I want to setup an ActiveMQ cluster. As I encountered problems with shared nothing approach, I'd like to do it using shared filesystem. However, the ActiveMQ documentation warns about possible problems related to filesystem locks. As I'm not sure, I'd like to ask, if GlusterFS would be a good choice for shared filesystem.
Shared-storage master-slave requires that the underlying file system supports network file locks. GlusterFS seems to support network locks going by the documentation (it's not 100% clear). Ultimately the best way to find out is to set it up and check.
If it doesn't you still have the option of falling back to a shared JDBC-based store.
Related
I have an instance of ActiveMQ 5.16.4 running that is using MySQL as a persistent data storage. Recently the MySQL server had some issues, and ActiveMQ lost its connection to MySQL. That caused multiple Spring microservices to throw errors because ActiveMQ wasn't working.
Is it possible to have master/slave ActiveMQ running where master and slave uses separate persistence storage?
I have done some research and found "pure master slave", but it says that it is deprecated and not recommend to use and will be removed in 5.8. It says to use shared storage which I am trying to avoid (cause my problem is what if storage itself is down).
What are my options to keep running ActiveMQ if it loses connection to database?
If you're using ActiveMQ "Classic" (i.e. 5.x) then your only option is to use shared storage between the master and the slave. This could be a shared file system or a relational database. This, of course, is a single point of failure.
However, there are both file system and database technologies that can mitigate this risk. For example you could use a replicated file system (e.g. Ceph or GlusterFS) or a replicated database (e.g. MySQL).
You might also consider using ActiveMQ Artemis (i.e. the next-generation broker from ActiveMQ) which supports replication natively.
In certain container boxes chronicle queue is not working.I am seeing this exception: 2018-11-17 16:30:57.825 [failsafe-sender] WARN n.o.c.q.i.s.SingleChronicleQueueExcerpts$StoreTailer - Unable to append EOF, skipping
java.util.concurrent.TimeoutException: header: 80000000, pos: 104666
at net.openhft.chronicle.wire.AbstractWire.writeEndOfWire(AbstractWire.java:459)
at net.openhft.chronicle.queue.impl.single.SingleChronicleQueueStore.writeEOF(SingleChronicleQueueStore.java:349)
at
I want to understand why only in certain VM's.
Note: We are using NFS file system
Tried to understand the behavior in NFS
Chronicle Queue does not support operating off any network file system, be it NFS, AFS, SAN-based storage or anything else. The reason for this is those file systems do not provide all the required primitives for memory-mapped files Chronicle Queue uses.
Or putting it another way, Chronicle Queue uses off-heap memory mapped files and these files utilize memory mapped CAS based locks, usually these CAS operations are not atomic between processes when using network attached storage and certainly not atomic between processes that are hosted on different machines. If your test sometimes works on different combinations of file-system and/or OS's, then it is possible your test did not experience a concurrency race, or that that on some combination of NAS and OS, it is possible the hardware and OS has honoured these CAS operations, however, we feel this is very unlikely. As a solution to this, we have created a product called chronicle-queue-enterprise, it is a commercial product that will let you share a queue between machines using TCP/IP. Please contact sales#chronicle.software for more information on chronicle-queue-enterprise.
For reliable distribution of data between machines you need to use Chronicle Queue Enterprise. NFS doesn't support atomic memory operations between machines.
We are planning to use the iscsi target to handle the Activemq master/slave setup. In this case we will mount a SAN storage volume on two virtual machines using the iscsi protocol and those two VMs would share the same mount (from SAN). So the question is, will the file locking works properly with this approach? And can we anticipate any issues in this design?
Mounting as NFS may need a fileserver between SAN and the VMs so we are not considering this as an option and planning to use iscsi. Any help would be greatly appreciated.
You must use a clustered, "shared disk" filesystem on the iSCSI LUNs. Conventional filesystems (ext3, xfs, ntfs, etc.) do not expect (or handle) the data changing out from underneath them. They just won't work.
I don't have any particular one to recommend, but the most accessible of these shared-disk filesystems is probably GFS2? The wikipedia page for clustered filesystems has several examples listed under the Shared-disk file system heading.
https://en.wikipedia.org/wiki/Clustered_file_system
I am new in
Apache ZooKeeper : ZooKeeper is a centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services.
Apache Mesos : Apache Mesos is a cluster manager that simplifies the complexity of running applications on a shared pool of servers.
Apache Helix : Apache Helix is a generic cluster management framework used for the automatic management of partitioned, replicated and distributed resources hosted on a cluster of nodes.
