David Duke

[David Duke @DavidDDukeMD]

@justcantscroll 1

[David Duke @DavidDDukeMD]

@Ustroopss D

[David Duke @DavidDDukeMD]

@GuntherEagleman I’m spending it

[David Duke @DavidDDukeMD]

@Thecargi01 F80

[David Duke @DavidDDukeMD]

@FanDuel F

[David Duke @DavidDDukeMD]

@SInow He sucked

[Synadia @synadia]

AI systems that interact with the physical world have a blind spot:

the boundary between cloud and edge.

Getting data from a sensor to a model is one problem. Getting a decision from a model back to an actuator is another.

Most architectures solve one direction well and treat the other as an afterthought.

But AI systems that interact with the physical world don’t get that luxury.
They have to close a control loop.

Events up:
Telemetry from thousands of sensors, distilled into meaningful signals at the source, flowing securely to wherever inference happens.

Commands down:
Decisions translated into actions and pushed back to the edge—reliably, securely, and fast enough to keep up with physics.

A turbine doesn’t care how good your model is if the throttle command arrives 500 ms late.

A robot arm doesn’t care about your 99.9% uptime if the 0.1% happens mid-motion.

This is where many architectures fail.

Stacks that stitch together Kafka for ingest, MQTT for delivery, Redis for state, and a custom edge gateway often look fine on arch diagrams.

But they break down when used as a true control plane.

Every seam adds latency.
Every translation adds failure modes.
Every boundary expands the security surface.

The cloud–edge handoff isn’t an implementation detail you can “solve later.”

For physical-world AI, it is the architecture.

The teams winning at edge AI aren’t the ones with the best models.

They’re the ones that built a real nervous system:

one architecture - bidirectional - secure - and fast enough to act while it still matters.

That's what we're building at Synadia with @nats_io

[David Duke @DavidDDukeMD]

@TreyBiddy We have 3 permanent SEC foes we CAN’T beat. We won’t see a bowl game for years

[David Duke @DavidDDukeMD]

@ScottiePippen Yep

[David Duke @DavidDDukeMD]

@RazorbackBSB It’s time for a coaching change

[Barun @barundebnath]

I’ve been playing with @nats_io at work for over a year, from building small POCs to configuring it for scale and reliability.

I just published a blog at @One2NC, Part 1 of a two-part series summarizing everything I’ve learned about deploying a scalable NATS cluster.

Please give it a read, link in the first comment! 👇

[David Duke @DavidDDukeMD]

@elonmuskTN Yes

[David Duke @DavidDDukeMD]

@ElonMuskAOC Love it. Nothing performs like a Tesla

[Tomasz Pietrek @TomaszPietrek]

Big day for NATS!

[Synadia @synadia]

Join us on March 20th for the largest NATS community event of the year!

Hosted by Synadia, RethinkConn 2025 will include roadmap updates, interactive demos, and stories from NATS users building and scaling innovative distributed systems.

https://t.co/D88vKfmPZf

[NATS.io @nats_io]

Check out this LI post from our .NET expert @_mtmk

A quick intro to using NATS .NET with the new simplified interface to help newcomers with expected defaults:
https://t.co/pS4mz6Sqs8

[Derek Collison @derekcollison]

Happy 14th Birthday to @nats_io. It has been an incredible journey so far and we at @synadia are excited about what the future holds!

A sincere thanks to our ecosystem of amazing users, partners and customers.

[David Duke @DavidDDukeMD]

@iamnot_elon A

[Synadia @synadia]

Our founder and CEO @derekcollison is featured in this Q&A article by @pulse2news, discussing his vision for Synadia: to deliver an open-source platform for real-time, secure access to services and data in any geography, with any cloud provider, in any edge environment.
https://t.co/Wpj9usf46M

[Dustin Deus @dustindeus]

After digging into how Kafka works, it is not surprising that @nats_io (JetStream) has become so popular for service-to-service communication. Nats is more powerful in message routing and is much easier to understand. Kafka seems like a good option for building raw data processing pipelines (ETL, Analytics).

In NATS, you can create a stream that covers subjects like "employeeUpdates.*". Any activity on the stream will be forwarded to all matching subscriptions, e.g., "employeeUpdates.12". This seems not possible in Kafka because Kafka doesn't support this level of abstraction. You can have regex topics on the consumer side, but this is not the same. The solution is to handle the matching on the processing layer rather than on the routing layer.