params(name)
            params("${providedBy.size + 1}")
        }
    }

    /**
     * For all modules providing a capability, always use the preferred module, even if there's no conflict.
     * In other words, will forcefully upgrade all modules providing a capability to a selected module.
     *
     * @param to the preferred module
     */
    private

  # addresses and ports, so that they can be used for advanced filtering
  # and manipulation.
  # The "TPROXY" mode also configures the sidecar to run with the
  # CAP_NET_ADMIN capability, which is required to use TPROXY.
  #interceptionMode: REDIRECT
  #
  # Port where Envoy listens (on local host) for admin commands
  # You can exec into the istio-proxy container in a pod and

  // +optional
  optional bool privileged = 1;

  // defaultAddCapabilities is the default set of capabilities that will be added to the container
  // unless the pod spec specifically drops the capability.  You may not list a capability in both
  // defaultAddCapabilities and requiredDropCapabilities. Capabilities added here are implicitly
  // allowed, and need not be included in the allowedCapabilities list.
  // +optional

        'you want to build with.\nYou can find the compute capability of your '
        'device at: https://developer.nvidia.com/cuda-gpus. Each capability '
        'can be specified as "x.y" or "compute_xy" to include both virtual and'
        ' binary GPU code, or as "sm_xy" to only include the binary '
        'code.\nPlease note that each additional compute capability '

Each GKE cluster's will have many categories of logs collected by Stackdriver.  Logs can be monitored via
the project's [log viewer](https://cloud.google.com/logging/docs/view/overview) and/or the `gcloud logging read`
capability.

The following example grabs the last 10 `kubelet` logs containing the string "cmdAdd" in the log message.

```console

 * We need to look at Maven, and Nexus as use cases and figure out what each of them needs to be
 * able to do
 *
 * - now what is really the difference between this and loading a component in plexus - custom
 * classloading capability - remote resolution of dependencies - do we want a model for sharing
 * information among plugins, is this more like an extension point - do we need a sort of bus for

# This is the same as the official TensorFlow builds.
# See https://developer.nvidia.com/cuda-gpus#compute
# `compute_XY` enables PTX embedding in addition to SASS. PTX
# is forward compatible beyond the current compute capability major
# release while SASS is only forward compatible inside the current
# major release. Example: sm_80 kernels can run on sm_89 GPUs but
# not on sm_90 GPUs. compute_80 kernels though can also run on sm_90 GPUs.

### SIG Scalability

SIG Scalability has mostly focused on stability and deflaking our tests, investing into framework for writing scalability tests (ClusterLoader v2) with a goal to migrate all tests to it by the end of 2018 and on the work towards extending definition of Kubernetes scalability by providing more/better user-friendly SLIs/SLOs.

### SIG Scheduling

  EXPECT_EQ(4, product[1]);
  EXPECT_EQ(6, product[2]);
  EXPECT_EQ(8, product[3]);

  // When we turn on grappler, confirm that the tf.Add has been rewritten into a
  // tf.Mul.
  // This capability of checking the executed op names is currently only enabled
  // for TFRT debug build, for performance and simplicity reasons.
  if (use_tfrt) {
    TF_Buffer* buf = TF_NewBuffer();

### SIG Scalability

[SIG Scalability][] is responsible for scalability testing, measuring and
improving system performance, and answering questions related to scalability.

For the 1.8 release, SIG Scalability focused on automating large cluster
scalability testing in a continuous integration (CI) environment. The SIG
defined a concrete process for scalability testing, created