ref(span-buffer/flusher): More metrics and more lenient backpressure.

src/sentry/options/defaults.py

@@ -2663,6 +2663,11 @@
     default=False,
     flags=FLAG_PRIORITIZE_DISK | FLAG_AUTOMATOR_MODIFIABLE,
 )
+register(
+    "standalone-spans.buffer.flusher.backpressure_seconds",
+    default=10,
+    flags=FLAG_PRIORITIZE_DISK | FLAG_AUTOMATOR_MODIFIABLE,
+)
 register(
     "indexed-spans.agg-span-waterfall.enable",
     default=False,

src/sentry/spans/buffer.py

@@ -344,15 +344,17 @@ def flush_segments(self, now: int, max_segments: int = 0) -> dict[SegmentKey, Fl
 
                 result = p.execute()
 
-        segment_keys: list[tuple[QueueKey, SegmentKey]] = []
+        segment_keys: list[tuple[int, QueueKey, SegmentKey]] = []
 
         with metrics.timer("spans.buffer.flush_segments.load_segment_data"):
             with self.client.pipeline(transaction=False) as p:
                 # ZRANGEBYSCORE output
-                for queue_key, segment_span_ids in zip(queue_keys, result):
+                for shard, queue_key, segment_span_ids in zip(
+                    self.assigned_shards, queue_keys, result
+                ):
                     # process return value of zrevrangebyscore
                     for segment_key in segment_span_ids:
-                        segment_keys.append((queue_key, segment_key))
+                        segment_keys.append((shard, queue_key, segment_key))
                         p.smembers(segment_key)
 
                 segments = p.execute()
@@ -361,7 +363,7 @@ def flush_segments(self, now: int, max_segments: int = 0) -> dict[SegmentKey, Fl
 
         num_has_root_spans = 0
 
-        for (queue_key, segment_key), segment in zip(segment_keys, segments):
+        for (shard, queue_key, segment_key), segment in zip(segment_keys, segments):
             segment_span_id = _segment_key_to_span_id(segment_key).decode("ascii")
 
             output_spans = []
@@ -396,6 +398,9 @@ def flush_segments(self, now: int, max_segments: int = 0) -> dict[SegmentKey, Fl
 
                 output_spans.append(OutputSpan(payload=val))
 
+            metrics.incr(
+                "spans.buffer.flush_segments.num_segments_per_shard", tags={"shard_i": shard}
+            )
             return_segments[segment_key] = FlushedSegment(queue_key=queue_key, spans=output_spans)
             num_has_root_spans += int(has_root_span)
 

src/sentry/spans/consumers/process/flusher.py

@@ -4,13 +4,14 @@
 import time
 from collections.abc import Callable
 
-import rapidjson
+import orjson
 import sentry_sdk
 from arroyo import Topic as ArroyoTopic
 from arroyo.backends.kafka import KafkaPayload, KafkaProducer, build_kafka_configuration
 from arroyo.processing.strategies.abstract import MessageRejected, ProcessingStrategy
 from arroyo.types import FilteredPayload, Message
 
+from sentry import options
 from sentry.conf.types.kafka_definition import Topic
 from sentry.spans.buffer import SpansBuffer
 from sentry.utils import metrics
@@ -51,7 +52,7 @@ def __init__(
         self.stopped = multiprocessing.Value("i", 0)
         self.redis_was_full = False
         self.current_drift = multiprocessing.Value("i", 0)
-        self.should_backpressure = multiprocessing.Value("i", 0)
+        self.backpressure_since = multiprocessing.Value("i", 0)
         self.produce_to_pipe = produce_to_pipe
 
         self._create_process()
@@ -73,7 +74,7 @@ def _create_process(self):
                 initializer,
                 self.stopped,
                 self.current_drift,
-                self.should_backpressure,
+                self.backpressure_since,
                 self.buffer,
                 self.max_flush_segments,
                 self.produce_to_pipe,
@@ -89,7 +90,7 @@ def main(
         initializer: Callable | None,
         stopped,
         current_drift,
-        should_backpressure,
+        backpressure_since,
         buffer: SpansBuffer,
         max_flush_segments: int,
         produce_to_pipe: Callable[[KafkaPayload], None] | None,
@@ -121,34 +122,36 @@ def produce(payload: KafkaPayload) -> None:
                 now = int(time.time()) + current_drift.value
                 flushed_segments = buffer.flush_segments(max_segments=max_flush_segments, now=now)
 
-                should_backpressure.value = len(flushed_segments) >= max_flush_segments * len(
-                    buffer.assigned_shards
-                )
+                if len(flushed_segments) >= max_flush_segments * len(buffer.assigned_shards):
+                    if backpressure_since.value == 0:
+                        backpressure_since.value = int(time.time())
+                else:
+                    backpressure_since.value = 0
 
                 if not flushed_segments:
                     time.sleep(1)
                     continue
 
-                for _, flushed_segment in flushed_segments.items():
-                    if not flushed_segment.spans:
-                        # This is a bug, most likely the input topic is not
-                        # partitioned by trace_id so multiple consumers are writing
-                        # over each other. The consequence is duplicated segments,
-                        # worst-case.
-                        metrics.incr("sentry.spans.buffer.empty_segments")
-                        continue
+                with metrics.timer("spans.buffer.flusher.produce"):
+                    for _, flushed_segment in flushed_segments.items():
+                        if not flushed_segment.spans:
+                            # This is a bug, most likely the input topic is not
+                            # partitioned by trace_id so multiple consumers are writing
+                            # over each other. The consequence is duplicated segments,
+                            # worst-case.
+                            metrics.incr("sentry.spans.buffer.empty_segments")
+                            continue
 
-                    spans = [span.payload for span in flushed_segment.spans]
+                        spans = [span.payload for span in flushed_segment.spans]
 
-                    kafka_payload = KafkaPayload(
-                        None, rapidjson.dumps({"spans": spans}).encode("utf8"), []
-                    )
+                        kafka_payload = KafkaPayload(None, orjson.dumps({"spans": spans}), [])
 
-                    metrics.timing("spans.buffer.segment_size_bytes", len(kafka_payload.value))
-                    produce(kafka_payload)
+                        metrics.timing("spans.buffer.segment_size_bytes", len(kafka_payload.value))
+                        produce(kafka_payload)
 
-                for future in producer_futures:
-                    future.result()
+                with metrics.timer("spans.buffer.flusher.wait_produce"):
+                    for future in producer_futures:
+                        future.result()
 
                 producer_futures.clear()
 
@@ -187,12 +190,12 @@ def submit(self, message: Message[FilteredPayload | int]) -> None:
         # efforts, it is still always going to be less durable than Kafka.
         # Minimizing our Redis memory usage also makes COGS easier to reason
         # about.
-        #
-        # should_backpressure is true if there are many segments to flush, but
-        # the flusher can't get all of them out.
-        if self.should_backpressure.value:
-            metrics.incr("sentry.spans.buffer.flusher.backpressure")
-            raise MessageRejected()
+        if self.backpressure_since.value > 0:
+            if int(time.time()) - self.backpressure_since.value > options.get(
+                "standalone-spans.buffer.flusher.backpressure_seconds"
+            ):
+                metrics.incr("sentry.spans.buffer.flusher.backpressure")
+                raise MessageRejected()
 
         # We set the drift. The backpressure based on redis memory comes after.
         # If Redis is full for a long time, the drift will grow into a large

tests/sentry/spans/consumers/process/test_flusher.py

@@ -80,4 +80,4 @@ def append(msg):
 
     assert messages
 
-    assert flusher.should_backpressure.value
+    assert flusher.backpressure_since.value