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Summary

ElasticMQ is a message queue system, offering an actor-based Scala and an SQS-compatible REST (query) interface.

ElasticMQ follows the semantics of SQS. Messages are received by polling the queue. When a message is received, it is blocked for a specified amount of time (the visibility timeout). If the message isn't deleted during that time, it will be again available for delivery. Moreover, queues and messages can be configured to always deliver messages with a delay.

The focus in SQS (and ElasticMQ) is to make sure that the messages are delivered. It may happen, however, that a message is delivered twice (if, for example, a client dies after receiving a message and processing it, but before deleting). That's why clients of ElasticMQ (and Amazon SQS) should be idempotent.

As ElasticMQ implements a subset of the SQS query (REST) interface, it is a great SQS alternative both for testing purposes (ElasticMQ is easily embeddable) and for creating systems which work both within and outside of the Amazon infrastructure.

A simple UI is available for viewing real-time queue statistics.

Community

Installation: stand-alone

You can download the stand-alone distribution here:

wget https://s3-eu-west-1.amazonaws.com/softwaremill-public/elasticmq-server-$VERSION.jar

Java 8 or above is required for running the server.

Simply run the jar and you should get a working server, which binds to localhost:9324:

java -jar elasticmq-server-$VERSION.jar

ElasticMQ uses Typesafe Config for configuration. To specify custom configuration values, create a file (e.g. custom.conf), fill it in with the desired values, and pass it to the server:

java -Dconfig.file=custom.conf -jar elasticmq-server-$VERSION.jar

The config file may contain any configuration for Akka and ElasticMQ. Current ElasticMQ configuration values are:

include classpath("application.conf")

# What is the outside visible address of this ElasticMQ node
# Used to create the queue URL (may be different from bind address!)
node-address {
  protocol = http
  host = localhost
  port = 9324
  context-path = ""
}

rest-sqs {
  enabled = true
  bind-port = 9324
  bind-hostname = "0.0.0.0"
  # Possible values: relaxed, strict
  sqs-limits = strict
}

rest-stats {
  enabled = true
  bind-port = 9325
  bind-hostname = "0.0.0.0"
}

# Should the node-address be generated from the bind port/hostname
# Set this to true e.g. when assigning port automatically by using port 0.
generate-node-address = false

queues {
  # See next sections
}

queues-storage {
  # See next sections
}

# Region and accountId which will be included in resource ids
aws {
  region = us-west-2
  accountId = 000000000000
}

You can also provide an alternative Logback configuration file (the default is configured to log INFO logs and above to the console):

java -Dlogback.configurationFile=my_logback.xml -jar elasticmq-server-$VERSION.jar

How are queue URLs created

Some of the responses include a queue URL. By default, the URLs will use http://localhost:9324 as the base URL. To customize, you should properly set the protocol/host/port/context in the node-address setting (see above).

You can also set node-address.host to a special value, "*", which will cause any queue URLs created during a request to use the path of the incoming request. This might be useful e.g. in containerized (Docker) deployments.

Note that changing the bind-port and bind-hostname settings do not affect the queue URLs in any way unless generate-node-address is true. In that case, the bind host/port are used to create the node address. This is useful when the port should be automatically assigned (use port 0 in such case, the selected port will be visible in the logs).

Automatically creating queues on startup

Queues can be automatically created on startup by providing appropriate configuration:

The queues are specified in a custom configuration file. For example, create a custom.conf file with the following:

# the include should be done only once, at the beginning of the custom configuration file
include classpath("application.conf")

queues {
  queue1 {
    defaultVisibilityTimeout = 10 seconds
    delay = 5 seconds
    receiveMessageWait = 0 seconds
    deadLettersQueue {
      name = "queue1-dead-letters"
      maxReceiveCount = 3 // from 1 to 1000
    }
    fifo = false
    contentBasedDeduplication = false
    copyTo = "audit-queue-name"
    moveTo = "redirect-queue-name"
    tags {
      tag1 = "tagged1"
      tag2 = "tagged2"
    }
  }
  queue1-dead-letters { }
  audit-queue-name { }
  redirect-queue-name { }
}

All attributes are optional (except name and maxReceiveCount when a deadLettersQueue is defined). copyTo and moveTo attributes allow to achieve behavior that might be useful primarily for integration testing scenarios - all messages could be either duplicated (using copyTo attribute) or redirected (using moveTo attribute) to another queue.

FIFO queue creation

To create FIFO queue set value of fifo config parameter to true. You can add .fifo suffix to queue name yourself (a name containing . has to be surrounded with quotes), for example:

queues {
  "testQueue.fifo" {
    fifo = true
    contentBasedDeduplication = true
  }
}

If not then suffix will be added automatically during queue creation.

