Automatic Let’s Encrypt Certificates with Apache Tomcat / Spring Boot


I implemented a solution for fetching and renewing TLS certs without restart via Let’s Encrypt that works with standalone and embedded Tomcat as well as Spring Boot. It’s packaged into a Docker image, allowing for easy reuse. The certs are fetched and renewed using dehydrated, a bash script with few dependencies. This makes the TLS requesting agnostic to the application or framework in use,  as long as the application is shipped as a Docker image. The downside is, that it’s not a plain Java solution, i.e. it requires an additional process (within the container) and a Linux environment.

Having used cloud-native products like Caddy, Traefik, CertManager or Micronaut that naturally obtain and renew Let’s Encrypt certificates for HTTPS communication, I wondered if there is an easy way to use a feature such as this in a web server as long-established as Apache Tomcat. You might say: Tomcat usually  is used behind reverse proxies that do all the TLS offloading. But then there’s something like the Apache Portable Runtime (APR) based Native library for Tomcat that brings the heart of the Apache Web Server to Tomcat as a system library and with it it’s high TLS performance, that might even outperform NGINX. So obviously, this should be possible.

Surprisingly, I couldn’t find a solution with batteries included. So, let’s quickly implement our own. How hard can it be?

Dehydrated tomcat

Presenting: letsencrypt-tomcat – it packs everything needed for automatic TLS with tomcat into a single docker image:

  • dehydrated to manage certs via Let’s Encrypt,
  • tomcat-reloading-connector for hot reloading certs at runtime after renewal,
  • an init system (dumb-init) for properly handling tomcat and dehydrated processes,
  • an entrypoint script that starts up tomcat and dehydrated as well as
  • a pre-compiled version of Apache Portable Runtime (APR) and JNI wrappers for APR used by Tomcat (libtcnative), so tomcat delivers the best TLS performance possible.

This sounds like a lot of complicated stuff, but as the examples bellow will show, it’s rather easy to use. If you care about the details, check the “Challenges” bellow.

From the image everything can be copied as needed in the actual application’s Dockerfile. It’s not intended to as a base image (“inheritance”), but as a mere file archive to copy everything from a single source.


The way to use depends on the tomcat “kind” in use: standalone, embedded Tomcat orSpring Boot (which also uses embedded tomcat under the hood).

There’s one thing the setup for all kinds have in common: you pass the FQDN as environment variable DOMAIN to the container at startup, e.g. with docker run -e <image>

If necessary more parameters (optional) are available.

The remaining setup depends on the kind of tomcat used.

Sprint Boot

  • pom.xml or build.gradle: Add tomcat-reloading-connector to your dependencies (example)
  • Dockefile:
    • Copy /letsencrypt and /lib folder to the root (/) of your application’s docker image (example),
    • Set ENTRYPOINT or CMD to execute / and pass the usual command for starting your spring boot app as parameter, for example:
      ENTRYPOINT [ "/", "java", "-jar", "/app/app.jar" ]
  • or .yaml (example):
    • Configure Tomcat to serve Let’s Encrypt challenges: spring.resources.staticLocations=file:/static
    • Configure paths for certificate files: server.ssl.certificateKeyFile, etc.
    • Serve both HTTP and HTTPS ports
  • In the code that creates your Spring Boot app: Setup tomcat-reloading-connector: @Import(ReloadingTomcatServletWebServerFactory.class) (complete example)

Embedded tomcat

  • pom.xml or build.gradle: Add tomcat-reloading-connector to your dependencies (example)
  • Dockefile:
    • Copy /letsencrypt and /lib folder to the root (/) of your application’s docker image (example),
    • Set ENTRYPOINT or CMD to execute / and pass the usual command for starting your app as parameter, for example:
      ENTRYPOINT [ "/", "java", "-jar", "-Dcatalina.home=/tmp", "/app/app.jar" ]
  • In the code that creates embedded tomcat:
    • Configure Tomcat to serve Let’s Encrypt challenges (example)
    • Use tomcat-reloading-connector and configure paths for certificate files: ReloadingTomcatConnectorFactory.addHttpsConnector(tomcat, HTTPS_PORT, PK, CRT, CA); (complete example)

