We use RabbitMQ as a queuing system for our client's 3rd party accounts application. There are a few reasons but one is that we can control the speed at which data goes into the application. Sometimes a massive queue will build up and this works really well.
However we want to use RabbitMQ for another application which we'd like to be separate and be more real-time.
Would a separate exchange/queue work best?
Do I need a separate console app?
If there are 100,000 messages queued up for the accounts app I'd like other app to process straight way
if you want to handle more applications, one solution is to use the rabbitmq virtual hosts, in this way you have different enviroments and you can also use different users/password to access.
In general the best way to scale is to scale the queues, in case you need to handle an high throughput you can create a cluster and scale the traffic between the nodes.
you should avoid to have one giant queue! .. so more queues more scale!
Related
We have been using ActiveMQ version 5.16.0 broker with single instances in production. Now we are planning to use cluster of AMQ brokers for HA and load distribution with consistency in message data. Currently we are using only one queue
HA can be achieved using failover but do we need to use the same datastore or it can be separated? If I use different instances for AMQ brokers then how to setup a common datastore.
Please guide me how to setup datastore for HA and load distribution
Multiple ActiveMQ servers clustered together can provide HA in a couple ways:
Scale message flow by using compute resources across multiple broker nodes
Maintain message flow during single node planned or unplanned outage of a broker node
Share data store in the event of ActiveMQ process failure.
Network of brokers solve #1 and #2. A standard 3-node cluster will give you excellent performance and ability to scale the number of producers and consumers, along with splitting the full flow across 3-nodes to provide increased capacity.
Solving for #3 is complicated-- in all messaging products. Brokers are always working to be completely empty-- so clustering the data store of a single-broker becomes an anti-pattern of sorts. Many times, relying on RAID disk with a single broker node will provide higher reliability than adding NFSv4, GFSv2, or JDBC and using shared-store.
That being said, if you must use a shared store-- follow best practices and use GFSv2 or NFSv4. JDBC is much slower and requires significant DB maintenance to keep running efficiently.
Note: [#Kevin Boone]'s note about CIFS/SMB is incorrect and CIFS/SMB should not be used. Otherwise, his responses are solid.
You can configure ActiveMQ so that instances share a message store, or so they have separate message stores. If they share a message store, then (essentially) the brokers will automatically form a master-slave configuration, such that only one broker (at a time) will accept connections from clients, and only one broker will update the store. Clients need to identify both brokers in their connection URIs, and will connect to whichever broker happens to be master.
With a shared message store like this, locks in the message store coordinate the master-slave assignment, which makes the choice of message store critical. Stores can be shared filesystems, or shared databases. Only a few shared filesystem implementations work properly -- anything based on NFS 4.x should work. CIFS/SMB stores can work, but there's so much variation between providers that it's hard to be sure. NFS v3 doesn't work, however well-implemented, because the locking semantics are inappropriate. In any case, the store needs to be robust, or replicated, or both, because the whole broker cluster depends on it. No store, no brokers.
In my experience, it's easier to get good throughput from a shared file store than a shared database although, of course, there are many factors to consider. Poor network connectivity will make it hard to get good throughput with any kind of shared store (or any kind of cluster, for that matter).
When using individual message stores, it's typical to put the brokers into some kind of mesh, with 'network connectors' to pass messages from one broker to another. Both brokers will accept connections from clients (there is no master), and the network connections will deal with the situation where messages are sent to one broker, but need to be consumed from another.
Clients' don't necessarily need to specify all brokers in their connection URIs, but generally will, in case one of the brokers is down.
A mesh is generally easier to set up, and (broadly speaking) can handle more client load, than a master-slave with shared filestore. However, (a) losing a broker amounts to losing any messages that were associated with it (until the broker can be restored) and (b) the mesh interferes with messaging patterns like message grouping and exclusive consumers.
There's really no hard-and-fast rule to determine which configuration to use. Many installers who already have some sort of shared store infrastructure (a decent relational database, or a clustered NFS, for example) will tend to want to use it. The rise in cloud deployments has had the effect that mesh operation with no shared store has become (I think) a lot more popular, because it's so symmetric.
