RabbitMQ has a throughput testing tool, PerfTest, that is based on the Java client and can be configured to simulate basic workloads and more advanced workloads as well. PerfTest has extra tools that produce HTML graphs of the output.
A RabbitMQ cluster can be limited by a number of factors, from infrastructure-level constraints (e.g. network bandwidth) to RabbitMQ configuration and topology to applications that publish and consume. PerfTest can demonstrate baseline performance of a node or a cluster of nodes.
PerfTest uses the AMQP 0.9.1 protocol to communicate with a RabbitMQ cluster. Use Stream PerfTest if you want to test RabbitMQ Streams with the stream protocol.
PerfTest is distributed as an uber JAR from GitHub releases.
It is also available on Maven Central if one needs to use it as library.
Milestone releases or release candidates are available from GitHub releases.
Snapshots are also available. The latest snapshot is available at a stable URL (useful for automation).
To verify a PerfTest installation, use:
java -jar perf-test.jar --help
From Docker Image
PerfTest has a Docker image as well. To use it:
docker run -it --rm pivotalrabbitmq/perf-test:latest --help
Note that the Docker container needs to be able to connect to the host where the RabbitMQ broker runs. Find out more at Docker network documentation. Once the Docker container where PerfTest runs can connect to the RabbitMQ broker, PerfTest can be run with the regular options, e.g.:
docker run -it --rm pivotalrabbitmq/perf-test:latest -x 1 -y 2 -u "throughput-test-1" -a --id "test 1"
To run the RabbitMQ broker within Docker, and run PerfTest against it, run the following commands:
docker network create perf-test docker run -it --rm --network perf-test --name rabbitmq -p 15672:15672 rabbitmq:3.10-management docker run -it --rm --network perf-test pivotalrabbitmq/perf-test:latest --uri amqp://rabbitmq
For Cloud Foundry
There is a template project to easily run PerfTest on Cloud Foundry.
The most basic way of running PerfTest only specifies a URI to connect to, a number of publishers to use (say, 1) and a number of consumers to use (say, 2). Note that RabbitMQ Java client can achieve high rates for publishing (up to 80 to 90K messages per second per connection), given enough bandwidth and when some safety measures (publisher confirms) are disabled, so overprovisioning publishers is rarely necessary (unless that’s a specific objective of the test).
The following command runs PerfTest with a single publisher without publisher confirms, two consumers (each receiving a copy of every message) that use automatic acknowledgement mode and a single queue named “throughput-test-x1-y2”. Publishers will publish as quickly as possible, without any rate limiting. Results will be prefixed with “test1” for easier identification and comparison:
java -jar perf-test.jar -x 1 -y 2 -u "throughput-test-1" -a --id "test 1"
This modification will use 2 publishers and 4 consumers, typically yielding higher throughput given enough CPU cores on the machine and RabbitMQ nodes:
java -jar perf-test.jar -x 2 -y 4 -u "throughput-test-2" -a --id "test 2"
This modification switches consumers to manual acknowledgements:
java -jar perf-test.jar -x 1 -y 2 -u "throughput-test-3" --id "test 3"
This modification changes message size from default (12 bytes) to 4 kB:
java -jar perf-test.jar -x 1 -y 2 -u "throughput-test-4" --id "test 4" -s 4000
PerfTest can use durable queues and persistent messages:
java -jar perf-test.jar -x 1 -y 2 -u "throughput-test-5" --id "test-5" -f persistent
When PerfTest is running, it is important to monitor various publisher and consumer metrics provided by the management UI. For example, it is possible to see how much network bandwidth a publisher has been using recently on the connection page.
Queue page demonstrates message rates, consumer count, acknowledgement mode used by the consumers, consumer utilisation and message location break down (disk, RAM, paged out transient messages, etc). When durable queues and persistent messages are used, node I/O and message store/queue index operation metrics become particularly important to monitor.
