feat(confluent-kafka): Add instrumentation to consume method (#1786)

Co-authored-by: Diego Hurtado <[email protected]>

Author: javferrod

CHANGELOG.md

@@ -61,6 +61,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Add optional distro and configurator selection for auto-instrumentation
   ([#1823](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/1823))
 
+### Added
+- `opentelemetry-instrumentation-kafka-python` Add instrumentation to `consume` method
+  ([#1786](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/1786))
+
 ## Version 1.18.0/0.39b0 (2023-05-10)
 
 - Update runtime metrics to follow semantic conventions

instrumentation/opentelemetry-instrumentation-confluent-kafka/src/opentelemetry/instrumentation/confluent_kafka/__init__.py

@@ -112,6 +112,8 @@ def instrument_consumer(consumer: Consumer, tracer_provider=None)
 from .package import _instruments
 from .utils import (
     KafkaPropertiesExtractor,
+    _end_current_consume_span,
+    _create_new_consume_span,
     _enrich_span,
     _get_span_name,
     _kafka_getter,
@@ -137,6 +139,12 @@ def __init__(self, config):
     def poll(self, timeout=-1):  # pylint: disable=useless-super-delegation
         return super().poll(timeout)
 
+    # This method is deliberately implemented in order to allow wrapt to wrap this function
+    def consume(
+        self, *args, **kwargs
+    ):  # pylint: disable=useless-super-delegation
+        return super().consume(*args, **kwargs)
+
 
 class ProxiedProducer(Producer):
     def __init__(self, producer: Producer, tracer: Tracer):
@@ -177,10 +185,14 @@ def committed(self, partitions, timeout=-1):
     def commit(self, *args, **kwargs):
         return self._consumer.commit(*args, **kwargs)
 
-    def consume(
-        self, num_messages=1, *args, **kwargs
-    ):  # pylint: disable=keyword-arg-before-vararg
-        return self._consumer.consume(num_messages, *args, **kwargs)
+    def consume(self, *args, **kwargs):
+        return ConfluentKafkaInstrumentor.wrap_consume(
+            self._consumer.consume,
+            self,
+            self._tracer,
+            args,
+            kwargs,
+        )
 
     def get_watermark_offsets(
         self, partition, timeout=-1, *args, **kwargs
@@ -275,6 +287,11 @@ def _inner_wrap_poll(func, instance, args, kwargs):
                 func, instance, self._tracer, args, kwargs
             )
 
+        def _inner_wrap_consume(func, instance, args, kwargs):
+            return ConfluentKafkaInstrumentor.wrap_consume(
+                func, instance, self._tracer, args, kwargs
+            )
+
         wrapt.wrap_function_wrapper(
             AutoInstrumentedProducer,
             "produce",
@@ -287,6 +304,12 @@ def _inner_wrap_poll(func, instance, args, kwargs):
             _inner_wrap_poll,
         )
 
+        wrapt.wrap_function_wrapper(
+            AutoInstrumentedConsumer,
+            "consume",
+            _inner_wrap_consume,
+        )
+
     def _uninstrument(self, **kwargs):
         confluent_kafka.Producer = self._original_kafka_producer
         confluent_kafka.Consumer = self._original_kafka_consumer
@@ -326,29 +349,14 @@ def wrap_produce(func, instance, tracer, args, kwargs):
     @staticmethod
     def wrap_poll(func, instance, tracer, args, kwargs):
         if instance._current_consume_span:
-            context.detach(instance._current_context_token)
-            instance._current_context_token = None
-            instance._current_consume_span.end()
-            instance._current_consume_span = None
+            _end_current_consume_span(instance)
 
         with tracer.start_as_current_span(
             "recv", end_on_exit=True, kind=trace.SpanKind.CONSUMER
         ):
             record = func(*args, **kwargs)
             if record:
-                links = []
-                ctx = propagate.extract(record.headers(), getter=_kafka_getter)
-                if ctx:
-                    for item in ctx.values():
-                        if hasattr(item, "get_span_context"):
-                            links.append(Link(context=item.get_span_context()))
-
-                instance._current_consume_span = tracer.start_span(
-                    name=f"{record.topic()} process",
-                    links=links,
-                    kind=SpanKind.CONSUMER,
-                )
-
+                _create_new_consume_span(instance, tracer, [record])
                 _enrich_span(
                     instance._current_consume_span,
                     record.topic(),
@@ -361,3 +369,26 @@ def wrap_poll(func, instance, tracer, args, kwargs):
         )
 
         return record
+
+    @staticmethod
+    def wrap_consume(func, instance, tracer, args, kwargs):
+        if instance._current_consume_span:
+            _end_current_consume_span(instance)
+
+        with tracer.start_as_current_span(
+            "recv", end_on_exit=True, kind=trace.SpanKind.CONSUMER
+        ):
+            records = func(*args, **kwargs)
+            if len(records) > 0:
+                _create_new_consume_span(instance, tracer, records)
+                _enrich_span(
+                    instance._current_consume_span,
+                    records[0].topic(),
+                    operation=MessagingOperationValues.PROCESS,
+                )
+
+        instance._current_context_token = context.attach(
+            trace.set_span_in_context(instance._current_consume_span)
+        )
+
+        return records

instrumentation/opentelemetry-instrumentation-confluent-kafka/src/opentelemetry/instrumentation/confluent_kafka/utils.py

