Remote worker

This program implements a remote execution worker that uses gRPC to accept work requests. It can work as a remote execution worker, a cache worker, or both. The simplest setup is as follows:

First build remote_worker and run it.

  bazel build src/tools/remote_worker:all
  bazel-bin/src/tools/remote_worker/remote_worker \
      --work_path=/tmp/test \
      --listen_port=8080

Then you run Bazel pointing to the remote_worker instance.

  bazel --host_jvm_args=-Dbazel.DigestFunction=SHA1 build \
      --spawn_strategy=remote --remote_cache=localhost:8080 \
      --remote_executor=localhost:8080 src/tools/generate_workspace:all

The above command will build generate_workspace with remote spawn strategy that uses the local worker as the distributed caching and execution backend.

Sandboxing

If you run the remote_worker on Linux, you can also enable sandboxing for increased hermeticity:

    bazel-bin/src/tools/remote_worker/remote_worker \
        --work_path=/tmp/test \
        --listen_port=8080 \
        --sandboxing \
        --sandboxing_writable_path=/run/shm \
        --sandboxing_tmpfs_dir=/tmp \
        --sandboxing_block_network

As you can see, the specific behavior of the sandbox can be tuned via the flags

--sandboxing_writable_path= makes a path writable for running actions.
--sandboxing_tmpfs_dir= will mount a fresh, empty tmpfs for each running action on a path.
--sandboxing_block_network will put each running action into its own network namespace that has no network connectivity except for its own “localhost”. Note that due to a Linux kernel issue this might result in a loss of performance if you run many actions in parallel. For long running tests it probably won't matter much, though.

Hazelcast caching

You can also use a Hazelcast server for the distributed cache as follows: Suppose your Hazelcast server is listening on address:port. Then, run the remote worker with --hazelcast_node=address:port.