Patterns for Building Realtime Features

Indeed. This is just about user interfaces driven by remote events.

There are patterns for "real time". Things such as:

- What matters is the slowest case, not the average case.

- What has to be real time, and what can run in background?

- Avoiding priority inversions.

- Is there a stall timer that trips if you miss the control loop timing? What happens when the stall timer trips?

- What influence do caches have on time repeatability? What's the worst case? Can you keep the worst case from being the nothing-in-cache case?

Realms matter. I don't really feel that holding terms hostage between hardware and software worlds is worth much energy.

People that know enough to care will know within 1 second what the article is about.

"Soft real-time" is probably the correct term here, but that is actually more confusing for 99% of people.

"Interactive" is not descriptive. "Duplex" is certainly not obvious.

I've been writing elixir for years (i think since 0.14?) and have been writing liveview for years. I'm all in on elixir in general, but I'm not sure I'd use liveview for another big project. Maybe it's just rose colored glasses because the TS/React world certainly has its own issues, but I think TS/react and regular old phoenix is a sweet spot. The composability of live view components still has a number of footguns (duplicate IDs, etc) and I think it has higher coupling than a nicely structured react app. You also have to treat liveviews and components fairly differently. All these design choices are for good reason, but it ends up being annoying in a large app. Also in deeply nested trees with lots of component reuse, static typing from TS really helps with refactors. As the projects grew to be large, I think I'm more productive with phoenix/TS than I am with phoenix/liveview.

I think there's a certain class of small to medium sized application (I'm building several) where liveview can be a good fit, but after writing it professionally and in hobby projects for several years, I'm less convinced that it's a great solution everywhere.

I have not enjoyed a language and framework like I'm enjoying Elixir and Phoenix! It has become my stack for just about everything.

Exactly! I was halfway through the article and thought how LiveView is basically equivalent of the "push ops" pattern described but beautifully abstracted away and comes for free, while you (mostly) write dynamic HTML markup. Magic!

Came to the comments to say this. As I've been learning Elixir + LiveView, I've been consistently surprised at the amount you get for "free"

I think Elixir/Phoenix has to be the best stack currently for building applications with real-time features and that's all thanks to BEAM. Perhaps Go is another decent alternative but I definitely prefer BEAM's concurrency model.

I assume you are using Postgres? If so i believe you will be limited by max_notify_queue_pages.

I would instead try would be to create an event table in the db, then create a publication on that table and have clients subscribe to that publication via logical replication. You would have to increase the number of replication slots though.

I think you'll for an app like this you'll eventually want to go with something that was designed for a high throughput (I don't think LISTEN/NOTIFY was). Yes, it's nice because you get it out of the box with Postgres, but you'll find that it's not resilient, you need to be careful with managing DB connections (in your case of hundreds/thousands users it is a significant thing), and it's lackluster compared to a specialized PubSub.

In general you do it by doing a failover behind some variation of a reverse proxy.

If you can start new instances quickly and clients can handle short delays you can do it by just stopping the old deployment and starting the new one, booting off of the snapshotted state from the prior deployment.

If you need “instant” you do it by implementing some form of catchup and then fail over.

It is a lot easier to do this if you have a dedicated component that ”does” the failover, rather than having the old and new deployments try to solve it bilaterally. Could just be a script ran by a human, or something like a k8s operator if you do this a lot

On BEAM/OTP you can control how state is handled at code updates. Finicky but you can.

In most other contexts you'd externalise state to a data store like Redis or RDBMS, and spawn one, kill one or do blue-green in the nebula behind your load balancer constellation.

Thanks for sharing your experience, and what you have found to work.

Sometimes I feel we (fellow HN readers) get caught into overly complex rabbit holes, so it's good to balance it out with some down-to-earth, practical perspectives.

I've worked in robotics for a long time. In robotics nowadays you always end up with a distributed system, where each robot has to have a view of the world, it's mission, etc, and also of each other robot, and also the command and control dashboards do too, etc etc.

Always always always follow parent's advice. Pick one canonical owner for the data, and have everyone query it. Build an estimator at each node that can predict what the robot is doing when you don't have timely data (usually just running a shadow copy of the robot's software), but try to never ever do distributed state.

Even something as simple as a map gets arbitrarily complicated when you're sensing multiple locations. Just push everyone's guesses to a central location and periodically batch update and disseminate updates. You'll be much happier.