Bazel builds that succeed locally may fail when executed remotely due to restrictions and requirements that do not affect local builds. The most common causes of such failures are described in Adapting Bazel Rules for Remote Execution.
This document describes how to identify and resolve the most common issues that arise with remote execution using the Docker sandbox feature, which imposes restrictions upon the build equal to those of remote execution. This allows you to troubleshoot your build without the need for a remote execution service.
The Docker sandbox feature mimics the restrictions of remote execution as follows:
Build actions execute in toolchain containers. You can use the same toolchain containers to run your build locally and remotely via a service supporting containerized remote execution.
No extraneous data crosses the container boundary. Only explicitly declared inputs and outputs enter and leave the container, and only after the associated build action successfully completes.
Each action executes in a fresh container. A new, unique container is created for each spawned build action.
Note: Builds take noticeably more time to complete when the Docker sandbox feature is enabled. This is normal.
You can troubleshoot these issues using one of the following methods:
Troubleshooting natively. With this method, Bazel and its build actions run natively on your local machine. The Docker sandbox feature imposes restrictions upon the build equal to those of remote execution. However, this method will not detect local tools, states, and data leaking into your build, which will cause problems with remote execution.
Troubleshooting in a Docker container. With this method, Bazel and its build actions run inside a Docker container, which allows you to detect tools, states, and data leaking from the local machine into the build in addition to imposing restrictions equal to those of remote execution. This method provides insight into your build even if portions of the build are failing. This method is experimental and not officially supported.
Before you begin troubleshooting, do the following if you have not already done so:
WORKSPACE file as described here..bazelrc file to enable the feature. Create the file in the root directory of your Bazel project if it does not exist. Flags below are a reference sample. Please see the latest .bazelrc file in the bazel-toolchains repo and copy the values of the flags defined there for config docker-sandbox.# Docker Sandbox Mode build:docker-sandbox --host_javabase=<...> build:docker-sandbox --javabase=<...> build:docker-sandbox --crosstool_top=<...> build:docker-sandbox --experimental_docker_image=<...> build:docker-sandbox --spawn_strategy=docker --strategy=Javac=docker --genrule_strategy=docker build:docker-sandbox --define=EXECUTOR=remote build:docker-sandbox --experimental_docker_verbose build:docker-sandbox --experimental_enable_docker_sandbox
Note: The flags referenced in the .bazelrc file shown above are configured to run within the rbe-ubuntu16-04 container.
If your rules require additional tools, do the following:
Create a custom Docker container by installing tools using a Dockerfile and building the image locally.
Replace the value of the --experimental_docker_image flag above with the name of your custom container image.
This method executes Bazel and all of its build actions directly on the local machine and is a reliable way to confirm whether your build will succeed when executed remotely.
However, with this method, locally installed tools, binaries, and data may leak into into your build, especially if it uses configure-style WORKSPACE rules. Such leaks will cause problems with remote execution; to detect them, troubleshoot in a Docker container in addition to troubleshooting natively.
Add the --config=docker-sandbox flag to the Bazel command that executes your build. For example:
bazel --bazelrc=.bazelrc build --config=docker-sandbox <target>
Run the build and wait for it to complete. The build will run up to four times slower than normal due to the Docker sandbox feature.
You may encounter the following error:
ERROR: 'docker' is an invalid value for docker spawn strategy.
If you do, run the build again with the --experimental_docker_verbose flag. This flag enables verbose error messages. This error is typically caused by a faulty Docker installation or lack of permissions to execute it under the current user account. See the Docker documentation for more information. If problems persist, skip ahead to Troubleshooting in a Docker container.
The following are the most commonly encountered issues and their workarounds.
A file, tool, binary, or resource referenced by the Bazel runfiles tree is missing.. Confirm that all dependencies of the affected targets have been explicitly declared. See Managing implicit dependencies for more information.
A file, tool, binary, or resource referenced by an absolute path or the PATH variable is missing. Confirm that all required tools are installed within the toolchain container and use toolchain rules to properly declare dependencies pointing to the missing resource. See Invoking build tools through toolchain rules for more information.
A binary execution fails. One of the build rules is referencing a binary incompatible with the execution environment (the Docker container). See Managing platform-dependent binaries for more information. If you cannot resolve the issue, contact bazel-discuss@google.com for help.
A file from @local-jdk is missing or causing errors. The Java binaries on your local machine are leaking into the build while being incompatible with it. Use java_toolchain in your rules and targets instead of @local_jdk. Contact bazel-discuss@google.com if you need further help.
Other errors. Contact bazel-discuss@google.com for help.
With this method, Bazel runs inside a host Docker container, and Bazel's build actions execute inside individual toolchain containers spawned by the Docker sandbox feature. The sandbox spawns a brand new toolchain container for each build action and only one action executes in each toolchain container.
This method provides more granular control of tools installed in the host environment. By separating the execution of the build from the execution of its build actions and keeping the installed tooling to a minimum, you can verify whether your build has any dependencies on the local execution environment.
Note: The commands below are tailored specifically for a debian:stretch base. For other bases, modify them as necessary.
Create a Dockerfile that creates the Docker container and installs Bazel with a minimal set of build tools:
FROM debian:stretch RUN apt-get update && apt-get install -y apt-transport-https curl software-properties-common git gcc gnupg2 g++ openjdk-8-jdk-headless python-dev zip wget vim RUN curl -fsSL https://download.docker.com/linux/debian/gpg | apt-key add - RUN add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/debian $(lsb_release -cs) stable" RUN apt-get update && apt-get install -y docker-ce RUN wget https://releases.bazel.build/<latest Bazel version>/release/bazel-<latest Bazel version>-installer-linux-x86_64.sh -O ./bazel-installer.sh && chmod 755 ./bazel-installer.sh RUN ./bazel-installer.sh
Build the container as bazel_container:
docker build -t bazel_container - < Dockerfile
Start the Docker container using the command shown below. In the command, substitute the path to the source code on your host that you want to build.
docker run -it \ -v /var/run/docker.sock:/var/run/docker.sock \ -v /tmp:/tmp \ -v <your source code directory>:/src \ -w /src \ bazel_container \ /bin/bash
This command runs the container as root, mapping the docker socket, and mounting the /tmp directory. This allows Bazel to spawn other Docker containers and to use directories under /tmp to share files with those containers. Your source code is available at /src inside the container.
The command intentionally starts from a debian:stretch base container that includes binaries incompatible with the rbe-ubuntu16-04 container used as a toolchain container. If binaries from the local environment are leaking into the toolchain container, they will cause build errors.
Run the following commands from inside the Docker container to test it:
docker ps bazel version
Run the build as shown below. The output user is root so that it corresponds to a directory that is accessible with the same absolute path from inside the host container in which Bazel runs, from the toolchain containers spawned by the Docker sandbox feature in which Bazel's build actions are running, and from the local machine on which the host and action containers run.
bazel --output_user_root=/tmp/bazel_docker_root --bazelrc=.bazelrc \ build --config=docker-sandbox <target>
You can resolve build failures as follows:
If the build fails with an “out of disk space” error, you can increase this limit by starting the host container with the flag --memory=XX where XX is the allocated disk space in gigabytes. This is experimental and may result in unpredictable behavior.
If the build fails during the analysis or loading phases, one or more of your build rules declared in the WORKSPACE file are not compatible with remote execution. See Adapting Bazel Rules for Remote Execution for possible causes and workarounds.
If the build fails for any other reason, see the troubleshooting steps in Step 2: Resolve detected issues.