},
	}

	// Iterating over the cases, fetching the object validating the response.
	for i, testCase := range testCases {
		// initialize HTTP NewRecorder, this records any mutations to response writer inside the handler.
		rec := httptest.NewRecorder()
		// construct HTTP request for Get Object end point.
		req, err := newTestSignedRequestV4(http.MethodHead, getHeadObjectURL("", testCase.bucketName, testCase.objectName),

	HostProbeSNATIPV6 = netip.MustParseAddr(env.RegisterStringVar("HOST_PROBE_SNAT_IPV6", DefaultHostProbeSNATIPV6, "").Get())
)

const (
	// to reliably identify kubelet healthprobes from inside the pod (versus standard kube-proxy traffic,
	// since the IP is normally the same), we SNAT identified host probes in the host netns to a fixed
	// APIPA/"link-local" IP.
	//

  /*
   * If we make these calls inline inside toImmutableSortedMultiset, we get an Animal Sniffer error,
   * despite the @IgnoreJRERequirement annotation there. My assumption is that, because javac
   * generates a synthetic method for the body of the lambda, the actual method calls that Animal
   * Sniffer is flagging don't appear inside toImmutableSortedMultiset but rather inside that

	if err != nil {
		return nil, fmt.Errorf("error configuring iptables: %w", err)
	}

	// Create hostprobe rules now, in the host netns
	// Later we will reuse this same configurator inside the pod netns for adding other rules
	iptablesConfigurator.DeleteHostRules()

	if err := iptablesConfigurator.CreateHostRulesForHealthChecks(&HostProbeSNATIP, &HostProbeSNATIPV6); err != nil {

	}

	return openNetns, nil
}

// AddPodToMesh adds a pod to mesh by
// 1. Getting the netns
// 2. Adding the pod's IPs to the hostnetns ipsets for node probe checks
// 3. Creating iptables rules inside the pod's netns
// 4. Notifying ztunnel via GRPC to create a proxy for the pod
//
// You may ask why we pass the pod IPs separately from the pod manifest itself (which contains the pod IPs as a field)

## Privileges required

    *   `conversion_params` is now deprecated inside `TrtGraphConverterV2` in
        favor of direct arguments: `max_workspace_size_bytes`, `precision_mode`,
        `minimum_segment_size`, `maximum_cached_engines`, `use_calibration` and
        `allow_build_at_runtime`.
    *   Added a new parameter called `save_gpu_specific_engines` to the
        `.save()` function inside `TrtGraphConverterV2`. When `False`, the

			ModTime: st.ModTime(),
		})
	}
	return stat, nil
}

// CleanAbandonedData will read metadata of the object on disk
// and delete any data directories and inline data that isn't referenced in metadata.
// Metadata itself is not modified, only inline data.
func (s *xlStorage) CleanAbandonedData(ctx context.Context, volume string, path string) error {
	if volume == "" || path == "" {
		return nil // Ignore
	}

		}

		written, err := erasure.Decode(ctx, writer, readers, partOffset, partLength, partSize, prefer)
		// Note: we should not be defer'ing the following closeBitrotReaders() call as
		// we are inside a for loop i.e if we use defer, we would accumulate a lot of open files by the time
		// we return from this function.
		closeBitrotReaders(readers)
		if err != nil {

If you used to rely on this behavior, now you should create the resources for background tasks inside the background task itself, and use internally only data that doesn't depend on the resources of dependencies with `yield`.