Persisting queues configuration

Queues configuration can be persisted in an external config file in the HOCON format. Note that only the queue metadata (which queues are created, and with what attributes) will be stored, without any messages.

To enable the feature, create a custom configuration file with the following content:

# the include should be done only once, at the beginning of the custom configuration file
include classpath("application.conf")

queues-storage {
  enabled = true
  path = "/path/to/storage/queues.conf"
}

Any time a queue is created, deleted, or its metadata change, the given file will be updated.

On startup, any queues defined in the given file will be created. Note that the persisted queues configuration takes precedence over queues defined in the main configuration file (as described in the previous section) in the queues section.

Persisting queues and messages to SQL database

Queues and their messages can be persisted to SQL database in runtime. All events like queue or message creation, deletion or update will be stored in H2 in-file database, so that the entire ElasticMQ state can be restored after server restart.

To enable the feature, create a custom configuration file with the following content:

# the include should be done only once, at the beginning of the custom configuration file
include classpath("application.conf")

messages-storage {
  enabled = true
}

By default, the database file is stored in /data/elasticmq.db. In order to change it, custom JDBC uri needs to be provided:

# the include should be done only once, at the beginning of the custom configuration file
include classpath("application.conf")

messages-storage {
  enabled = true
  uri = "jdbc:h2:/home/me/elasticmq"
}

On startup, any queues and their messages persisted in the database will be recreated. Note that the persisted queues take precedence over the queues defined in the main configuration file (as described in the previous section) in the queues section.

Starting an embedded ElasticMQ server with an SQS interface

Add ElasticMQ Server to build.sbt dependencies

libraryDependencies += "org.elasticmq" %% "elasticmq-server" % Version

Simply start the server using custom configuration (see examples above):

val config = ConfigFactory.load("elasticmq.conf")
val server = new ElasticMQServer(new ElasticMQServerConfig(config))
server.start()

Alternatively, custom rest server can be built using SQSRestServerBuilder provided in elasticmq-rest-sqs package:

val server = SQSRestServerBuilder.start()
// ... use ...
server.stopAndWait()

If you need to bind to a different host/port, there are configuration methods on the builder:

val server = SQSRestServerBuilder.withPort(9325).withInterface("localhost").start()
// ... use ...
server.stopAndWait()

You can also set a dynamic port with a port value of 0 or by using the method withDynamicPort. To retrieve the port (and other configuration) when using a dynamic port value you can access the server via waitUntilStarted for example:

val server = SQSRestServerBuilder.withDynamicPort().start()
server.waitUntilStarted().localAddress().getPort()

You can also provide a custom ActorSystem; for details see the javadocs.

Embedded ElasticMQ can be used from any JVM-based language (Java, Scala, etc.).

(Note that the embedded server created with SQSRestServerBuilder does not load any configuration files, so you cannot automatically create queues on startup as described above. You can of course create queues programmatically.)

Using the Amazon Java SDK to access an ElasticMQ Server

To use Amazon Java SDK as an interface to an ElasticMQ server you just need to change the endpoint:

String endpoint = "http://localhost:9324";
String region = "elasticmq";
String accessKey = "x";
String secretKey = "x";
AmazonSQS client = AmazonSQSClientBuilder.standard()
    .withCredentials(new AWSStaticCredentialsProvider(new BasicAWSCredentials(accessKey, secretKey)))
    .withEndpointConfiguration(new AwsClientBuilder.EndpointConfiguration(endpoint, region))
    .build();

The endpoint value should be the same address as the NodeAddress provided as an argument to SQSRestServerBuilder or in the configuration file.

The rest-sqs-testing-amazon-java-sdk module contains some more usage examples.

Using the Amazon boto (Python) to access an ElasticMQ Server

To use Amazon boto as an interface to an ElasticMQ server you set up the connection using:

region = boto.sqs.regioninfo.RegionInfo(name='elasticmq',
                                        endpoint=sqs_endpoint)
conn = boto.connect_sqs(aws_access_key_id='x',
                        aws_secret_access_key='x',
                        is_secure=False,
                        port=sqs_port,
                        region=region)

where sqs_endpoint and sqs_port are the host and port.

The boto3 interface is different:

client = boto3.resource('sqs',
                        endpoint_url='http://localhost:9324',
                        region_name='elasticmq',
                        aws_secret_access_key='x',
                        aws_access_key_id='x',
                        use_ssl=False)
queue = client.get_queue_by_name(QueueName='queue1')

ElasticMQ via Docker

A Docker image built using GraalVM's native-image, is available as softwaremill/elasticmq-native.

