Tag Archives: ActiveMQ

Migrating from RabbitMQ to Amazon MQ

Post Syndicated from Rachel Richardson original https://aws.amazon.com/blogs/compute/migrating-from-rabbitmq-to-amazon-mq/

This post is courtesy of Sam Dengler, AWS Solutions Architect.

Message brokers can be used to solve a number of needs in enterprise architectures, including managing workload queues and broadcasting messages to a number of subscribers. Some AWS customers are using RabbitMQ today and would like to migrate to a managed service to reduce the overhead of operating their own message broker.

Amazon MQ is a managed message broker service for Apache ActiveMQ that makes it easier to operate and scale message brokers in the cloud. Amazon MQ provides compatibility with your existing workloads that use standard protocols such as OpenWire, AMQP, MQTT, and Stomp (all enabled with SSL). Amazon MQ automatically provisions infrastructure configured as a single-instance broker or as an active/standby broker for high availability.

In this post, I describe how to launch a new Amazon MQ instance. I review example Java code to migrate from a RabbitMQ to Amazon MQ message broker using clients for ActiveMQ, Apache Qpid JMS, and Spring JmsTemplates. I also review best practices for Amazon MQ and changes from RabbitMQ to Amazon MQ to support Publish/Subscribe message patterns.

Getting started with Amazon MQ

To start, open the Amazon MQ console. Enter a broker name and choose Next step.

Launch a new Amazon MQ instance, choosing the mq.t2.micro instance type and Single-instance broker deployment mode, creating a user name and password, and choosing Create broker.

After several minutes, your instance changes status from Creation in progress to Running.  You can visit the Details page of your broker to retrieve connection information, including a link to the ActiveMQ web console where you can monitor the status of your instance queues, etc. In the following code examples, you use the OpenWire and AMQP endpoints.

To be able to access your broker, you must configure one of your security groups to allow inbound traffic. For more information, see the link to Detailed instructions in the blue box in the Connections section.

Now that your Amazon MQ broker is running, let’s look at some code!

Dependencies

The following code examples have dependencies across a range of libraries in order to demonstrate RabbitMQ, ActiveMQ, Qpid, Spring JMS templates, and connection pooling. I’ve listed all the dependencies in a single Maven pom.xml:

<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>
    <groupId>MyGroup</groupId>
    <artifactId>MyArtifact</artifactId>
    <version>0.0.1-SNAPSHOT</version>
    <dependencies>
    
        <!-- RabbitMQ -->
        <dependency>
            <groupId>com.rabbitmq</groupId>
            <artifactId>amqp-client</artifactId>
            <version>5.1.2</version>
        </dependency>

        <!-- Apache Connection Pooling -->
        <dependency>
            <groupId>org.apache.commons</groupId>
            <artifactId>commons-pool2</artifactId>
            <version>2.2</version>
        </dependency>
        <dependency>
            <groupId>org.apache.activemq</groupId>
            <artifactId>activemq-pool</artifactId>
            <version>5.15.0</version>
        </dependency>
        
        <!-- Apache ActiveMQ -->
        <dependency>
            <groupId>org.apache.activemq</groupId>
            <artifactId>activemq-client</artifactId>
            <version>5.15.0</version>
        </dependency>
        
        <!-- Apache QPid -->
        <dependency>
            <groupId>org.apache.qpid</groupId>
            <artifactId>qpid-client</artifactId>
            <version>6.3.0</version>
        </dependency>
        <dependency>
            <groupId>org.apache.qpid</groupId>
            <artifactId>qpid-jms-client</artifactId>
            <version>0.29.0</version>
        </dependency>
                
        <!-- Spring JmsTemplate -->
         <dependency>
            <groupId>org.springframework</groupId>
            <artifactId>spring-jms</artifactId>
            <version>5.0.3.RELEASE</version>
        </dependency>
        
        <!-- Logging -->
        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-log4j12</artifactId>
            <version>1.7.25</version>
        </dependency>

    </dependencies>
</project>

RabbitMQ

Here’s an example using RabbitMQ to send and receive a message via queue. The installation and configuration of RabbitMQ is out of scope for this post. For instructions for downloading and installing RabbitMQ, see Downloading and Installing RabbitMQ.

RabbitMQ uses the AMQP 0-9-1 protocol by default, with support for AMQP 1.0 via a plugin. The RabbitMQ examples in this post use the AMQP 0-9

RabbitMQ queue example

To start, here’s some sample code to send and receive a message in RabbitMQ using a queue.

import java.io.IOException;
import java.net.URISyntaxException;
import java.security.KeyManagementException;
import java.security.NoSuchAlgorithmException;
import java.util.concurrent.TimeoutException;

import com.rabbitmq.client.Channel;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.ConnectionFactory;
import com.rabbitmq.client.GetResponse;

public class RabbitMQExample {

    private static final boolean ACKNOWLEDGE_MODE = true;

    // The Endpoint, Username, Password, and Queue should be externalized and
    // configured through environment variables or dependency injection.
    private static final String ENDPOINT;
    private static final String USERNAME;
    private static final String PASSWORD;
    private static final String QUEUE = "MyQueue";

    public static void main(String[] args) throws KeyManagementException, NoSuchAlgorithmException, URISyntaxException, IOException, TimeoutException {
        // Create a connection factory.
        ConnectionFactory connectionFactory = new ConnectionFactory();
        connectionFactory.setUri(ENDPOINT);

        // Specify the username and password.
        connectionFactory.setUsername(USERNAME);
        connectionFactory.setPassword(PASSWORD);

        // Establish a connection for the producer.
        Connection producerConnection = connectionFactory.newConnection();

        // Create a channel for the producer.
        Channel producerChannel = producerConnection.createChannel();

        // Create a queue named "MyQueue".
        producerChannel.queueDeclare(QUEUE, false, false, false, null);

        // Create a message.
        String text = "Hello from RabbitMQ!";

        // Send the message.
        producerChannel.basicPublish("", QUEUE, null, text.getBytes());
        System.out.println("Message sent: " + text);

        // Clean up the producer.
        producerChannel.close();
        producerConnection.close();

        // Establish a connection for the consumer.
        Connection consumerConnection = connectionFactory.newConnection();

        // Create a channel for the consumer.
        Channel consumerChannel = consumerConnection.createChannel();

        // Create a queue named "MyQueue".
        consumerChannel.queueDeclare(QUEUE, false, false, false, null);

        // Receive the message.
        GetResponse response = consumerChannel.basicGet(QUEUE, ACKNOWLEDGE_MODE);
        String message = new String(response.getBody(), "UTF-8");
        System.out.println("Message received: " + message);

        // Clean up the consumer.
        consumerChannel.close();
        consumerConnection.close();
    }
}

In this example, you need to specify the ENDPOINT, USERNAME, and PASSWORD for your RabbitMQ message broker using environment variables or dependency injection.

This example uses the RabbitMQ client library to establish connectivity to the message broker and a channel for communication. In RabbitMQ, messages are sent over the channel to a named queue, which stores messages in a buffer, and from which consumers can receive and process messages. In this example, you publish a message using the Channel.basicPublish method, using the default exchange, identified by an empty string (“”).

To receive and process the messages in the queue, create a second connection, channel, and queue. Queue declaration is an idempotent operation, so there is no harm in declaring it twice. In this example, you receive the message using the Channel.basicGet method, automatically acknowledging message receipt to the broker.

This example demonstrates the basics of sending and receiving a message of one type. However, what if you wanted to publish messages of different types such that various consumers could subscribe only to pertinent message types (that is, pub/sub)?  Here’s a RabbitMQ example using topic exchanges to route messages to different queues.

