activemq-artemis/docs/user-manual/en/perf-tuning.md

# Performance Tuning

In this chapter we'll discuss how to tune Apache ActiveMQ Artemis for optimum
performance.

## Tuning persistence

- To get the best performance from Apache ActiveMQ Artemis whilst using
  persistent messages it is recommended that the file store is used.  Apache
  ActiveMQ Artemis also supports JDBC persistence, but there is a performance
  cost when persisting to a database vs local disk.

- Put the message journal on its own physical volume. If the disk is shared
  with other processes e.g. transaction co-ordinator, database or other
  journals which are also reading and writing from it, then this may greatly
  reduce performance since the disk head may be skipping all over the place
  between the different files. One of the advantages of an append only journal is
  that disk head movement is minimised - this advantage is destroyed if the disk
  is shared. If you're using paging or large messages make sure they're ideally
  put on separate volumes too.

- Minimum number of journal files. Set `journal-min-files` to a number of files
  that would fit your average sustainable rate.  This number represents the
  lower threshold of the journal file pool.

- To set the upper threshold of the journal file pool. (`journal-min-files` being
  the lower threshold).  Set `journal-pool-files` to a number that represents
  something near your maximum expected load.  The journal will spill over the
  pool should it need to, but will shrink back to the upper threshold, when
  possible.  This allows reuse of files, without taking up more disk space than
  required.  If you see new files being created on the journal data directory too
  often, i.e. lots of data is being persisted, you need to increase the
  journal-pool-size, this way the journal would reuse more files instead of
  creating new data files, increasing performance

- Journal file size. The journal file size should be aligned to the capacity of
  a cylinder on the disk. The default value 10MiB should be enough on most
  systems.

- Use `ASYNCIO` journal. If using Linux, try to keep your journal type as
  `ASYNCIO`. `ASYNCIO` will scale better than Java NIO.

- Tune `journal-buffer-timeout`. The timeout can be increased to increase
  throughput at the expense of latency.

- If you're running `ASYNCIO` you might be able to get some better performance by
  increasing `journal-max-io`. DO NOT change this parameter if you are running
  NIO.
  
- If you are 100% sure you don't need power failure durability guarantees,
  disable `journal-data-sync` and use `NIO` or `MAPPED` journal: you'll benefit
  a huge performance boost on writes with process failure durability guarantees.  

## Tuning JMS

There are a few areas where some tweaks can be done if you are using the JMS
API

- Disable message id. Use the `setDisableMessageID()` method on the
  `MessageProducer` class to disable message ids if you don't need them. This
  decreases the size of the message and also avoids the overhead of creating a
  unique ID.

- Disable message timestamp. Use the `setDisableMessageTimeStamp()` method on
  the `MessageProducer` class to disable message timestamps if you don't need
  them.

- Avoid `ObjectMessage`. `ObjectMessage` is convenient but it comes at a cost.
  The body of a `ObjectMessage` uses Java serialization to serialize it to
  bytes. The Java serialized form of even small objects is very verbose so takes
  up a lot of space on the wire, also Java serialization is slow compared to
  custom marshalling techniques. Only use `ObjectMessage` if you really can't use
  one of the other message types, i.e. if you really don't know the type of the
  payload until run-time.

- Avoid `AUTO_ACKNOWLEDGE`. `AUTO_ACKNOWLEDGE` mode requires an acknowledgement
  to be sent from the server for each message received on the client, this
  means more traffic on the network. If you can, use `DUPS_OK_ACKNOWLEDGE` or use
  `CLIENT_ACKNOWLEDGE` or a transacted session and batch up many acknowledgements
  with one acknowledge/commit.

- Avoid durable messages. By default JMS messages are durable. If you don't
  really need durable messages then set them to be non-durable.  Durable
  messages incur a lot more overhead in persisting them to storage.

- Batch many sends or acknowledgements in a single transaction.  Apache
  ActiveMQ Artemis will only require a network round trip on the commit, not on
  every send or acknowledgement.

