A D Vishnu Prasad

Director of Cloud Engineering @ Team8Solutions, Freelancer

Locust in Kubernetes for Performance Testing: A Powerful Combination

Performance testing ensures your applications gracefully handle the anticipated—and even the unanticipated—demands of real-world use. Locust, an open-source load testing framework, and Kubernetes, a container orchestration system, offer a potent mix for streamlining and scaling your performance testing efforts.

Why Locust?

Python Power: Locust uses Python to define user behavior, making test creation intuitive and flexible. If you can code it, Locust can simulate it.

Distributed Testing: Effortlessly simulate massive numbers of concurrent users by running Locust in a distributed mode.

Elegant Web UI: Monitor your tests in real-time, gain deep insights into performance metrics, and identify bottlenecks thanks to Locust’s user-friendly interface.

Why Kubernetes?

Scalability: Seamlessly provision and manage the resources your Locust deployment needs. Spin up workers as required and scale down when testing is complete.

Resilience: Kubernetes protects your test environment. If a worker node goes down, it automatically restarts pods, minimizing test disruption.

Portability: Replicate your Locust test infrastructure across different environments (testing, staging, production) with ease.

Locust UI

Step 1 : Create kubernetes manifests

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
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
---
apiVersion: v1
kind: ConfigMap
metadata:
  name: locust-script-cm
data:
  locustfile.py: |
    from locust import HttpUser, between, task
    import time


    class Quickstart(HttpUser):
        wait_time = between(1, 5)

        @task
        def google(self):
            self.client.request_name = "google"
            self.client.get("https://google.com/")

        @task
        def microsoft(self):
            self.client.request_name = "microsoft"
            self.client.get("https://microsoft.com/")

        @task
        def facebook(self):
            self.client.request_name = "facebook"
            self.client.get("https://facebook.com/")
---
apiVersion: apps/v1
kind: Deployment
metadata:
  annotations:
    deployment.kubernetes.io/revision: "1"
  labels:
    role: locust-master
    app: locust-master
  name: locust-master
spec:
  replicas: 1
  selector:
    matchLabels:
      role: locust-master
      app: locust-master
  strategy:
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 1
    type: RollingUpdate
  template:
    metadata:
      labels:
        role: locust-master
        app: locust-master
    spec:
      containers:
      - image: locustio/locust
        imagePullPolicy: Always
        name: master
        args: ["--master"]
        volumeMounts:
          - mountPath: /home/locust
            name: locust-scripts
        ports:
        - containerPort: 5557
          name: bind
        - containerPort: 5558
          name: bind-1
        - containerPort: 8089
          name: web-ui
        resources: {}
        terminationMessagePath: /dev/termination-log
        terminationMessagePolicy: File
      dnsPolicy: ClusterFirst
      restartPolicy: Always
      volumes:
      - name: locust-scripts
        configMap:
          name: locust-script-cm
---
apiVersion: apps/v1
kind: Deployment
metadata:
  annotations:
    deployment.kubernetes.io/revision: "1"
  labels:
    role: locust-worker
    app: locust-worker
  name: locust-worker
spec:
  replicas: 1 # Scale it as per your need
  selector:
    matchLabels:
      role: locust-worker
      app: locust-worker
  strategy:
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 1
    type: RollingUpdate
  template:
    metadata:
      labels:
        role: locust-worker
        app: locust-worker
    spec:
      containers:
      - image: locustio/locust
        imagePullPolicy: Always
        name: worker
        args: ["--worker", "--master-host=locust-master"]
        volumeMounts:
          - mountPath: /home/locust
            name: locust-scripts
        terminationMessagePath: /dev/termination-log
        terminationMessagePolicy: File
        resources:
          requests:
            memory: "1Gi"
            cpu: "1"
          limits:
            memory: "1Gi"
      dnsPolicy: ClusterFirst
      restartPolicy: Always
      volumes:
      - name: locust-scripts
        configMap:
          name: locust-script-cm
---
apiVersion: v1
kind: Service
metadata:
  labels:
    role: locust-master
  name: locust-master
spec:
  type: ClusterIP
  ports:
  - port: 5557
    name: master-bind-host
  - port: 5558
    name: master-bind-host-1
  selector:
    role: locust-master
    app: locust-master
---
apiVersion: v1
kind: Service
metadata:
  labels:
    role: locust-ui
  name: locust-ui
spec:
  type: LoadBalancer
  ports:
  - port: 8089
    targetPort: 8089
    name: web-ui
  selector:
    role: locust-master
    app: locust-master

Step 2 : Scale

If you want to scale more worker to support more requests per seconds, you can do that by just scaling up the worker pods

1
kubectl scale --replicas=5 deploy/locust-worker -n locust
1
2
3
4
5
6
locust-master-74c9f6db7c-klk4l   1/1     Running   0          18m
locust-worker-6674d66d5-kgxlp    1/1     Running   0          6s
locust-worker-6674d66d5-m8bdf    1/1     Running   0          6s
locust-worker-6674d66d5-r9v7p    1/1     Running   0          6s
locust-worker-6674d66d5-z2w4x    1/1     Running   0          6s
locust-worker-6674d66d5-zfswz    1/1     Running   0          19m

Comments