I have gone through (not fully) ActiveMQ and tried to figure out the deployment model for my application.
I am bit confused on that.
I want to make the system High Availability and decided to use the following. Please correct me if anything is wrong or disadvantage of the model.
Deployment Modle:
Will deploy Brokers in M1 and M2 respectivley.
Use Hardware load balancer (Either F5 or Zeus) to connect either one of the broker (M1 or M2) based on the load.
Want to publish a message using Load balancer URL.
I have gone through network of brokers and we need to mintain some topology. I fell which makes the system more complicated if system grows horizontally. So it is better to have one load balancer to distribute the load.
Questions
Is this above model will send message to any one of the Broker?
Consumer Will be deployed in Tomcat (Think i need to use embeded brokers to configure either M1 or M2). Is it possible to use Load balancer URL instaed of M1 or M2?
Is it possible to have single Web Console Admin to monitor both M1 and M2.
Do we have any performance issue using Spring's feature to consume message.
Sorry to shoot out so many questions. Please help me to correct the deployment model.
I think the best way to get some load balancing with some activemq servers is having a : network of brokers and your consumers/producers (in your webapps) should use some failover
So if a producer p1 send a message on a queue on broker 1, the consumer c1 can read the message on broker 2.
[Edit] I have never tried to add some hardware balancer instead of the activemq protocole failover. It should work : just try it and tell us.
3- I do not think it is possible to have only one Web Console to monitor both of your brokers.
4- As far as I am concerned I do not have any performance issue with my Spring configuration.
There are a lot of questions there.
The first thing is to do is start simple. If your application's load is being handled with just one broker, consider setting up high availability through a master-slave setup. For this you do not need a load balancer - the ActiveMQ client library has a failover mechanism where you can define the URLs to a set of brokers that the client should attempt to connect to.
If you are looking at setting up an infrastructure where one broker will not be able to deal with the message load (you can test the maximum throughput of your broker using the performance module), I would advise you to read up on how networks of brokers work. If you do go down this path, you really need to understand ActiveMQ.
On monitoring, a web console can only show you the internals of a single broker. To get insight around what is going on around a set of brokers you will need a monitoring tool such as FuseHQ/Hyperic that is able to aggregate JMX information from a number of boxes.
Performance with Spring is not a problem as long as you configure it correctly (see the section on PooledConnectionFactory).
I see that you are a new user, so if this answers your question, please tick it.
Related
We have a problem with Apache ActiveMQ Artemis cluster queues. Sometimes messages are beginning to pile up in the particular cluster queues. It usually happens 1-4 times per day and mostly on production (it was only one time for last 90 days when it has happened on one of the test environments).
These messages are not delivered to consumers on other cluster brokers until we restart cluster connector (or entire broker).
The problem looks related to ARTEMIS-3809.
Our setup is: 6 servers in one environment (3 pairs of master/backup servers). Operating system is Linux (Red Hat).
We have tried to:
upgrade from 2.22.0 to 2.23.1
increase minLargeMessageSize on the cluster connectors to 1024000
The messages are still being stuck in the cluster queues.
Another problem that I tried to configure min-large-message-size as it written in documentation (in cluster-connection), but it caused errors at start (broker.xml did not pass validation with xsd), so it was only option to specify minLargeMessageSize in the URL parameters of connector for each cluster broker. I don't know if this setting has effect.
So we had to make a script which checks if messages are stuck in the cluster queues and restarts cluster connector.
How can we debug this situation?
When the messages are stuck, nothing wrong is written to the log (no errors, no stacktraces etc.).
Which logging level (for what classes) should we enable to debug or trace level to find out what happens with the cluster connectors?
I believe you can remedy the situation by setting this on your cluster-connection:
<producer-window-size>-1</producer-window-size>
See ARTEMIS-3805 for more details.
Generally speaking, moving message around the cluster via the cluster-connection, while convenient, isn't terribly efficient (much less so for "large" messages). Ideally you would have a sufficient number of clients on each node to consume the messages that were originally produced there. If you don't have that many clients then you may want to re-evaluate the size of your cluster as it may actually decrease overall message throughput rather than increase it.
If you're just using 3 HA pairs in order to establish a quorum for replication then you should investigate the recently added pluggable quorum voting which allows integration with a 3rd party component (e.g. ZooKeeper) for leader election eliminating the need for a quorum of brokers.
I'm new to kafka.
Kafka is supposed to be used as a distributed service. But the tutorials and blog posts i found online never mention if there is one or several zookeeper nodes.