Erlang Langauge : Erlang is a programming language used to build massively scalable soft real-time systems with requirements on high availability.
It sounds to me that Helix and Mesos both are useful for Clustering management System. How they are related to ZooKeeper? It'd better if someone give me a real world example for their usage.
I am curious to know How [BOINC][1] are distributing tasks to their clients? Are they using any of the above technologies? (Forget about Erlang).
I just need a brief view on it :)
Erlang was built by Ericsson, designed for use in phone systems. By design, it runs hundreds, thousands, or even 10s of thousands of small processes to handle tasks by sending information between them instead of sharing memory or state. This enables all sorts of interesting features that are great for high availability distributed systems such as:
hot code reloading. Each process is paused, it's relevant module code is swapped out, and it is resumed where it left off, so deploys can happen without restarting or causing significant interruption.
Easy distributed messaging and clustering. Sending a message to a local process or a remote one is fairly seamless in most instances.
Process-local GC. Garbage collection happens in each process independently instead of a global stop-the-world even like java, aiding in low-latency results.
Supervision trees and complex process hierarchy and monitoring/managing.
A few concrete real-world examples that makes great use of Erlang would be:
MongooseIM A highly performant and incredibly scalable, distributed XMPP / Chat server
Riak A distributed key/value store.
Mesos, on the other hand, you can sort of think of as a platform effectively for turning a datacenter of servers into a platform for teams and developers. If I, say as a company, own a datacenter with 10,000 physical servers, and I have 1,000 engineers developing hundreds of services, a good way to allow the engineers to deploy and manage services across that hardware without them needing to worry about the servers directly. It's an abstraction layer over-top of the physical servers to that allows you to share and intelligently allocate resources.
As a user of Mesos, I might say that I have Service X. It's an executable bundle that lives in location Y. Each instance of Service X needs 4 GB of RAM and 2 cores. And I need 8 instances which will be attached to a load balancer. You can specify this in configuration and deploy based on that config. Mesos will find hardware that has enough ram and CPU capacity available to handle each instance of that service and start it running in each of those locations.
It can handle a lot of other more complex topics about the orchestration of them as well, but that's probably a bit in-depth for this :)
Zookeepers most common use cases are Service Discover and configuration management. You can think of it, fundamentally, a bit like a nested key value store, where services can look at pre-defined paths to see where other services currently live.
A simple example is that I have a web service using a shared database cluster. I know a simple name for that database cluster and where the configuration for it lives in zookeeper. I can look up (or repeatedly poll) that path in zookeeper to check what the addresses of the active database hosts are. And on the other side, if I take a database node out of rotation and replace it with a new one, the config in zookeeper gets updated with the new address, and anything continually looking at it will detect this change and change where it's connected to.
A more complex use case for zookeeper is how Kafka uses it (or did at the time that I last used Kafka). Kafka has streams, and streams have many shards. Each consumer of each stream use zookeeper to save checkpoints in each shard after they have read and processed up to a certain point in the stream. That way if the consumer crashes or is restarted, it knows where to pick up in the stream.
I dont know about Meos and Earlang language. But this article might help you with Helix and Zookeeper.
This article tells us:
Zookeeper is responsible for gluing all parts together where Helix is cluster management component that registers all cluster details (cluster itself, nodes, resources).
The article is related to clustering in JBPM using helix and zookeeper.But with this you will get a basic idea on what helix and zookeeper is used for.
And from most of the articles i read online it seems like zookeeper and helix are used together.
Apache Zookeeper can be installed on a single machine or on a cluster.
It can be used to keep track of logs. It can provide various services on a distributed platform.
Storm and Kafka rely on Zookeeper.
Storm uses Zookeeper to store all state so that it can recover from an outage in any of its (distributed) component services.
Kafka queue consumers can use Zookeeper to store information on what has been consumed from the queue.
My group is looking to distribute our ActiveMQ queues across multiple brokers to achieve high availability. Of the three supported master-slave setups (pure, shared filesystem, JDBC) we are considering shared file system and JDBC.
I am seeing conflicting statements within the ActiveMQ documentation. Can, or can not, JDBC master-slave setup use ActiveMQ's high-performance journal?
On this page, ActiveMQ claims that
it cannot use the high performance journal.
On this page, ActiveMQ suggests that the two can, in fact, be used together:
For long term persistence we recommend using JDBC coupled with our high performance journal.
Can anyone shed light on this apparent conflict?
you should not use journaling with JDBC master/slave because the journal is not replicated. Any messages in the journal of the master that have not yet been batch submitted to the jdbc store will be isolated till restart. ie: the journal is not visible to the slave.