Standalone tomcat

  • Dockefile:
    • copy the following to the root (/) of your application’s docker image (example):
      • /letsencryptfolder,
      • tomcat-reloading-connector and
      • (if necessary) /lib folder (already included in bitnami-tomcat used in our example) ,
    • Make standalone tomcat serve Let’s Encrypt challenges (example)
  • server.xml:
    • Use tomcat-reloading-connector (example)
    • Configure paths for certificate files (example)

Real-world example

My use case for using this whole thing is my git-based wiki smeagol-galore, which relies on letsencrypt-tomcat. It already had a quite complex startup process, so I decided here to not use the meta-entrypoint but to copy the parts needed into the existing entrypoint.


Now that we have seen working examples, it’s a good time to sum up technical challenges and decisions encountered within the process. Turns out the whole indeavor had more challenges than expected.

Choosing an ACME implementation

As of 09/2020 there doesn’t seem to be a drop-in web app for tomcat or a spring boot annotation that just handles the ACME protocol used by Let’s encrypt for us.

There are Java libraries that promise to help achieving this, most prominently acme4j. But looking at the docs or this tutorial the whole process seems rather complicated. There’s the spring-boot-starter-acme which seems be able to get a cert. To use the cert, we have to restart the server, though. It also does not renew, is still a SNAPSHOT and hasn’t been updates for some years.

A completely different alternative would be to use the certbot client. But then it brings it’s own server, which would require our application to stop and start again, once certbot has finished renewing the cert.

This is where dehydrated comes in handy: it implements the whole ACME protocol used by Let’s encrypt, in a single bash script with no other dependencies than bash, curl and OpenSSL. It’s also easy to use and does not bring it’s own webserver. That’s good, because we already have a webserver: Tomcat.

How to best integrate a bash script and a tomcat process into a single artifact? Why not use an OCI (a.k.a. Docker) image? Two processes in one container? But doesn’t this violate the “one process per container” mantra?
I’m convinced that if there are good reasons for it, why not use two coherent processes in one container? We might even start chaning the mantra to “one thing per container“. The fact that there a multiple popular init systems for Docker images makes me think that I’m not the only one holding this opinion.

So let’s combine tomcat with dehydrated within a Docker container.

Integrating Tomcat and Dehydrated

The basic idea is:

  • Tomcat starts,
  • Dehydrated starts the certificate signing process via Let’s Encrypt,
  • serves the challenge via Tomcat, then
  • downloads the certificate, so that finally
  • Tomcat can server the certificate.
  • Once a day, Dehydrates checks again if the certs must be renewed.

This results in two “interfaces” between Tomcat and Dehydrated:

  • the folder where Dehydrated places the challenges must be served by Tomcat at http://$DOMAIN/.well-known/acme-challenge/and
  • the cert files, written by Dehydrated and read by Tomcat.

Depending on the kind of Tomcat, configuring the cert files and making Tomcat serve the the challenge folder on the HTTP port requires a different setup (see “Usage” above).

Self-signed cert

Once this is done, let’s start Tomcat. Only it does not start without certificate. But we need it started, in order to answer Let’s Encrypt’s challenge.
Who was first, the chicken or the egg?

One solution: create a self-signed cert at startup (see With a validity of 30 days or less, dehydrated will try to renew the cert right away.

Synchronize startup of Tomcat and Dehydrated

Tomcat might get its HTTP ports ready to serve traffic in a matter of seconds but, depending on the application, it could als take minutes. The latter resulting in Dehydrated failing to get the the certificate from Let’s Encrypt. Solution: Poll the HTTP port, waiting for a succesfull HTTP status code.