## Other Tunings

There are various other places in Apache ActiveMQ Artemis where we can perform
some tuning:

- Use Asynchronous Send Acknowledgements. If you need to send durable messages
  non transactionally and you need a guarantee that they have reached the
  server by the time the call to send() returns, don't set durable messages to be
  sent blocking, instead use asynchronous send acknowledgements to get your
  acknowledgements of send back in a separate stream, see [Guarantees of sends
  and commits](send-guarantees.md) for more information on this.

- Use pre-acknowledge mode. With pre-acknowledge mode, messages are
  acknowledged `before` they are sent to the client. This reduces the amount of
  acknowledgement traffic on the wire. For more information on this, see [Extra
  Acknowledge Modes](pre-acknowledge.md).

- Disable security. You may get a small performance boost by disabling security
  by setting the `security-enabled` parameter to `false` in `broker.xml`.

- Disable persistence. If you don't need message persistence, turn it off
  altogether by setting `persistence-enabled` to false in `broker.xml`.

- Sync transactions lazily. Setting `journal-sync-transactional` to `false` in
  `broker.xml` can give you better transactional persistent performance at the
  expense of some possibility of loss of transactions on failure. See
  [Guarantees of sends and commits](send-guarantees.md) for more information.

- Sync non transactional lazily. Setting `journal-sync-non-transactional` to
  `false` in `broker.xml` can give you better non-transactional persistent
  performance at the expense of some possibility of loss of durable messages on
  failure. See  [Guarantees of sends and commits](send-guarantees.md) for more
  information.

- Send messages non blocking. Setting `block-on-durable-send` and
  `block-on-non-durable-send` to `false` in the jms config (if you're using JMS
  and JNDI) or directly on the ServerLocator. This means you don't have to wait a
  whole network round trip for every message sent. See  [Guarantees of sends and
  commits](send-guarantees.md) for more information.

- If you have very fast consumers, you can increase consumer-window-size. This
  effectively disables consumer flow control.

- Use the core API not JMS. Using the JMS API you will have slightly lower
  performance than using the core API, since all JMS operations need to be
  translated into core operations before the server can handle them. If using the
  core API try to use methods that take `SimpleString` as much as possible.
  `SimpleString`, unlike java.lang.String does not require copying before it is
  written to the wire, so if you re-use `SimpleString` instances between calls
  then you can avoid some unnecessary copying.
  
- If using frameworks like Spring, configure destinations permanently broker
  side and enable `cacheDestinations` on the client side.  See the [Setting The
  Destination Cache](using-jms.md) for more information on this.

## Tuning Transport Settings

- TCP buffer sizes. If you have a fast network and fast machines you may get a
  performance boost by increasing the TCP send and receive buffer sizes. See
  the [Configuring the Transport](configuring-transports.md) for more information
  on this.

  > **Note:**
  >
  > Note that some operating systems like later versions of Linux include TCP
  > auto-tuning and setting TCP buffer sizes manually can prevent auto-tune
  > from working and actually give you worse performance!

- Increase limit on file handles on the server. If you expect a lot of
  concurrent connections on your servers, or if clients are rapidly opening and
  closing connections, you should make sure the user running the server has
  permission to create sufficient file handles.

  This varies from operating system to operating system. On Linux systems you
  can increase the number of allowable open file handles in the file
  `/etc/security/limits.conf` e.g. add the lines

  ```
  serveruser   soft  nofile  20000
  serveruser   hard  nofile  20000
  ```

  This would allow up to 20000 file handles to be open by the user
  `serveruser`.

- Use `batch-delay` and set `direct-deliver` to false for the best throughput
  for very small messages. Apache ActiveMQ Artemis comes with a preconfigured
  connector/acceptor pair (`netty-throughput`) in `broker.xml` and JMS connection
  factory (`ThroughputConnectionFactory`) in `activemq-jms.xml`which can be used
  to give the very best throughput, especially for small messages. See the
  [Configuring the Transport](configuring-transports.md) for more information on
  this.