To start, run (9324 is the default REST-SQS API port; 9325 is the default UI port, exposing it is fully optional):

docker run -p 9324:9324 -p 9325:9325 softwaremill/elasticmq-native

The elasticmq-native image is much smaller (30MB vs 240MB) and starts up much faster (milliseconds instead of seconds), comparing to the full JVM version (see below). Custom configuration can be provided by creating a custom configuration file (see above) and using it when running the container:

docker run -p 9324:9324 -p 9325:9325 -v `pwd`/custom.conf:/opt/elasticmq.conf softwaremill/elasticmq-native

If messages storage is enabled, the directory containing database files can also be mapped:

docker run -p 9324:9324 -p 9325:9325 -v `pwd`/custom.conf:/opt/elasticmq.conf -v `pwd`/data:/data softwaremill/elasticmq-native

It is possible to specify custom logback.xml config as well to enable additional debug logging for example. Some logback features, like console coloring, will not work due to missing classes in the native image. This can only be solved by building a custom image.

docker run -p 9324:9324 -p 9325:9325 -v `pwd`/custom.conf:/opt/elasticmq.conf -v `pwd`/logback.xml:/opt/logback.xml softwaremill/elasticmq-native

As for now to run elasticmq-native docker image on ARM based CPU one have to install Qemu docker for amd64.

docker run --privileged --rm tonistiigi/binfmt --install amd64

ElasticMQ via Docker (full JVM)

A Docker image is built on each release an pushed as softwaremill/elasticmq. Run using:

docker run -p 9324:9324 -p 9325:9325 softwaremill/elasticmq

The image uses default configuration. Custom configuration can be provided (e.g. to change the port, or create queues on startup) by creating a custom configuration file (see above) and using it when running the container:

docker run -p 9324:9324 -p 9325:9325 -v `pwd`/custom.conf:/opt/elasticmq.conf softwaremill/elasticmq

If messages storage is enabled, the directory containing database files can also be mapped:

docker run -p 9324:9324 -p 9325:9325 -v `pwd`/custom.conf:/opt/elasticmq.conf -v `pwd`/data:/data softwaremill/elasticmq

To pass additional java system properties (-D) you need to prepare an application.ini file. For instance, to set custom logback.xml configuration, application.ini should look as follows:

application.ini:
-Dconfig.file=/opt/elasticmq.conf
-Dlogback.configurationFile=/opt/docker/conf/logback.xml

To run container with customized application.ini file (and custom logback.xml in this particular case) the following command should be used:

docker run -v `pwd`/application.ini:/opt/docker/conf/application.ini -v `pwd`/logback.xml:/opt/docker/conf/logback.xml -p 9324:9324 -p 9325:9325 softwaremill/elasticmq

In case of problems with file mounting on Windows place the application.ini and the configuration file elasticmq.conf in the same directory then mount this directory to /opt/docker/conf:

--mount type=bind,source="$(pwd)"/somefolder,target=/opt/docker/conf.

Another option is to use custom Dockerfile:

FROM openjdk:8-jre-alpine

ARG ELASTICMQ_VERSION
ENV ELASTICMQ_VERSION ${ELASTICMQ_VERSION}

RUN apk add --no-cache curl ca-certificates
RUN mkdir -p /opt/elasticmq/log /opt/elasticmq/lib /opt/elasticmq/conf
RUN curl -sfLo /opt/elasticmq/lib/elasticmq.jar https://s3-eu-west-1.amazonaws.com/softwaremill-public/elasticmq-server-${ELASTICMQ_VERSION}.jar

COPY ${PWD}/elasticmq.conf /opt/elasticmq/conf/elasticmq.conf

WORKDIR /opt/elasticmq

EXPOSE 9324

ENTRYPOINT [ "/usr/bin/java", "-Dconfig.file=/opt/elasticmq/conf/elasticmq.conf", "-jar", "/opt/elasticmq/lib/elasticmq.jar" ]

and override the entrypoint passing the required properties.

ElasticMQ dependencies in SBT

// Scala 2.13 and 2.12
val elasticmqSqs        = "org.elasticmq" %% "elasticmq-rest-sqs" % Version

If you don't want the SQS interface, but just use the actors directly, you can add a dependency only to the core module:

val elasticmqCore       = "org.elasticmq" %% "elasticmq-core" % Version

If you want to use a snapshot version, you will need to add the https://oss.sonatype.org/content/repositories/snapshots/ repository to your configuration.

ElasticMQ dependencies in Maven

Dependencies:

<dependency>
    <groupId>org.elasticmq</groupId>
    <artifactId>elasticmq-rest-sqs_2.12</artifactId>
    <version>${version}</version>
</dependency>

If you want to use a snapshot version, you will need to add the https://oss.sonatype.org/content/repositories/snapshots/ repository to your configuration.

