Augury: Real-Time Insights for the Industrial IoT

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Real-time insights for the
Industrial IoT
Daniel Barsky, Senior Data Scientist

Presenter
Daniel Barsky, Senior Data Scientist
I have been at Augury for most of its existence. I’m leveraging
Augury’s ma...

About Augury

The
Team

OUR VISION
A world where people can always rely on the
machines that matter.
OUR MISSION
To give our customers superior in...

Millions of machine hours continuously diagnosed

How it works
Diagnose
Algorithms diagnose
malfunctions and
provide alerts and
recommendations
Visualize
You get full visib...

How we connect
machines
continuous monitoring
of all critical line
components
Filling
systems
Supply
systems
Washing
syste...

Overview
■ The multivariate time-series challenge
● Real-time insights
● Offline (batch) processing
■ Our solution
● Clust...

The multivariate time-series
challenge at Augury

■ Sensors on machines are sampled and processed hourly
● Multi-dimensional time-series per machine
■ Changes over time can...

Every hour:
■ All sensors on a monitored machine provide latest readings
The Streaming Setting - anomaly / change detection

The Streaming Setting - anomaly / change detection
Every hour:
■ All sensors on a monitored machine provide latest reading...

Every hour:
■ All sensors on a monitored machine provide latest readings
■ Raw data is converted to features indicative of...

Every hour:
■ All sensors on a monitored machine provide latest readings
■ Raw data is converted to features indicative of...

Periodically:
■ Load (multivariate) feature time-series for multiple events, multiple machines
The Batch Setting - Trainin...

Periodically:
■ Load (multivariate) feature time-series for multiple events, multiple machines
■ Process data and construc...

Periodically:
■ Load (multivariate) feature time-series for multiple events, multiple machines
■ Process data and construc...

Searching a solution that will hit all the marks in 3 categories:
■ Streaming flow requirements
■ Batch (offline) requirem...

Streaming flow requirements
Write rate Retrieval
rate
Extendable

Batch (offline) requirements
Parallel access Data
migration
Safe access to
production

Deployment & maintenance requirements
Easy to set up Easy to scale up Easy to back up

The alternatives we considered
Pros - Industry
standard
- large
community
- Fully hosted - no
devops required
- SQL interf...

Our solution -
ScyllaDB

Data modelling
Machine ID Quarter
Machine A 2018 Q4
Machine A 2018 Q3
Machine B 2018 Q4
Partition key

Data modelling
Machine ID Quarter Location on
machine
Timestamp
Machine A 2018 Q4 Motor, x axis 1541506192
Machine A 2018 ...

Data modelling
Machine ID Quarter Location on
machine
Timestamp Feature A Feature B
Machine A 2018 Q4 Motor, x axis 154150...

Cluster Deployment
Production DC Research DC

Cluster Deployment
Research DCProduction DC
Production
keyspace
Production
keyspace

Cluster Deployment
Production DC
Research
keyspace
Research DC

Cluster Deployment
Production DC
Production
Client
Read
Write
Production
keyspace
Production
keyspace
Research
keyspace
Re...

Cluster Deployment
Production DC
Batch Client
Read
Write
Production
keyspace
Production
keyspace
Research
keyspace
Researc...

Additional Benefit:
Machine Trend Dashboard

Machine Trend
Dashboard
■ Sub-second load times for
typical view
■ Immediate introspection
into the core of the
algorithms...

Next Gen Architecture:
Stream Processing

Next Gen Architecture
■ Based on data
pipelines (Apache
Beam, Google
Dataflow)
■ Scylla as an
“intermediate” data
represen...

To Summarize

Summary
IoT and machine learning impose different,
often contradictory requirements for data
modeling and access.
Defining...

Thank you Stay in touch
Any questions?
Daniel Barsky
dbarsky@augury.com

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