RabbitMQ topic example

This example is similar to the one earlier. To enable topic publishing, specify two additional properties: EXCHANGE and ROUTING_KEY. RabbitMQ uses the exchange and routing key properties for routing messaging. Look at how these properties change the code to publish a message.

import java.io.IOException;
import java.net.URISyntaxException;
import java.security.KeyManagementException;
import java.security.NoSuchAlgorithmException;
import java.util.concurrent.TimeoutException;

import com.rabbitmq.client.BuiltinExchangeType;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.ConnectionFactory;
import com.rabbitmq.client.GetResponse;

public class RabbitMQExample {

    private static final boolean ACKNOWLEDGE_MODE = true;

    // The Endpoint, Username, Password, Queue, Exhange, and Routing Key should
    // be externalized and configured through environment variables or
    // dependency injection.
    private static final String ENDPOINT; // "amqp://localhost:5672"
    private static final String USERNAME;
    private static final String PASSWORD;
    private static final String QUEUE = "MyQueue";
    private static final String EXCHANGE = "MyExchange";
    private static final String ROUTING_KEY = "MyRoutingKey";
    
    public static void main(String[] args) throws KeyManagementException, NoSuchAlgorithmException, URISyntaxException, IOException, TimeoutException {
        // Create a connection factory.
        ConnectionFactory connectionFactory = new ConnectionFactory();
        connectionFactory.setUri(ENDPOINT);

        // Specify the username and password.
        connectionFactory.setUsername(USERNAME);
        connectionFactory.setPassword(PASSWORD);

        // Establish a connection for the producer.
        Connection producerConnection = connectionFactory.newConnection();

        // Create a channel for the producer.
        Channel producerChannel = producerConnection.createChannel();

        // Create a queue named "MyQueue".
        producerChannel.queueDeclare(QUEUE, false, false, false, null);

        // Create an exchange named "MyExchange".
        producerChannel.exchangeDeclare(EXCHANGE, BuiltinExchangeType.TOPIC);

        // Bind "MyQueue" to "MyExchange", using routing key "MyRoutingKey".
        producerChannel.queueBind(QUEUE, EXCHANGE, ROUTING_KEY);

        // Create a message.
        String text = "Hello from RabbitMQ!";

        // Send the message.
        producerChannel.basicPublish(EXCHANGE, ROUTING_KEY, null, text.getBytes());
        System.out.println("Message sent: " + text);

        // Clean up the producer.
        producerChannel.close();
        producerConnection.close();
        
        ...


As before, you establish a connection to the RabbitMQ message broker, a channel for communication, and a queue to buffer messages for consumption. In addition to these components, you declare an explicit exchange of type BuiltinExchangeType.TOPIC and bind the queue to the exchange using the ROUTING_KEY that filters messages to send to the queue.

Again, publish a message using the Channel.basicPublish method. This time, instead of publishing the message to a queue, specify the EXCHANGE and ROUTING_KEY values for the message. RabbitMQ uses these properties to route the message to the appropriate queue, from which a consumer receives the message using the same code from the first example.

JMS API

Now that you’ve seen examples for queue and topic publishing in RabbitMQ, look at code changes to support Amazon MQ, starting with the ActiveMQ client. But first, a quick review of the Java Messaging Service (JMS) API.

The remainder of the examples in this post use the JMS API, which abstracts messaging methods from underlying protocol and client implementations. The JMS API programming model uses a combination of connection factories, connections, sessions, destinations, message producers, and message consumers to send and receive messages. The following image (from The Java EE 6 Tutorial) shows the relationship between these components:

ActiveMQ OpenWire connectivity to Amazon MQ

Here’s how JMS is used with ActiveMQ to send and receive messages on a queue.

The ActiveMQ client uses the OpenWire protocol, supported by Amazon MQ. The OpenWire protocol can be found in your Amazon MQ broker’s endpoint list (screenshot). It requires that the security group for the Amazon MQ be open for the ActiveMQ OpenWire protocol endpoint port, 61617.

ActiveMQ queue example

Next, here’s an example to send and receive messages to Amazon MQ using the ActiveMQ client. This example should look familiar, as it follows the same flow to send and receive messages via a queue. I’ve included the example in full and then highlighted the differences to consider when migrating from RabbitMQ.

import javax.jms.Connection;
import javax.jms.DeliveryMode;
import javax.jms.Destination;
import javax.jms.JMSException;
import javax.jms.Message;
import javax.jms.MessageConsumer;
import javax.jms.MessageProducer;
import javax.jms.Session;
import javax.jms.TextMessage;

import org.apache.activemq.ActiveMQConnectionFactory;
import org.apache.activemq.jms.pool.PooledConnectionFactory;

public class ActiveMQClientExample {

    private static final int DELIVERY_MODE = DeliveryMode.NON_PERSISTENT;
    private static final int ACKNOWLEDGE_MODE = Session.AUTO_ACKNOWLEDGE;

    // The Endpoint, Username, Password, and Queue should be externalized and
    // configured through environment variables or dependency injection.
    private static final String ENDPOINT; // "ssl://x-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx-x.mq.us-east-1.amazonaws.com:61617"
    private static final String USERNAME;
    private static final String PASSWORD;
    private static final String QUEUE = "MyQueue";
    
    public static void main(String[] args) throws JMSException {
        // Create a connection factory.
        ActiveMQConnectionFactory connectionFactory = new ActiveMQConnectionFactory(ENDPOINT);

        // Specify the username and password.
        connectionFactory.setUserName(USERNAME);
        connectionFactory.setPassword(PASSWORD);

        // Create a pooled connection factory.
        PooledConnectionFactory pooledConnectionFactory = new PooledConnectionFactory();
        pooledConnectionFactory.setConnectionFactory(connectionFactory);
        pooledConnectionFactory.setMaxConnections(10);

        // Establish a connection for the producer.
        Connection producerConnection = pooledConnectionFactory.createConnection();
        producerConnection.start();

        // Create a session.
        Session producerSession = producerConnection.createSession(false, ACKNOWLEDGE_MODE);

        // Create a queue named "MyQueue".
        Destination producerDestination = producerSession.createQueue(QUEUE);

        // Create a producer from the session to the queue.
        MessageProducer producer = producerSession.createProducer(producerDestination);
        producer.setDeliveryMode(DELIVERY_MODE);

        // Create a message.
        String text = "Hello from Amazon MQ!";
        TextMessage producerMessage = producerSession.createTextMessage(text);

        // Send the message.
        producer.send(producerMessage);
        System.out.println("Message sent.");

        // Clean up the producer.
        producer.close();
        producerSession.close();
        producerConnection.close();

        // Establish a connection for the consumer.
        // Note: Consumers should not use PooledConnectionFactory.
        Connection consumerConnection = connectionFactory.createConnection();
        consumerConnection.start();

        // Create a session.
        Session consumerSession = consumerConnection.createSession(false, ACKNOWLEDGE_MODE);

        // Create a queue named "MyQueue".
        Destination consumerDestination = consumerSession.createQueue(QUEUE);

        // Create a message consumer from the session to the queue.
        MessageConsumer consumer = consumerSession.createConsumer(consumerDestination);

        // Begin to wait for messages.
        Message consumerMessage = consumer.receive(1000);

        // Receive the message when it arrives.
        TextMessage consumerTextMessage = (TextMessage) consumerMessage;
        System.out.println("Message received: " + consumerTextMessage.getText());

        // Clean up the consumer.
        consumer.close();
        consumerSession.close();
        consumerConnection.close();
        pooledConnectionFactory.stop();
    }
}

In this example, you use the ActiveMQ client to establish connectivity to AmazonMQ using the OpenWire protocol with the ActiveMQConnectionFactory class to specify the endpoint and user credentials. For this example, use the master user name and password chosen when creating the Amazon MQ broker earlier. However, it’s a best practice to create additional Amazon MQ users for brokers in non-sandbox environments.

