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Atlassian Bitbucket Mesh Bitbucket Mesh


Bitbucket Data Center is an on-premises source code management solution for Git that's secure, fast, and enterprise grade. Create and manage repositories, set up fine-grained permissions, and collaborate on code - all with the flexibility of your servers.

Bitbucket Mesh is an optional scalability extension for Bitbucket. For more information see

This Docker image is published as atlassian/bitbucket-mesh.

This Docker container makes it easy to get Mesh nodes for a Bitbucket Data Center up and running. It will only work in conjunction with a Bitbucket Data Center server.

For full documentation on running Bitbucket Data Center with Mesh nodes, see the Bitbucket documentation.

If running this image in a production environment, we strongly recommend you run this image using a specific version tag instead of latest. This is because the image referenced by the latest tag changes often and we cannot guarantee that it will be backwards compatible.

Use docker version >= 20.10.10

Quick Start

For the MESH_HOME directory that is used to store the repository data (amongst other things) we recommend mounting a host directory as a data volume, or via a named volume.

Volume permissions are managed by entry scripts. To get started you can use a data volume, or named volumes. In this example we'll use named volumes.

docker volume create --name bitbucketMeshVolume
docker run -v bitbucketMeshVolume:/var/atlassian/application-data/mesh --name="bitbucket-mesh" -d -p 7777:7777 atlassian/bitbucket-mesh

Note that this command can substitute folder paths with named volumes.

Please ensure your container has the necessary resources allocated to it. We recommend 2GiB of memory allocated to accommodate both the application server and the git processes. See Supported Platforms for further information.

Common settings

Verbose container entrypoint logging

During the startup process of the container, various operations and checks are performed to ensure that the application is configured correctly and ready to run. To help in troubleshooting and to provide transparency into this process, you can enable verbose logging. The VERBOSE_LOGS environment variable enables detailed debug messages to the container's log, offering insights into the actions performed by the entrypoint script.

  • VERBOSE_LOGS (default: false)

Set to true to enable detailed debug messages during the container initialization.

Mesh Node Configuration


The home directory used by the Mesh node. This should have full read/write permissions and be persistent – your Bitbucket Mesh data will be stored here.

  • GRPC_SERVER_PORT (default: 7777)

The port used by the Mesh node to communicate with the server.

Mesh Node JVM Configuration

If you need to override the Mesh node's default memory configuration or pass additional JVM arguments, use the environment variables below

  • JVM_MINIMUM_MEMORY (default: 512m)

The minimum heap size of the JVM

  • JVM_MAXIMUM_MEMORY (default: 1024m)

The maximum heap size of the JVM


Additional JVM arguments for the Mesh node , such as a custom Java Trust Store

JMX Monitoring

JMX monitoring can be enabled with JMX_ENABLED=true. Information on additional settings and available metrics is available in the Bitbucket JMX documentation.

Other settings

As well as the above settings, all settings that are available in the file can also be provided via Docker environment variables. For a full explanation of converting Bitbucket properties into environment variables see the relevant Spring Boot documentation.

Container Configuration

  • SET_PERMISSIONS (default: true)

Define whether to set home directory permissions on startup. Set to false to disable this behaviour.

Home directory and user IDs

By default the Bitbucket application runs as the user bitbucket, with a UID and GID of 2003. If for some reason a different UID must be used, there are a number of options available:

  • The Docker image can be rebuilt with a different UID.
  • Under Linux, the UID can be remapped using user namespace remapping.


The Mesh node allows a configurable grace period for active operations to finish before termination; by default this is 30s. If sending a docker stop this should be taken into account with the --time flag.

Alternatively, the script / is provided, which will initiate a clean shutdown and wait for the process to complete. This is the recommended method for shutdown in environments which provide for orderly shutdown, e.g. Kubernetes via the preStop hook.


You should ensure you are running the appropriate Mesh version for your Bitbucket Data Center server. A support matrix is available here: Bitbucket Mesh compatibility matrix.

Supported JDK versions and base images

All the Atlassian Docker images are now JDK11 and JDK17 (since version 2.4) only, and generated from the official Eclipse Temurin OpenJDK Docker images.

Starting from 2.4 UBI based tags are published as well. UBI tags are available in 2 formats: <version>-ubi9 and <version>-ubi9-jdk17.

The Docker images follow the Atlassian Support end-of-life policy; images for unsupported versions of the products remain available but will no longer receive updates or fixes.

If for some reason you need a different version, see "Building your own image"

Migration to UBI

If you have been mounting any files to ${JAVA_HOME} directory in eclipse-temurin based container, JAVA_HOME in UBI JDK17 container is set to /usr/lib/jvm/java-17.

Also, if you have been mounting and running any custom scripts in the container, UBI-based images may lack some tools and utilities that are available out of the box in eclipse-temurin tags. If that's the case, see "Building your own image".

Building your own image

  • Clone the Atlassian repository at
  • Modify or replace the Jinja templates under config; NOTE: The files must have the .j2 extensions. However, you don't have to use template variables if you don't wish.
  • Build the new image with e.g: docker build --tag my-bitbucket-mesh-image --build-arg MESH_VERSION=1.x.x .
  • Optionally push to a registry, and deploy.

Supported architectures

Currently, the Atlassian Docker images are built for the linux/amd64 target platform; we do not have other architectures on our roadmap at this point. However the Dockerfiles and support tooling have now had all architecture-specific components removed, so if necessary it is possible to build images for any platform supported by Docker.

Building on the target architecture

The simplest method of getting a platform image is to build it on a target machine; see "Building your own image" above.

Note: This method is known to work on Mac M1 and AWS ARM64 machines, but has not be extensively tested.


These images include built-in scripts to assist in performing common JVM diagnostic tasks.

Thread dumps

/opt/atlassian/support/ can be run via docker exec to easily trigger the collection of thread dumps from the containerized application. For example:

docker exec my_container /opt/atlassian/support/

By default, this script will collect 10 thread dumps at 5 second intervals. This can be overridden by passing a custom value for the count and interval, by using -c / --count and -i / --interval respectively. For example, to collect 20 thread dumps at 3 second intervals:

docker exec my_container /opt/atlassian/support/ --count 20 --interval 3

Thread dumps will be written to $APP_HOME/thread_dumps/<date>.

Disable capturing output from top run

By default this script will also capture output from top run in 'Thread-mode'. This can be disabled by passing -n / --no-top

Heap dump

/opt/atlassian/support/ can be run via docker exec to easily trigger the collection of a heap dump from the containerized application. For example:

docker exec my_container /opt/atlassian/support/

A heap dump will be written to $APP_HOME/heap.bin. If a file already exists at this location, use -f / --force to overwrite the existing heap dump file.

Manual diagnostics

The jcmd utility is also included in these images and can be used by starting a bash shell in the running container:

docker exec -it my_container /bin/bash


For product support, go to

You can also visit the Atlassian Data Center forum for discussion on running Atlassian Data Center products in containers.


For a detailed list of changes to the Docker image configuration see the Git commit history.


Copyright © 2022 Atlassian Corporation Pty Ltd. Licensed under the Apache License, Version 2.0.