assertThat("Thu, 01 Jan 1970 00:00:00 PST".toHttpDateOrNull()!!.time).isEqualTo(28800000L)
    // Ignore trailing junk
    assertThat("Thu, 01 Jan 1970 00:00:00 GMT JUNK".toHttpDateOrNull()!!.time).isEqualTo(0L)
    // Missing timezones treated as bad.
    assertThat("Thu, 01 Jan 1970 00:00:00".toHttpDateOrNull()).isNull()
    // Missing seconds treated as bad.
    assertThat("Thu, 01 Jan 1970 00:00 GMT".toHttpDateOrNull()).isNull()

                duration.entries
                    .filter { (key, _) -> key != "testProject" }
                    .map { (osString, timeInMs) ->
                        val os = Os.valueOf(osString.uppercase(Locale.US))
                        val performanceTestDuration = PerformanceTestDuration(scenario, timeInMs as Int)
                        os to (testProject to performanceTestDuration)
                    }
            }
        }

## How the configuration works

We use Kotlin portable DSL to store TeamCity configuration, which means you can easily create a new pipeline
based on a specific branch. Currently, we have two pipelines: `master` and `release`, but you can easily create
and test another isolated pipeline from any branch. 

We'll explain everything via an example. Let's say you make some changes on your branch `myTestBranch`

		./pkg/bootstrap/... \
		./pkg/kube/inject/... \
		./pilot/pkg/security/authz/builder/... \
		./cni/pkg/plugin/...

update-golden: refresh-goldens

# Keep dummy target since some build pipelines depend on this
gen-charts:
	@echo "This target is no longer required and will be removed in the future"

gen-addons:
	manifests/addons/gen.sh

gen: \
	mod-download-go \
	go-gen \

            }));
            return list;
        });
    }

    public boolean update(final String index, final String id, final String field, final Object value) {
        // Using ingest pipelines with doc_as_upsert is not supported.
        if (usePipeline) {
            return updateByIdWithScript(index, id, field, value);
        }
        try {

    `self_adjoint_eig` or `self_adjoint_eigvals`.
*   Eliminated `batch_*` methods for most linear algebra and FFT ops and
    promoted the non-batch version of the ops to handle batches of matrices.
*   Tracing/timeline support for distributed runtime (no GPU profiler yet).
*   C API gives access to inferred shapes with `TF_GraphGetTensorNumDims` and
    `TF_GraphGetTensorShape`.
*   Shape functions for core ops have moved to C++ via

### Structured Logging in Kubelet

Kubelet has adopted structured logging, thanks to community effort in accomplishing this within the release timeline. Structured logging in the project remains an ongoing effort -- for folks interested in participating, [keep an eye / chime in to the mailing list discussion](https://groups.google.com/g/kubernetes-dev/c/y4WIw-ntUR8).