You could use the ActiveMQConnectionFactory to establish connectivity to the Amazon MQ broker. However, it is a best practice in Amazon MQ to group multiple producer requests using the ActiveMQ PooledConnectionFactory to wrap the ActiveMQConnectionFactory.

Using the PooledConnectionFactory, you can create a connection to Amazon MQ and establish a session to send a message. Like the RabbitMQ queue example, create a message queue destination using the Session.createQueue method, and a message producer to send the message to the queue.

For the consumer, use the ActiveMQConnectionFactory, NOT the PooledConnectionFactory, to create a connection, session, queue destination, and message consumer to receive the message because pooling of consumers is not considered a best practice. For more information, see the ActiveMQ Spring Support page.

ActiveMQ virtual destinations on Amazon MQ

Here’s how topic publishing differs from RabbitMQ to Amazon MQ.

If you remember from the RabbitMQ topic example, you bound a queue to an exchange using a routing key to control queue destinations when sending messages using a key attribute.

You run into a problem if you try to implement topic subscription using the message consumer in the preceding ActiveMQ queue example. The following is an excerpt from Virtual Destinations, which provides more detail on this subject:

A JMS durable subscriber MessageConsumer is created with a unique JMS clientID and durable subscriber name. To be JMS-compliant, only one JMS connection can be active at any point in time for one JMS clientID, and only one consumer can be active for a clientID and subscriber name. That is, only one thread can be actively consuming from a given logical topic subscriber.

To solve this, ActiveMQ supports the concept of a virtual destination, which provides a logical topic subscription access to a physical queue for consumption without breaking JMS compliance. To do so, ActiveMQ uses a simple convention for specifying the topic and queue names to configure message routing.

  • Topic names must use the “VirtualTopic.” prefix, followed by the topic name. For example, VirtualTopic.MyTopic.
  • Consumer names must use the “Consumer.” prefix, followed by the consumer name, followed by the topic name. For example, Consumer.MyConsumer.VirtualTopic.MyTopic.

ActiveMQ topic example

Next, here’s an example for the ActiveMQ client that demonstrates publishing messaging to topics. This example is similar to the ActiveMQ Queue Example. In this one, create a Topic destination instead of a queue destination.

import javax.jms.Connection;
import javax.jms.DeliveryMode;
import javax.jms.Destination;
import javax.jms.JMSException;
import javax.jms.Message;
import javax.jms.MessageConsumer;
import javax.jms.MessageProducer;
import javax.jms.Session;
import javax.jms.TextMessage;

import org.apache.activemq.ActiveMQConnectionFactory;
import org.apache.activemq.jms.pool.PooledConnectionFactory;

public class ActiveMQClientExample {

    private static final int DELIVERY_MODE = DeliveryMode.NON_PERSISTENT;
    private static final int ACKNOWLEDGE_MODE = Session.AUTO_ACKNOWLEDGE;

    // The Endpoint, Username, Password, Producer Topic, and Consumer Topic
    // should be externalized and configured through environment variables or
    // dependency injection.
    private static final String ENDPOINT; // "ssl://x-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx-x.mq.us-east-1.amazonaws.com:61617"
    private static final String USERNAME;
    private static final String PASSWORD;
    private static final String PRODUCER_TOPIC = "VirtualTopic.MyTopic";
    private static final String CONSUMER1_TOPIC = "Consumer.Consumer1." + PRODUCER_TOPIC;
    
    public static void main(String[] args) throws JMSException {
        // Create a connection factory.
        ActiveMQConnectionFactory connectionFactory = new ActiveMQConnectionFactory(ENDPOINT);

        // Specify the username and password.
        connectionFactory.setUserName(USERNAME);
        connectionFactory.setPassword(PASSWORD);

        // Create a pooled connection factory.
        PooledConnectionFactory pooledConnectionFactory = new PooledConnectionFactory();
        pooledConnectionFactory.setConnectionFactory(connectionFactory);
        pooledConnectionFactory.setMaxConnections(10);

        // Establish a connection for the producer.
        Connection producerConnection = pooledConnectionFactory.createConnection();
        producerConnection.start();

        // Create a session.
        Session producerSession = producerConnection.createSession(false, ACKNOWLEDGE_MODE);

        // Create a topic named "VirtualTopic.MyTopic".
        Destination producerDestination = producerSession.createTopic(PRODUCER_TOPIC);

        // Create a producer from the session to the topic.
        MessageProducer producer = producerSession.createProducer(producerDestination);
        producer.setDeliveryMode(DELIVERY_MODE);

        // Create a message.
        String text = "Hello from Amazon MQ!";
        TextMessage producerMessage = producerSession.createTextMessage(text);

        // Send the message.
        producer.send(producerMessage);
        System.out.println("Message sent.");

        // Clean up the producer.
        producer.close();
        producerSession.close();
        producerConnection.close();

        // Establish a connection for the consumer.
        // Note: Consumers should not use PooledConnectionFactory.
        Connection consumerConnection = connectionFactory.createConnection();
        consumerConnection.start();

        // Create a session.
        Session consumerSession = consumerConnection.createSession(false, ACKNOWLEDGE_MODE);

        // Create a queue called "Consumer.Consumer1.VirtualTopic.MyTopic".
        Destination consumerDestination = consumerSession.createQueue(CONSUMER1_TOPIC);

        // Create a message consumer from the session to the queue.
        MessageConsumer consumer = consumerSession.createConsumer(consumerDestination);

        // Begin to wait for messages.
        Message consumerMessage = consumer.receive(1000);

        // Receive the message when it arrives.
        TextMessage consumerTextMessage = (TextMessage) consumerMessage;
        System.out.println("Message received: " + consumerTextMessage.getText());

        // Clean up the consumer.
        consumer.close();
        consumerSession.close();
        consumerConnection.close();
        pooledConnectionFactory.stop();
    }
}

In this example, the message producer uses the Session.createTopic method with the topic name, VirtualTopic.MyTopic, as the publishing destination. The message consumer code does not change, but the queue destination uses the virtual destination convention, Consumer.Consumer1.VirtualTopic.MyTopic. ActiveMQ uses these names for the topic and queue to route messages accordingly.

AMQP connectivity to Amazon MQ

Now that you’ve explored some examples using an ActiveMQ client, look at examples using the Qpid JMS client to connect to the Amazon MQ broker over the AMQP 1.0 protocol and see how they differ.

The Qpid client uses the Advanced Message Queuing Protocol (AMQP) 1.0 protocol, supported by Amazon MQ. The AMQP 1.0 protocol can be found in your Amazon MQ broker’s endpoint list (screenshot). It uses port 5671, which must be opened in the Security Group associated with the Amazon MQ broker.

The AMQP endpoint specifies a transport, amqp+ssl. For encrypted connections, Qpid expects the protocol name to be amqps, instead of amqp+ssl, however the rest of the connection address remains the same.

