diff --git a/CHANGELOG.md b/CHANGELOG.md
index 232bf0f4f..a47979a85 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -14,6 +14,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   pipeline. This can be useful, for example, to implement frame loggers or
   debuggers among other things.
 
+- Added `30-observer.py` to show how to add an Observer to a pipeline for
+  debugging.
+
 - Added `OpenRouter` for OpenRouter integration with an OpenAI-compatible
   interface. Added foundational example `14m-function-calling-openrouter.py`.
 
diff --git a/examples/foundational/30-observer.py b/examples/foundational/30-observer.py
new file mode 100644
index 000000000..9929829c1
--- /dev/null
+++ b/examples/foundational/30-observer.py
@@ -0,0 +1,125 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import os
+import sys
+
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from runner import configure
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import EndFrame, Frame, StartInterruptionFrame
+from pipecat.observers.base_observer import BaseObserver
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
+from pipecat.services.cartesia import CartesiaTTSService
+from pipecat.services.openai import OpenAILLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+class InterruptionDebugObserver(BaseObserver):
+    async def on_push_frame(
+        self,
+        src: FrameProcessor,
+        dst: FrameProcessor,
+        frame: Frame,
+        direction: FrameDirection,
+        timestamp: int,
+    ):
+        if isinstance(frame, (StartInterruptionFrame)):
+            # Convert timestamp to seconds for readability
+            time_sec = timestamp / 1_000_000_000
+
+            # Create direction arrow
+            arrow = "→" if direction == FrameDirection.DOWNSTREAM else "←"
+
+            logger.info(f"INTERRUPTION START: {src} {arrow} {dst} at {time_sec:.2f}s")
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, token) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Respond bot",
+            DailyParams(
+                audio_out_enabled=True,
+                transcription_enabled=True,
+                vad_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
+        )
+
+        tts = CartesiaTTSService(
+            api_key=os.getenv("CARTESIA_API_KEY"),
+            voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
+        )
+
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
+
+        messages = [
+            {
+                "role": "system",
+                "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+            },
+        ]
+
+        context = OpenAILLMContext(messages)
+        context_aggregator = llm.create_context_aggregator(context)
+
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                context_aggregator.user(),  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                context_aggregator.assistant(),  # Assistant spoken responses
+            ]
+        )
+
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+                observers=[InterruptionDebugObserver()],
+            ),
+        )
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            await transport.capture_participant_transcription(participant["id"])
+            # Kick off the conversation.
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.queue_frame(EndFrame())
+
+        runner = PipelineRunner()
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())