Prometheus Monitoring for Java Web Applications without Modifying their Source Code
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Prometheus Monitoring for Java Web Applications without Modifying their Source Code.

The promagent-maven-plugin is a tool for creating custom Java agents for Prometheus monitoring. The Java agents instrument Java Web Applications with Prometheus metrics without modifying the applications' source code. The agents use the Byte Buddy bytecode manipulation library to insert Prometheus metrics during application startup.

The Promagent code repository contains two projects:

  • promagent-framework: Provides, among other things, the promagent-api and the promagent-maven-plugin helping you to create your own agents.
  • promagent-example: An example agent providing metrics for Spring Boot and Java EE applications:
    • HTTP: Number and duration of web requests.
    • SQL: Number and duration of database queries (including the HTTP context if the query was triggered by a REST call).

The example agent was tested with Tomcat for the Spring Boot example and with the Wildfly application server for the Java EE example.



Downloading and Compiling the Example Agent

Clone Promagent from GitHub:

git clone
cd promagent

The promagent-api and promagent-maven-plugin are not on Maven Central yet. Run the following commands to make them available locally (in ~/.m2/repository/):

cd promagent-framework
mvn clean install
cd ..

Compile the example agent. This should create the file ./promagent-example/target/promagent.jar:

cd promagent-example
mvn clean verify
cd ..

Spring Boot Demo

The following runs with Java 8 and was not tested with Java 9 yet.

Download and compile a Spring Boot Getting Started application.

git clone
cd gs-accessing-data-rest/complete
mvn clean package
cd ../..

Run the Spring Boot application with the Promagent attached.

java \
    -javaagent:promagent/promagent-example/target/promagent.jar=port=9300 \
    -jar gs-accessing-data-rest/complete/target/gs-accessing-data-rest-0.1.0.jar

Go to http://localhost:8080 to view the Spring Boot application, go to http://localhost:9300/metrics to view the Prometheus metrics.

Java EE Demo on Wildfly

This demo runs with Java 8. For a Java 9 version, see

Download and compile a Wildfly Quickstart application.

git clone
cd quickstart/kitchensink
mvn clean package
cd ../..

Download and extract the Wildfly application server.

curl -O
tar xfz wildfly-10.1.0.Final.tar.gz

Run the Wildfly application server with the Promagent attached.

cd wildfly-10.1.0.Final
LOGMANAGER_JAR=$(find $(pwd) -name 'jboss-logmanager-*.jar')
export JAVA_OPTS="

In a new Shell window, deploy the quickstart application.

cd wildfly-10.1.0.Final
./bin/ --connect --command="deploy ../quickstart/kitchensink/target/kitchensink.war"

Go to http://localhost:8080/kitchensink to view the quickstart application, go to http://localhost:9300/metrics to view the Prometheus metrics.

Creating your Own Agent

A Promagent is implemented as a set of Hooks. A Hook is a Java class meeting the following requirements:

  • The class is annotated with @Hook.
  • The class has a public constructor taking a single parameter of type MetricsStore.
  • The class provides methods annotated with @Before or @After. Those methods must take exactly the same parameters as the method you want to intercept (there is one exception to that rule: @Afer methods may have two additional parameters annotated with @Returned and @Thrown, see Hook Annotations below).

The best way to get started is to have a look at the ServletHook and JdbcHook in the promagent-example.

A simple Hook counting the number of Servlet requests looks as follows:

@Hook(instruments = "javax.servlet.Servlet")
public class ServletHook {

    private final Counter servletRequestsTotal;

        public ServletHook(MetricsStore metricsStore) {
            servletRequestsTotal = metricsStore.createOrGet(new MetricDef<>(
                    (name, registry) ->
                        .help("Total number of Servlet requests.")

        @After(method = "service")
        public void after(ServletRequest request, ServletResponse response) {

To build a Promagent project with Maven, you need two entries in the pom.xml. First, the promagent-api must be included as a dependency:

    <scope>provided</scope> <!-- provided at runtime by the internal agent implementation -->

Second, the promagent-maven-plugin that creates an agent JAR:


With these two things included, mvn clean package should produce a working Java agent in target/promagent.jar.

A Hook's Life Cycle

A Hook's lifecycle depends on whether the instrumented method call is a nested call or not. A call is nested when the method is called by another method that was instrumented with the same hook. This happens for example if a Servlet's service() method calls another Servlet's service() method.

By default, nested calls are ignored and the Hook is only invoked for the outer call. In the Servlet example, this is the intended behavior, because it guarantees that each HTTP request is counted only once, even even if a Servlet internally calls another Servlet to handle the request.

If the Hook is defined with @Hook(skipNestedCalls = false) the Hook will be invoked for all nested calls, not only for the outer call.

For each outer call, a new Hook instance is created. If the Hook implements both a @Before and an @After method, the same instance is used for @Before and @After. That way, you can set a start time as a member variable in the @Before method, and use it in the @After method to calculate the duration of the call.

For nested calls, the Hook instance from the outer call is re-used. That way, you can put data into member variables in order to pass that data down the call stack.

The Hook's Constructor Parameter

Most applications use static variables to maintain Prometheus metrics, as described in the Prometheus Client Library for Java documentation:

# Doesn't work with Promagent
static final Counter counter =
    .help("Total requests.")

Unfortunately, static variables are maintained per deployment in an application server. When an application is re-deployed, a new instance of the same Counter is created, which causes conflicts in the Prometheus registry (as the Prometheus registry is maintained by Promagent, it survives re-deployments). Moreover, it is impossible to instrument a mix of internal modules (like an internal Servlet in the JAX-RS implementation) and deployments (like Servlets in a WAR file) with static variables.