Consumers can ack multiple messages at once, for example, 100 in this configuration:
java -jar perf-test.jar -x 1 -y 2 -u "throughput-test-6" --id "test-6" \ -f persistent --multi-ack-every 100
Consumer prefetch (QoS) can be configured as well (in this example to 500):
java -jar perf-test.jar -x 1 -y 2 -u "throughput-test-7" --id "test-7" \ -f persistent --multi-ack-every 200 -q 500
Publisher confirms can be used with a maximum of N outstanding publishes:
java -jar perf-test.jar -x 1 -y 2 -u "throughput-test-8" --id "test-8" \ -f persistent -q 500 -c 500
PerfTest can publish only a certain number of messages instead of running until shut down:
java -jar perf-test.jar -x 1 -y 2 -u "throughput-test-10" --id "test-10" \ -f persistent -q 500 -pmessages 100000
Publisher rate can be limited:
java -jar perf-test.jar -x 1 -y 2 -u "throughput-test-11" --id "test-11" \ -f persistent -q 500 --rate 5000
Consumer rate can be limited as well to simulate slower consumers or create a backlog:
java -jar perf-test.jar -x 1 -y 2 -u "throughput-test-12" --id "test-12" \ -f persistent --rate 5000 --consumer-rate 2000
Note that the consumer rate limit is applied per consumer, so in the configuration above the limit is actually 2 * 2000 = 4000 deliveries/second.
PerfTest automatically converts low publishing rates (between 1 and 10 messages / second) to publishing intervals. This makes the simulation more accurate when simulating many slow publishers.
PerfTest can be configured to run for a limited amount of time in seconds with the
java -jar perf-test.jar -x 1 -y 2 -u "throughput-test-13" --id "test-13" \ -f persistent -z 30
Running PerfTest without consumers and with a limited number of messages can be used to pre-populate a queue, e.g. with 1M messages 1 kB in size each::
java -jar perf-test.jar -y0 -p -u "throughput-test-14" \ -s 1000 -C 1000000 --id "test-14" -f persistent
-D option to limit the number of consumed messages. Note
-z (time limit),
-C (number of
published messages), and
-D (number of consumed messages)
options can be used together but their combination can lead to funny results.
-r 1 -x 1 -C 10 -y 1 -D 20 would for example stop the producer
once 10 messages have been published, letting the consumer wait forever
the remaining 10 messages (as the publisher is stopped).
To consume from a pre-declared and pre-populated queue without starting any publishers, use
java -jar perf-test.jar -x0 -y10 -p -u "throughput-test-14" --id "test-15"
PerfTest is useful for establishing baseline cluster throughput with various configurations but does not simulate many other aspects of real world applications. It is also biased towards very simplistic workloads that use a single queue, which provides limited CPU utilisation on RabbitMQ nodes and is not recommended for most cases.
Multiple PerfTest instances running simultaneously can be used to simulate more realistic workloads.
How It Works
If a queue name is defined (
PerfTest will create a queue with this name and all
consumers will consume from this queue. The queue will be
bound to the direct exchange with its name as the routing
key. The routing key will be used by producers to send
messages. This will cause messages from all producers to be
sent to this single queue and all consumers to receive
messages from this single queue.
If the queue name is not defined, PerfTest will create a random UUID routing key with which producers will publish messages. Each consumer will create its own anonymous queue and bind it to the direct exchange with this routing key. This will cause each message from all producers to be replicated to multiple queues (number of queues equals number of consumers), while each consumer will be receiving messages from only one queue.
Note it is possible to customise the queue and to work against several queues as well.
There are 2 reasons for a PerfTest run to stop:
one of the limits has been reached (time limit, producer or consumer message count)
the process is stopped by the user, e.g. by using Ctrl-C in the terminal
In both cases, PerfTest tries to exit as cleanly as possible, in a reasonable amount of time. Nevertheless, when PerfTest AMQP connections are throttled by the broker, because they’re publishing too fast or because broker alarms have kicked in, it can take time to close them (several seconds or more for one connection).
If closing connections in the gentle way takes too long (5 seconds by default), PerfTest
will move on to the most important resources to free and terminates. This can result
client unexpectedly closed TCP connection messages in the broker logs. Note this
means the AMQP connection hasn’t been closed with the right sequence of AMQP frames,
but the socket has been closed properly. There’s no resource leakage here.
