Tachographservices
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Tachographservices – keypoints
• Multiple .NET Core services instead of
Java/Kotlin Spring Boot
• Windows application with card reader
• Automated download and archival of
digital tachograph and driver card to
Amazon S3
• Enabled compliant processing and
storage of personal data on AWS to fulfill
legal obligation of customers
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Fleet monitor
Organization and architectural
End-to-end responsibility
• From embedded app to service
• Fast, local decisions
• Fit for initial purpose
Performance Analysis
Remaining driving time
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Organization and architectural
Align local optimizations with overall strategy
• Abstractions at the right level
• Connector abstraction required to address mixed fleets
Fleet monitor
Performance Analysis
Remaining driving time
Connector
Connector
78. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Domain-driven design
Improve collaboration with
domain experts by
• Explicitly defining bounded
contexts
• Building a context map of the
domain
• Exploring and designing with
event storming
• Using ubiquitous language
79. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Multi-AccountStrategy
One Account Dozens of
Accounts
80. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Multi-AccountStrategy
AWS Account AWS Account AWS Account AWS Account
Instances Instances Instances Instances Instances Instances
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Whymultipleaccounts?
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Undifferentiated heavylifting
Value for
RIO customers
Undifferentiated
heavy lifting
On premise
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Undifferentiated heavylifting
Value for
RIO customers
Undifferentiated
heavy lifting
On premise
Value for
RIO customers
Undifferentiated
heavy lifting
AWS as infrastructure provider
85. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Undifferentiated heavylifting
Value for
RIO customers
Undifferentiated
heavy lifting
On premise
Value for
RIO customers
Undifferentiated
heavy lifting
AWS as infrastructure provider
Value for
RIO customers
Undifferentiated
heavy lifting
Embrace higher level AWS services
86. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
AWS Firstprinciple
Favor AWS platform service
over managed service,
over self-hosted OSS,
over self-built solutions
Self-hosted OSS
Self-built solution
Managed service
AWS service
Higher level
AWS service
87. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
AWS First– Examples
Self-hosted OSS
Self-built solution
Managed service
AWS service
Higher level
AWS service
88. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
AWS First– Examples
Self-hosted OSS
Self-built solution
Managed service
AWS service
Higher level
AWS service
OSS IAM and
API Gateway
Amazon Cognito and
Amazon API Gateway
89. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
AWS First– Examples
Self-hosted OSS
Self-built solution
Managed service
AWS service
Higher level
AWS service
OSS IAM and
API Gateway
Amazon Cognito and
Amazon API Gateway
Monitoring and
logging
DataDog
90. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
AWS First– Examples
Self-hosted OSS
Self-built solution
Managed service
AWS service
Higher level
AWS service
OSS IAM and
API Gateway
Amazon Cognito and
Amazon API Gateway
Monitoring and
logging
DataDog
ECS launch
type EC2
ECS launch
type Fargate
91. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
AWS First– Re-evaluatedecisions
Self-hosted OSS
Self-built solution
Managed service
AWS service
Higher level
AWS service
92. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
AWS First– Re-evaluatedecisions
Self-hosted OSS
Self-built solution
Managed service
AWS service
Higher level
AWS service
IoT and MQTT stack
AWS IoT Core
93. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
AWS First– Re-evaluatedecisions
Self-hosted OSS
Self-built solution
Managed service
AWS service
Higher level
AWS service
IoT and MQTT stack
AWS IoT Core
Managed Kafka
Kafka
94. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
AWS First– Re-evaluatedecisions
Self-hosted OSS
Self-built solution
Managed service
AWS service
Higher level
AWS service
IoT and MQTT stack
AWS IoT Core
Managed Kafka
Kafka
Amazon Managed
Streaming for Kafka
95. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
AWS First– Re-evaluatedecisions
Self-hosted OSS
Self-built solution
Managed service
AWS service
Higher level
AWS service
IoT and MQTT stack
AWS IoT Core
Kafka
Kinesis and Lambda
Amazon Managed
Streaming for Kafka
Managed Kafka
96. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Additional skills required:
Multi-account strategy,
AWS First and
You build it, you run it
97. That's why we need you!
https://rio.cloud/en/careers.html
SOFTWARE CAN
NEVER BE FINISHED
98. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Thank you!
S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Christian Deger
@cdeger
99. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I TS U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Notes de l'éditeur With RIO since end of 2017
Formerly known as Volkswagen Truck & Bus Line-fitment in MAN trucks started August 2017
Platform launched December 2017 Third connectivity for device signing is not shown.
It is the only part that is actually on premise, using a hardware HSM. Embedded SIM
Cloud only connectivity without intermediates
Microservices architecture with local persistence requires a different approach for cross service data use cases, then with a shared database.
Data Hub uses optimized format for querying:
Zipped, flattened, partitioned by time and stored in Parquet format Massage and filter data for specific use cases Microservices size and boundaries discussion lead to thinking model bounded context, which comes from domain-driven design. The technical implementation and size is not the focus anymore. Especially when heading towards serverless. So what is a bounded context... Context accounts Not everything within a bounded context is an AWS service.
Account provisioning is almost completely self-service. Bitbucket Account bootstrapping.
Convention based pipeline definition in repo.
Infrastructure as code used to create supporting resources in the account Showing a Fargate based deployable unit,
Serverless blueprints are also available. Autonomy is one of the ingredients in microservices architecture Map based information hub for the dispatcher at a transport service provider Simplified view. Not all interactions shown. Simplified view, skipped:
GeoFences, Trailer, Fleet adminstration Essentials -> GEO upgrade
Data rate, History, POI Configuration: Adjust sample rate 1 minute with 3 data points vs. 15 minutes.
Analyses and rates the performance on an asset and driver level.
Like foresighted driving, coasting, harsh breaking, speed, fuel consumption
Configurable data displays
Fleet performance data from the last three months Simplified: Left out Fleetadmin and driver info service.
Configuration changes include how signals are aggregated on the box: Thresholds, sampling rate and median
RIO Compliant is a service for fleet managers who needs to download and oversee data from digital tachographs and driver cards.
AWS improved tooling support to simplify managing multiple accounts. Most prominently with Organizations, Landing Zone, Control Tower Started with a single, shared production account and move to multiple context accounts. Separation
Easy and transparent cost allocation
Organize and categorize accounts by security, function and structure
Ownership, Autonomy
Aligned with bounded context
Enforcing the architecture with explicit boundary
Freedom and responsibility within an account
Clearly defined public interfaces, APIs, Events (incl. Kafka)
Faster development cycles due to fewer dependencies
Allows organizational scaling due to less centralization
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