var (
	memTotalMD     = NewGaugeMD(memTotal, "Total memory on the node")
	memUsedMD      = NewGaugeMD(memUsed, "Used memory on the node")
	memUsedPercMD  = NewGaugeMD(memUsedPerc, "Used memory percentage on the node")
	memFreeMD      = NewGaugeMD(memFree, "Free memory on the node")
	memBuffersMD   = NewGaugeMD(memBuffers, "Buffers memory on the node")
	memCacheMD     = NewGaugeMD(memCache, "Cache memory on the node")

   * 2^n}, its memory usage is only {@code O(n)}. When the power set is constructed, the input set
   * is merely copied. Only as the power set is iterated are the individual subsets created, and
   * these subsets themselves occupy only a small constant amount of memory.
   *
   * @param set the set of elements to construct a power set from

	rootAccess                  bool
	syncEvents                  bool
	objectMaxVersions           int64
}

const (
	cgroupV1MemLimitFile = "/sys/fs/cgroup/memory/memory.limit_in_bytes"
	cgroupV2MemLimitFile = "/sys/fs/cgroup/memory.max"
	cgroupMemNoLimit     = 9223372036854771712
)

func cgroupMemLimit() (limit uint64) {
	buf, err := os.ReadFile(cgroupV2MemLimitFile)
	if err != nil {

### Memory per Process

Now, when the program loads things in memory, for example, a machine learning model in a variable, or the contents of a large file in a variable, all that **consumes a bit of the memory (RAM)** of the server.

 *       <i>deeply</i> immutable.
 * </ul>
 *
 * <h4>Performance notes</h4>
 *
 * <ul>
 *   <li>Implementations can be generally assumed to prioritize memory efficiency, then speed of
 *       access, and lastly speed of creation.
 *   <li>The {@code copyOf} methods will sometimes recognize that the actual copy operation is

 *       <i>deeply</i> immutable.
 * </ul>
 *
 * <h4>Performance notes</h4>
 *
 * <ul>
 *   <li>Implementations can be generally assumed to prioritize memory efficiency, then speed of
 *       access, and lastly speed of creation.
 *   <li>The {@code copyOf} methods will sometimes recognize that the actual copy operation is

* Restarts
* Replication (the number of processes running)
* Memory
* Previous steps before starting

## Memory

If you run **a single process per container** you will have a more or less well-defined, stable, and limited amount of memory consumed by each of those containers (more than one if they are replicated).

		return err
	}

	// Goroutine to periodically save batch-expire job's in-memory state
	saverQuitCh := make(chan struct{})
	go func() {
		saveTicker := time.NewTicker(10 * time.Second)
		defer saveTicker.Stop()
		for {
			select {
			case <-saveTicker.C:
				// persist in-memory state to disk after every 10secs.
				batchLogIf(ctx, ri.updateAfter(ctx, api, 10*time.Second, job))

			case <-ctx.Done():

      startupProbe:
        enabled: true
        failureThreshold: 600 # 10 minutes
      # Resources for the sidecar.
      resources:
        requests:
          cpu: 100m
          memory: 128Mi
        limits:
          cpu: 2000m
          memory: 1024Mi

All Go pointers passed to C must point to pinned Go memory. Go pointers
passed as function arguments to C functions have the memory they point to
implicitly pinned for the duration of the call. Go memory reachable from
these function arguments must be pinned as long as the C code has access
to it. Whether Go memory is pinned is a dynamic property of that memory
region; it has nothing to do with the type of the pointer.