The connection closing timeout can be set up with the
--shutdown-timeout argument (or
The default timeout can be increased to let more time to close connections, e.g. the
command below uses a shutdown timeout of 20 seconds:
java -jar perf-test.jar --shutdown-timeout 20
The connection closing sequence can also be skipped by setting the timeout to 0 or any negative value:
java -jar perf-test.jar --shutdown-timeout -1
With the previous command, PerfTest won’t even try to close AMQP connections, it will exit as fast as possible, freeing only the most important resources. This is perfectly acceptable when performing runs on a test environment.
PerfTest can create queues using provided queue arguments:
java -jar perf-test.jar --queue-args x-max-length=10
The previous command will create a queue with a length limit of 10. You can also provide several queue arguments by separating the key/value pairs with commas:
java -jar perf-test.jar \ --queue-args x-max-length=10,x-dead-letter-exchange=some.exchange.name
It is possible to use several arguments to
create quorum queues, but PerfTest provides
--quorum-queue flag to do that:
java -jar perf-test.jar \ --quorum-queue --queue name
--quorum-queue is a shortcut for
--flag persistent --queue-args x-queue-type=quorum --auto-delete false. Note a quorum queue cannot have a server-generated name, so the
--queue argument must be used to specify the name of the queue(s).
It is possible to customise messages that PerfTest publishes. This allows getting as close as possible to the target traffic or to populate queues with messages that real consumers will process.
You can specify message properties with key/value pairs separated by commas:
java -jar perf-test.jar \ --message-properties priority=5,timestamp=2007-12-03T10:15:30+01:00
The supported property keys are:
clusterId. If some provided
keys do not belong to the previous list, the pairs will be considered
as headers (arbitrary key/value pairs):
java -jar perf-test.jar \ --message-properties priority=10,header1=value1,header2=value2
Message Payload from Files
You can mimic real messages by specifying their content and content type. This can be useful when plugging real application consumers downstream. The content can come from one or several files and the content-type can be specified:
java -jar perf-test.jar --consumers 0 \ --body content1.json,content2.json --body-content-type application/json
Random JSON Payload
PerfTest can generate random JSON payload for messages. This is useful to
experiment with traffic that (almost) always changes. To generate random JSON
payloads, use the
--json-body flag and the
--size argument to specify
the size in bytes:
java -jar perf-test.jar --json-body --size 16000
Generate random values is costly, so PerfTest generates a pool of payloads upfront and uses them randomly in published messages. This way the generation of payloads does not impede publishing rate. There are 2 options to change the pre-generation of random JSON payload:
--body-count: the size of the pool of payloads PerfTest will generate and use in published messages. The default size is 100. Increase this value if you want more randomness in published messages.
--body-field-count: the size of the pool of random strings used for field names and values in the JSON document. Before generating JSON payloads, PerfTest generates random strings and will use them randomly for field names and values in the JSON documents. The default value is 1,000. Increasing this value can be useful for "large" payloads (a few hundreds of kilobytes or more), which can "exhaust" the pool of random strings and then end up with duplicated field names. Duplicated field names are fine if the random JSON payloads are used to simulate traffic, but can be problematic if real consumers are plugged in and try to parse the JSON documents (JSON parsers do not always tolerate duplicated fields).
The defaults for
--body-field-count are usually fine, but can be increased
for more randomness, at the cost of slower startup time and higher memory consumption.
Bear in mind that a large cache of generated payloads combined with a moderately large size
can easily take up a significant amount of memory. As an example,
--json-body --body-count 50000 --size 100000
(50,000 payloads of 100 kB) will use about 5 GB of memory.
Limiting and varying publishing rate
By default, PerfTest publishes as fast as possible.
