cleanup code

src/example2/Dockerfile

 FROM python:3.9-slim
 
+RUN apt-get update && apt-get install -y procps
+RUN apt install -y stress-ng
+
 RUN mkdir /app
 # Set the working directory in the container
 WORKDIR /app

src/example2/function.py

@@ -35,15 +35,21 @@ cpu_process = None
 
 def occupy_cpu(percentage):
     while True:
+        # Get the current CPU usage
+        cpu_percent = psutil.cpu_percent()
+
+        # Adjust the workload based on the difference between actual and desired CPU usage
+        workload = min(1.0, percentage / cpu_percent)
+
         # Start time
         start_time = time.time()
 
         # Perform CPU-bound task
-        while (time.time() - start_time) < (percentage / 100):
+        while (time.time() - start_time) < (workload):
             pass
 
         # Sleep to balance CPU usage
-        time.sleep(1 - (percentage / 100))
+        time.sleep(1 - workload)
 
 @app.route('/occupy_cpu/<int:percentage>', methods=['GET'])
 def start_cpu_occupier(percentage):
@@ -105,6 +111,37 @@ def use_allocated_memory():
 
     return jsonify({'message': 'Data written to allocated memory successfully'}), 200
 
+stress_process = None
+
+@app.route('/mem')
+def index():
+    return 'Memory Usage: ' + get_memory_usage()
+
+def get_memory_usage():
+    # Call system command to get memory usage using top
+    result = subprocess.run(['top', '-b', '-n', '1'], capture_output=True, text=True)
+    return result.stdout
+
+@app.route('/memory')
+def manage_memory():
+    global stress_process
+    size = request.args.get('size')
+    if size:
+        if stress_process:
+            # Kill existing stress-ng process
+            subprocess.run(['pkill', 'stress-ng'])
+            stress_process = None
+
+        # Start stress-ng process with specified size
+        stress_process = subprocess.Popen(['stress-ng', '--vm', '1', '--vm-bytes', size])
+        return f'Started new stress-ng process with {size} memory size.'
+    else:
+        if stress_process:
+            # Kill existing stress-ng process
+            subprocess.run(['pkill', 'stress-ng'])
+            stress_process = None
+        return 'Not running stress-ng.'
+
 @app.route("/")
 def hello():
     time_invoked=time.time()
@@ -112,8 +149,8 @@ def hello():
     # Increment request counter
     function_requests_total.inc()
 
-    for i in range(1000000):
-        for j in range(10000):
+    for i in range(100000):
+        for j in range(1000):
             pass
 
     

src/faas.py

@@ -125,8 +125,7 @@ def scale_deployment():
             scale_api.read_namespaced_horizontal_pod_autoscaler(name=f"{function_name}-hpa", namespace=namespace)
             hpa_exists = True
         except ApiException as e:
-            if e.status != 404:
-                raise
+            pass
 
         # Define HorizontalPodAutoscaler object
         hpa = {
@@ -166,9 +165,13 @@ def scale_deployment():
             }
         }
 
-
-        # Create or update HorizontalPodAutoscaler
-        scale_api.create_namespaced_horizontal_pod_autoscaler(namespace=namespace, body=hpa)
+        # Create or update HPA based on whether it already exists
+        if hpa_exists:
+            print("Updating HorizontalPodAutoscaler...")
+            scale_api.replace_namespaced_horizontal_pod_autoscaler(name=f"{function_name}-hpa", namespace=namespace, body=hpa)
+        else:
+            print("Creating HorizontalPodAutoscaler...")
+            scale_api.create_namespaced_horizontal_pod_autoscaler(namespace=namespace, body=hpa)
 
         print(f"HorizontalPodAutoscaler '{function_name}-hpa' created/updated successfully.")
 
@@ -203,8 +206,8 @@ def expose_service():
         printf("Invalid choice")
         return
 
-    src_port = int(input("Enter your source port: "))
-    dst_port = int(input("Enter your target port: "))
+    src_port = int(input("Enter your cluster port: "))
+    dst_port = int(input("Enter your port program is listening: "))
     namespace="default"
     try:
         # Check if service already exists
@@ -275,7 +278,6 @@ def get_deployment_info():
                 pod_name = pod.metadata.name
 
                 # Get resource metrics for the pod
-                print(pod_name)
                 try:
                     metrics = metrics_api.get_namespaced_custom_object(
                         group="metrics.k8s.io",
@@ -294,6 +296,8 @@ def get_deployment_info():
                     memory_usage_total += int(memory_usage[:-2])  # Convert string like "1234Ki" to int (removing "Ki" suffix)
                 except ApiException as e:
                     pass
+                except ValueError as value_error:
+                    pass
 
             # Calculate average usage across all pods
             num_pods = len(pods)

src/temp.py

+import psutil
+import time
+
+def hello():
+
+    for i in range(100000):
+        for j in range(1000):
+            pass
+
+
+
+
+    return "Hello from Python function"
+
+hello()