@@ -1,6 +1,8 @@
 from logging import getLogger
 from typing import List, Optional
 
+from opentelemetry import context, propagate
+from opentelemetry.trace import SpanKind, Link
 from opentelemetry.propagators import textmap
 from opentelemetry.semconv.trace import (
     MessagingDestinationKindValues,
@@ -81,6 +83,34 @@ def set(self, carrier: textmap.CarrierT, key: str, value: str) -> None:
 _kafka_getter = KafkaContextGetter()
 
 
+def _end_current_consume_span(instance):
+    context.detach(instance._current_context_token)
+    instance._current_context_token = None
+    instance._current_consume_span.end()
+    instance._current_consume_span = None
+
+
+def _create_new_consume_span(instance, tracer, records):
+    links = _get_links_from_records(records)
+    instance._current_consume_span = tracer.start_span(
+        name=f"{records[0].topic()} process",
+        links=links,
+        kind=SpanKind.CONSUMER,
+    )
+
+
+def _get_links_from_records(records):
+    links = []
+    for record in records:
+        ctx = propagate.extract(record.headers(), getter=_kafka_getter)
+        if ctx:
+            for item in ctx.values():
+                if hasattr(item, "get_span_context"):
+                    links.append(Link(context=item.get_span_context()))
+
+    return links
+
+
 def _enrich_span(
     span,
     topic,
@@ -94,7 +124,7 @@ def _enrich_span(
     span.set_attribute(SpanAttributes.MESSAGING_SYSTEM, "kafka")
     span.set_attribute(SpanAttributes.MESSAGING_DESTINATION, topic)
 
-    if partition:
+    if partition is not None:
         span.set_attribute(SpanAttributes.MESSAGING_KAFKA_PARTITION, partition)
 
     span.set_attribute(
@@ -109,7 +139,7 @@ def _enrich_span(
 
     # https://stackoverflow.com/questions/65935155/identify-and-find-specific-message-in-kafka-topic
     # A message within Kafka is uniquely defined by its topic name, topic partition and offset.
-    if partition and offset and topic:
+    if partition is not None and offset is not None and topic:
         span.set_attribute(
             SpanAttributes.MESSAGING_MESSAGE_ID,
             f"{topic}.{partition}.{offset}",

instrumentation/opentelemetry-instrumentation-confluent-kafka/tests/test_instrumentation.py

@@ -14,7 +14,12 @@
 
 # pylint: disable=no-name-in-module
 
-from unittest import TestCase
+from opentelemetry.semconv.trace import (
+    SpanAttributes,
+    MessagingDestinationKindValues,
+)
+from opentelemetry.test.test_base import TestBase
+from .utils import MockConsumer, MockedMessage
 
 from confluent_kafka import Consumer, Producer
 
@@ -29,7 +34,7 @@
 )
 
 
-class TestConfluentKafka(TestCase):
+class TestConfluentKafka(TestBase):
     def test_instrument_api(self) -> None:
         instrumentation = ConfluentKafkaInstrumentor()
 
