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That's like $0.50/day in aws costs. Absolutely no reason to switch if it's working.
When you said that number, I had a completely different reaction. 20 messages per second is absolutely nothing, $0.50 per day for that is dreadful. A $5 per month ($0.16 per day) VPS can deliver many thousands of messages per second.
I've regarded RabbitMQ as a secret weapon in plain sight for years. The killer reason people don't use it more is it "doesn't scale" to truly enormous sizes, but for anyone with less than a million users it's great. Too many people end up with their own half rolled pubsub via things like grpc, and they'd be far better off using this, particularly in the early stages of development.
Also want to give a shoutout to BeanStalkd: https://github.com/beanstalkd/beanstalkd If you are looking at RabbitMQ with "Maybe this is too much". Beanstalkd likely has features you need with almost none of the setup. Just don't web expose it ;)
I only used it on one project years ago and it was a pleasure, dead easy to get up and running and rock solid.
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I agree, but there are a lot of footguns with RMQ. A great example of one is that you'll slow down your cluster by adding more RMQ servers (something that's bit us in the past). Which is a forgivable mistake as most people would expect that more cores == faster RMQ. (For RMQ, that doesn't work because Durable messages need to be replicated to the other nodes in the cluster. More nodes == more replication) The ideal R…
The most common elephant foot gun in the room is buggy processes letting queues grow. RMQ immediately slows down (due to mnesia causing delays) and processes start dropping messages despite having system resources to grow.
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Two different models. The metaphor I like to use is that RabbitMQ is a postal system, while NATS is a switchboard. RabbitMQ is a "classical" message broker. It routes messages between queues. Messages are treated like little letters that fly everywhere. They're filed in different places, and consumers come by and pick them up. Core NATS isn't really a message broker, but more of a network transport. There are no queu…
Sorry, I'm not familiar with this tech so looked up Jetstream and it seems to be archived https://github.com/nats-io/jetstream . Not sure that would be a good endorsement to try to use something that is no longer maintained or am I looking at the wrong one?
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When I read this message I think this an absolutely terrible waste of time for a startup/small company. I want to spend my time building features not infrastructure.
This stuff is so trivially easy these days. 20 years ago it was hard to deploy a clustered message queue application, but now we've got so much open source tooling. Are you telling me you can't deploy RabbitMQ in an afternoon? Give it a day or two and you've got a monitoring stack and some swanky GitOps. Now your OpEx has been reduced 80x for hardly doing anything. As for continual maintenance, us-east-1 has gone dow…
When you think about it, ideally most managed services have found some natural price for their services that helps make the above logic work. And if it does not, it might be actually overpriced. I suspect a lot of folks that say roll your own are undervaluing their time.
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The most common elephant foot gun in the room is buggy processes letting queues grow. RMQ immediately slows down (due to mnesia causing delays) and processes start dropping messages despite having system resources to grow.
can you elaborate on the details? I have some memories about running OpenStack where Rabbit "was slow", but we never figured out why. mnesia is the storage layer?
I decided to add expiry policies to each queue so that the system cleans itself from stale messages and that fixed all the message dropping issues.
4.0 Changelogs state that they are switching to a new k/v storage (switching from experimental to default)
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can you elaborate on the details? I have some memories about running OpenStack where Rabbit "was slow", but we never figured out why. mnesia is the storage layer?
Yes, it was using mnesia as the storage layer, and if I had a few dozen queues with a few hundred messages each, it caused timeouts in some clients (celery/kombu is an example). I decided to add expiry policies to each queue so that the system cleans itself from stale messages and that fixed all the message dropping issues. 4.0 Changelogs state that they are switching to a new k/v storage (switching from experimental…
Yep, similar symptoms. (OpenStack's services are also written in Python, or at least were back then, so probably similar to Celery.) We had regular problems with RMQ restarting. (Unfortunately I can't recall if it was for OOM or just some BEAM timeout.)
A few hundred messages in a few dozen queues seem ... inconsequential. I mean whatever on-disk / in-memory data structure mnesia has should be able to handle ~100K stale messages ... but, well, of course there's a reason they switched to a new storage component :)
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This stuff is so trivially easy these days. 20 years ago it was hard to deploy a clustered message queue application, but now we've got so much open source tooling. Are you telling me you can't deploy RabbitMQ in an afternoon? Give it a day or two and you've got a monitoring stack and some swanky GitOps. Now your OpEx has been reduced 80x for hardly doing anything. As for continual maintenance, us-east-1 has gone dow…
Depends if you value your time more than minimum wage. There is certainly a time and a place for everything but I don’t really feel like being responsible for something that costs the $N a month managed. Sure I could do it myself but my time is worth more. When you think about it, ideally most managed services have found some natural price for their services that helps make the above logic work. And if it does not, i…
Link without description or anything, nice. After reading the website for 30 seconds, my question would be: What is RabbitMQ?