The code below creates artificial resource usage, useful for reproducing threshold alerts

generate_load.py

import time
import math
import multiprocessing
from argparse import ArgumentParser

def generate_cpu_load(interval, utilization):
    "Generate a utilization % for a duration of interval seconds"
    start_time = time.time()
    for i in range(0, int(interval)):
        while time.time() - start_time < utilization / 100.0:
            a = math.sqrt(64 * 64 * 64 * 64 * 64)
        time.sleep(1 - utilization / 100.0)
        start_time += 1

if __name__ == '__main__':
    parser = ArgumentParser()
    parser.add_argument('--interval', type=int, default=60) # Default interval 60s
    parser.add_argument('--cpu', type=int, default=80) # Default to 80% CPU
    parser.add_argument('--memory', type=int, default=2048) # Default to 2GB
    args = parser.parse_args()

    buffer = bytearray(1024 * 1024 * args.memory)

    processes = []
    for _ in range(multiprocessing.cpu_count()):
        p = multiprocessing.Process(target=generate_cpu_load, args=(args.interval, args.cpu))
        p.start()
        processes.append(p)
    for process in processes:
        process.join()

Usage example for running for 30 seconds, with the process consuming around 90% CPU, and 2GBs of memory:

python generate_load.py --interval 30 --cpu 90 --memory 2048

load_generator.mp4