There's more -- a lot more -- that could be said here. As a broad question, I suspect the OP is a bit out-of-scope for SO. You'll probably get more traction if you break your question up into smaller, more focused, parts.
If as admin I wanted to know from a particular queue A, how many calls initiated by which person and how many get dequeued, and how many are still in queue # any time.
I just want to develop one UI in my application to show those user-specific records from ActiveMQ.
There is no built in functionality in the broker that does this sort of thing. You could develop your own broker plugin that tracks these things but you'd need to build some sort of DB or other storage as you would lose any in-memory stats when a broker is restarted. You should use caution when trying to push all requirements into the message broker for system level management as that is not its purpose and will likely result in other issues when you do.
I have a cluster of backend servers on GCP, and they need to send messages to each other. All the servers need to receive every message, but I can tolerate a low error rate. I can deal with receiving the message more than once on a given server. Packet ordering doesn't matter.
I don't need much of a persistence layer. A message becomes stale within a couple of seconds after sending it.
I wired up Google Cloud PubSub and pretty quickly realized that for a given subscription, you can have any number of subscribers but only one of them is guaranteed to get the message. I considered making the subscribers all fail to ack it, but that seems like a gross hack that probably won't work well.
My server cluster is sized dynamically by an autoscaler. It spins up VM instances as needed, with dynamic hostnames and IP addresses. There is no convenient way to map the dynamic hosts to static subscriptions, but it feels like that's my only real option: Create more subscriptions than my max server pool size, and then use some sort of paxos system (runtime config, zookeeper, whatever) to allocate servers to subscriptions.
I'm starting to feel that even though my use case feels really simple ("Every server can multicast a message to every other server in my group"), it may not be a good fit for Cloud PubSub.
Should I be using GCM/FCM? Or some other technology?
Cloud Pub/Sub may or may not be a fit for you, depending on the size of your server cluster. Failing to ack the messages certainly won't work because you can't be sure each instance will get the message; it could just be redelivered to the same instance over and over again.
You could use multiple subscriptions and have each instance create a new subscription when it starts up. This only works if you don't plan to scale beyond 10,000 instances in your cluster, as that is the maximum number of subscriptions per topic allowed. The difficulty here is in cleaning up subscriptions for instances that go down. Ones that cleanly shut down could probably delete their own subscriptions, but there will always be some that don't get cleaned up. You'd need some kind of external process that can determine if the instance for each subscription is still up and running and if not, delete the subscription. You could use GCE shutdown scripts to catch this most of the time, though there will still be edge cases where deletes would have to be done manually.
I would like to create a cluster for high availability and put a load balancer front of this cluster. In our configuration, we would like to create exchanges and queues manually, so one exchanges and queues are created, no client should make a call to redeclare them. I am using direct exchange with a routing key so its possible to route the messages into different queues on different nodes. However, I have some issues with clustering and queues.
As far as I read in the RabbitMQ documentation a queue is specific to the node it was created on. Moreover, we can only one queue with the same name in a cluster which should be alive in the time of publish/consume operations. If the node dies then the queue on that node will be gone and messages may not be recovered (depends on the configuration of course). So, even if I route the same message to different queues in different nodes, still I have to figure out how to use them in order to continue consuming messages.
I wonder if it is possible to handle this failover scenario without using mirrored queues. Say I would like switch to a new node in case of a failure and continue to consume from the same queue. Because publisher is just using routing key and these messages can go into more than one queue, same situation is not possible for the consumers.
In short, what can I to cope with the failures in an environment explained in the first paragraph. Queue mirroring is the best approach with a performance penalty in the cluster or a more practical solution exists?
Data replication (mirrored queues in RabbitMQ) is a standard approach to achieve high availability. I suggest to use those. If you don't replicate your data, you will lose it.
If you are worried about performance - RabbitMQ does not scale well.
The only way I know to improve performance is just to make your nodes bigger or create second cluster. Adding nodes to cluster does not really improve things. Also if you are planning to use TLS it will decrease throughput significantly as well. If you have high throughput requirement +HA I'd consider Apache Kafka.