Qpid JMS queue example

Next, here’s an example to send and receive messages to Amazon MQ using the Qpid client. The Qpid JMS client is built using Apache Qpid Proton, an AMQP messaging toolkit.

import java.util.Hashtable;

import javax.jms.Connection;
import javax.jms.ConnectionFactory;
import javax.jms.DeliveryMode;
import javax.jms.Destination;
import javax.jms.JMSException;
import javax.jms.Message;
import javax.jms.MessageConsumer;
import javax.jms.MessageProducer;
import javax.jms.Session;
import javax.jms.TextMessage;
import javax.naming.Context;
import javax.naming.NamingException;

import org.apache.activemq.jms.pool.PooledConnectionFactory;

public class QpidClientExample {

    private static final int DELIVERY_MODE = DeliveryMode.NON_PERSISTENT;
    private static final int ACKNOWLEDGE_MODE = Session.AUTO_ACKNOWLEDGE;

    // The Endpoint, Username, Password, and Queue should be externalized and
    // configured through environment variables or dependency injection.
    private static final String ENDPOINT; // "amqps://x-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx-x.mq.us-east-1.amazonaws.com:5671"
    private static final String USERNAME;
    private static final String PASSWORD;
    private static final String QUEUE = "MyQueue";

    public static void main(String[] args) throws JMSException, NamingException {
        // Use JNDI to specify the AMQP endpoint
        Hashtable<Object, Object> env = new Hashtable<Object, Object>();
        env.put(Context.INITIAL_CONTEXT_FACTORY, "org.apache.qpid.jms.jndi.JmsInitialContextFactory");
        env.put("connectionfactory.factoryLookup", ENDPOINT);
        javax.naming.Context context = new javax.naming.InitialContext(env);

        // Create a connection factory.
        ConnectionFactory connectionFactory = (ConnectionFactory) context.lookup("factoryLookup");

        // Create a pooled connection factory.
        PooledConnectionFactory pooledConnectionFactory = new PooledConnectionFactory();
        pooledConnectionFactory.setConnectionFactory(connectionFactory);
        pooledConnectionFactory.setMaxConnections(10);

        // Establish a connection for the producer.
        Connection producerConnection = pooledConnectionFactory.createConnection(USERNAME, PASSWORD);
        producerConnection.start();

        // Create a session.
        Session producerSession = producerConnection.createSession(false, ACKNOWLEDGE_MODE);

        // Create a queue named "MyQueue".
        Destination producerDestination = producerSession.createQueue(QUEUE);

        // Create a producer from the session to the queue.
        MessageProducer producer = producerSession.createProducer(producerDestination);
        producer.setDeliveryMode(DELIVERY_MODE);

        // Create a message.
        String text = "Hello from Qpid Amazon MQ!";
        TextMessage producerMessage = producerSession.createTextMessage(text);

        // Send the message.
        producer.send(producerMessage);
        System.out.println("Message sent.");

        // Clean up the producer.
        producer.close();
        producerSession.close();
        producerConnection.close();

        // Establish a connection for the consumer.
        // Note: Consumers should not use PooledConnectionFactory.
        Connection consumerConnection = connectionFactory.createConnection(USERNAME, PASSWORD);
        consumerConnection.start();

        // Create a session.
        Session consumerSession = consumerConnection.createSession(false, ACKNOWLEDGE_MODE);

        // Create a queue named "MyQueue".
        Destination consumerDestination = consumerSession.createQueue(QUEUE);

        // Create a message consumer from the session to the queue.
        MessageConsumer consumer = consumerSession.createConsumer(consumerDestination);

        // Begin to wait for messages.
        Message consumerMessage = consumer.receive(1000);

        // Receive the message when it arrives.
        TextMessage consumerTextMessage = (TextMessage) consumerMessage;
        System.out.println("Message received: " + consumerTextMessage.getText());

        // Clean up the consumer.
        consumer.close();
        consumerSession.close();
        consumerConnection.close();
        pooledConnectionFactory.stop();
    }
}

The Qpid queue example is similar to the ActiveMQ Queue Example. They both use the JMS API model to send and receive messages, but the difference is in how the ConnectionFactory and AMQP endpoint is specified. According to the Qpid client configuration documentation, the ConnectionFactory is specified using a JNDI InitialContext to look up JMS objects. The JNDI configuration is popularly specified in a file named jndi.properties on the Java Classpath. In this example, do it programmatically using a HashTable for simplicity.

NOTE: Although the Qpid client and Qpid JMS client are used to establish connectivity to Amazon MQ using the AMQP 1.0 protocol, the producer should still use the ActiveMQ PooledConnectionFactory to wrap the Qpid ConnectionFactory. This can be confusing because Qpid client provides a PooledConnectionFactory that should NOT be used for AMQP 1.0.

The Qpid topic example is identical to the earlier ActiveMQ topic example with the same substitution, which establishes the ConnectionFactory to the AMQP 1.0 endpoint via JNDI.

Spring JMS template queue example

Finally, here are examples using the Spring JmsTemplate to send and receive messages.

This example established connectivity to Amazon MQ using the same protocol and client library used in the ActiveMQ queue example. That example requires that the security group for the Amazon MQ be open for the ActiveMQ OpenWire protocol endpoint port, 61617.

The Spring JmsTemplate provides a higher-level abstraction on top of JMS. Code using the JmsTemplate class only needs to implement handlers to process messages, while the management of connections, sessions, message producers, and message consumers is delegated to Spring. Look at the following code:

import javax.jms.DeliveryMode;
import javax.jms.JMSException;
import javax.jms.Message;
import javax.jms.Session;
import javax.jms.TextMessage;

import org.apache.activemq.ActiveMQConnectionFactory;
import org.apache.activemq.command.ActiveMQQueue;
import org.apache.activemq.jms.pool.PooledConnectionFactory;
import org.springframework.jms.core.JmsTemplate;
import org.springframework.jms.core.MessageCreator;

public class ActiveMQSpringExample {

    private static final int DELIVERY_MODE = DeliveryMode.NON_PERSISTENT;
    private static final int ACKNOWLEDGE_MODE = Session.AUTO_ACKNOWLEDGE;

    // The Endpoint, Username, Password, and Queue should be externalized and
    // configured through environment variables or dependency injection.
    private static final String ENDPOINT; // ssl://x-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx-x.mq.us-east-1.amazonaws.com:61617"
    private static final String USERNAME;
    private static final String PASSWORD;
    private static final String QUEUE = "MyQueue";

    public static void main(String[] args) throws JMSException {
        // Create a connection factory.
        ActiveMQConnectionFactory connectionFactory = new ActiveMQConnectionFactory(ENDPOINT);

        // Specify the username and password.
        connectionFactory.setUserName(USERNAME);
        connectionFactory.setPassword(PASSWORD);

        // Create a pooled connection factory.
        PooledConnectionFactory pooledConnectionFactory = new PooledConnectionFactory();
        pooledConnectionFactory.setConnectionFactory(connectionFactory);
        pooledConnectionFactory.setMaxConnections(10);

        // Create a JmsTemplate for the producer.
        JmsTemplate producerJmsTemplate = new JmsTemplate();
        producerJmsTemplate.setConnectionFactory(pooledConnectionFactory);
        producerJmsTemplate.setDefaultDestination(new ActiveMQQueue(QUEUE));
        producerJmsTemplate.setSessionAcknowledgeMode(ACKNOWLEDGE_MODE);
        producerJmsTemplate.setDeliveryMode(DELIVERY_MODE);
        
        // Create a message creator.
        MessageCreator messageCreator = new MessageCreator() {
            public Message createMessage(Session session) throws JMSException {
                return session.createTextMessage("Hello from Spring Amazon MQ!");
            }
        };

        // Send the message.
        producerJmsTemplate.send(messageCreator);
        System.out.println("Message sent.");

        // Clean up the producer.
        // producer JmsTemplate will close underlying sessions and connections.

