pass -XepCompilingTestOnlyCode, and that argument needs to
                     be passed as part of the same <arg> as -Xplugin:ErrorProne,
                     and I gave up trying to figure out how to do that for test
                     compilation only. -->
                <arg>-Xplugin:ErrorProne -Xep:NullArgumentForNonNullParameter:OFF -Xep:Java8ApiChecker:ERROR</arg>

  # to work in an offline environment:
  # https://github.com/coredns/coredns/issues/2494#issuecomment-457215452
  # CoreDNS should handle those domains and answer with NXDOMAIN instead of SERVFAIL
  # otherwise pods stops trying to resolve the domain.
  if [ "${IP_FAMILY}" = "ipv6" ] || [ "${IP_FAMILY}" = "dual" ]; then
    # Get the current config
    original_coredns=$(kubectl get -oyaml -n=kube-system configmap/coredns)

// descriptions for all the error responses.
var errorCodes = errorCodeMap{
	ErrInvalidCopyDest: {
		Code:           "InvalidRequest",
		Description:    "This copy request is illegal because it is trying to copy an object to itself without changing the object's metadata, storage class, website redirect location or encryption attributes.",
		HTTPStatusCode: http.StatusBadRequest,
	},
	ErrInvalidCopySource: {

ifneq ($(findstring google,$(HOSTNAME)),)
warning+=Googlers: go/installdocker\#the-version-of-docker-thats-installed-is-old-eg-1126
endif
# The old docker issue manifests as not being able to run *any* binary. So we can test
# by trying to run a trivial program and ensuring it actually ran. If not, emit our warning.
# Note: we cannot do anything like $(shell docker version) to check, since that would also fail.
CAN_RUN := $(shell echo "can I run echo")

		for _, v := range vectors {
			b.Run(v.label, func(b *testing.B) {
				b.ReportAllocs()
				for i := 0; i < b.N; i++ {
					// Writing to io.Discard because we want to
					// test purely the writer code and not bring in disk performance into this.
					tw := NewWriter(io.Discard)
					for _, file := range v.files {
						if err := tw.WriteHeader(file.hdr); err != nil {
							b.Errorf("unexpected WriteHeader error: %v", err)
						}

	p.diskID.Store(&id)
}

func (p *xlStorageDiskIDCheck) checkDiskStale() error {
	if *p.diskID.Load() == emptyDiskID {
		// For empty disk-id we allow the call as the server might be
		// coming up and trying to read format.json or create format.json
		return nil
	}
	storedDiskID, err := p.storage.GetDiskID()
	if err != nil {
		// return any error generated while reading `format.json`
		return err
	}

It would take the same amount of time to finish with or without turns (concurrency) and you would have done the same amount of work.

But in this case, if you could bring the 8 ex-cashier/cooks/now-cleaners, and each one of them (plus you) could take a zone of the house to clean it, you could do all the work in **parallel**, with the extra help, and finish much sooner.

    tensorflow::ImmediateExecutionTensorHandle* unwrapped_handle =
        tensorflow::unwrap(handles[i]);
    if (tensorflow::CustomDeviceTensorHandle::classof(unwrapped_handle)) {
      // One of the inputs we're trying to pack is on a custom device. We'll let
      // the first custom device we see handle all of the packing.
      auto* custom_device_handle =
          tensorflow::down_cast<tensorflow::CustomDeviceTensorHandle*>(

      "certChain": []
    },
    {
      "identity": "spiffe://cluster.local/ns/istio-system/sa/istiod",
      "state": "Unavailable: signing gRPC error (The service is currently unavailable): error trying to connect: TLS handshake failed: cert verification failed - unable to get local issuer certificate [CERTIFICATE_VERIFY_FAILED]",
      "certChain": []
    }
  ]

So, if your application consumes a lot of memory (for example with machine learning models), and your server has a lot of CPU cores **but little memory**, then your container could end up trying to use more memory than what is available, and degrading performance a lot (or even crashing). 🚨

### Create a `Dockerfile`

Here's how you would create a `Dockerfile` based on this image:

```Dockerfile