PEM vs KeyStore

With Tomcat’s default Java implementation of HTTPS (Http11NioProtocol) we would also have issues with the certificate file formats, because it requires a Java Keystore, whereas Let’s Encrypt provides private key, certificate and CA as PEM. However, we are using APR (Http11AprProtocol), which also requires PEM. So it just works™️.

Reloading the certificate

Believe it or now: At this point we have a valid certificate. Only that Tomcat still serves the old self-signed one.

Next stop, how to make Tomcat reload the cert? Tomcat 9.x (might even have been backported to 8.5) provides an AbstractHttp11Protocol.reloadSslHostConfigs() method. But how to call it?
Dehydrated offers a hook for calling “something” after success.  But how to call this method inside Tomcat from a shell script? JMX? Or via an URL request on Tomcat Manager web app? These solution would all require configuration, increase complexity and might even impair security.

The other option is to call the method from within Tomcat, by implementing our own protocol class. It could regularly check and reload the certificate on change. But then polling is just a waste of resources and it will always take longer than something that is called on change.
Other idea: Set a file watch. For better reuse, maintainance and separation of concerns, I implemented this in a separate project, tomcat-reloading-connector (too late I figured out that “tomcat-reloading-protocol” would be a better fit 🙈 ) and published it on maven central. While implementing, I came to the realization that reloading “the certificate” should be an atomic operation, containing all certificate-related files. After all, what I refer to as “the certificate” above, actually consists of a number of files, like private key, cert and CA. Reloading only one file might result in an inconsistent state. In order to avoid this, I added a reload delay of a few seconds. A changing file within the folder of the certificate results in all SSLHostConfigs being reloaded a couple of seconds later. Still not perfect, as the delay is a compromise between a fast reload and an inconsistent SSLHostConfig. For starters, let’s stick with it. For Dehydrated 3s seemed fine from my empirical studies. If it does not work for you, just define what ever suits your needs via the TOMCAT_DELAY_RELOAD_CERTIFICATES_MILLIS environment variable.


Creating a dehydrated Tomcat wasn’t straightforward. The most laborious task being the reload of the certificate, resulting in a separate project: tomcat-reloading-connector.

With letsencrypt-tomcat most of the work has been done, allowing for rather easy reuse. However, for each project, there still is some bootstrapping to be done. A 3rd party solution such as this can never compete with built-in support for Let’s Encrypt as offered by other products. On the other hand there now is a reliable solution that can run on all kinds of Tomcats be it standalone or embedded, even with Spring Boot.

Future work

That’s all for now. As always, there some work is still to be done for the curios reader.

Getting letsencrypt-tomcat to work wit Let’s Encrypt’s TLS-ALPN-01 challenge would be useful to get rid of the HTTP port. It generally is supported by Dehydrated but might be challengin to realize using Tomcat.

One issue with relying on a custom Dockerfile for creating the artifact is that it does not work intuitively with Cloud Native Build Packs. Spring Boot 2.3 comes with built-in support for building OCI images without Dockerfile. How can we integrate this with letsencrypt-tomcat? It should be possible to just add another layer, and adapt the entrypoint.

Short comparison: Building Graal Native Images with Quarkus, Micronaut and Helidon

The technological innovations of the last years such as the adoption of containers, cloud-native technologies, the microservice architectural style, the inception of GraalVM and the end of JavaEE (as we know it) has energized the Java framework market.

As of May 2019, there are at least three frameworks supporting GraalVM native images out of the box, targeting cloud-native microservices:

  • Quarkus,
  • Micronaut and
  • Helidon.

As building GraalVM native images is a bit challenging, I was curious to find out how these three frameworks keep up with their promises. I worked through the respective getting started guides and wrote down some similarities and differences resulting in this short (and surely incomplete) comparison of the three frameworks. See the following table for an overview.