The publishing rate per producer can be limited with the
--rate option (
-r). E.g. to
publishing at most 100 messages per second for the whole run:
java -jar perf-test.jar --rate 100
-vr) option can be used several times to specify a publishing rate
for a duration, e.g.:
java -jar perf-test.jar \ --variable-rate 100:60 --variable-rate 1000:10 --variable-rate 500:15
The variable rate option uses the
[RATE]:[DURATION] syntax, where
RATE is in messages per second
DURATION is in seconds. In the previous example, the publishing rate
will be 100 messages per second for 60 seconds, then 1000 messages per second
for 10 seconds, then 500 messages per second for 15 seconds, then back to 100 messages per second
for 60 seconds, and so on.
--variable-rate option is useful to simulate steady rates and burst of messages for short periods.
Setting and varying the message size
The default size of the messages that PerfTest publishes is 12 bytes (PerfTest stores some data in the message to calculate latency on the consumer side).
It is possible to make messages bigger with the
-s) option, e.g. to publish
4 kB messages:
java -jar perf-test.jar --size 4000
-vs) option allows to specify different message sizes
for periods of time, e.g.:
java -jar perf-test.jar \ --variable-size 1000:30 --variable-size 10000:20 --variable-size 5000:45
The variable rate option uses the
[SIZE]:[DURATION] syntax, where
SIZE is in bytes
DURATION is in seconds. In the previous example, the size of published messages
will be 1 kB for 30 seconds, then 10 kB for 20 seconds, then 5 kB for 45 seconds,
then back to 1 kB for 30 seconds, and so on.
Setting and varying consumer latency
You can simulate processing time per message with either a fixed or a variable latency value in microseconds.
-L) option sets a fixed consumer latency in microseconds. In the example
below a 1 ms latency is set:
java -jar perf-test.jar --consumer-latency 1000
-vl) option sets a variable consumer latency. In the example below it is
set to 1 ms for 60 seconds then 1 second for 30 seconds:
java -jar perf-test.jar --variable-latency 1000:60 --variable-latency 1000000:30
Working With Many Queues
PertTest supports balancing the publishing and the consumption across a sequence of queues, e.g.:
java -jar perf-test.jar --queue-pattern 'perf-test-%d' \ --queue-pattern-from 1 --queue-pattern-to 10 \ --producers 100 --consumers 100
The previous command would create the
perf-test-10 queues and spreads the producers and consumers across them.
This way each queue will have 10 consumers and 10 producers sending messages to it.
Load is balanced in a round-robin fashion:
java -jar perf-test.jar --queue-pattern 'perf-test-%d' \ --queue-pattern-from 1 --queue-pattern-to 10 \ --producers 15 --consumers 30
With the previous command, queues from
will have 2 producers, and queues from
will have only 1 producer. Each queue will have 3 consumers.
--queue-pattern value is a
Java printf-style format string.
The queue index is the only argument passed in. The formatting is very close to C’s
--queue-pattern 'perf-test-%03d' --queue-pattern-from 1 --queue-pattern-to 500 would for
instance create queues from
Simulating High Loads
PerfTest can easily run hundreds of connections on a simple desktop machine. Each producer and consumer use a Java thread and a TCP connection though, so a PerfTest process can quickly run out of file descriptors, depending on the OS settings. A simple solution is to use several PerfTest processes, on the same machine or not. This is especially handy when combined with the queue sequence feature.
The following command line launches a first PerfTest process that
creates 500 queues (from
Each queue will have 3 consumers and 1 producer sending messages to it:
java -jar perf-test.jar --queue-pattern 'perf-test-%d' \ --queue-pattern-from 1 --queue-pattern-to 500 \ --producers 500 --consumers 1500
Then the following command line launches a second PerfTest process
that creates 500 queues (from
Each queue will have 3 consumers and 1 producer sending messages to it:
java -jar perf-test.jar --queue-pattern 'perf-test-%d' \ --queue-pattern-from 501 --queue-pattern-to 1000 \ --producers 500 --consumers 1500
Those 2 processes will simulate 1000 producers and 3000 consumers spread across 1000 queues.
