This document discusses SunPower's transition from a legacy SQL server to a Confluent & Kafka monitoring system. Some key points: - SunPower has over 6 million devices in the field sending data every 5 minutes that they need to monitor to ensure 20-year performance guarantees. - They want to understand performance challenges like weather or faults using data to deliver customer value. - They implemented Kafka as a central system to blend sensor and other data sources to generate value and allow engineering teams access to enriched data. - Future plans include panel-level monitoring in an app to quickly identify issues and determine resolutions.

1. © 2021 SunPower Corporation
From Legacy SQL Server to
High-Powered Confluent &
Kafka Monitoring System
Patrick Franz
SEPTEMBER 2021
Senior Director, Engineering

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OUR MISSION
Changing the Way
Our World is Powered
We do this by building a great company, putting
our customers first, and making solar the most
compelling energy option. If we empower our
people and communities to thrive, we’ll build a
sustainable future together.

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MONITORING
Why Monitoring Matters
• SunPower has approximately 6M devices in
the field sending data, on average, every 5
minutes.
• We offer a 20-year guarantee for lease
customers that the system will produce a
target kWh/year.
• Example impacts on performance: weather,
shading, or component faults.
• We want to understand these challenges with
data.

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MONITORING
Delivering Customer
Value
• How much data do we need to predict and
detect performance issues before they impact
the customer?
• How do we collect this data and act on it
quickly?
• Fundamentals
• Measurement ingestion
• Metadata association
• Storage
• Analysis and presentation

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Early Solar Adopters
MONITORING
• In 2008 we had this idea that customers
wanted to know how much energy their
system is producing.
• Supported SunPower’s residential and
commercial customers successfully for a
decade.
• SunPower’s customer base grew, average
solar installation size increased, and the
industry transitioned to microinverters.

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Customer Value At Scale
MONITORING
• By 2018 we knew we needed to support
modern IoT devices on our platform.
• Customers’ energy habits were changing (EV
adoption, smart appliances) and policy shifts
in favor of renewable energy drove increased
adoption of solar and storage.
• Took an engineering first approach and
designed new fundamentals with an emphasis
on customer experience.
IoT Sensor Data Confluent Cloud
Customer Site
and Device
Metadata
Time-series
API
Data Warehouse
Weather Data,
Utility Rates, etc.

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MONITORING
Why Kafka?
• Sensor data alone is not valuable. How do we
connect a solar panel at an address to a
sensor reading?
• Kafka is the central nervous system that
allows us to blend multiple data sources
together and generate value from the raw
sensor data.
• Engineering teams get access to fully-enriched
data via Kafka and build the features
important to them.

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CASE STUDY
Panel-Level Monitoring
• With launch of the mySunPower™ app we
continue to iterate on customer experience.
• Panel-level monitoring addresses the earlier
need of what data we collect and how we use
it to solve real customer issues.
• Quickly identify underperforming components
and determine appropriate resolution.
Feature planned for release in Q3.

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MONITORING
We Are Hiring
• Help us change the way the world is powered
with Kafka.
• patrick.franz@sunpower.com
• LinkedIn

10. Changing the way
our world is powered
THANK YOU
© 2021 SunPower Corporation