The tutorials just pop one zookeper instance, and then multiple kafka brokers.
Is it how it is supposed to be done?
Zookeeper is a co-ordination service (in a centralized manner) for distributed systems that is used by clusters for maintenance of distributed system . The distributed synchronization achieved by it via metadata such as configuration information, naming, etc.
In general architectures, Kafka cluster shall be served by 3 ZooKeeper nodes, but if the size of deployment is huge, then it can be ramped up to 5 ZooKeeper nodes but that in turn will add load on the nodes as all nodes try to be in sync as all metadata related activities are handled by ZooKeeper.
Also, it should be noted that as an improvement, the new release of Kafka reduces dependency on ZooKeeper in order to enhance scalability of metadata across, to reduce the complexity in maintaining the meta data with external components and to enhance the recovery from unexpected shutdowns. With new approach, the controller failover is almost instantaneous. This is achieved by Kafka Raft Metadata mode termed as 'KRaft' that will run Kafka without ZooKeeper by merging all the responsibilities handled by ZooKeeper inside a service in the Kafka Cluster itself and operates on event based mechanism that is used in the KRaft protocol.
Tutorials generally keep things nice and simple, so one ZooKeeper (often one Kafka broker too). Useful for getting started; useless for any kind of resilience :)
In practice, you are going to need three ZooKeeper nodes minimum.
If it helps, here is an enterprise reference architecture whitepaper for the deployment of Apache Kafka
Disclaimer: I work for Confluent, who publish the above whitepaper.
we are testing out kafka connect and in our testing noticed that when one of our kafka nodes goes down or is unavailable, kafka connect goes down (hangs).
In our rest and distributed properties, our broker configuration looks like: dp-kafka-01:9092, dp-kafka-02:9092, dp-kafka-03:9092.
We are looking at possibly using a load balancer to maintain uptime but I would be interested in seeing 1) if others have had this problem 2) their solution to it.
Many Thanks.
Putting a load balancer in front of the Connect REST API will not stop them from crashing upon broker failure.
You need to administer Kafka better to prevent the whole system from going down.
I have a critical Kafka application that needs to be up and running all the time. The source topics are created by debezium kafka connect for mysql binlog. Unfortunately, many things can go wrong with this setup. A lot of times debezium connectors fail and need to be restarted, so does my apps then (because without throwing any exception it just hangs up and stops consuming). My manual way of testing and discovering the failure is checking kibana log, then consume the suspicious topic through terminal. I can mimic this in code but obviously no way the best practice. I wonder if there is the ability in KafkaStream api that allows me to do such health check, and check other parts of kafka cluster?
Another point that bothers me is if I can keep the stream alive and rejoin the topics when connectors are up again.
You can check the Kafka Streams State to see if it is rebalancing/running, which would indicate healthy operations. Although, if no data is getting into the Topology, I would assume there would be no errors happening, so you need to then lookup the health of your upstream dependencies.
Overall, sounds like you might want to invest some time into using monitoring tools like Consul or Sensu which can run local service health checks and send out alerts when services go down. Or at the very least Elasticseach alerting
As far as Kafka health checking goes, you can do that in several ways
Is the broker and zookeeper process running? (SSH to the node, check processes)
Is the broker and zookeeper ports open? (use Socket connection)
Are there important JMX metrics you can track? (Metricbeat)
Can you find an active Controller broker (use AdminClient#describeCluster)
Are there a required minimum number of brokers you would like to respond as part of the Controller metadata (which can be obtained from AdminClient)
Are the topics that you use having the proper configuration? (retention, min-isr, replication-factor, partition count, etc)? (again, use AdminClient)
I'd like to host apps that uses queue to communicate with each other on OpenShift.
One kind of apps - producers will put some data to the queue and another type - consumer will process the message. My question is how to implement message queue. I've thought about two approaches:
Create an app with JBoss, HornetQ and consumer and create proxy port for HornetQ, so that producers can send messages there.
Create an app with JBoss and consumer, and make a JBoss's HornetQ available to producers. It sounds a bit better for me, but I don't know if I can make queue available to producers and how it works if there are more instances of consumer on different nodes (and different JBoss instances).
I'm not sure how else to answer you besides showing you a link on how to use Wildfly. You can just use the Wildfly Cartridge:
https://www.openshift.com/quickstarts/wildfly-8
If you provide me some extra context I can try to enrich the answer a bit better. I need to know what is your problem, and what's not working.
If you just want to know how to configure Wildfly with HornetQ, the Wildfly cartridge I posted is the way to go.