triggerflow/tests/autoscaling_test.py at master · cloudbutton/triggerflow · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139

import json
import time
from confluent_kafka import Producer
from concurrent.futures import ThreadPoolExecutor as Pool

TOPIC = 'pywren{}-kafka-eventsource'
active_workflows = {}


def publish_events():

    config = {'bootstrap.servers': '192.168.5.35:9092'}

    def delivery_callback(err, msg):
        return
        if err:
            print('Failed delivery: {}'.format(err))
        else:
            print('Message delivered: {} {} {}'.format(msg.topic(), msg.partition(), msg.offset()))

    def generate_events(i):
        global active_workflows
        n_events = 30
        active_workflows[i] = time.time()
        kafka_producer = Producer(**config)

        for _ in range(n_events):
            termination_event = {'source': 'kafka_test', 'subject': 'map_{}'.format(i),
                                 'type': 'termination.event.success', 'data': '"test"'}
            kafka_producer.produce(topic=TOPIC.format(i),
                                   value=json.dumps(termination_event),
                                   callback=delivery_callback)
            kafka_producer.flush()
            time.sleep(5)

        if i >= 30:
            del active_workflows[i]
            return

        time.sleep(60)

        for _ in range(n_events):
            termination_event = {'source': 'kafka_test', 'subject': 'map_{}'.format(i),
                                 'type': 'termination.event.success', 'data': '"test"'}
            kafka_producer.produce(topic=TOPIC.format(i),
                                   value=json.dumps(termination_event),
                                   callback=delivery_callback)
            kafka_producer.flush()
            time.sleep(3)

        del active_workflows[i]

    def generate_events_2(i):
        global active_workflows
        n_events = 10
        active_workflows[i] = time.time()
        kafka_producer = Producer(**config)

        for _ in range(n_events):
            termination_event = {'source': 'kafka_test', 'subject': 'map_{}'.format(i),
                                 'type': 'termination.event.success', 'data': '"test"'}
            kafka_producer.produce(topic=TOPIC.format(i),
                                   value=json.dumps(termination_event),
                                   callback=delivery_callback)
            kafka_producer.flush()
            time.sleep(5)

        if i > 55:
            del active_workflows[i]
            return

        time.sleep(30)

        for _ in range(n_events):
            termination_event = {'source': 'kafka_test', 'subject': 'map_{}'.format(i),
                                 'type': 'termination.event.success', 'data': '"test"'}
            kafka_producer.produce(topic=TOPIC.format(i),
                                   value=json.dumps(termination_event),
                                   callback=delivery_callback)
            kafka_producer.flush()
            time.sleep(5)

        del active_workflows[i]

    def generate_events_3(i):
        global active_workflows
        n_events = 20
        active_workflows[i] = time.time()
        kafka_producer = Producer(**config)

        for _ in range(n_events):
            termination_event = {'source': 'kafka_test', 'subject': 'map_{}'.format(i),
                                 'type': 'termination.event.success', 'data': '"test"'}
            kafka_producer.produce(topic=TOPIC.format(i),
                                   value=json.dumps(termination_event),
                                   callback=delivery_callback)
            kafka_producer.flush()
            time.sleep(5)

        time.sleep(44)

        for _ in range(n_events):
            termination_event = {'source': 'kafka_test', 'subject': 'map_{}'.format(i),
                                 'type': 'termination.event.success', 'data': '"test"'}
            kafka_producer.produce(topic=TOPIC.format(i),
                                   value=json.dumps(termination_event),
                                   callback=delivery_callback)
            kafka_producer.flush()
            time.sleep(5)

        del active_workflows[i]

    def monitor():
        while True:
            print("[{}, {}],".format(int(time.time()), len(active_workflows)))
            time.sleep(1)

    with Pool(max_workers=128) as executor:
        executor.submit(monitor)
        for i in range(50):
            executor.submit(generate_events, i)
            time.sleep(0.5)

        time.sleep(100)

        for i in range(35, 85):
            executor.submit(generate_events_2, i)
            time.sleep(0.3)

        time.sleep(70)

        for i in range(85, 99):
            executor.submit(generate_events_3, i)
            time.sleep(0.3)


if __name__ == '__main__':
    publish_events()