* gigantic heap, in which case we scale by heap size.
   */
  private static long timeoutSeconds() {
    // This class can make no hard guarantees.  The methods in this class are inherently flaky, but
    // we try hard to make them robust in practice.  We could additionally try to add in a system
    // load timeout multiplier.  Or we could try to use a CPU time bound instead of wall clock time

	NilPodAffinity PodAffinityKind = iota
	// PodAffinityWithRequiredReq applies a HARD requirement to pod.spec.affinity.PodAffinity.
	PodAffinityWithRequiredReq
	// PodAffinityWithPreferredReq applies a SOFT requirement to pod.spec.affinity.PodAffinity.
	PodAffinityWithPreferredReq
	// PodAffinityWithRequiredPreferredReq applies HARD and SOFT requirements to pod.spec.affinity.PodAffinity.
	PodAffinityWithRequiredPreferredReq

// This just makes it easier to catch all actions that has a name; instead of hard-coding all request that has it associated
type actionWithName interface {
	core.Action
	GetName() string
}

// actionWithObject is the generic interface for an action that has an object associated with it
// This just makes it easier to catch all actions that has an object; instead of hard-coding all request that has it associated
type actionWithObject interface {

== Symbolic links

When using symbolic links, Gradle does not store the link in the build cache but the actual file contents of the destination of the link.
As a consequence you might have a hard time when trying to reuse outputs which heavily use symbolic links.
There currently is no workaround for this behavior.

    public Iterable<Node> getAllSuccessors() {
        return getHardSuccessors();
    }

    /**
     * Returns all the nodes which are hard successors, i.e. which have a non-removable relationship to the current node.
     *
     * For example, for tasks `shouldRunAfter` isn't a hard successor while `mustRunAfter` is.
     */
    @OverridingMethodsMustInvokeSuper
    public Iterable<Node> getHardSuccessors() {

   * gigantic heap, in which case we scale by heap size.
   */
  private static long timeoutSeconds() {
    // This class can make no hard guarantees.  The methods in this class are inherently flaky, but
    // we try hard to make them robust in practice.  We could additionally try to add in a system
    // load timeout multiplier.  Or we could try to use a CPU time bound instead of wall clock time

			pod.Labels,
			v1.DoNotSchedule,
		)
		if err != nil {
			return nil, fmt.Errorf("obtaining pod's hard topology spread constraints: %w", err)
		}
	} else {
		constraints, err = pl.buildDefaultConstraints(pod, v1.DoNotSchedule)
		if err != nil {
			return nil, fmt.Errorf("setting default hard topology spread constraints: %w", err)
		}
	}
	return constraints, nil
}

it is not yet clear this is desired.

### Performance

Compared to a perfectly optimized hand-written controller, `krt` adds some overhead.
However, writing a perfectly optimized controller is hard, and often not done.
As a result, for many scenarios it is expected that `krt` will perform on-par or better.

	MOVW	code+0(FP), R0
	MOVW	$SYS_exit_group, R7
	SWI	$0
	MOVW	$1234, R0
	MOVW	$1002, R1
	MOVW	R0, (R1)	// fail hard

TEXT exit1<>(SB),NOSPLIT|NOFRAME,$0
	MOVW	code+0(FP), R0
	MOVW	$SYS_exit, R7
	SWI	$0
	MOVW	$1234, R0
	MOVW	$1003, R1
	MOVW	R0, (R1)	// fail hard

// func exitThread(wait *atomic.Uint32)
TEXT runtime·exitThread(SB),NOSPLIT|NOFRAME,$0-4
	MOVW	wait+0(FP), R0

		" fnID:", fnID, " numCtrs:", nCtrs)
	println("list of hard-coded runtime package IDs needs revising.")
	println("[see the comment on the 'rtPkgs' var in ")
	println(" <goroot>/src/internal/coverage/pkid.go]")
	println("registered list:")
	for k, b := range metaList {
		print("slot: ", k, " path='", b.PkgPath, "' ")
		if b.PkgID != -1 {
			print(" hard-coded id: ", b.PkgID)
		}
		println("")
	}