If your use case allows not to care about HA, then just re-declare queues/exchanges whenever your consumers/publishers connect to the broker, which is absolutely fine. When you declare queue that's already exists nothing wrong will happen, queue won't be purged etc, same with exchange.
Also, check out RabbitMQ sharding plugin, maybe that will do for your usecase.
I'm using RabbitMQ as a message queue in a service-oriented architecture, where many separate web services publish messages bound for RabbitMQ queues. Those queues are in turn subscribed to by various consumers, which perform background work; a pretty vanilla use-case for RabbitMQ.
Now I'd like to change some of the queue parameters (specifically, I'd like to bind queues to a new dead-letter exchange with a certain routing key). My problem is that making this change in place on a production system is problematic for a couple reasons.
Whats the best way for me to transition to these new queues without losing messages in a production system?
I've considered everything from versioning queue names to making a new vhost with the new settings to doing all the changes in place.
Here are some of the problems I'm facing:
Because RabbitMQ queues are idempotent, the disparate web services have been declaring the queues before publishing to them (in case they don't already exist). Once you change the queue parameters (but maintain the same routing key), the queue declare fails and RabbitMQ closes the channel.
I'd like to not lose messages when changing a queue (here I'm planning on subscribing an exclusive consumer that saves the messages and then republishes to the new queue).
General coordination between disparate publishers and the consumer base (or, even better, a way to avoid needing to coordinate them).
Queues bindings can be added and removed at runtime without any impact on clients, unless clients manually modify bindings. So if your question only about bindings just change them via CLI or web management panel and skip what written below.
It's a common problem to make back-incompatible changes, especially in heterogeneous environment, especially when multiple applications attempts to declare same entity in their own way (with their specific settings). There are no easy way to change queue declaration at the same time in multiple applications and it highly depends on how whole working process organized, how critical your apps are, what is your infrastructure and etc.
Fast and dirty way:
While the publishers doesn't deals with queues declaration and bindings (at least they should not do that), you can focus on consumers. Wrapping queues declaration in try-except block may be the fast and dirty choice. Also most projects, even numerous can survive small downtime, so you can block rabbitmq user in one shell, alter queue as you wish (create new one and make your consumers use it instead of old one) and then unblock user and let consumers works as before (your workers are under supervisor or monit, right?). Then migrate manually messages from old queue to new one.
Fast and safe solution:
Is is a bit tricky and based on a hack how to migrate messages from one queue to another inside single vhost. The whole solution works inside single vhost but requires extra queue for every queue you want to modify. Set up Dead Letter Exchanges on source queue and point it to route expired messages to your new target queue. Then apply Per-Queue Message TTL to source queue, set x-message-ttl=0 (to it's minimal value, see No Queueing at all note about immediate delivery). Both actions can be done via CLI or management panel and can be done on already declared queue. In this way your publishers can publish messages as usual and even old consumers can work as expected for the first time, but in parallel new consumers can consume from new queue which can be pre-declared with new args manually or in other way.
Note, that on queues with large messages number and huge messages flow there are some risks to met flow control limits, especially if your server utilize almost all of it resources.
Much more complicated but safer approach (for cases when whole messages workflow logic changed):
Make all necessary changes to applications and run new codebase in parallel to existing one, but on the different RabbitMQ vhost (or even use separate server, it depends on your applications load and hardware). Actually, it may be possible to run on the same vhost but change exchanges and queues name, but it even doesn't sound good and smells even in written form. After you set up new apps, switch them with old one and run messages migration from old queues to new one (or just let old system empty the queues). It guaranties seamless migration with minimal downtime. If you have your deployment automatized, whole process will not takes too much efforts.
P.S.: in any case above, if you can, let old consumers to empty queues so you don't need to migrate messages manually.
Update:
You may find very useful Shovel plugin, especially Dynamic Shovels to move messages between exchanges and queues, even between different vhosts and servers. It's the fastest and safest way to migrate messages between queues/exchanges.