Release 1.11.0-rc0

Major Features and Improvements

Prometheus exporter for TF metrics (see https://github.com/tensorflow/serving/commit/021efbd3281aa815cab0b35eab6d6d25249c12d4 for details).
Added new REST API to get status of model(s) from ModelServer.

Built against TensorFlow 1.11.0-rc0.
Directly import tensor.proto.h (the transitive import will be removed from tensor.h soon)
Building optimized TensorFlow Serving binaries is now easier (see docs for details)
Adds columnar format support for input/output tensors in Predict REST API (fixes #1047)
Development Dockerfiles now produce a more optimized ModelServer
Fixed TensorFlow Serving API PyPi package overwriting TensorFlow package.

TensorFlow Serving API now uses gRPC's GA release. The beta gRPC API has been deprecated, and will be removed in a future version of TensorFlow Serving. Please update your gRPC client code (sample)
Docker images for GPU are built against NCCL 2.2, in following with Tensorflow 1.10.

Built against TensorFlow 1.10.
Added GPU serving Docker image.
Repo cloning and shell prompt in example readme.
Updated Docker instructions.
Updated min Bazel version (0.15.0).
Convert TF_CHECK_OKs to TF_ASSERT_OK in some unit tests.
Remove error suppression (.IgnoreError()) from BasicManager.
Add new bazel_in_docker.sh tool for doing hermetic bazel builds.
Fix erroneous formatting of numbers in REST API output that are larger than 6 digits.
Add support for Python 3 while also compatible with Python 2.7 in mnist_saved_model.py.
Fix an incorrect link to Dockerfile.devel-gpu.
Add util for get model status.
Adding support for secure channel to ModelServer.
Add version output to model server binary.
Change ServerRequestLogger::Update to only create new and delete old loggers if needed.
Have the Model Server interpret specific hard-coded model version labels "stable" and "canary" as the smallest and largest version#, respectively.
Add half_plus_two CPU and GPU models to test data.

Initial release of TensorFlow Serving.