Normally, RabbitMQ is designed to push individual messages to API endpoints. The legacy systems I'm working with would prefer to either pull batches of messages by calling an API or receive batched messages in a file placed in a folder. Are there any tools or best practices for using RabbitMQ for these types of integrations?
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I would like to know how, if possible, a client app (winform) sends NServicebus command A to be processed by a MSMQ queue and command B to be processed by a Azure storage queue or Azure service bus? If not, how may I get around of it?
Since this question was asked, there is now a transport bridge which is specifically for this scenario: bridging messages between two different transports.
Will this help? https://docs.particular.net/samples/azure/azure-service-bus-msmq-bridge/
Common examples include:
A hybrid solution that spans across endpoints deployed on-premises and in a cloud environment.
Departments within organization integrating their systems that use different messaging technologies for historical reasons.
Traditionally, such integrations would require native messaging or relaying. Bridging is an alternative, allowing endpoints to communicate over different transports without a need to get into low-level messaging technology code. With time, when endpoints can standardize on a single transport, bridging can be removed with a minimal impact on the entire system.```
I have a producer of tasks and multiple workers to consume those tasks. Many places recommend rabbitmq and/or celery. However python has a builtin multiprocessing queue that can be shared on an ip/port using a manager/proxy. What would be the advantages of using something like rabbitmq instead?
RabbitMq is an enterprise level tool, typically deployed separately on out-of-process servers / VMs / Containers, and plays in the enterprise service bus space.
Rabbit has reliable messaging as an objective - e.g. messages are persisted, and nodes in the cluster can be restarted without losing messages.
Supports a large range of messaging topologies, such as Point-Point, Fan out, and Topic subscriptions
Can be scaled for volume by adding multiple nodes to a cluster
Allows for conditional routing of messages to queues using routing keys or header filters
Agnostic of client technology, i.e. Clients can be on any platform which support the AMQP protocol
Has an out of the box administration, monitoring and diagnostics UI
Has a wide range of extensions and tools, such as shovels allowing messages to be replicated across multiple RabbitMQ clusters.
I'm no Python expert, but from what I understand of the multiprocessing package, it serves as an manager for distributing work between worker processes and threads, so IMO would be regarded as a more local system concern, as opposed to 'enterprise' level.
e.g. you would need to handle persistence, i.e. so messages are not lost during a crash / restart, and would likely need to built your own administration and monitoring tools.
I need to know the actual difference between them. I just learned of these techs at the high level.
No. AWS SWF is a workflow orchestration engine which has internal queueing support to deliver activity tasks. It is focused on coordinating execution of those tasks. SQS is a pure queue without any other additional features.
My understanding is that RubbitMQ is more like SQS, just not as fault tolerant and scalable and Celery is just a Python client side library to consume from it.
AWS SWF provides its own client side libraries to consume from its internal queues (called task lists)
I am currently developing a typical IoT service. At the moment multiple devices connect to one MQTT broker (mosquitto) and my java backend also connects to the broker (Paho).
The problem i see is the following:
When i am going to have multiple instances of my java backend every backend will receive and process every message received. That`s a big issue. I just want to deliver a message to only one java backend. Anybody an idea how to deal with this problem?
Btw: Java backends will be added or removed depending on the load.
There are a couple of options
Place a queuing system between your application and the MQTT broker, possibly something like Apache Kafka
HiveMQ and IBM MessageSight brokers support (different implementations) of something called shared subscriptions. This allows messages to be shared out between more than one client. Shared subscriptions is likely to be formally added to the MQTTv5 spec which should mean that it will be added to more broker and have a standard implementation.
Being new to the RabbitMQ I was wondering how to deal with an offline target node.
As an example this scenario:
1 log recording application that stores logs to some persistent storage
N log publishing applications that want their logs to be written to the persistent storage via the log recording server.
There would be two options:
Each publishing application publishes it's log messages to it's local RabbitMQ instance and the log recording server must subscribe to each of these
The log recording application has it's local RabbitMQ instance on which each log publishing application delivers it's messages.
Option 1 would require me to reconfigure/recode/notify the recording application each time a new application appears or moves. Therefore I would think Option 2 is the right one, each new publishing application simply writes to the RabbitMQ Node of the recording application.
The only thing I am struggling with is how to deal with a situation in which the Node of the recording application is down. Do I need to build my own system to store the messages until it's back online or can I use some functionality of RabbitMQ to deal with that? I.e. could the local RabbitMQ of each of the publishing applications just receive the messages and forward them to the recording application RabbitMQ as soon as it's back online?
I found something about the Federated plugin be couldn't understand if that's the solution. Maybe I need something different or maybe I have to write my own local queueing system (which I hope I don't have to) to queue messages when the target Node is offline.
Any links to architectural examples or solutions are more than welcome.
BTW: https://groups.google.com/forum/#!topic/easynetq/nILIKSjxyMg states that you shouldn't be installing a RabbitMQ Node for each application, so maybe I should resort to something like MSQM or ZeroMQ (?)
From experience in what sounds like a similar situation, I would suggest using something other than a queue to store the messages locally, when offline.
Years ago, I built a system that had to work offline - no network connection at all - and then had to push messages through a message queue to the central server, when the laptop was brought back to the office.
I solved this by using a local database (sqlite at the time) to store my messages when the message queue was not available.
You should do something similar. Use a local database or even a plain text file or CSV file to store your messages when RabbitMQ is offline. When it reconnects, read the messages from your local file system and send them through RabbitMQ.
This is a good strategy to use, even if you do not expect RabbitMQ to go offline. Frankly, it will go offline at some point and you will have to deal with it. You should be prepared for that situation, and having a local store for your messages will help that.
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regarding rqm node per application: bad idea. this adds a ton of complexity to your system. You want as few RabbitMQ nodes as you can get away with. Meaning, 1 per system (a system being comprised of many applications) when possible... with the exception of RabbitMQ clusters for availability - but that's another line of questions and design, entirely.
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I did an interview with Aria Stewart about designing for failure with RabbitMQ and messaging systems, and have a small excerpt where she talks about how networks fail.
The point is, the network or RabbitMQ or something will fail and you will need a solution like a local datastore so that you can recover when RabbitMQ comes back online.