General comparison

Quarkus Micronaut Helidon
Core Project Source quarkusio/quarkus micronaut-projects/micronaut-core oracle/helidon
Started/Backed By RedHat objectcomputing Oracle
First Commit 2018-06-22 2017-03-06 2018-08-28
GitHub Stars (05/2019) 1693 2283 1371
GitHub Contributers (05/2019) 88 120 26
# Commits (05/2019) 3970 5907 617
Supported languages Java, Kotlin Java, Groovy, Kotlin Java
Supported build tools mvn, Gradle mvn, Gradle mvn
Supported APIs for graal native Microprofile, vert.x,


Micronaut, ReactiveX/RxJava Helidon SE (Microprofile, without native image)
Programming paradigms for graal native Imperative, reactive Reactive, imperative? Reactive (imperative, without native image)
Code generation via mvn plugin CLI (mn) mvn archetype
Getting Started (Graal native) Guide Docs Blog
Resulting src of Getting Started schnatterer/quarkus-getting-started schnatterer/micronaut-getting-started schnatterer/helidon-getting-started
Size of getting started docker image
Getting started base docker image fedora-minimal alpine-glibc scratch
Getting started uses native image? N N Y
Size of getting started in scratch docker image

All three projects are rather young (grandpa Micronaut is about 2 years old as of 05/2019) but have what looks like extensive documentation at first glance. The only thing that made my stumble a bit was that Helidon’s docs don’t return a result for “graal”. I later found a brand new getting started with graal on oracle’s developers blog. Hopefully, this will be added to the docs soon.

There are a couple of notable differences between the three frameworks:

    • Programming style (reactive vs. imperative)
      • Quarkus explicitly supports both (reactive as an extension),
      • Helidon claims to support both, but only reactive in conjunction with native images right now
      • Micronaut is reactive only From the docs it seems that micronaut focuses on reactive, but blocking approaches are supported (see Graeme Rocher’s comment).
    • Language
      • Micronaut and Quarkus both support Java and Kotlin.
        Micronaut also supports Groovy 🎉 (having Graeme Rocher, the creator of Grails, on board it’s probably a must)
      • Helidon only supports Java
    • Build tool / code generation
      • Micronaut and Quarkus support Maven and Gradle.
        • Quarkus uses a Maven plugin for code generation (bad luck for Gradle users) whereas
        • Micronaut brings its own CLI tool that thankfully can easily be installed using sdkman.
      • Helidon supports only Maven and has only initial code generation support via a Maven archetype.
    • Kubernetes
    • Community
      Hard to tell. The amount of discussions on my tweet about Quarkus makes me think they’re the ones that are most interested in feedback and people getting involved.

GraalVM native Image / Docker Image

  • The Dockerfiles provided by the getting started of Quarkus and Micronaut each require an external Maven build.
    The images base on fedora-minimal (resulting in a 44MB compressed image) or alpine-glibc (resulting in a 32MB compressed image) respectively.
    A base image containing a libc is required because the native image is linked dynamically.
  • Helidon provides a proper self-contained Dockerfile that can be built by simply calling docker build, not requiring anything locally (except Docker, of course).
    Here, the native image is linked statically. Therefore the binary can run in an empty scratch image (resulting in an 8MB compressed image).

Bearing in mind that a Java 8 JRE Image requires about 100MB (debian) or 50 MB (alpine), 44MB or even 32MB for a small webapp is not so bad. OTOH the 8 MB for the statically linked image are a real revelation, leaving me stunned.

The fact that Helidon plays well with GraalVM shouldn’t be too surprising, as they both are official Oracle products.

Beyond getting started

As Quarkus was the first framework I tried, I wondered why they rely on fedora and not just compile a static binary (later, I learned about some of their reasons on twitter). So I tried a couple of other images, eventually setting the switch for creating a static binary and using a scratch image. Voilà: It results in a 7MB image, even a wee bit smaller than the Helidon one. See the table bellow for an overview of images and their features and sizes (taken from the README of my getting started repo).

