SwimOS is an Apache 2.0 licensed runtime platform that makes it easy to build stateful, distributed, data-driven applications. SwimOS is a stateful real-time stream processor that auto-scales apps from real-world event data, building a stateful graph from the data on-the-fly. SwimOS subscribes to event streams from real-world things, creates a stateful web agent for each data source, and links related agents to form an intelligent stream processing graph where the agents continuously compute on incoming data and share insights in real-time.

1. Copyright © 2019 SWIM.AI inc
SwimOS & NATS
Simon Crosby, CTO
Swim.ai

2. Copyright © 2019 Swim.AI inc
SwimOS is an Apache 2.0 licensed runtime
platform that makes it easy to build stateful,
distributed, data-driven applications https://github.com/
swimos/

3. Copyright © 2019 SWIM.AI inc3
• CNCF NATS
• Apache Kafka
• Apache Pulsar
• Amazon Kinesis
• Google pub/sub
• Azure Enterprise Data Bus
• Salesforce Kafka
• Confluent Cloud
Streaming Platforms
➢ SwimOS is a stream processor for streaming data services
• Support pub/sub at (massive) scale
• Do not run applications
• Buffer data between pubs/subs
• Event-time ordered delivery
• Event storage (even forever)

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SwimOS is a Stateful Real-time Stream Processor
• Auto-scales apps from real-world
event data, building a stateful
graph from the data, on-the-fly
• Apps are easy to develop
• Fully integrated into DevOps
lifecycle
• Bridges the gap between IT and
application owners
• Delivers unimaginable
performance

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SwimOS is like for Things
• SwimOS subscribes to an event stream from real-world things
• It creates a stateful, concurrent web agent for each data source
• Each web agent cleans, labels, analyzes data from its real-world twin
• Things dynamically link to related things, building a stateful in-memory graph
• Linked web agents share their state in real-time
• Operators for analysis, learning and prediction, can be attached to web agents
• Each vertex in the graph thus continually computes on its contextual state as
data flows over the graph – and in turn shares its insights in real-time
• The graph of web agents is like an intelligent stream processing pipeline
• Containment, Proximity – other Geospatial
• Any programmatic relationship eg correlation

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• A stateful, concurrent object created
dynamically for each “thing”
• Actively consumes raw event data
• A stateful, in-memory computational
object that processes data on-the-fly
• Continually evolves to mirror the state
of the real-world
• “Web agent” → object ID is a URI
Web Agent = Digital Twin
On-the-fly
Analysis,
Learning &
Prediction

7. Copyright © 2019 SWIM.AI inc7
Web Agents Concurrently Compute as Data Flows
MapReduce
Graph
Alerts & Analytics
Learning & Prediction
Analyze data to determine state
Relational
Relational Queries
Real-world Digital Twins

8. Copyright © 2019 SWIM.AI inc
Web agents continuously compute on their own
state and the state of linked web agents
enabling granular contextual analysis on-the-fly
① SwimOS creates a web agent
for each thing in streaming data
② Agents interlink to reflect
real-world relationships
③ Powerful operators for analysis, learning &
prediction continuously compute on state of
this and linked agents & stream results
Web Agents Link to Form a Computational Graph

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Eg:Un-supervised Training & Prediction
Back
Propagation
Training
Δ
Predicted
Observed

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Fabric
NATS
EventsAnalyzed
Data
Mesh of SwimOS
Instances
Distributed graph
of web agents
Compute continuously
as data flows over the
graph
Web agent
address space
Clustered Stream Processor Operation

11. Copyright © 2019 SWIM.AI inc
• A scaled application is a graph
dynamically built from data
• Objects are stateful and concurrent
• SwimOS typescript / js UI tools show
insights in real time
• SwimOS scales to billions of web agents
in a hybrid, distributed cloud environment

12. Copyright © 2019 SWIM.AI inc
https://traffic.swim.ai

13. Copyright © 2019 SWIM.AI inc
Swim Automates App Lifecycle
• SwimOS is a set of extensions for the Graal VM
• Runs in user-mode on Linux
• Integrated into DevOps workflow using standard Java tools
• (See developer.swim.ai)
• Builds a fabric of SwimOS instances
• Each instance is a container deployed using Kubernetes
• Supports hybrid and multi-cloud deployments
• Each instance is fully connected to all other instances
• Mesh is built using web sockets
• Wire protocol is WARP, used to stream state of web agents

14. Copyright © 2019 SWIM.AI inc
• 150 million+ devices
• 10Gbps+ of streaming data
• Continuous analytics, aggregations &
reductions, with millisecond latency
• Pervasively real-time user interface
• Completely decentralized
Example: Mobile Operator

15. Copyright © 2019 SWIM.AI inc
Swim DataFabric
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• Fast Granular Decisions with visibility in
milliseconds
• Immediate Action from real-time analysis/
alerts
• Stateful Model (live) of critical state from
raw data feeds reduces volumes and
costs
• Massively Reduced Costs typically under
5% of big data cost
Business Advantages
Fabric Computing
Digital Twins
Analytics
Machine Learning

16. Copyright © 2019 SWIM.AI inc
Swim
Traffic - http://traffic.swim.ai
Transit - https://www.swim.ai/showcase/transit
Local Learning - https://splash.swim.ai/
Interactive- http://ripple.swim.ai/