* 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.

* 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).

					success = false
				} else {
					stopFn(oi, nil)
				}
				ri.trackCurrentBucketObject(r.Target.Bucket, oi, success)
				globalBatchJobsMetrics.save(job.ID, ri)
				// persist in-memory state to disk after every 10secs.
				batchLogIf(ctx, ri.updateAfter(ctx, api, 10*time.Second, job))

				if wait := globalBatchConfig.ReplicationWait(); wait > 0 {
					time.Sleep(wait)
				}
			}()
		}
		wk.Wait()

| `minio_system_memory_total`      | `gauge` | Total memory on the node           | `server` |
| `minio_system_memory_buffers`    | `gauge` | Buffers memory on the node         | `server` |
| `minio_system_memory_cache`      | `gauge` | Cache memory on the node           | `server` |
| `minio_system_memory_shared`     | `gauge` | Shared memory on the node          | `server` |

        {{- end }}
        resources:
          limits:
            cpu: "2"
            memory: 1Gi
          requests:
            cpu: 100m
            memory: 128Mi
        startupProbe:
          failureThreshold: 30
          httpGet:
            path: /healthz/ready
            port: 15021
            scheme: HTTP

## Composition by architecture modules

Each [architecture module and platform](platforms.md) can contribute code to any of the runtimes.
Not every module contributes to every runtime.

The core-runtime module defines each runtime:

- The target JVM for the runtime. Each runtime has its own JVM compatibility constraints.

            value: "{{ $.Values.global.multiCluster.clusterName | default `Kubernetes` }}"
          - name: GOMEMLIMIT
            valueFrom:
              resourceFieldRef:
                resource: limits.memory
          - name: GOMAXPROCS
            valueFrom:
              resourceFieldRef:
                resource: limits.cpu
          - name: PLATFORM
            value: "{{ .Values.global.platform }}"

## Composition by architecture modules

Each [architecture module and platform](platforms.md) can contribute code to any of the elements.
Not every module contributes to every element.