Base Image Size Shell Package Manager libc Basic Linux Folders Static Binary Dockerfile
fedora 📄
debian 📄
alpine-glibc 📄
distroless-base 📄
busybox 📄
distroless-static 📄
scratch 📄

I applied more or less the same on Micronaut. Here, the scratch image is only 5 MB smaller than the alpine one – 27 MB. This is not too surprising, because the plain alpine-glibc image is only about 6MB. It also felt like the native image generation took longer and needed more memory (observed with docker stats).

As for Helidon’s self-contained, scratch image containing only a static binary, there was not much to be done. I only extend the Dockerfile by a maven cache stage for faster Docker builds.

There’s one last thing I changed in all Dockerfiles: Don’t run as root. I used the USER statement in the Dockerfile. docker run -u ... would also be fine. This way, it’s much more unlikely that possible vulnerabilities (such as CVE-2019-5736 in runc) are exploited.

So summing up: Quarkus and Helidon can be used to create really small docker images, Micronauts are “only” small 😉. It’s worth mentioning that I didn’t look what features are included in those images, so maybe it’s a bit naive to just compare the minimal sizes resulting from the individual getting started guides.

Going even further

If I were to continue my comparison at this point (which I won’t because it’s only a short comparison) I would look into the following features of each framework:

  • integration and unit testing,
  • extensions (e.g. Cloud Native features, Tracing, Monitoring, etc.)


So, for a new green field project, which one of e frameworks would I use?

As far as I can tell after completing the getting started, all three look promising. As for all architectural decisions, I’d definitely try to build a walking skeleton (technical roundtrip) before finally deciding, in order to gain more field experience and find out what’s beyond getting started.

I’d base this decision on the experience or preferences of the team

  • reactive vs. imperative
  • Maven vs. Gradle
  • Java vs. Kotlin (or even groovy)
  • APIs – Microprofile, vert.x, RxJava

Personally, I like the fact that Quarkus builds on existing APIs such as Microprofile, so existing experience can be reused for faster results. It also seems to me the most flexible of the three, supporting Java, Kotlin, Maven, Gradle, reactive and imperative.

As for native images, I’d definitely either try it from the beginning or stick to a regular JRE. I suppose switching from plain JRE-based to native could be complicated for an existing app, due to the native image limitations. If the app under development does not have the requirement to be scaled horizontally, this could be an argument for skipping the native image part. But this is beyond the scope of this article.

As for the docker image – it’s obviously not only the size that matters. An image without shell and package manager is always more secure but harder to debug.



  • 2019/05/17: John Clingan pointed out that Quarkus supports Kubernetes resource generation an multiple reactive extensions
  • 2019/05/19: As commentef by Graeme Rocher’s, Micronaut also supports blocking workloads

The pragmatic migration to JUnit 5

This article shows how get from JUnit 3.x / 4.x to JUnit 5.x as fast as possible.

Just a short clarification of the term “JUnit 5” (from the user guide) before we take off:

JUnit 5 = JUnit Platform + JUnit Jupiter + JUnit Vintage


  • Platform provides the Maven and Gradle Plugins and is the extension point for IDE integration,
  • Vintage contains legacy JUnit 4 API and engine,
  • Jupiter contains the new JUnit 5 API and engine.

Step 1 – Run existing tests with JUnit 5 vintage

The first thing we do is to replace the existing junit:junit depedency with the following


For Gradle see this article.

For a real world example see this commit.

Note: After upgrading fromjunit:junit:4.12 to org.junit.vintage:junit-vintage-engine:5.1.0 the execution order of @Rule seems to have changed: They seem to be now executed sequentially (from top to bottom, as defined in the test class).

Step 2 – Getting started with JUnit Jupiter and the Platform

Now lets go from vintage to the fancy new stuff. Just add the Jupiter dependency and empower surefire to use the JUnit platform:


	<!-- ... -->

Make sure to juse either surefire 2.19.1 or 2.21.0+, as there seem to be a bug in the versions in between.

As above, for Gradle see this article.

For a real world example see this commit.

As of now, we’re ready to write new tests with JUnit Jupiter.