Logging

ElasticMQ uses Slf4j for logging. By default no logger backend is included as a dependency, however Logback is recommended.

Performance

Tests done on a 2012 MBP, 2.6GHz, 16GB RAM, no replication. Throughput is in messages per second (messages are small).

Directly accessing the client:

Running test for [in-memory], iterations: 10, msgs in iteration: 100000, thread count: 1.
Overall in-memory throughput: 21326.054040

Running test for [in-memory], iterations: 10, msgs in iteration: 100000, thread count: 2.
Overall in-memory throughput: 26292.956117

Running test for [in-memory], iterations: 10, msgs in iteration: 100000, thread count: 10.
Overall in-memory throughput: 25591.155697

Through the SQS REST interface:

Running test for [rest-sqs + in-memory], iterations: 10, msgs in iteration: 1000, thread count: 20.
Overall rest-sqs + in-memory throughput: 2540.553587

Running test for [rest-sqs + in-memory], iterations: 10, msgs in iteration: 1000, thread count: 40.
Overall rest-sqs + in-memory throughput: 2600.002600

Note that both the client and the server were on the same machine.

Test class: org.elasticmq.performance.LocalPerformanceTest.

Building, running, and packaging

To build and run with debug (this will listen for a remote debugger on port 5005):

~/workspace/elasticmq $ sbt -jvm-debug 5005
> project server
> run

To build a jar-with-dependencies:

~/workspace/elasticmq $ sbt
> project server
> assembly

Building the native image

Do not forget to adjust the CPU and memory settings for the Docker process. It was checked with 6CPUs, 8GB of memory and 2GB of swap. Also, make sure that you are running sbt with the graalvm java, as the way the jars are composed seem to differ from other java implementations, and affect the native-image process that is run later! To rebuild the native image, run:

sbt "project nativeServer; clean; assembly; docker:publishLocal"

Generating GraalVM config files is a manual process currently. You need to run the fat-jar using the GraalVM VM (w/ native-image installed using gu), and then run the following commands to generate the configs:

These files should be placed in native-server/src/main/resources/META-INF/native-image and are automatically used by the native-image process.

In case of issues with running GraalVM with native-image-agent it's possible to execute above commands inside of docker container (the image is generated by the sbt command above). graalVmVersion is defined in build.sbt:

docker run -it -v `pwd`:/opt/graalvm --entrypoint /bin/bash --rm ghcr.io-graalvm-graalvm-ce-native-image:java11-${graalVmVersion}

Building multi-architecture image

Publishing Docker image for two different platforms: amd64 and arm64 is possible with Docker Buildx plugin. Docker Buildx is included in Docker Desktop and Docker Linux packages when installed using the DEB or RPM packages. build.sbt has following setup:

For the native server configuration is the same apart from Docker base image.

Parameter --push is very crucial. Since docker buildx build subcommand is not storing the resulting image in the local docker image list, we need that flag to determine where the final image will be stored. Flag --load makes output destination of type docker. However, this currently works only for single architecture images. Therefore, both sbt commands - docker:publishLocal and docker:publish are pushing images to a Docker registry.

To change this - switch parameters for dockerBuildOptions:

To build images locally:

docker buildx build --platform=linux/arm64,linux/amd64 --push -t softwaremill/elasticmq .

docker buildx build --platform=linux/amd64 --load -t softwaremill/elasticmq .

Tests and coverage

To run the tests:

~/workspace/elasticmq $ sbt test

To check the coverage reports:

~/workspace/elasticmq $ sbt
> coverage
> tests
> coverageReport
> coverageAggregate

Although it's mostly only the core project that is relevant for coverage testing, each project's report can be found in their target directory:

The aggregate report can be found at target/scala-2.12/scoverage-report/index.html

UI

ElasticMQ-UI

UI provides real-time information about the state of messages and attributes of queue.

Using UI in docker image

UI is bundled with both standard and native images. It is exposed on the address that is defined in rest-stats configuration (by default 0.0.0.0:9325).

In order to turn it off, you have to switch it off via rest-stats.enabled flag.

Using UI locally

You can start UI via yarn start command in the ui directory, which will run on localhost:3000 address.

MBeans

ElasticMQ exposes Queues MBean. It contains three operations:

Health check endpoint

When running the server in a container orchestration environment, it may be useful to have a health check endpoint. ElasticMQ provides a simple health check endpoint that can be used for this purpose. The endpoint is available at /health.

Technology

Commercial Support

We offer commercial support for ElasticMQ and related technologies, as well as development services. Contact us to learn more about our offer!

Copyright

Copyright (C) 2011-2021 SoftwareMill https://softwaremill.com.