diff --git a/kafka_2.13-3.9.0.tgz b/test_dockerfiles/kafka_2.13-3.9.0.tgz
similarity index 100%
rename from kafka_2.13-3.9.0.tgz
rename to test_dockerfiles/kafka_2.13-3.9.0.tgz
diff --git a/test_dockerfiles/kafka_consumer.py b/test_dockerfiles/kafka_consumer.py
new file mode 100644
index 0000000000000000000000000000000000000000..a546e4c9b26d6047be54277a0c85f909e3cef2b5
--- /dev/null
+++ b/test_dockerfiles/kafka_consumer.py
@@ -0,0 +1,36 @@
+from confluent_kafka import Consumer, KafkaException
+import json
+
+# Create Confluent Kafka consumer
+consumer = Consumer({
+    'bootstrap.servers': 'localhost:9092',
+    'group.id': 'my-group',
+    'auto.offset.reset': 'earliest'
+})
+
+# Subscribe to 'sensor-data' topic
+consumer.subscribe(['sensor-data'])
+
+# Consume messages from 'sensor-data' topic
+try:
+    while True:
+        msg = consumer.poll(1.0)  # Poll for messages with a timeout of 1 second
+
+        if msg is None:
+            continue
+        if msg.error():
+            if msg.error().code() == KafkaException._PARTITION_EOF:
+                # End of partition event
+                print(f"{msg.topic()} [{msg.partition()}] reached end at offset {msg.offset()}")
+            elif msg.error():
+                raise KafkaException(msg.error())
+        else:
+            # Proper message
+            sensor_data = json.loads(msg.value().decode('utf-8'))  # Deserialize the JSON data
+            print(f"Received: {sensor_data}")
+            # You can process the data here (e.g., analyze, store in a DB)
+except KeyboardInterrupt:
+    print("Stopped by user")
+finally:
+    # Close down consumer to commit final offsets.
+    consumer.close()
\ No newline at end of file
diff --git a/test_dockerfiles/kafka_producer.py b/test_dockerfiles/kafka_producer.py
new file mode 100644
index 0000000000000000000000000000000000000000..22efac718eceb4d08eafb707fa12de04a3bb2a9b
--- /dev/null
+++ b/test_dockerfiles/kafka_producer.py
@@ -0,0 +1,33 @@
+from confluent_kafka import Producer
+import random
+import json
+import time
+
+# Delivery report callback
+def delivery_report(err, msg):
+    if err is not None:
+        print(f"Message delivery failed: {err}")
+    else:
+        print(f"Message delivered to {msg.topic()} [{msg.partition()}]")
+
+# Create Confluent Kafka producer
+producer = Producer({'bootstrap.servers': 'localhost:9092'})
+
+# Generate random sensor data and send to 'sensor-data' topic
+try:
+    while True:
+        sensor_data = {
+            "sensor_id": random.randint(1, 10),  # Simulating sensor ID
+            "temperature": random.uniform(20.0, 30.0),  # Random temperature value
+            "humidity": random.uniform(30.0, 80.0)  # Random humidity value
+        }
+        
+        # Send data to 'sensor-data' topic
+        producer.produce('sensor-data', key=str(sensor_data["sensor_id"]), value=json.dumps(sensor_data), callback=delivery_report)
+        producer.poll(0)  # Serve delivery callback queue
+        
+        time.sleep(2)  # Simulate data being sent every 2 seconds
+except KeyboardInterrupt:
+    print("Stopped by user")
+finally:
+    producer.flush()
\ No newline at end of file