        // Create a JmsTemplate for the consumer.
        // Note: Consumers should not use PooledConnectionFactory.
        JmsTemplate consumerJmsTemplate = new JmsTemplate();
        consumerJmsTemplate.setConnectionFactory(connectionFactory);
        consumerJmsTemplate.setDefaultDestination(new ActiveMQQueue(QUEUE));
        consumerJmsTemplate.setSessionAcknowledgeMode(ACKNOWLEDGE_MODE);
        consumerJmsTemplate.setReceiveTimeout(1000);
        
        // Begin to wait for messages.
        Message consumerMessage = consumerJmsTemplate.receive();

        // Receive the message when it arrives.
        TextMessage consumerTextMessage = (TextMessage) consumerMessage;
        System.out.println("Message received: " + consumerTextMessage.getText());

        // Clean up the consumer.
        // consumer JmsTemplate will close underlying sessions and connections.
        pooledConnectionFactory.stop();
    }
}
Although Spring manages connections, sessions, and message producers, the grouping of producer connections is still a best practice. The ActiveMQ PooledConnectionFactory class is used in this example. However, the Spring CachingConnectionFactory object is another option.
Following the PooledConnectionFactory creation, a JmsTemplate is created for the producer and an ActiveMQQueue is created as the message destination. To use JmsTemplate to send a message, a MessageCreator callback is defined that generates a text message via the JmsTemplate.
A second JmsTemplate with an ActiveMQQueue is created for the consumer. In this example, a single message is received synchronously, however, asynchronous message reception is a popular alternative when using message-driven POJOs.
Unlike the ActiveMQ examples, the Spring JMS template example does not require the explicit cleanup of the connection, session, message producer, or message consumer resources, as that is managed by Spring. Make sure to call the PooledConnectionFactory.stop method to cleanly exit the main method.
Finally, here’s an example using a Spring JmsTemplate for topic publishing.
Spring JmsTemplate topic example
This example combines the Spring JmsTemplate queue example with the virtual destinations approach from the ActiveMQ topic example. Look at the following code.
import javax.jms.DeliveryMode;
import javax.jms.JMSException;
import javax.jms.Message;
import javax.jms.Session;
import javax.jms.TextMessage;

import org.apache.activemq.ActiveMQConnectionFactory;
import org.apache.activemq.command.ActiveMQQueue;
import org.apache.activemq.command.ActiveMQTopic;
import org.apache.activemq.jms.pool.PooledConnectionFactory;
import org.springframework.jms.core.JmsTemplate;
import org.springframework.jms.core.MessageCreator;

public class ActiveMQSpringExample {

    private static final int DELIVERY_MODE = DeliveryMode.NON_PERSISTENT;
    private static final int ACKNOWLEDGE_MODE = Session.AUTO_ACKNOWLEDGE;

    // The Endpoint, Username, Password, Producer Topic, and Consumer Topic
    // should be externalized and configured through environment variables or
    // dependency injection.
    private static final String ENDPOINT; // "ssl://x-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx-x.mq.us-east-1.amazonaws.com:61617"
    private static final String USERNAME;
    private static final String PASSWORD;
    private static final String PRODUCER_TOPIC = "VirtualTopic.MyTopic";
    private static final String CONSUMER1_TOPIC = "Consumer.Consumer1." + PRODUCER_TOPIC;
    
    public static void main(String[] args) throws JMSException {
        // Create a connection factory.
        ActiveMQConnectionFactory connectionFactory = new ActiveMQConnectionFactory(ENDPOINT);

        // Specify the username and password.
        connectionFactory.setUserName(USERNAME);
        connectionFactory.setPassword(PASSWORD);

        // Create a pooled connection factory.
        PooledConnectionFactory pooledConnectionFactory = new PooledConnectionFactory();
        pooledConnectionFactory.setConnectionFactory(connectionFactory);
        pooledConnectionFactory.setMaxConnections(10);

        // Create a JmsTemplate for the producer.
        JmsTemplate producerJmsTemplate = new JmsTemplate();
        producerJmsTemplate.setConnectionFactory(pooledConnectionFactory);
        producerJmsTemplate.setDefaultDestination(new ActiveMQTopic(PRODUCER_TOPIC));
        producerJmsTemplate.setSessionAcknowledgeMode(ACKNOWLEDGE_MODE);
        producerJmsTemplate.setDeliveryMode(DELIVERY_MODE);

        // Create a message creator.
        MessageCreator messageCreator = new MessageCreator() {
            public Message createMessage(Session session) throws JMSException {
                return session.createTextMessage("Hello from Spring Amazon MQ!");
            }
        };

        // Send the message.
        producerJmsTemplate.send(messageCreator);
        System.out.println("Message sent.");

        // Clean up the producer.
        // producer JmsTemplate will close underlying sessions and connections.

        // Create a JmsTemplate for the consumer.
        // Note: Consumers should not use PooledConnectionFactory.
        JmsTemplate consumerJmsTemplate = new JmsTemplate();
        consumerJmsTemplate.setConnectionFactory(connectionFactory);
        consumerJmsTemplate.setDefaultDestination(new ActiveMQQueue(CONSUMER1_TOPIC));
        consumerJmsTemplate.setSessionAcknowledgeMode(ACKNOWLEDGE_MODE);
        consumerJmsTemplate.setReceiveTimeout(1000);
        
        // Begin to wait for messages.
        Message consumerMessage = consumerJmsTemplate.receive();

        // Receive the message when it arrives.
        TextMessage consumerTextMessage = (TextMessage) consumerMessage;
        System.out.println("Message received: " + consumerTextMessage.getText());

        // Clean up the consumer.
        // consumer JmsTemplate will close underlying sessions and connections.
        pooledConnectionFactory.stop();
    }
}
In this example, follow the ActiveMQ virtual destination naming convention for topics and queues:
  • When creating the producer JMS template, specify an ActiveMQTopic as the destination using the name VirtualTopic.MyTopic.
  • When creating the consumer JMS template, specify an ActiveMQQueue as the destination using the name Consumer.Consumer1.VirtualTopic.MyTopic.
ActiveMQ automatically handles routing messages from topic to queue.
Conclusion
In this post, I reviewed how to get started with an Amazon MQ broker and walked you through several code examples that explored the differences between RabbitMQ and Apache ActiveMQ client integrations. If you are considering migrating to Amazon MQ, these examples should help you understand the changes that might be required.
If you’re thinking about integrating your existing apps with new serverless apps, see the related post, Invoking AWS Lambda from Amazon MQ.
To learn more, see the Amazon MQ website and Developer Guide. You can try Amazon MQ for free with the AWS Free Tier, which includes up to 750 hours of a single-instance mq.t2.micro broker and up to 1 GB of storage per month for one year for new AWS accounts.
Measuring the throughput for Amazon MQ using the JMS Benchmark
  
