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Christoph Bussler
October 3rd, 2019
IoT Event Processing and
Analytics with InfluxDB in
Google Cloud
Agenda
Energy
Sector
Energy sector
use case
analysis
Life cycle
of an
IoT event
Google Cloud
1 2 3 4 5 6
TICK
architecture
Cloud native
IoT event
processing
architecture
● Production
○ Energy production systems monitoring and anomaly detection
■ Oil, gas, wind, hydro, solar and others
● Distribution
○ Smart grid: maintaining an equilibrium across energy supply and demand
■ Renewable and non-renewable energy production/demand forecasting
■ https://towardsdatascience.com/how-machine-learning-can-transform-the-ener
gy-industry-caaa965e282a (devices: synchrophasers)
● Consumption
○ Fleet performance optimization (cars, trucks, planes, etc.)
○ Commercial manufacturing sites, office buildings
○ Public infrastructure
○ Private households
Use Cases: Energy Sector
● Event collection
○ From production systems
○ From consumption locations
○ Absence check: requires static
equipment inventory data
● Event monitoring
○ Outages
○ Trends
○ Anomalies
■ Was there actually an outage?
Use Cases: Analysis
● Forecasting / prediction
○ Combination of
■ Current events
■ Historic events
■ Non-event data like models,
weather data, road conditions,
etc.
● Off-line analysis
○ Combination with non-event data
● Archiving
○ Long duration analysis
Life Cycle of an IoT Event
Gateway
Ingest
Time Series
Database
Real-time
Analytics
Offline
Analytics
Static data
sources
Dynamic data
sources
Application
Systems
Short / Long
term archive
Life Cycle of an IoT Event
Gateway
Ingest
Time Series
Database
Real-time
Analytics
Offline
Analytics
Static data
sources
Dynamic data
sources
Application
Systems
Short / Long
term archive
Life Cycle of an IoT Event
Gateway
Ingest
Time Series
Database
Real-time
Analytics
Offline
Analytics
Static data
sources
Dynamic data
sources
Application
Systems
Short / Long
term archive
Life Cycle of an IoT Event
Gateway
Ingest
Time Series
Database
Real-time
Analytics
Offline
Analytics
Static data
sources
Dynamic data
sources
Application
Systems
Short / Long
term archive
Life Cycle of an IoT Event
Gateway
Ingest
Time Series
Database
Real-time
Analytics
Offline
Analytics
Static data
sources
Dynamic data
sources
Application
Systems
Short / Long
term archive
Life Cycle of an IoT Event
Gateway
Ingest
Time Series
Database
Real-time
Analytics
Offline
Analytics
Static data
sources
Dynamic data
sources
Application
Systems
Short / Long
term archive
Google Cloud: Regions and Zones
https://cloud.google.com/about/locations/#regions-tab
Google Cloud: Global Network
https://cloud.google.com/about/locations/#network-tab
Google Cloud: Cloud Services
https://cloud.google.com/-select“Products”
Google Cloud: Select Services
BigQuery (https://cloud.google.com/bigquery/)
● Cloud native analytics database
● Columnar - SQL - large scale (PB) - multi-regional service
Cloud Spanner (https://cloud.google.com/spanner/)
● Cloud native global relational database
● Relational - SQL - consistent - linear scaling - multi-regional and intercontinental service
Coldline Storage (https://cloud.google.com/storage/docs/storage-classes)
● Cloud native storage - long term storage
Cloud Machine Learning Engine (https://cloud.google.com/ml-engine/)
● Cloud native ML engine - online and batch predictions
InfluxDB - TICK Architecture
https://www.influxdata.com/time-series-platform/
Cloud Native IoT Event Processing Architecture
Gateway
Cloud Native IoT Event Processing Architecture
Gateway
Cloud
IoT Core
Cloud Native IoT Event Processing Architecture
Gateway
Cloud
IoT Core
TICK
Stack
Cloud Native IoT Event Processing Architecture
Gateway
Cloud
IoT Core
TICK
Stack
Cloud
Pub/Sub
BigQuery
Cloud
Dataflow
Cloud
SQL
Cloud
Dataflow
Cloud Native IoT Event Processing Architecture
Gateway
Cloud
IoT Core
TICK
Stack
Cloud
Pub/Sub
BigQuery
Cloud
Dataflow
Cloud
SQL
Cloud
Dataflow
Cloud
Pub/Sub
Cloud
Spanner
Kubernetes
Engine
Cloud
Dataflow
Cloud Native IoT Event Processing Architecture
Gateway
Cloud
IoT Core
TICK
Stack
Cloud
Pub/Sub
BigQuery
Cloud
Dataflow
Cloud
SQL
Cloud
Dataflow
Cloud
Pub/Sub
Cloud
Spanner
Kubernetes
Engine
Cloud
Dataflow
Cloud Native IoT Event Processing Architecture
Gateway
Cloud
IoT Core
TICK
Stack
Cloud
Pub/Sub
BigQuery
Cloud
Dataflow
Cloud
SQL
Cloud
Pub/Sub
Cloud
Dataflow
Cloud
Pub/Sub
Cloud
Spanner
Kubernetes
Engine
Cloud Run
Cloud
Storage
AI Platform
Cloud
Dataflow
Cloud Native IoT Event Processing Architecture
Gateway
Cloud
IoT Core
TICK
Stack
Cloud
Pub/Sub
BigQuery
Cloud
Dataflow
Cloud
SQL
Cloud
Run
Cloud
Storage
Cloud
Pub/Sub
Cloud
Dataflow
Cloud
Pub/Sub
Cloud
Spanner
Kubernetes
Engine
Cloud
Scheduler
Cloud Run
Cloud
Storage
AI Platform
Cloud
Dataflow
Summary
Gateway
Ingest
Time Series
Database
Real-time
Analytics
Offline
Analytics
Static data
sources
Dynamic data
sources
Application
Systems
Short / Long
term archive
Thank You!
