Zebra with Docker

The easiest way to run Zebra is using Docker.

We've embraced Docker in Zebra for most of the solution lifecycle, from development environments to CI (in our pipelines), and deployment to end users.

[!TIP] We recommend using docker compose sub-command over the plain docker CLI, especially for more advanced use-cases like running CI locally, as it provides a more convenient and powerful way to manage multi-container Docker applications. See CI/CD Local Testing for more information, and other compose files available in the docker folder.

Quick usage

You can deploy Zebra for daily use with the images available in Docker Hub or build it locally for testing.

Ready to use image

Using docker compose:

docker compose -f docker/docker-compose.yml up

With plain docker CLI:

docker volume create zebrad-cache

docker run -d --platform linux/amd64 \
  --restart unless-stopped \
  --env-file .env \
  --mount type=volume,source=zebrad-cache,target=/var/cache/zebrad-cache \
  -p 8233:8233 \
  --memory 16G \
  --cpus 4 \

Build it locally

git clone --depth 1 --branch v1.7.0 https://github.com/ZcashFoundation/zebra.git
docker build --file docker/Dockerfile --target runtime --tag zebra:local .
docker run --detach zebra:local


See Building Zebra for more information.

Advanced usage

You're able to specify various parameters when building or launching the Docker image, which are meant to be used by developers and CI pipelines. For example, specifying the Network where Zebra will run (Mainnet, Testnet, etc), or enabling features like metrics with Prometheus.

For example, if we'd like to enable metrics on the image, we'd build it using the following build-arg:

[!IMPORTANT] To fully use and display the metrics, you'll need to run a Prometheus and Grafana server, and configure it to scrape and visualize the metrics endpoint. This is explained in more detailed in the Metrics section of the User Guide.

docker build -f ./docker/Dockerfile --target runtime --build-arg FEATURES='default-release-binaries prometheus' --tag local/zebra.mining:latest .

To increase the log output we can optionally add these build-args:

--build-arg RUST_BACKTRACE=full --build-arg RUST_LOG=debug --build-arg COLORBT_SHOW_HIDDEN=1

And after our image has been built, we can run it on Mainnet with the following command, which will expose the metrics endpoint on port 9999 and force the logs to be colored:

docker run --env LOG_COLOR="true" -p 9999:9999 local/zebra.mining

Based on our actual entrypoint.sh script, the following configuration file will be generated (on the fly, at startup) and used by Zebra:

network = "Mainnet"
listen_addr = ""
cache_dir = "/var/cache/zebrad-cache"
endpoint_addr = ""

Running Zebra with Lightwalletd

To run Zebra with Lightwalletd, we recommend using the provided docker compose files for Zebra and Lightwalletd, which will start both services and connect them together, while exposing ports, mounting volumes, and setting environment variables.

docker compose -f docker/docker-compose.yml -f docker/docker-compose.lwd.yml up

CI/CD Local Testing

To run CI tests locally, which mimics the testing done in our CI pipelines on GitHub Actions, use the docker-compose.test.yml file. This setup allows for a consistent testing environment both locally and in CI.

Running Tests Locally

  1. Setting Environment Variables:

    • Modify the test.env file to set the desired test configurations.
    • For running all tests, set RUN_ALL_TESTS=1 in test.env.
  2. Starting the Test Environment:

    • Use Docker Compose to start the testing environment:

      docker-compose -f docker/docker-compose.test.yml up
    • This will start the Docker container and run the tests based on test.env settings.

  3. Viewing Test Output:

    • The test results and logs will be displayed in the terminal.
  4. Stopping the Environment:

    • Once testing is complete, stop the environment using:

      docker-compose -f docker/docker-compose.test.yml down

This approach ensures you can run the same tests locally that are run in CI, providing a robust way to validate changes before pushing to the repository.

Build and Run Time Configuration

Build Time Arguments


  • FEATURES: Specifies the features to build zebrad with. Example: "default-release-binaries getblocktemplate-rpcs"
  • TEST_FEATURES: Specifies the features for tests. Example: "lightwalletd-grpc-tests zebra-checkpoints"


  • RUST_LOG: Sets the trace log level. Example: "debug"
  • RUST_BACKTRACE: Enables or disables backtraces. Example: "full"
  • RUST_LIB_BACKTRACE: Enables or disables library backtraces. Example: 1
  • COLORBT_SHOW_HIDDEN: Enables or disables showing hidden backtraces. Example: 1


  • TEST_FEATURES: Specifies the features for tests. Example: "lightwalletd-grpc-tests zebra-checkpoints"
  • ZEBRA_SKIP_IPV6_TESTS: Skips IPv6 tests. Example: 1
  • ENTRYPOINT_FEATURES: Overrides the specific features used to run tests in entrypoint.sh. Example: "default-release-binaries lightwalletd-grpc-tests"


  • SHORT_SHA: Represents the short SHA of the commit. Example: "a1b2c3d"

Run Time Variables

  • NETWORK: Specifies the network type. Example: "Mainnet"

Zebra Configuration

  • ZEBRA_CHECKPOINT_SYNC: Enables or disables checkpoint sync. Example: true
  • ZEBRA_LISTEN_ADDR: Address for Zebra to listen on. Example: ""
  • ZEBRA_CACHED_STATE_DIR: Directory for cached state. Example: "/var/cache/zebrad-cache"

Mining Configuration

  • RPC_LISTEN_ADDR: Address for RPC to listen on. Example: ""
  • RPC_PORT: Port for RPC. Example: 8232
  • MINER_ADDRESS: Address for the miner. Example: "t1XhG6pT9xRqRQn3BHP7heUou1RuYrbcrCc"

Other Configuration

  • METRICS_ENDPOINT_ADDR: Address for metrics endpoint. Example: ""
  • METRICS_ENDPOINT_PORT: Port for metrics endpoint. Example: 9999
  • LOG_FILE: Path to the log file. Example: "/path/to/log/file.log"
  • LOG_COLOR: Enables or disables log color. Example: false
  • TRACING_ENDPOINT_ADDR: Address for tracing endpoint. Example: ""
  • TRACING_ENDPOINT_PORT: Port for tracing endpoint. Example: 3000

Specific tests are defined in docker/test.env file and can be enabled by setting the corresponding environment variable to 1.


The images built by the Zebra team are all publicly hosted. Old image versions meant to be used by our CI pipeline (zebrad-test, lighwalletd) might be deleted on a scheduled basis.

We use Docker Hub for end-user images and Google Artifact Registry to build external tools and test images.