A PerfTest process can exhaust its file descriptors limit and throw
java.lang.OutOfMemoryError: unable to create new native thread
exceptions. A first way to avoid this is to reduce the number of Java threads
PerfTest uses with the
--heartbeat-sender-threadsto reduce the number of threads
java -jar perf-test.jar --queue-pattern 'perf-test-%d' \ --queue-pattern-from 1 --queue-pattern-to 1000 \ --producers 1000 --consumers 3000 --heartbeat-sender-threads 10
By default, each producer and consumer connection uses a dedicated thread
to send heartbeats to the broker, so this is 4000 threads for heartbeats
in the previous sample. Considering producers and consumers always communicate
with the broker by publishing messages or sending acknowledgments, connections
are never idle, so using 10 threads for heartbeats for the 4000 connections
should be enough. Don’t hesitate to experiment to come up with the appropriate
--heartbeat-sender-threads value for your use case.
Another way to avoid
java.lang.OutOfMemoryError: unable to create new native thread
exceptions is to tune the number of file descriptors allowed per process
at the OS level, as some distributions use very low limits.
Here the recommendations are the same as for the broker, so you
can refer to our networking guide.
Workloads With a Large Number of Clients
A typical connected device workload (a.k.a "IoT workload") involves many producers and consumers (dozens or hundreds of thousands) that exchange messages at a low and mostly constant rate, usually a message every few seconds or minutes. Simulating such workloads requires a different set of settings compared to the workloads that have higher throughput and a small number of clients. With the appropriate set of flags, PerfTest can simulate IoT workloads without requiring too many resources, especially threads. Let’s explore these flags.
With an IoT workload, publishers usually don’t publish many messages per second,
but rather a message every fixed period of time. This can be achieved by using the
flag instead of the
--rate one. For example:
--publishing-intervalfor low-throughput workloads
java -jar perf-test.jar --publishing-interval 5
The command above makes the publisher publish a message every 5 seconds.
To simulate a group of consumers, use the
--queue-pattern flag to simulate many consumers across
java -jar perf-test.jar --queue-pattern 'perf-test-%d' \ --queue-pattern-from 1 --queue-pattern-to 1000 \ --producers 1000 --consumers 1000 \ --heartbeat-sender-threads 10 \ --publishing-interval 5
Mind the sampling interval with slow publishers!
To prevent publishers from publishing at roughly the same time and
distribute the rate more evenly, use
--producer-random-start-delay option to add a random
delay before the first published message:
--producer-random-start-delayto spread publishing in a random way
java -jar perf-test.jar --queue-pattern 'perf-test-%d' \ --queue-pattern-from 1 --queue-pattern-to 1000 \ --producers 1000 --consumers 1000 \ --heartbeat-sender-threads 10 \ --publishing-interval 5 --producer-random-start-delay 120
With the command above, each publisher will start with a random delay between 1 and 120 seconds.
--publishing-interval, PerfTest will use one thread for 100 operations per second.
So 1,000 producers publishing at 1 message / second should keep 10 threads busy for
the publishing scheduling.
It is possible to set the number of threads used with the
Set your own value if the default value is not appropriate for some reasons:
--producer-scheduler-threadsto set the number of publishing threads
java -jar perf-test.jar --queue-pattern 'perf-test-%d' \ --queue-pattern-from 1 --queue-pattern-to 1000 \ --producers 1000 --consumers 1000 \ --heartbeat-sender-threads 10 \ --publishing-interval 60 --producer-random-start-delay 1800 \ --producer-scheduler-threads 5
In the example above, 1000 publishers will publish every 60 seconds with a random start-up delay between 1 second and 30 minutes (1800 seconds). They will be scheduled by only 5 threads. Such delay values are suitable for long running tests.
Another option can be useful when simulating many consumers with a moderate message rate:
--consumers-thread-pools. It allows to use a given number of thread pools for all the consumers,
instead of one thread pool for each consumer by default. In the previous example, each consumer
would use a 1-thread thread pool, which is overkill considering consumers processing
is fast and producers publish one message every second. We can set the number of thread pools
to use with
--consumers-thread-pools and they will be shared by the consumers:
--consumers-thread-poolsto reduce the number of consumer threads
java -jar perf-test.jar --queue-pattern 'perf-test-%d' \ --queue-pattern-from 1 --queue-pattern-to 1000 \ --producers 1000 --consumers 1000 \ --heartbeat-sender-threads 10 \ --publishing-interval 60 --producer-random-start-delay 1800 \ --producer-scheduler-threads 10 \ --consumers-thread-pools 10
The previous example uses only 10 thread pools for all consumers instead of 1000 by default. These are 1-thread thread pools in this case, so this is 10 threads overall instead of 1000, another huge resource saving to simulate more clients with a single PerfTest instance for large IoT workloads.
