// - replicated size for all objects sent to this target
// - replica size for all objects received from this target
// - replication pending size for all objects pending replication to this target
// - replication failed size for all objects failed replication to this target
// - replica pending count
// - replica failed count
type BucketTargetUsageInfo struct {
	ReplicationPendingSize  uint64 `json:"objectsPendingReplicationTotalSize"`

			b.updateXferRate(rs.TransferSize, rs.TransferDuration)
		}
	case rs.Failed:
		b.FailStats.addsize(rs.TransferSize, rs.Err)
	case rs.Pending:
	}
}

type replStat struct {
	Arn       string
	Completed bool
	Pending   bool
	Failed    bool
	opType    replication.Type
	// transfer size
	TransferSize int64
	// transfer duration
	TransferDuration time.Duration

    }

    protected abstract String doBuildColumnString(String dm);

    @Override
    public String toStringWithRelation() { // #pending
        return toString();
    }

    @Override
    public String buildDisplayString(String name, boolean column, boolean relation) { // #pending
        return toString();
    }

    // ===================================================================================

MinIO is built ground up on the cloud-native premise. With features like erasure-coding, distributed and shared setup, it focuses only on storage and does it very well. While, it can be scaled by just replicating MinIO instances per tenant via an orchestration platform.

    }

    protected abstract String doBuildColumnString(String dm);

    @Override
    public String toStringWithRelation() { // #pending
        return toString();
    }

    @Override
    public String buildDisplayString(String name, boolean column, boolean relation) { // #pending
        return toString();
    }

    // ===================================================================================

        return facadeSelectList(createCB(cbLambda));
    }

    public PagingResultBean<LabelType> selectPage(CBCall<LabelTypeCB> cbLambda) {
        // #pending same?
        return (PagingResultBean<LabelType>) facadeSelectList(createCB(cbLambda));
    }

    public void selectCursor(CBCall<LabelTypeCB> cbLambda, EntityRowHandler<LabelType> entityLambda) {

        return facadeSelectList(createCB(cbLambda));
    }

    public PagingResultBean<SearchLog> selectPage(CBCall<SearchLogCB> cbLambda) {
        // #pending same?
        return (PagingResultBean<SearchLog>) facadeSelectList(createCB(cbLambda));
    }

    public void selectCursor(CBCall<SearchLogCB> cbLambda, EntityRowHandler<SearchLog> entityLambda) {

        return facadeSelectList(createCB(cbLambda));
    }

    public PagingResultBean<CrawlingInfo> selectPage(CBCall<CrawlingInfoCB> cbLambda) {
        // #pending same?
        return (PagingResultBean<CrawlingInfo>) facadeSelectList(createCB(cbLambda));
    }

    public void selectCursor(CBCall<CrawlingInfoCB> cbLambda, EntityRowHandler<CrawlingInfo> entityLambda) {

    public ListResultBean<Role> selectList(CBCall<RoleCB> cbLambda) {
        return facadeSelectList(createCB(cbLambda));
    }

    public PagingResultBean<Role> selectPage(CBCall<RoleCB> cbLambda) {
        // #pending same?
        return (PagingResultBean<Role>) facadeSelectList(createCB(cbLambda));
    }

    public void selectCursor(CBCall<RoleCB> cbLambda, EntityRowHandler<Role> entityLambda) {

TensorFlow in a multitenant design mixes the risks described above with the
inherent ones from multitenant configurations. The primary areas of concern are
tenant isolation, resource allocation, model sharing and hardware attacks.

### Tenant isolation

Since any tenants or users providing models, graphs or checkpoints can execute
code in context of the TensorFlow service, it is important to design isolation