@@ -104,3 +109,140 @@ def test_context_getter(self) -> None:
         context_setter.set(carrier_list, "key1", "val1")
         self.assertEqual(context_getter.get(carrier_list, "key1"), ["val1"])
         self.assertEqual(["key1"], context_getter.keys(carrier_list))
+
+    def test_poll(self) -> None:
+        instrumentation = ConfluentKafkaInstrumentor()
+        mocked_messages = [
+            MockedMessage("topic-10", 0, 0, []),
+            MockedMessage("topic-20", 2, 4, []),
+            MockedMessage("topic-30", 1, 3, []),
+        ]
+        expected_spans = [
+            {"name": "recv", "attributes": {}},
+            {
+                "name": "topic-10 process",
+                "attributes": {
+                    SpanAttributes.MESSAGING_OPERATION: "process",
+                    SpanAttributes.MESSAGING_KAFKA_PARTITION: 0,
+                    SpanAttributes.MESSAGING_SYSTEM: "kafka",
+                    SpanAttributes.MESSAGING_DESTINATION: "topic-10",
+                    SpanAttributes.MESSAGING_DESTINATION_KIND: MessagingDestinationKindValues.QUEUE.value,
+                    SpanAttributes.MESSAGING_MESSAGE_ID: "topic-10.0.0",
+                },
+            },
+            {"name": "recv", "attributes": {}},
+            {
+                "name": "topic-20 process",
+                "attributes": {
+                    SpanAttributes.MESSAGING_OPERATION: "process",
+                    SpanAttributes.MESSAGING_KAFKA_PARTITION: 2,
+                    SpanAttributes.MESSAGING_SYSTEM: "kafka",
+                    SpanAttributes.MESSAGING_DESTINATION: "topic-20",
+                    SpanAttributes.MESSAGING_DESTINATION_KIND: MessagingDestinationKindValues.QUEUE.value,
+                    SpanAttributes.MESSAGING_MESSAGE_ID: "topic-20.2.4",
+                },
+            },
+            {"name": "recv", "attributes": {}},
+            {
+                "name": "topic-30 process",
+                "attributes": {
+                    SpanAttributes.MESSAGING_OPERATION: "process",
+                    SpanAttributes.MESSAGING_KAFKA_PARTITION: 1,
+                    SpanAttributes.MESSAGING_SYSTEM: "kafka",
+                    SpanAttributes.MESSAGING_DESTINATION: "topic-30",
+                    SpanAttributes.MESSAGING_DESTINATION_KIND: MessagingDestinationKindValues.QUEUE.value,
+                    SpanAttributes.MESSAGING_MESSAGE_ID: "topic-30.1.3",
+                },
+            },
+            {"name": "recv", "attributes": {}},
+        ]
+
+        consumer = MockConsumer(
+            mocked_messages,
+            {
+                "bootstrap.servers": "localhost:29092",
+                "group.id": "mygroup",
+                "auto.offset.reset": "earliest",
+            },
+        )
+        self.memory_exporter.clear()
+        consumer = instrumentation.instrument_consumer(consumer)
+        consumer.poll()
+        consumer.poll()
+        consumer.poll()
+        consumer.poll()
+
+        span_list = self.memory_exporter.get_finished_spans()
+        self._compare_spans(span_list, expected_spans)
+
+    def test_consume(self) -> None:
+        instrumentation = ConfluentKafkaInstrumentor()
+        mocked_messages = [
+            MockedMessage("topic-1", 0, 0, []),
+            MockedMessage("topic-1", 2, 1, []),
+            MockedMessage("topic-1", 3, 2, []),
+            MockedMessage("topic-2", 0, 0, []),
+            MockedMessage("topic-3", 0, 3, []),
+            MockedMessage("topic-2", 0, 1, []),
+        ]
+        expected_spans = [
+            {"name": "recv", "attributes": {}},
+            {
+                "name": "topic-1 process",
+                "attributes": {
+                    SpanAttributes.MESSAGING_OPERATION: "process",
+                    SpanAttributes.MESSAGING_SYSTEM: "kafka",
+                    SpanAttributes.MESSAGING_DESTINATION: "topic-1",
+                    SpanAttributes.MESSAGING_DESTINATION_KIND: MessagingDestinationKindValues.QUEUE.value,
+                },
+            },
+            {"name": "recv", "attributes": {}},
+            {
+                "name": "topic-2 process",
+                "attributes": {
+                    SpanAttributes.MESSAGING_OPERATION: "process",
+                    SpanAttributes.MESSAGING_SYSTEM: "kafka",
+                    SpanAttributes.MESSAGING_DESTINATION: "topic-2",
+                    SpanAttributes.MESSAGING_DESTINATION_KIND: MessagingDestinationKindValues.QUEUE.value,
+                },
+            },
+            {"name": "recv", "attributes": {}},
+            {
+                "name": "topic-3 process",
+                "attributes": {
+                    SpanAttributes.MESSAGING_OPERATION: "process",
+                    SpanAttributes.MESSAGING_SYSTEM: "kafka",
+                    SpanAttributes.MESSAGING_DESTINATION: "topic-3",
+                    SpanAttributes.MESSAGING_DESTINATION_KIND: MessagingDestinationKindValues.QUEUE.value,
+                },
+            },
+            {"name": "recv", "attributes": {}},
+        ]
+
+        consumer = MockConsumer(
+            mocked_messages,
+            {
+                "bootstrap.servers": "localhost:29092",
+                "group.id": "mygroup",
+                "auto.offset.reset": "earliest",
+            },
+        )
+
+        self.memory_exporter.clear()
+        consumer = instrumentation.instrument_consumer(consumer)
+        consumer.consume(3)
+        consumer.consume(1)
+        consumer.consume(2)
+        consumer.consume(1)
+        span_list = self.memory_exporter.get_finished_spans()
+        self._compare_spans(span_list, expected_spans)
+
+    def _compare_spans(self, spans, expected_spans):
+        for span, expected_span in zip(spans, expected_spans):
+            self.assertEqual(expected_span["name"], span.name)
+            for attribute_key, expected_attribute_value in expected_span[
+                "attributes"
+            ].items():
+                self.assertEqual(
+                    expected_attribute_value, span.attributes[attribute_key]
+                )