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Segment is probably the biggest NSQ user right now, and they're moving to Kafka - any employees want to weigh in? :)
by rjeli 9y ago
Segment is probably the biggest NSQ user right now, and they're moving to Kafka - any employees want to weigh in? :)
- caffeineninja 9y agoWe run 1.5 million messages per minute through our NSQ framework and we're starting to run into architectural limitations i.r.t to the number of workers in each producer/consumer pool, and are now testing/benchmarking Kafka in our staging environment.
- Roritharr 9y agoI think the biggest question is, do you think its feasible to directly start with Kafka instead of NSQ or does Kafka just require a much stronger/larger team to operate than NSQ?
- wand3r 9y agoIf you are starting off just use what you/the team is comfortable with. I mean, unless you think you will need capacity for over 25,000 messages per second.
- kasey_junk 9y agoKafka and NSQ have widely variant promises around things like durability, order, etc. In most use cases you can get NSQ like behavior out of Kafka and the inverse isn't true. Kafka's performance and added gaurantees come at the expense of being harder to operate.
- StavrosK 9y agoCan someone summarize the promises? Specifically, would NSQ work well as an easier-to-operate, Kafka alternative, or are there low-throughput use cases it's just not suitable for?
- rthille 9y agoI think it's less about throughput and more about durability guarantees. Kafka producers can specify the number of 'acks' (brokers which have written the message to disk) when they produce a message and the request will only return successfully if that can be done.
- StavrosK 9y agoI see, thank you. Can't NSQ do that, or at least get probabilistically close to it with multiple nodes (i.e. doesn't having more nodes reduce the probability of data loss)?
- be_erik 9y agoAbsolutely, but you can't rely on it to be persistent like Kafka. We use it extensively and are incredibly happy with it, but we follow best practices around not putting state in messages, making changes idempotent, and ensuring that we can always replay a message if needed. We've yet to lose any messages in production, but it could happen and we're okay with the tradeoffs between that and the operational complexity of kafka.
- StavrosK 9y agoYeah, at-least-once is definitely the way to go, sounds like you've got a good architecture around that. Another nice thing I've heard with Kafka is that it can store all messages since the beginning of time (if you want) and you can replay them to retrieve all your MQ-related state. Does NSQ do that, do you know?
- be_erik 9y agoWe debated the same question and went with NSQ for now. We might need some of the guarantees that Kafka makes in the longterm or for some specific use cases, but for a no thrills distributed messaging platform that is incredibly simple to operate at scale, NSQ is pretty fantastic. Building client libraries is also a joy. I blogged about it a bit here: https://product.reverb.com/how-to-write-an-nsq-consumer-in-go-96ed8bde29ef https://product.reverb.com/how-to-write-an-nsq-consumer-in-g...
- rafaeljesus 9y agoNice one! Just as a info, I wrapped producer/consumer in a pkg https://github.com/rafaeljesus/nsq-event-bus https://github.com/rafaeljesus/nsq-event-bus also it exposes request-reply/rpc like
- titobrown 9y agoKafka is much harder to operate in a production environment, I would only start there if you have a specific reason to.
- TheHydroImpulse 9y agoEngineer @ Segment NSQ has served us pretty well but long term persistence has been a massive concern to us. If any of our NSQ nodes go down it's a big problem. Kafka has been far more complicated to operate in production and developing against it requires more thought than NSQ (where you can just consume from a topic/channel, ack the message and be done). More to that, if you want more capacity you can just scale up your services and be done. With Kafka we had to plan how many partitions we needed and autoscaling has become a bit trickier. We now have critical services running against Kafka and started moving our whole pipeline to it as well. It's a slow process but we're getting there. We've had to build some tooling to operate Kafka and ramp up everyone else on how to use it. To be fair, we've also had to build tooling for NSQ, specifically nsq-lookup to allow us to scale up. We have an nsq-go library that we use in production along with some tooling: https://github.com/segmentio/nsq-go https://github.com/segmentio/nsq-go
- ah- 9y agoOut of interest, what kind of tooling did you build for Kafka?
- TheHydroImpulse 9y agoWe started deploying our Kafka cluster as a set of N EC2 instances but we started running into a bunch of issues (rolling the cluster, rolling an instance without moving partitions around, moving partitions around, etc...) Now we run Kafka through ECS and wrote some tooling to manage rolling the cluster and replacing brokers. krollout(1) (currently private) basically prevents partitions from becoming unavailable while rolling. Now that multiple teams are using Kakfa we started exploring how to scale up. Each team may have different requirements and isolation can become an issue. Likely more tooling will need to be built around this.
- doh 9y agoHave you ever looked at any proprietary solutions like Google's PubSub? We're running on PubSub for over year now and outside of some unplanned downtimes it's scaling very well. But as we're looking to branch out out of GCP we are looking at Kafka as an alternative. Could you comment on particular problems and challenges that you ran into? For the context, we're currently sending around 60k messages/sec and around 1k of them contains data larger than 10kb.