{
    "_peak_memory": 5.32,
    "_peak_process_memory": "PID\tMEM\tCOMMAND\n186\t1.61GiB\t/home/ray/anaconda3/lib/python3.7/site-packages/ray/core/src/ray/gcs/gcs_server --log_dir=/tmp/ray/s\n2169\t0.88GiB\tpython distributed/test_many_actors.py\n211\t0.26GiB\t/home/ray/anaconda3/bin/python -u /home/ray/anaconda3/lib/python3.7/site-packages/ray/dashboard/dash\n294\t0.12GiB\t/home/ray/anaconda3/bin/python -u /home/ray/anaconda3/lib/python3.7/site-packages/ray/dashboard/agen\n76\t0.11GiB\t/home/ray/anaconda3/bin/python /home/ray/anaconda3/bin/anyscale session web_terminal_server --deploy\n404\t0.11GiB\t/home/ray/anaconda3/bin/python /home/ray/anaconda3/bin/anyscale session auth_start\n2214\t0.06GiB\tray::MemoryMonitorActor.run()\n77\t0.05GiB\t/home/ray/anaconda3/bin/python /home/ray/anaconda3/bin/jupyter-notebook --NotebookApp.token=63d80251\n204\t0.05GiB\t/home/ray/anaconda3/bin/python -m ray.util.client.server --address=172.31.80.251:9031 --host=0.0.0.0\n244\t0.05GiB\t/home/ray/anaconda3/bin/python -u /home/ray/anaconda3/lib/python3.7/site-packages/ray/_private/log_m",
    "actors_per_second": 321.72392004133843,
    "num_actors": 10000,
    "perf_metrics": [
        {
            "perf_metric_name": "actors_per_second",
            "perf_metric_type": "THROUGHPUT",
            "perf_metric_value": 321.72392004133843
        }
    ],
    "success": "1",
    "time": 31.082550525665283
}