By default, PerfTest uses blocking network socket I/O to communicate with
the broker. This mode works fine for clients in many cases but the RabbitMQ Java client
also supports an asynchronous I/O mode,
where resources like threads can be easily tuned. The goal here is to use as few
resources as possible to simulate as much load as possible with a single PerfTest instance.
In the slow publisher example above, a handful of threads should be enough
to handle the I/O. That’s what the
--nio-threads flag is for:
java -jar perf-test.jar --queue-pattern 'perf-test-%d' \ --queue-pattern-from 1 --queue-pattern-to 1000 \ --producers 1000 --consumers 1000 \ --heartbeat-sender-threads 10 \ --publishing-interval 60 --producer-random-start-delay 1800 \ --producer-scheduler-threads 10 \ --nio-threads 10
This way PerfTest will use 12 threads for I/O over all the connections. With the default blocking I/O mode, each producer (or consumer) uses a thread for the I/O loop, that is 2000 threads to simulate 1000 producers and 1000 consumers. Using NIO in PerfTest can dramatically reduce the resources used to simulate workloads with a large number of connections with appropriate tuning.
Note that in NIO mode the number of threads used can increase temporarily when connections close
unexpectedly and connection recovery kicks in. This is due to the NIO mode dispatching
connection closing to non-I/O threads to avoid deadlocks. Connection recovery can be disabled
Running Producers and Consumers on Different Machines
If you run producers and consumers on different machines or even
in different processes, and you want PerfTest to calculate latency,
you need to use the
--use-millis flag. E.g. for sending messages
from one host:
java -jar perf-test.jar --producers 1 --consumers 0 \ --predeclared --routing-key rk --queue q --use-millis
And for consuming messages from another host:
java -jar perf-test.jar --producers 0 --consumers 1 \ --predeclared --routing-key rk --queue q --use-millis
Note that as soon as you use
--use-millis, latency is calculated in
milliseconds instead of microseconds. Note also the different machines should have
their clock synchronised, e.g. by NTP.
If you don’t run producers and consumers on different machines or if you don’t
want PerfTest to calculate latency, you don’t need the
Why does one need to care about the
--use-millis flag? PerfTest uses
System.nanoTime() in messages to calculate latency
between producers and senders.
System.nanoTime() provides nanosecond precision
but must be used only in the same Java process. So PerfTest can fall back to
which provides only milliseconds precision, but is reliable between different machines
as long as their clocks are synchronised.
Asynchronous Consumers vs Synchronous Consumers
Consumers are asynchronous by default in PerfTest. This means they are registered with the AMQP
method and the broker pushes messages to them. This is the optimal way to consume messages. PerfTest
also provides the
--polling-interval options to consume messages by polling the broker
with the AMQP
basic.get method. These options are available to evaluate the performance and the effects
basic.get, but real applications should avoid using
basic.get as much as possible because
it has several drawbacks compared to asynchronous consumers: it needs a network round trip for each message,
it typically keeps a thread busy for polling in the application, and it intrinsically increases latency.
PerfTest can use TLS to connect to a node that is configured to accept TLS connections.
To enable TLS, simply specify a URI that uses the
java -jar perf-test.jar -h amqps://localhost:5671
By default, PerfTest automatically trusts the server and doesn’t present any client certificate (a warning
shows up in the console).
In many benchmarking or load testing scenarios this may be sufficient.
If peer verification is necessary, it is possible to use the appropriate
JVM properties on the command line to override the default
For example, to trust a given server:
java -Djavax.net.ssl.trustStore=/path/to/server_key.p12 \ -Djavax.net.ssl.trustStorePassword=bunnies \ -Djavax.net.ssl.trustStoreType=PKCS12 \ -jar perf-test.jar -h amqps://localhost:5671
The previous snippet defines appropriate system properties to locate the trust store to use.
