Satish Ramjee
Principal Software Engineer
First Utility
June 2017
Managing Smart Meter
Data with DataStax DSE
• Who are First Utility
• Creating a high availability platform
• Enabling customer control and insights through analytics
• Providing a self healing platform with event history
• Monitoring and alerting across the platform
• Conclusion
Contents
Who are First Utility
First Utility
● Largest independent energy supplier
● Supply almost 1 million UK homes
● One of the first to provide Smart meters
● Provide broadband and home services as well
● Technology driven company
Creating a high availability platform
Creating a high availability platform
● National smart meter rollout
○ Aim is to have all 53 million residential premises in
England, Wales, Scotland with Smart Meters by 2020
● Energy suppliers are required to offer smart meters to all
their customers
● Our immediate need to manage a high volume of meter
reads with high availability
● Meter access devices can potentially provide data every 5-
10 seconds from the total meter estate
Creating a high availability platform
● Smart reads ideal for an event sourced type database
● Saw the need to add resilience, high volume and linear scaling capability into
our key information base
● Opportunity to manage business expectation through service layers
● Providing a meter agnostic business layer
“One of the things DataStax offered to us was the ability to really compress that learning curve. So we had
some of their key experts come in and spend a few weeks with us over a period of time and provide that
technical leadership” Bill Wilkins, CIO, First Utility.
http://diginomica.com/2017/02/02/first-utility-makes-smart-meters-even-smarter-datastax-platform/
Creating a high availability platform
store
From Monolithic to Microservices Architecture
Application Server
store
application
(instance 1)
application
(instance 1)
application
(instance 1)
Docker Container
application
(instance 2)
Application Server
Docker Container
application
(instance 1)
application
(instance 2)
single node
rdms
multiple node
distributed store
Creating a high availability platform
Meter Type
2
Meter Type
1
Customer
Insights
Billing
Industry
Data
Warehouse
Meter Type
n
spark
Usage View
Billing View
Industry
View
Data Stores
spark
Meter Data 1
Meter Data 2
Meter Data 3
spark
Creating a high availability platform
● Multiple DCs
● Appropriate
RF
● DCs split
between
Business
Critical access
and Analytics
Enabling Customer Control and
Insights
Enabling Customer Control and Insights
● Provide customers with an insightful view
● Help customers better manage their usage
● My energy comparison of usage
● Allow control of read submission frequency
● In home display reflects current tariff and usage
Enabling Customer Control and Insights
Meter
Customer
Insights
Meter
Preferences
Meter Data
Usage Viewread
preference/price TariffIHD
Data Storage
read
Enabling Customer Control and Insights
Enabling Customer Control and Insights
Enabling Customer Control and Insights
Providing a self healing platform
Providing a self healing platform
● Record commands sent to the meter
● Detect failures
● Replay commands (with retry limit)
Meter
commands
meter state
reconcile
replay
spark
Event
command
response
Monitoring and alerting across the
platform
Monitoring and alerting across the platform
● Eyes and ears
● Dashboards of platform behaviour
● Operational: is the platform working
● Business information: reporting and analytics
Monitoring and alerting across the platform
Conclusion
Conclusion
● Gone from read only system to ability control of meter (read/write)
● Self healing
● Real time monitoring and alerting
● Enduring solution can scale both processing and persistence
● Lessons learnt
○ Denormalise - many copies with different PK
○ Know your queries in advance
○ Reporting and aggregation - duplicate, spark or counters
That’s all folks

Managing Smart Meter with DataStax DSE

  • 1.
    Satish Ramjee Principal SoftwareEngineer First Utility June 2017 Managing Smart Meter Data with DataStax DSE
  • 2.
    • Who areFirst Utility • Creating a high availability platform • Enabling customer control and insights through analytics • Providing a self healing platform with event history • Monitoring and alerting across the platform • Conclusion Contents
  • 3.
  • 4.
    First Utility ● Largestindependent energy supplier ● Supply almost 1 million UK homes ● One of the first to provide Smart meters ● Provide broadband and home services as well ● Technology driven company
  • 5.
    Creating a highavailability platform
  • 6.
    Creating a highavailability platform ● National smart meter rollout ○ Aim is to have all 53 million residential premises in England, Wales, Scotland with Smart Meters by 2020 ● Energy suppliers are required to offer smart meters to all their customers ● Our immediate need to manage a high volume of meter reads with high availability ● Meter access devices can potentially provide data every 5- 10 seconds from the total meter estate
  • 7.
    Creating a highavailability platform ● Smart reads ideal for an event sourced type database ● Saw the need to add resilience, high volume and linear scaling capability into our key information base ● Opportunity to manage business expectation through service layers ● Providing a meter agnostic business layer “One of the things DataStax offered to us was the ability to really compress that learning curve. So we had some of their key experts come in and spend a few weeks with us over a period of time and provide that technical leadership” Bill Wilkins, CIO, First Utility. http://diginomica.com/2017/02/02/first-utility-makes-smart-meters-even-smarter-datastax-platform/
  • 8.
    Creating a highavailability platform store From Monolithic to Microservices Architecture Application Server store application (instance 1) application (instance 1) application (instance 1) Docker Container application (instance 2) Application Server Docker Container application (instance 1) application (instance 2) single node rdms multiple node distributed store
  • 9.
    Creating a highavailability platform Meter Type 2 Meter Type 1 Customer Insights Billing Industry Data Warehouse Meter Type n spark Usage View Billing View Industry View Data Stores spark Meter Data 1 Meter Data 2 Meter Data 3 spark
  • 10.
    Creating a highavailability platform ● Multiple DCs ● Appropriate RF ● DCs split between Business Critical access and Analytics
  • 11.
  • 12.
    Enabling Customer Controland Insights ● Provide customers with an insightful view ● Help customers better manage their usage ● My energy comparison of usage ● Allow control of read submission frequency ● In home display reflects current tariff and usage
  • 13.
    Enabling Customer Controland Insights Meter Customer Insights Meter Preferences Meter Data Usage Viewread preference/price TariffIHD Data Storage read
  • 14.
  • 15.
  • 16.
  • 17.
    Providing a selfhealing platform
  • 18.
    Providing a selfhealing platform ● Record commands sent to the meter ● Detect failures ● Replay commands (with retry limit) Meter commands meter state reconcile replay spark Event command response
  • 19.
    Monitoring and alertingacross the platform
  • 20.
    Monitoring and alertingacross the platform ● Eyes and ears ● Dashboards of platform behaviour ● Operational: is the platform working ● Business information: reporting and analytics
  • 21.
    Monitoring and alertingacross the platform
  • 22.
  • 23.
    Conclusion ● Gone fromread only system to ability control of meter (read/write) ● Self healing ● Real time monitoring and alerting ● Enduring solution can scale both processing and persistence ● Lessons learnt ○ Denormalise - many copies with different PK ○ Know your queries in advance ○ Reporting and aggregation - duplicate, spark or counters
  • 24.