Q&A

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IoT Event Processing and Analytics with InfluxDB in Google Cloud | Christoph Bussler | Google, Inc

  • 1. Christoph Bussler October 3rd, 2019 IoT Event Processing and Analytics with InfluxDB in Google Cloud
  • 2. Agenda Energy Sector Energy sector use case analysis Life cycle of an IoT event Google Cloud 1 2 3 4 5 6 TICK architecture Cloud native IoT event processing architecture
  • 3. ● Production ○ Energy production systems monitoring and anomaly detection ■ Oil, gas, wind, hydro, solar and others ● Distribution ○ Smart grid: maintaining an equilibrium across energy supply and demand ■ Renewable and non-renewable energy production/demand forecasting ■ https://towardsdatascience.com/how-machine-learning-can-transform-the-ener gy-industry-caaa965e282a (devices: synchrophasers) ● Consumption ○ Fleet performance optimization (cars, trucks, planes, etc.) ○ Commercial manufacturing sites, office buildings ○ Public infrastructure ○ Private households Use Cases: Energy Sector
  • 4. ● Event collection ○ From production systems ○ From consumption locations ○ Absence check: requires static equipment inventory data ● Event monitoring ○ Outages ○ Trends ○ Anomalies ■ Was there actually an outage? Use Cases: Analysis ● Forecasting / prediction ○ Combination of ■ Current events ■ Historic events ■ Non-event data like models, weather data, road conditions, etc. ● Off-line analysis ○ Combination with non-event data ● Archiving ○ Long duration analysis
  • 5. Life Cycle of an IoT Event Gateway Ingest Time Series Database Real-time Analytics Offline Analytics Static data sources Dynamic data sources Application Systems Short / Long term archive
  • 6. Life Cycle of an IoT Event Gateway Ingest Time Series Database Real-time Analytics Offline Analytics Static data sources Dynamic data sources Application Systems Short / Long term archive
  • 7. Life Cycle of an IoT Event Gateway Ingest Time Series Database Real-time Analytics Offline Analytics Static data sources Dynamic data sources Application Systems Short / Long term archive
  • 8. Life Cycle of an IoT Event Gateway Ingest Time Series Database Real-time Analytics Offline Analytics Static data sources Dynamic data sources Application Systems Short / Long term archive
  • 9. Life Cycle of an IoT Event Gateway Ingest Time Series Database Real-time Analytics Offline Analytics Static data sources Dynamic data sources Application Systems Short / Long term archive
  • 10. Life Cycle of an IoT Event Gateway Ingest Time Series Database Real-time Analytics Offline Analytics Static data sources Dynamic data sources Application Systems Short / Long term archive
  • 11. Google Cloud: Regions and Zones https://cloud.google.com/about/locations/#regions-tab
  • 12. Google Cloud: Global Network https://cloud.google.com/about/locations/#network-tab
  • 13. Google Cloud: Cloud Services https://cloud.google.com/-select“Products”
  • 14. Google Cloud: Select Services BigQuery (https://cloud.google.com/bigquery/) ● Cloud native analytics database ● Columnar - SQL - large scale (PB) - multi-regional service Cloud Spanner (https://cloud.google.com/spanner/) ● Cloud native global relational database ● Relational - SQL - consistent - linear scaling - multi-regional and intercontinental service Coldline Storage (https://cloud.google.com/storage/docs/storage-classes) ● Cloud native storage - long term storage Cloud Machine Learning Engine (https://cloud.google.com/ml-engine/) ● Cloud native ML engine - online and batch predictions
  • 15. InfluxDB - TICK Architecture https://www.influxdata.com/time-series-platform/
  • 16. Cloud Native IoT Event Processing Architecture Gateway
  • 17. Cloud Native IoT Event Processing Architecture Gateway Cloud IoT Core
  • 18. Cloud Native IoT Event Processing Architecture Gateway Cloud IoT Core TICK Stack
  • 19. Cloud Native IoT Event Processing Architecture Gateway Cloud IoT Core TICK Stack Cloud Pub/Sub BigQuery Cloud Dataflow Cloud SQL Cloud Dataflow
  • 20. Cloud Native IoT Event Processing Architecture Gateway Cloud IoT Core TICK Stack Cloud Pub/Sub BigQuery Cloud Dataflow Cloud SQL Cloud Dataflow Cloud Pub/Sub Cloud Spanner Kubernetes Engine Cloud Dataflow
  • 21. Cloud Native IoT Event Processing Architecture Gateway Cloud IoT Core TICK Stack Cloud Pub/Sub BigQuery Cloud Dataflow Cloud SQL Cloud Dataflow Cloud Pub/Sub Cloud Spanner Kubernetes Engine Cloud Dataflow
  • 22. Cloud Native IoT Event Processing Architecture Gateway Cloud IoT Core TICK Stack Cloud Pub/Sub BigQuery Cloud Dataflow Cloud SQL Cloud Pub/Sub Cloud Dataflow Cloud Pub/Sub Cloud Spanner Kubernetes Engine Cloud Run Cloud Storage AI Platform Cloud Dataflow
  • 23. Cloud Native IoT Event Processing Architecture Gateway Cloud IoT Core TICK Stack Cloud Pub/Sub BigQuery Cloud Dataflow Cloud SQL Cloud Run Cloud Storage Cloud Pub/Sub Cloud Dataflow Cloud Pub/Sub Cloud Spanner Kubernetes Engine Cloud Scheduler Cloud Run Cloud Storage AI Platform Cloud Dataflow
  • 26. Q&A