Please refer to the TLS guide to learn about how to set up RabbitMQ with TLS.
A convenient way to generate a CA and some self-signed certificate/key pairs for development and QA environments is with
tls-gen basic profile is a good starting point.
Here is how to run PerfTest with a certificate/key pair generated by the aforementioned profile:
java -Djavax.net.ssl.trustStore=/path/to/server_key.p12 \ -Djavax.net.ssl.trustStorePassword=bunnies \ -Djavax.net.ssl.trustStoreType=PKCS12 \ -Djavax.net.ssl.keyStore=/path/to/client_key.p12 \ -Djavax.net.ssl.keyStorePassword=bunnies \ -Djavax.net.ssl.keyStoreType=PKCS12 \ -jar perf-test.jar -h amqps://localhost:5671
Using Environment Variables as Options
Environment variables can sometimes be easier to work with than command line options, for example when using a manifest file to configure PerfTest (with Docker Compose or Cloud Foundry), especially when the number of options used grows.
PerfTest will automatically use environment variables that match the snake case version of the long version of its options
(e.g. PerfTest will automatically pick up the value of the
CONFIRM_TIMEOUT environment variable
--confirm-timeout option, but only if the environment variable is defined).
You can list the environment variables that PerfTest will pick up with the following command:
java -jar perf-test.jar --env
Note that some options can be used several times to define several values, e.g.:
java -jar perf-test.jar \ --variable-rate 100:60 --variable-rate 1000:10 --variable-rate 500:15
Declaring an environment variable several times just overrides the previous value, so to define several values for an environment variable, just separate the values with a comma:
To avoid collisions with environment variables that already exist, it is possible to specify
a prefix for the environment variables that PerfTest will look up. This prefix is defined
RABBITMQ_PERF_TEST_ENV_PREFIX environment variable, e.g.:
RABBITMQ_PERF_TEST_ENV_PREFIX="PERF_TEST_" defined, PerfTest will for example look for
PERF_TEST_CONFIRM_TIMEOUT environment variable, not only
Result Reporting in HTML
PerfTest HTML extension are a set of tools
that can help you run automated benchmarks by wrapping around PerfTest. You can provide
benchmark specs, and the tool will take care of running the benchmark,
collecting results and displaying them in an HTML page. Learn more
Console Output Format
PerfTest default console output format is explicit as each line contains a label for each value:
id: test-101517-299, time 1.000 s, sent: 188898 msg/s, received: 85309 msg/s, min/median/75th/95th/99th consumer latency: 24/234/364/462/474 ms id: test-101517-299, time 2.000 s, sent: 101939 msg/s, received: 117152 msg/s, min/median/75th/95th/99th consumer latency: 483/759/830/896/907 ms id: test-101517-299, time 3.000 s, sent: 137450 msg/s, received: 118324 msg/s, min/median/75th/95th/99th consumer latency: 691/816/854/893/909 ms
Advanced users who prefer a more compact format can use the
--metrics-format compact option (
-mf compact for short).
The output looks like the following then:
time sent received consumer latency 1.000s 173920 msg/s 84405 msg/s 1/25/189/312/331 ms 2.000s 133044 msg/s 117703 msg/s 329/728/814/887/897 ms 3.000s 103736 msg/s 117134 msg/s 705/804/846/892/920 ms
PerfTest can gather metrics and make them available to various monitoring systems. Metrics include messaging-centric metrics (message latency, number of connections and channels, number of published messages, etc) as well as OS process and JVM metrics (memory, CPU usage, garbage collection, JVM heap, etc).
Here is how to list the available metrics options:
java -jar perf-test.jar --metrics-help
This command displays the available flags to enable the various metrics PerfTest can gather, as well as options to configure the exposure to the monitoring systems PerfTest supports.