To prevent this, Promagent requires Hooks to use the MetricsStore to maintain metrics:

# This is the correct way with Promagent
Counter counter = metricsStore.createOrGet(new MetricDef<>(
                    (name, registry) ->
                        .help("Total requests.")

The Promagent library will take care that the Counter is created only once, and that the Counter instance is re-used across multiple deployments and internal modules in an application server.

Hook Annotations

  • @Hook: Hook classes are annotated with @Hook(instruments = {...}, skipNestedCalls = true). The instruments parameter takes a list of Strings specifying the names of the classes or interfaces to be instrumented, like {"javax.servlet.Servlet", "javax.servlet.Filter"}. The Hook instruments not only the classes or interfaces themselves, but all sub-classes or implementations of these classes or interfaces. The skipNestedCalls parameter is described in A Hook's Life Cycle above.
  • @Before: Hook methods annotated with @Before(method = {...}) are invoked when an instrumented method is entered. The method parameter takes a list of Strings specifying the names of the intercepted methods, like {"service", "doFilter"}. The number and types of arguments are derived from the method itself, i.e. the Hook method annotated with @Before must take the exact same parameters as the methods it wants to instrument.
  • @After: Hook methods annotated with @After(method = {...}) are invoked when an instrumented method is left. @After methods are always called, even if the instrumented method terminates with an Exception. The semantics is the same as with the @Before annotation. Methods annotated with @After may have two additional parameters, one parameter annotated with @Returned and one parameter annotated with @Thrown. These parameters are ignored when determining the signature of the instrumented method.
  • @Returned: It might be useful to learn the return value of an instrumented method. In order to do so, methods annotated with @After may have an additional parameter annotated with @Returned, where the type corresponds to the return type of the intercepted method. If the instrumented method returns regularly, the return value is provided. If the method returns exceptionally, null (or the default type for primitive types, like 0 for int) is provided. @Returned parameters are only allowed in @After methods, not in @Before methods.
  • @Thrown: The @Thrown annotation is like @Returned, but to learn an Exception thrown from an instrumented method. The type should be Throwable to avoid class cast errors on unexpected RuntimeExceptions or Errors. If the instrumented method does not throw an exception, the parameter annotated with @Thrown will be null.

Using Labels

The Prometheus server internally stores one time series for each observed set of label values. The time series database in the Prometheus server can easily handle thousands of different time series, but millions of different time series could be a problem. Therefore, it is important to keep the number of different label values relatively small. Unique user IDs, timestamps, or session keys should not be used as label values.

The promagent-example strips HTTP URLs and SQL queries to make sure that there are not too many different label values:

  • For HTTP requests, path parameters are replaced with placeholders. The goal is to use REST resources like /item/{id} as labels, not in actual paths like /item/123.
  • For SQL queries, values are stripped. The goal is to use the structure of the query like INSERT INTO ITEMS (ID, NAME, PRICE) VALUES (...) as a label, not in its values like INSERT INTO ITEMS (ID, NAME, PRICE) VALUES (23, 'abc', 17.5).

Of course, replacing path parameters and SQL values is application specific. The promagent-example implements a very simple replacement in ServletHook.stripPathParameters() and JdbcHook.stripValues(), but you probably need to customize these methods for your application.

Running Docker Tests

The promagent-example project contains an alternative Maven configuration in pom-with-docker-tests.xml. This configuration uses the docker-maven-plugin to create Docker images and run integration tests against Docker containers.

The Wildfly tests can be run as follows:

cd promagent-example
mvn -f pom-with-docker-tests.xml clean verify -Pwildfly
cd ..

The Spring Boot tests can be run as follows:

cd promagent-example
mvn -f pom-with-docker-tests.xml clean verify -Pspring
cd ..

The first run takes a while, because the Docker images need to be built. Once the images are available on the local systems, runs are significantly faster.

Exposing Metrics

Promagent supports three different ways of exposing metrics to the Prometheus server:

  • The agent has a built-in HTTP server. This is used in the examples above. The server is started when the command line argument port is used, as for example -javaagent:agent.jar=host=localhost,port=9300. The host argument is optional, it defaults to the wildcard IP address. If port is omitted the built-in server is not started.
  • The promagent-exporter module implements a simple Web application in WAR file format. If you deploy the promagent-framework/promagent-exporter/target/promagent.war on your server, it will collect Promagent metrics via JMX and expose them under its deployment URL, like http://localhost:8080/promagent.
  • All metrics are made available via JMX, so any JMX client can be used to access the metrics.


This is a demo project. The main goal is to learn the internals of bytecode manipulation and class loading in Java application servers. I am planning to work on the following:

  • Try it with more application servers (Payara, TomEE) and adjust the code if necessary.
  • Write documentation about the internal implementation, mainly the bytecode manipulation and class loading aspects.
  • Generalize the concept so that users can not only write Hooks, but also other collectors. A proof-of-concept is includes in the class JmxCollector in promagent-example.
  • Generalize the concept so we don't only support monitoring with Prometheus, but also tracing with OpenTracing API compatible tools.

The promagent-api and promagent-maven-plugin are not yet available on Maven Central, but they will be uploaded when the API becomes a bit more stable.

If you want to write your own agent and are looking for examples of methods you might want to instrument, look at related projects, like inspectIT (hooks are configured here) or stagemonitor.


Thank You ConSol

This project is supported as part of the R&D activities at ConSol Software GmbH. See the ConSol Labs Blog for more info.