Post Syndicated from Rachel Richardson original https://aws.amazon.com/blogs/compute/measuring-the-throughput-for-amazon-mq-using-the-jms-benchmark/
This post is courtesy of Alan Protasio, Software Development Engineer, Amazon Web Services
Just like compute and storage, messaging is a fundamental building block of enterprise applications. Message brokers (aka “message-oriented middleware”) enable different software systems, often written in different languages, on different platforms, running in different locations, to communicate and exchange information. Mission-critical applications, such as CRM and ERP, rely on message brokers to work.
A common performance consideration for customers deploying a message broker in a production environment is the throughput of the system, measured as messages per second. This is important to know so that application environments (hosts, threads, memory, etc.) can be configured correctly.
In this post, we demonstrate how to measure the throughput for Amazon MQ, a new managed message broker service for ActiveMQ, using JMS Benchmark. It should take between 15–20 minutes to set up the environment and an hour to run the benchmark. We also provide some tips on how to configure Amazon MQ for optimal throughput.
Benchmarking throughput for Amazon MQ
ActiveMQ can be used for a number of use cases. These use cases can range from simple fire and forget tasks (that is, asynchronous processing), low-latency request-reply patterns, to buffering requests before they are persisted to a database.
The throughput of Amazon MQ is largely dependent on the use case. For example, if you have non-critical workloads such as gathering click events for a non-business-critical portal, you can use ActiveMQ in a non-persistent mode and get extremely high throughput with Amazon MQ.
On the flip side, if you have a critical workload where durability is extremely important (meaning that you can’t lose a message), then you are bound by the I/O capacity of your underlying persistence store. We recommend using mq.m4.large for the best results. The mq.t2.micro instance type is intended for product evaluation. Performance is limited, due to the lower memory and burstable CPU performance.
Tip: To improve your throughput with Amazon MQ, make sure that you have consumers processing messaging as fast as (or faster than) your producers are pushing messages.
Because it’s impossible to talk about how the broker (ActiveMQ) behaves for each and every use case, we walk through how to set up your own benchmark for Amazon MQ using our favorite open-source benchmarking tool: JMS Benchmark. We are fans of the JMS Benchmark suite because it’s easy to set up and deploy, and comes with a built-in visualizer of the results.
Non-Persistent Scenarios – Queue latency as you scale producer throughput
JMS Benchmark nonpersistent scenarios
Getting started
At the time of publication, you can create an mq.m4.large single-instance broker for testing for $0.30 per hour (US pricing).
This walkthrough covers the following tasks:
  1.  Create and configure the broker.
  2. Create an EC2 instance to run your benchmark
  3. Configure the security groups
  4.  Run the benchmark.
Step 1 – Create and configure the broker
 Create and configure the broker using Tutorial: Creating and Configuring an Amazon MQ Broker.
Step 2 – Create an EC2 instance to run your benchmark
 Launch the EC2 instance using Step 1: Launch an Instance. We recommend choosing the m5.large instance type.
Step 3 – Configure the security groups
 Make sure that all the security groups are correctly configured to let the traffic flow between the EC2 instance and your broker.
  1. Sign in to the Amazon MQ console.
  2. From the broker list, choose the name of your broker (for example, MyBroker)
  3. In the Details section, under Security and network, choose the name of your security group or choose the expand icon ( ).
  4. From the security group list, choose your security group.
  5. At the bottom of the page, choose Inbound, Edit.
  6. In the Edit inbound rules dialog box, add a role to allow traffic between your instance and the broker:
     • Choose Add Rule.
     • For Type, choose Custom TCP.
     • For Port Range, type the ActiveMQ SSL port (61617).
     • For Source, leave Custom selected and then type the security group of your EC2 instance.
     • Choose Save.
Your broker can now accept the connection from your EC2 instance.
Step 4 – Run the benchmark
 Connect to your EC2 instance using SSH and run the following commands:
$ cd ~
$ curl -L https://github.com/alanprot/jms-benchmark/archive/master.zip -o master.zip
$ unzip master.zip
$ cd jms-benchmark-master
$ chmod a+x bin/*
$ env \
  SERVER_SETUP=false \
  SERVER_ADDRESS={activemq-endpoint} \
  ACTIVEMQ_TRANSPORT=ssl\
  ACTIVEMQ_PORT=61617 \
  ACTIVEMQ_USERNAME={activemq-user} \
  ACTIVEMQ_PASSWORD={activemq-password} \
  ./bin/benchmark-activemq
After the benchmark finishes, you can find the results in the ~/reports directory. As you may notice, the performance of ActiveMQ varies based on the number of consumers, producers, destinations, and message size.
Amazon MQ architecture
The last bit that’s important to know so that you can better understand the results of the benchmark is how Amazon MQ is architected.
Amazon MQ is architected to be highly available (HA) and durable. For HA, we recommend using the multi-AZ option. After a message is sent to Amazon MQ in persistent mode, the message is written to the highly durable message store that replicates the data across multiple nodes in multiple Availability Zones. Because of this replication, for some use cases you may see a reduction in throughput as you migrate to Amazon MQ. Customers have told us they appreciate the benefits of message replication as it helps protect durability even in the face of the loss of an Availability Zone.
Conclusion
We hope this gives you an idea of how Amazon MQ performs. We encourage you to run tests to simulate your own use cases.
To learn more, see the Amazon MQ website. You can try Amazon MQ for free with the AWS Free Tier, which includes up to 750 hours of a single-instance mq.t2.micro broker and up to 1 GB of storage per month for one year.
Running ActiveMQ in a Hybrid Cloud Environment with Amazon MQ
  
Post Syndicated from Tara Van Unen original https://aws.amazon.com/blogs/compute/running-activemq-in-a-hybrid-cloud-environment-with-amazon-mq/
This post courtesy of Greg Share, AWS Solutions Architect
Many organizations, particularly enterprises, rely on message brokers to connect and coordinate different systems. Message brokers enable distributed applications to communicate with one another, serving as the technological backbone for their IT environment, and ultimately their business services. Applications depend on messaging to work.
In many cases, those organizations have started to build new or “lift and shift” applications to AWS. In some cases, there are applications, such as mainframe systems, too costly to migrate. In these scenarios, those on-premises applications still need to interact with cloud-based components.
Amazon MQ is a managed message broker service for ActiveMQ that enables organizations to send messages between applications in the cloud and on-premises to enable hybrid environments and application modernization. For example, you can invoke AWS Lambda from queues and topics managed by Amazon MQ brokers to integrate legacy systems with serverless architectures. ActiveMQ is an open-source message broker written in Java that is packaged with clients in multiple languages, Java Message Server (JMS) client being one example.
This post shows you can use Amazon MQ to integrate on-premises and cloud environments using the network of brokers feature of ActiveMQ. It provides configuration parameters for a one-way duplex connection for the flow of messages from an on-premises ActiveMQ message broker to Amazon MQ.
ActiveMQ and the network of brokers
First, look at queues within ActiveMQ and then at the network of brokers as a mechanism to distribute messages.
The network of brokers behaves differently from models such as physical networks. The key consideration is that the production (sending) of a message is disconnected from the consumption of that message. Think of the delivery of a parcel: The parcel is sent by the supplier (producer) to the end customer (consumer). The path it took to get there is of little concern to the customer, as long as it receives the package.
The same logic can be applied to the network of brokers. Here’s how you build the flow from a simple message to a queue and build toward a network of brokers. Before you look at setting up a hybrid connection, I discuss how a broker processes messages in a simple scenario.
When a message is sent from a producer to a queue on a broker, the following steps occur:
  1. A message is sent to a queue from the producer.
  2. The broker persists this in its store or journal.
  3. At this point, an acknowledgement (ACK) is sent to the producer from the broker.
     