Here are the metrics PerfTest can gather:
default metrics: number of published, returned, confirmed, nacked, and consumed messages, message latency, publisher confirm latency. Message latency is a major concern in many types of workload, it can be easily monitored here. Publisher confirm latency reflects the time a message can be considered unsafe. It is calculated as soon as the
-coption is used. Default metrics are available as long as PerfTest support for a monitoring system is enabled.
client metrics: these are the Java Client metrics. Enabling these metrics shouldn’t bring much compared to the default PerfTest metrics, except to see how PerfTest behaves with regards to number of open connections and channels for instance. Client metrics are enabled with the
JVM memory metrics: these metrics report memory usage of the JVM, e.g. current heap size, etc. They can be useful to have a better understanding of the client behavior, e.g. heap memory fluctuation could be due to frequent garbage collection that could explain high latency numbers. These metrics are enabled with the
JVM thread metrics: these metrics report the number of JVM threads used in the PerfTest process, as well as their state. This can be useful to optimize the usage of PerfTest to simulate high loads with fewer resources. These metrics are enabled with the
JVM GC metrics: these metrics reports garbage collection activity. They can vary depending on the JVM used, its version, and the GC settings. They can be useful to correlate the GC activity with PerfTest behavior, e.g. abnormal low throughput because of very frequent garbage collection. These metrics are enabled with the
JVM class loader metrics: the number of loaded and unloaded classes. These metrics are enabled with the
Processor metrics: there metrics report CPU activity as gathered by the JVM. They can be enabled with the
The JVM-related metrics are not available when using the native executable.
One can specify metrics tags with the
--metrics-tags options, e.g.
--metrics-tags env=performance,datacenter=eu to tell monitoring systems that those
metrics are from the
performance environment located in the
eu data center.
Monitoring systems that support dimensions can then make it easier to
navigate across metrics (group by, drill down). See Micrometer documentation
for more information about tags and dimensions.
Supported Monitoring Systems
PerfTest builds on top Micrometer to report gathered metrics to various monitoring systems. Nevertheless, not all systems supported by Micrometer are actually supported by PerfTest. PerfTest currently supports Datadog, JMX, and Prometheus. Don’t hesitate to request support for other monitoring systems.
The API key is the only required option to send metrics to Datadog:
java -jar perf-test.jar --metrics-datadog-api-key YOUR_API_KEY
Another useful option is the step size or reporting frequency. The default value is 10 seconds.
java -jar perf-test.jar --metrics-datadog-api-key YOUR_API_KEY \ --metrics-datadog-step-size 20
JMX support provides a simple way to view metrics locally. Use the
--metrics-jmx flag to
export metrics to JMX:
java -jar perf-test.jar --metrics-jmx
--metrics-prometheus flag to enable metrics reporting to Prometheus:
java -jar perf-test.jar --metrics-prometheus
Prometheus expects to scrape or poll individual app instances for metrics, so PerfTest starts up
a web server listening on port 8080 and exposes metrics on the
/metrics endpoint. These defaults
can be changed:
java -jar perf-test.jar --metrics-prometheus \ --metrics-prometheus-port 8090 --metrics-prometheus-endpoint perf-test-metrics
Expected and Exposed Metrics
PerfTest automatically exposes 2
expected_consumed metrics that represent the theoretical published and consumed rates, respectively.
PertTest calculates the values and exposes the metrics as soon as rate instructions are provided (e.g. with
These expected metrics aim at helping external monitoring tools to trigger alerts if the actual rates are different from the expected rates.
PerfTest does its best to calculate and update the expected rates, but it may be wrong or just cannot figure out the correct values.
It is then possible to override the metrics values thanks to the
--exposed-metrics option (
-em for short):
java -jar perf-test.jar --metrics-prometheus \ --exposed-metrics expected_published=50000,expected_consumed=50000
Note PerfTest adds the metrics prefix to the provided name automatically (
perftest_ by default).
It is also possible to expose any metrics, e.g. setting an expected value for the publisher confirm latency so the external monitoring system could trigger an alert if the actual latency is higher:
java -jar perf-test.jar --metrics-prometheus --rate 1000 \ --exposed-metrics expected_confirm_latency=0.1