Here’s a pragmatic aproach how to introduce JUnit 5 from here:

  • Use the new API and all the new features for new test classes.
  • Don’t try to migrate all existing tests. It causes a lot of effort with no direct business value.
  • Instead, apply the boyscout rule by gradually migrating existing tests before they need to be changed.

When getting started wiht JUnit Jupiter you will recognize that some familiar features of JUnit now have a new API or can be achieved using different concepts. After that, there are a some new features to explore.

One way to get accustomed to the new API and concrepts is to migrate some (not all) existing tests, preferably the most complex ones. This way, you will find out how to use the new concepts and which limitations there still might be about JUnit Jupiter (e.g JUnit 4 rules that have not been ported to extensions).

Step 3 – Get accustomted to the API changes in JUnit Jupiter

There are some simple API changes but also two major concept changes: Rules and Runners are gone.

Simple API changes

  • public modifier can be removed (class and methods)
  • org.junit.Test➡️ org.junit.jupiter.api.Test
  • org.junit.Assert.assertX ➡️ org.junit.jupiter.api.Assertions.assertX
    (except assertThat)
  • Order of parameters changed in assert methods. The message parameter is now after expected and actual parameters! This can be a pitfall when migrating, because the message (strings) might silently turn to expected, if you just change the import.
  • assertThat is no longer part of the JUnit API. Instead, just use your favorite assertion library as AssertJ, Google truth or even hamcrest.
  • @Before ➡️ @BeforeEach
  • @After ➡️ @AfterEach
  • @BeforeClass ➡️ @BeforeAll
  • @AfterClass ➡️ @AfterAll
  • @Ignore ➡️ @Disabled
  • @Category ➡️ @Tag

For a real world example see this commit.

Make sure to not mix the APIs, because the tests are either run by the Jupiter or the vintage Engine, which will ignore unknown annotations.

Note that IntellI has a quick fix for migrating JUnit 4 to JUnit Jupiter. However, as of version 2018.1 this seems to only affect @Test, no asserts, exceptions, rules or runners.

Advanced API changes

Basically, Runners and Rules are replaced by Extensions, where one test class can have more than one extension.
However, some Runners have not been ported to Extensions, yet. For those you can try to use@EnableRuleMigrationSupport (see Temporary Folders). If this does not work, you will have to stick with the JUnit 4 API and vintage Engine for now.

Exceptions & Timeouts

Exceptions no longer need a Rule or the expected param in @Test. Instead, the API provides an assert mechanism now.

ExpectedException and @Test(expected = Exception.class) ➡️ assertThrows(Exception.class,() -> method());

For a real world example see this commit.

The same applies to timeouts:

@Test(timeout = 1) ➡️ assertTimeout(Duration.ofMillis(1), () ->method());


Instead of the mockito runner, we use the new extension, which comes in a separate module.


@RunWith(MockitoJUnitRunner.class) ➡️ @ExtendWith(MockitoExtension.class)

For a real world example see this commit.

Temporary Folders

Until there is an Extension, we can use @EnableRuleMigrationSupport from this module:


With this we can use the new API (org.junit.jupiter.api.Test). Howerver, rules and classes must stay public. ClassRules seem not to work.

For a real world example see this commit.

Other Rules

Here are some more rules and their equivalent in JUnit Jupiter.

  • @RunWith(SpringJUnit4ClassRunner.class) ➡️ @ExtendWith(SpringExtension.class)
  • stefanbirkner/system-rules, such as ExpectedSystemExit
    Work in progress! That is, these tests will have remain on the JUnit 4 APIs for now.
  • TestLoggerFactoryResetRule from slf4j-test
    No progress to be seen.
    Could be replaced by logback-spike. For a real world example see this commit.
  • Of course this list is non-exhaustive, there are a lot more runners I have not stumbled upon, yet.

Step 4 – Make use of new features in JUnit Jupiter

Just using the same features with different API is boring, right?
JUnit Jupiter offers some long-awaited features that we should make use of!
Here are some examples:

Optional: Further Reading