When a consumer looks to consume the message from that same queue, the following steps occur:
  1. The message listener (consumer) calls the broker, which creates a subscription to the queue.
  2. Messages are fetched from the message store and sent to the consumer.
  3. The consumer acknowledges that the message has been received before processing it.
  4. Upon receiving the ACK, the broker sets the message as having been consumed. By default, this deletes it from the queue.
    • You can set the consumer to ACK after processing by setting up transaction management or handle it manually using Session.CLIENT_ACKNOWLEDGE.
Static propagation
I now introduce the concept of static propagation with the network of brokers as the mechanism for message transfer from on-premises brokers to Amazon MQ.  Static propagation refers to message propagation that occurs in the absence of subscription information. In this case, the objective is to transfer messages arriving at your selected on-premises broker to the Amazon MQ broker for consumption within the cloud environment.
After you configure static propagation with a network of brokers, the following occurs:
  1. The on-premises broker receives a message from a producer for a specific queue.
  2. The on-premises broker sends (statically propagates) the message to the Amazon MQ broker.
  3. The Amazon MQ broker sends an acknowledgement to the on-premises broker, which marks the message as having been consumed.
  4. Amazon MQ holds the message in its queue ready for consumption.
  5. A consumer connects to Amazon MQ broker, subscribes to the queue in which the message resides, and receives the message.
  6. Amazon MQ broker marks the message as having been consumed.
Getting started
The first step is creating an Amazon MQ broker.
  1. Sign in to the Amazon MQ console and launch a new Amazon MQ broker.
  2. Name your broker and choose Next step.
  3. For Broker instance type, choose your instance size:
     – mq.t2.micro
     – mq.m4.large
  4. For Deployment mode, enter one of the following:
     – Single-instance broker for development and test implementations (recommended)
     – Active/standby broker for high availability in production environments
  5. Scroll down and enter your user name and password.
  6. Expand Advanced Settings.
  7. For VPC, Subnet, and Security Group, pick the values for the resources in which your broker will reside.
  8. For Public Accessibility, choose Yes, as connectivity is internet-based. Another option would be to use private connectivity between your on-premises network and the VPC, an example being an AWS Direct Connect or VPN connection. In that case, you could set Public Accessibility to No.
  9. For Maintenance, leave the default value, No preference.
  10. Choose Create Broker. Wait several minutes for the broker to be created.
     
After creation is complete, you see your broker listed.
For connectivity to work, you must configure the security group where Amazon MQ resides. For this post, I focus on the OpenWire protocol.
For Openwire connectivity, allow port 61617 access for Amazon MQ from your on-premises ActiveMQ broker source IP address. For alternate protocols, see the Amazon MQ broker configuration information for the ports required:
OpenWire – ssl://xxxxxxx.xxx.com:61617
 AMQP – amqp+ssl:// xxxxxxx.xxx.com:5671
 STOMP – stomp+ssl:// xxxxxxx.xxx.com:61614
 MQTT – mqtt+ssl:// xxxxxxx.xxx.com:8883
 WSS – wss:// xxxxxxx.xxx.com:61619
Configuring the network of brokers
Configuring the network of brokers with static propagation occurs on the on-premises broker by applying changes to the following file:
 <activemq install directory>/conf activemq.xml
Network connector
This is the first configuration item required to enable a network of brokers. It is only required on the on-premises broker, which initiates and creates the connection with Amazon MQ. This connection, after it’s established, enables the flow of messages in either direction between the on-premises broker and Amazon MQ. The focus of this post is the uni-directional flow of messages from the on-premises broker to Amazon MQ.
The default activemq.xml file does not include the network connector configuration. Add this with the networkConnector element. In this scenario, edit the on-premises broker activemq.xml file to include the following information between <systemUsage> and <transportConnectors>:
<networkConnectors>
             <networkConnector 
                name="Q:source broker name->target broker name"
                duplex="false" 
                uri="static:(ssl:// aws mq endpoint:61617)" 
                userName="username"
                password="password" 
                networkTTL="2" 
                dynamicOnly="false">
                <staticallyIncludedDestinations>
                    <queue physicalName="queuename"/>
                </staticallyIncludedDestinations> 
                <excludedDestinations>
                      <queue physicalName=">" />
                </excludedDestinations>
             </networkConnector> 
     <networkConnectors>
The highlighted components are the most important elements when configuring your on-premises broker.
  • name – Name of the network bridge. In this case, it specifies two things:
    • That this connection relates to an ActiveMQ queue (Q) as opposed to a topic (T), for reference purposes.
    • The source broker and target broker.
  • duplex –Setting this to false ensures that messages traverse uni-directionally from the on-premises broker to Amazon MQ.
  • uri –Specifies the remote endpoint to which to connect for message transfer. In this case, it is an Openwire endpoint on your Amazon MQ broker. This information could be obtained from the Amazon MQ console or via the API.
  • username and password – The same username and password configured when creating the Amazon MQ broker, and used to access the Amazon MQ ActiveMQ console.
  • networkTTL – Number of brokers in the network through which messages and subscriptions can pass. Leave this setting at the current value, if it is already included in your broker connection.
  • staticallyIncludedDestinations > queue physicalName – The destination ActiveMQ queue for which messages are destined. This is the queue that is propagated from the on-premises broker to the Amazon MQ broker for message consumption.
After the network connector is configured, you must restart the ActiveMQ service on the on-premises broker for the changes to be applied.
Verify the configuration
There are a number of places within the ActiveMQ console of your on-premises and Amazon MQ brokers to browse to verify that the configuration is correct and the connection has been established.
On-premises broker
Launch the ActiveMQ console of your on-premises broker and navigate to Network. You should see an active network bridge similar to the following:
This identifies that the connection between your on-premises broker and your Amazon MQ broker is up and running.
Now navigate to Connections and scroll to the bottom of the page. Under the Network Connectors subsection, you should see a connector labeled with the name: value that you provided within the ActiveMQ.xml configuration file. You should see an entry similar to:
Amazon MQ broker
Launch the ActiveMQ console of your Amazon MQ broker and navigate to Connections. Scroll to the Connections openwire subsection and you should see a connection specified that references the name: value that you provided within the ActiveMQ.xml configuration file. You should see an entry similar to:
If you configured the uri: for AMQP, STOMP, MQTT, or WSS as opposed to Openwire, you would see this connection under the corresponding section of the Connections page.
Testing your message flow
The setup described outlines a way for messages produced on premises to be propagated to the cloud for consumption in the cloud. This section provides steps on verifying the message flow.
Verify that the queue has been created
After you specify this queue name as staticallyIncludedDestinations > queue physicalName: and your ActiveMQ service starts, you see the following on your on-premises ActiveMQ console Queues page.
As you can see, no messages have been sent but you have one consumer listed. If you then choose Active Consumers under the Views column, you see Active Consumers for TestingQ.
This is telling you that your Amazon MQ broker is a consumer of your on-premises broker for the testing queue.
Produce and send a message to the on-premises broker
Now, produce a message on an on-premises producer and send it to your on-premises broker to a queue named TestingQ. If you navigate back to the queues page of your on-premises ActiveMQ console, you see that the messages enqueued and messages dequeued column count for your TestingQ queue have changed:
What this means is that the message originating from the on-premises producer has traversed the on-premises broker and propagated immediately to the Amazon MQ broker. At this point, the message is no longer available for consumption from the on-premises broker.
If you access the ActiveMQ console of your Amazon MQ broker and navigate to the Queues page, you see the following for the TestingQ queue:
This means that the message originally sent to your on-premises broker has traversed the network of brokers unidirectional network bridge, and is ready to be consumed from your Amazon MQ broker. The indicator is the Number of Pending Messages column.
Consume the message from an Amazon MQ broker
Connect to the Amazon MQ TestingQ queue from a consumer within the AWS Cloud environment for message consumption. Log on to the ActiveMQ console of your Amazon MQ broker and navigate to the Queue page:
As you can see, the Number of Pending Messages column figure has changed to 0 as that message has been consumed.
This diagram outlines the message lifecycle from the on-premises producer to the on-premises broker, traversing the hybrid connection between the on-premises broker and Amazon MQ, and finally consumption within the AWS Cloud.
Conclusion
This post focused on an ActiveMQ-specific scenario for transferring messages within an ActiveMQ queue from an on-premises broker to Amazon MQ.
For other on-premises brokers, such as IBM MQ, another approach would be to run ActiveMQ on-premises broker and use JMS bridging to IBM MQ, while using the approach in this post to forward to Amazon MQ. Yet another approach would be to use Apache Camel for more sophisticated routing.
I hope that you have found this example of hybrid messaging between an on-premises environment in the AWS Cloud to be useful. Many customers are already using on-premises ActiveMQ brokers, and this is a great use case to enable hybrid cloud scenarios.
To learn more, see the Amazon MQ website and Developer Guide. You can try Amazon MQ for free with the AWS Free Tier, which includes up to 750 hours of a single-instance mq.t2.micro broker and up to 1 GB of storage per month for one year.
 
