I want to use acks_late=True for some idempotent tasks, but I'm unsure how hard disconnections between the workers and RMQ are treated when there are no application heartbeats probing the connection.
librabbitmq does not support heartbeats, but the pyampq libs do. I'm being cautious about what that means for acks_late, as I don't want messages sitting in the queue being "processed" forever.
Related
I have an app with hundreds of horizontally scaled servers which uses redis pub/sub, and it works just fine.
The redis server is a central point of failure. Whenever redis fails (well, it happens sometimes), our application falls into inconsistent state and have to follow recovery process which takes time. During this time the entire app is hardly useful.
Is there any messaging system/framework option, similar to redis pub/sub, but with redundancy and high availability so that if one instance fails, other will continue to deliver the messages exchanged between application hosts?
Or, better, is there any distributed messaging system in which app instances exchange the messages in a peer-to-peer manner, so that there is no single point of failure?
I have a 3 node cluster of Rabbitmq behind a HAproxy Load Balancer. When I shut down a node, Rabbitmq successfully switches the queue to the other nodes. However, I notice that Logstash stops pulling messages from the queue unless I restart it. Is this a problem with the way rabbitmq operates? i.e. it deactivates all active consumers. I am not sure if log stash has any retry capability. Anyone run into this issue?
Quoting rabbit mq documentation, page for clustering first
What is Replicated? All data/state required for the operation of a
RabbitMQ broker is replicated across all nodes. An exception to this
are message queues, which by default reside on one node, though they
are visible and reachable from all nodes.
and high availability
Clients that are consuming from a mirrored queue may wish to know that
the queue from which they have been consuming has failed over. When a
mirrored queue fails over, knowledge of which messages have been sent
to which consumer is lost, and therefore all unacknowledged messages
are redelivered with the redelivered flag set. Consumers may wish to
know this is going to happen.
If so, they can consume with the argument x-cancel-on-ha-failover set
to true. Their consuming will then be cancelled on failover and a
consumer cancellation notification sent. It is then the consumer's
responsibility to reissue basic.consume to start consuming again.
So, what does all this mean:
You have to mirror queues
The consumers should use manual ACK
The consumers should reconnect on their own
So the answer to your question is no, it's not a problem with rabbitmq, that's simply how it works. It's up to clients to reconnect.
I have used BlockingQueue implementation to process my events by services from a queue. However in case if the server goes down, all my events from that queue are getting deleted and hence I am missing events to process. (I am looking for some internal DB where server can store the event/messages from queue and if server goes down and up again, it can load all events/messages to process again, without manually intervention).
Any help on this. I am not sure if I should use Apache ActiveMQ. I am using apache servicemix.
Thanks in advance.
I can not answer about how to do this with BlockingQueue.
But ActiveMQ has two features that you will benefit from:
Persistent Queues and possibly you might also want to look at Durable Queues
It has a built in database that just does this under the hood and allows messages to be persisted in queue even if broker or consumer has to restart.
Can I access SEDA or VM queue from another machine or JVM?
I actually want to implement load balancing with the help of Camel but do not want introduce another messaging framework for this. I just want to distribute load to different consumers from a producers using some in built queue.
Is it possible? If no then what are my options?
Another Approach:(Pull Approach)
Not sure how optimum new approach is or what are the advantages and disadvantages of new approach, So please help me to analyze this approach.
Messages will be put into a Master queue and all the worker systems will be listening to Master queue.Let's say 100,000 messages are being put into Master queue and 5 worker systems are listening to it. Worker systems will process the messages one by one from the master queue. There are two big benefits with this approach:
I don't need to worry about registering my worker systems with the producer. Sixth system just boot up and start listening to Master queue.
I don't need to worry about sending message to a consumer system which is free. When worker system will be done processing a message, it pick up another one from the Master queue.
Let me know your thoughts on it.
SEDA and VM:// work only on the same JVM.
Load balancing in Java messaging is usually achieved using the JMS and Competing Consumers pattern. You send messages to the queue and multiple consumers compete to process them.
If broker with its queue becomes a bottleneck - consider using fan-out pattern and the network of brokers.
SEDA and VM endpoints are valid for the host Context and JVM respectively. To facilitate JVM-to-JVM messaging you will need to use an over-the-wire protocol component such as, but not limited to, Mina, HTTP or JMS.
The easiest way is to use jms. If you have n routes listening on the same jms queue then they will automatically load balance. If one goes away the load will be balanced over the remaining ones. I recommend starting with ActiveMQ as it is very easy to setup and well integrated with Camel.To make the broker highly available you can either setup two standalone brokers or setup one embedded broker per camel instance.
All,
I'm looking for advice over the following scenario:
I have a component running in one part of the corporate network that sends messages to an application logic component for processing. These components might reside on the same server, different servers in the same network (LAN ot WAN) or live outside in the cloud. The application server should be scalable and resilient.
The messages are related in that the sequence they arrive is important. They are time-stamped with the client timestamp.
My thinking is that I'll get the clients to use WCF basicHttpBinding (some are based on .NET CF which only has basic) to send messages to the Application Server (this is because we can guarantee port 80/443 will be open for outgoing connections). Server accepts these, and writes these into a queue. This queue can be scaled out if needed over multiple machines.
I'm hesitant to use MSMQ for the queue though as to properly scale out we are going to have to install seperate private queues on each application server and round-robin monitor the queues. I'm concerned though that we could lose a message on a server that's gone down until the server is restored, and we could end up processing a later message from a different server and disrupt the sequence.
What I'd prefer is a central queue (e.g. a database table) that all application servers monitor.
With this in mind, what I'd like to do is to create a custom WCF binding, similar to netMsmqBinding, but that uses the DB table instead but I'm confused as to whether I can simply create a custom transport or a I need a full binding, and whether the binding will allow the client to send over HTTP. I've looked around the internet but I'm a little confused as to where to start.
I could not bother with the custom WCF binding but it seems a good way to introduce scalability if I do need to seperate the servers.
Any suggestions please would be helpful, including alternatives.
Many thanks
I would start with MSMQ because it is exactly for this purpouse. Use single transactional queue on clustered machine and let application servers to take messages for processing from this queue. Each message processing has to be part of distributed transaction (MSDTC).
This scenario will ensure:
clustered queue host will ensure that if one cluster node fails the other will still be able to handle requests
sending each message as recoverable - it means that message will be persisted on hard drive (not only in memory) so in critical failure of the whole cluster you will still have all messages.
transactional queue will ensure that all message transport operations will be atomic - moving message from outgoing queue to destination queue will be processed as transaction. It means that original message from outgoing queue will be kept in queue until ack from destination queue arrives. Transactional processing can ensure in order delivery.
Distributed transaction will allow application servers consuming messages in transaction. Message will not be deleted from queue until application server commits transaction or transaction time outs.
MSMQ is also available on .NET CF so you can send messages directly to queue without intermediate non-reliable web service layer.
It should be possible to configure MSMQ over HTTP (but I have never used it so I'm not sure how it cooperates with previous mentioned features).
Your proposed solution will be pretty hard. You will end up in building BizTalk's MessageBox. But if you really want to do it, check Omar's post about building database queue table.