## Tuning the VM

We highly recommend you use the latest Java JVM for the best performance. We
test internally using the Sun JVM, so some of these tunings won't apply to JDKs
from other providers (e.g. IBM or JRockit)

- Garbage collection. For smooth server operation we recommend using a parallel
  garbage collection algorithm, e.g. using the JVM argument
  `-XX:+UseParallelOldGC` on Sun JDKs.

- Memory settings. Give as much memory as you can to the server.  Apache
  ActiveMQ Artemis can run in low memory by using paging (described in
  [Paging](paging.md)) but if it can run with all queues in RAM this will improve
  performance.  The amount of memory you require will depend on the size and
  number of your queues and the size and number of your messages. Use the JVM
  arguments `-Xms` and `-Xmx` to set server available RAM. We recommend setting
  them to the same high value.
  
  When under periods of high load, it is likely that Artemis will be generating
  and destroying lots of objects. This can result in a build up of stale objects.
  To reduce the chance of running out of memory and causing a full GC (which may
  introduce pauses and unintentional behaviour), it is recommended that the max
  heap size (`-Xmx`) for the JVM is set at least to 5 x the `global-max-size` of
  the broker.  As an example, in a situation where the broker is under high load
  and running with a `global-max-size` of 1GB, it is recommended the max heap
  size is set to 5GB.

## Avoiding Anti-Patterns

- Re-use connections / sessions / consumers / producers. Probably the most
  common messaging anti-pattern we see is users who create a new
  connection/session/producer for every message they send or every message they
  consume. This is a poor use of resources. These objects take time to create and
  may involve several network round trips.  Always re-use them.

  > **Note:**
  >
  > Spring's `JmsTemplate` is known to use this anti-pattern. It can only
  > safely be used with a connection pool (e.g. in a Java EE application server
  > using JCA), and even then it should only be used for sending messages. It
  > cannot be safely be used for synchronously consuming messages, even with
  > a connection pool. If you need a connection pool take a look at 
  > [this](https://github.com/messaginghub/pooled-jms) which was forked from the
  > ActiveMQ code-base into its own project with full support for JMS 2.

- Avoid fat messages. Verbose formats such as XML take up a lot of space on the
  wire and performance will suffer as result. Avoid XML in message bodies if
  you can.

- Don't create temporary queues for each request. This common anti-pattern
  involves the temporary queue request-response pattern.  With the temporary
  queue request-response pattern a message is sent to a target and a reply-to
  header is set with the address of a local temporary queue. When the recipient
  receives the message they process it then send back a response to the address
  specified in the reply-to. A common mistake made with this pattern is to create
  a new temporary queue on each message sent. This will drastically reduce
  performance. Instead the temporary queue should be re-used for many requests.

- Don't use Message-Driven Beans for the sake of it. As soon as you start using
  MDBs you are greatly increasing the codepath for each message received
  compared to a straightforward message consumer, since a lot of extra
  application server code is executed. Ask yourself do you really need MDBs? Can
  you accomplish the same task using just a normal message consumer?

## Troubleshooting

### UDP not working

In certain situations UDP used on discovery may not work. Typical situations are:

1. The nodes are behind a firewall. If your nodes are on different machines
   then it is possible that the firewall is blocking the multicasts. you can
   test this by disabling the firewall for each node or adding the appropriate
   rules.
2. You are using a home network or are behind a gateway. Typically home
   networks will redirect any UDP traffic to the Internet Service Provider
   which is then either dropped by the ISP or just lost. To fix this you will need
   to add a route to the firewall/gateway that will redirect any multicast traffic
   back on to the local network instead.
3. All the nodes are in one machine. If this is the case then it is a similar
   problem to point 2 and the same solution should fix it. Alternatively you
   could add a multicast route to the loopback interface. On linux the command
   would be:

   ```sh
   # you should run this as root
   route add -net 224.0.0.0 netmask 240.0.0.0 dev lo
   ```
   
   This will redirect any traffic directed to the 224.0.0.0 to the loopback
   interface. This will also work if you have no network at all. On Mac OS X, the
   command is slightly different:

   ```sh
   sudo route add 224.0.0.0 127.0.0.1 -netmask 240.0.0.0
   ```