Invoking AWS Lambda from Amazon MQ
  
Post Syndicated from Tara Van Unen original https://aws.amazon.com/blogs/compute/invoking-aws-lambda-from-amazon-mq/
Contributed by Josh Kahn, AWS Solutions Architect
Message brokers can be used to solve a number of needs in enterprise architectures, including managing workload queues and broadcasting messages to a number of subscribers. Amazon MQ is a managed message broker service for Apache ActiveMQ that makes it easy to set up and operate message brokers in the cloud.
In this post, I discuss one approach to invoking AWS Lambda from queues and topics managed by Amazon MQ brokers. This and other similar patterns can be useful in integrating legacy systems with serverless architectures. You could also integrate systems already migrated to the cloud that use common APIs such as JMS.
For example, imagine that you work for a company that produces training videos and which recently migrated its video management system to AWS. The on-premises system used to publish a message to an ActiveMQ broker when a video was ready for processing by an on-premises transcoder. However, on AWS, your company uses Amazon Elastic Transcoder. Instead of modifying the management system, Lambda polls the broker for new messages and starts a new Elastic Transcoder job. This approach avoids changes to the existing application while refactoring the workload to leverage cloud-native components.
This solution uses Amazon CloudWatch Events to trigger a Lambda function that polls the Amazon MQ broker for messages. Instead of starting an Elastic Transcoder job, the sample writes the received message to an Amazon DynamoDB table with a time stamp indicating the time received.
Getting started
To start, navigate to the Amazon MQ console. Next, launch a new Amazon MQ instance, selecting Single-instance Broker and supplying a broker name, user name, and password. Be sure to document the user name and password for later.
For the purposes of this sample, choose the default options in the Advanced settings section. Your new broker is deployed to the default VPC in the selected AWS Region with the default security group. For this post, you update the security group to allow access for your sample Lambda function. In a production scenario, I recommend deploying both the Lambda function and your Amazon MQ broker in your own VPC.
After several minutes, your instance changes status from “Creation Pending” to “Available.” You can then visit the Details page of your broker to retrieve connection information, including a link to the ActiveMQ web console where you can monitor the status of your broker, publish test messages, and so on. In this example, use the Stomp protocol to connect to your broker. Be sure to capture the broker host name, for example:
<BROKER_ID>.mq.us-east-1.amazonaws.com
You should also modify the Security Group for the broker by clicking on its Security Group ID. Click the Edit button and then click Add Rule to allow inbound traffic on port 8162 for your IP address.
Deploying and scheduling the Lambda function
To simplify the deployment of this example, I’ve provided an AWS Serverless Application Model (SAM) template that deploys the sample function and DynamoDB table, and schedules the function to be invoked every five minutes. Detailed instructions can be found with sample code on GitHub in the amazonmq-invoke-aws-lambda repository, with sample code. I discuss a few key aspects in this post.
First, SAM makes it easy to deploy and schedule invocation of our function:
SubscriberFunction:
	Type: AWS::Serverless::Function
	Properties:
		CodeUri: subscriber/
		Handler: index.handler
		Runtime: nodejs6.10
		Role: !GetAtt SubscriberFunctionRole.Arn
		Timeout: 15
		Environment:
			Variables:
				HOST: !Ref AmazonMQHost
				LOGIN: !Ref AmazonMQLogin
				PASSWORD: !Ref AmazonMQPassword
				QUEUE_NAME: !Ref AmazonMQQueueName
				WORKER_FUNCTIOn: !Ref WorkerFunction
		Events:
			Timer:
				Type: Schedule
				Properties:
					Schedule: rate(5 minutes)

WorkerFunction:
Type: AWS::Serverless::Function
	Properties:
		CodeUri: worker/
		Handler: index.handler
		Runtime: nodejs6.10
Role: !GetAtt WorkerFunctionRole.Arn
		Environment:
			Variables:
				TABLE_NAME: !Ref MessagesTable
In the code, you include the URI, user name, and password for your newly created Amazon MQ broker. These allow the function to poll the broker for new messages on the sample queue.
The sample Lambda function is written in Node.js, but clients exist for a number of programming languages.
stomp.connect(options, (error, client) => {
	if (error) { /* do something */ }

	let headers = {
		destination: ‘/queue/SAMPLE_QUEUE’,
		ack: ‘auto’
	}

	client.subscribe(headers, (error, message) => {
		if (error) { /* do something */ }

		message.readString(‘utf-8’, (error, body) => {
			if (error) { /* do something */ }

			let params = {
				FunctionName: MyWorkerFunction,
				Payload: JSON.stringify({
					message: body,
					timestamp: Date.now()
				})
			}

			let lambda = new AWS.Lambda()
			lambda.invoke(params, (error, data) => {
				if (error) { /* do something */ }
			})
		}
})
})
Sending a sample message
For the purpose of this example, use the Amazon MQ console to send a test message. Navigate to the details page for your broker.
About midway down the page, choose ActiveMQ Web Console. Next, choose Manage ActiveMQ Broker to launch the admin console. When you are prompted for a user name and password, use the credentials created earlier.
At the top of the page, choose Send. From here, you can send a sample message from the broker to subscribers. For this example, this is how you generate traffic to test the end-to-end system. Be sure to set the Destination value to “SAMPLE_QUEUE.” The message body can contain any text. Choose Send.
You now have a Lambda function polling for messages on the broker. To verify that your function is working, you can confirm in the DynamoDB console that the message was successfully received and processed by the sample Lambda function.
First, choose Tables on the left and select the table name “amazonmq-messages” in the middle section. With the table detail in view, choose Items. If the function was successful, you’ll find a new entry similar to the following:
If there is no message in DynamoDB, check again in a few minutes or review the CloudWatch Logs group for Lambda functions that contain debug messages.
Alternative approaches
Beyond the approach described here, you may consider other approaches as well. For example, you could use an intermediary system such as Apache Flume to pass messages from the broker to Lambda or deploy Apache Camel to trigger Lambda via a POST to API Gateway. There are trade-offs to each of these approaches. My goal in using CloudWatch Events was to introduce an easily repeatable pattern familiar to many Lambda developers.
Summary
I hope that you have found this example of how to integrate AWS Lambda with Amazon MQ useful. If you have expertise or legacy systems that leverage APIs such as JMS, you may find this useful as you incorporate serverless concepts in your enterprise architectures.
To learn more, see the Amazon MQ website and Developer Guide. You can try Amazon MQ for free with the AWS Free Tier, which includes up to 750 hours of a single-instance mq.t2.micro broker and up to 1 GB of storage per month for one year.