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_telemetry.py
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365 lines (312 loc) · 12.9 KB
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import threading
from queue import Queue, Full
import time
from enum import Enum
from abc import ABC
from cachetools import TTLCache
from prefab_pb2 import (
ConfigEvaluationSummary,
ConfigEvaluationSummaries,
ConfigEvaluationCounter,
TelemetryEvent,
TelemetryEvents,
ExampleContext as ProtoExampleContext,
ExampleContexts,
)
from .context import Context
from .options import Options
from .config_resolver import Evaluation
from collections import defaultdict
from .context_shape_aggregator import ContextShapeAggregator
from .log_path_aggregator import LogPathAggregator
from ._internal_logging import InternalLogger
logger = InternalLogger(__name__)
def current_time_millis() -> int:
return int(time.time() * 1000)
class BaseTelemetryEvent(ABC):
class Type(Enum):
EVAL = 1
FLUSH = 2
LOG = 3
def __init__(self, event_type=Type.FLUSH, timestamp=None):
self.event_type = event_type
self.timestamp = timestamp if timestamp is not None else current_time_millis()
class FlushTelemetryEvent(BaseTelemetryEvent):
def __init__(self):
super().__init__(event_type=BaseTelemetryEvent.Type.FLUSH)
self.processed_event = threading.Event()
def block_until_consumed(self):
self.processed_event.wait()
def mark_finished(self):
self.processed_event.set()
class EvaluationTelemetryEvent(BaseTelemetryEvent):
def __init__(self, evaluation: Evaluation):
super().__init__(event_type=BaseTelemetryEvent.Type.EVAL)
self.evaluation = evaluation
class LogEvent(BaseTelemetryEvent):
def __init__(self, path: str, level):
super().__init__(event_type=BaseTelemetryEvent.Type.LOG)
self.path = path
self.level = level
class TelemetryManager(object):
def __init__(self, client, options: Options) -> None:
self.client = client
self.report_interval = options.collect_sync_interval
self.report_summaries = options.collect_evaluation_summaries
self.collect_example_contexts = (
options.context_upload_mode == Options.ContextUploadMode.PERIODIC_EXAMPLE
)
self.collect_context_shapes = (
options.context_upload_mode != Options.ContextUploadMode.NONE
)
self.collect_logs = options.collect_logs
self.sync_started = False
self.event_processor = TelemetryEventProcessor(
base_client=self.client,
evaluation_event_handler=self._handle_evaluation,
flush_event_handler=self._handle_flush,
log_event_handler=self._handle_log,
)
self.event_processor.start()
self.timer = None
self.evaluation_rollup = EvaluationRollup()
self.example_contexts = ContextExampleAccumulator()
self.context_shape_aggregator = ContextShapeAggregator(
max_shapes=options.collect_max_shapes
)
self.log_path_aggregator = LogPathAggregator(options.collect_max_paths)
self.listeners = []
def start_periodic_sync(self) -> None:
if self.report_interval:
self.sync_started = True
self.timer = threading.Timer(self.report_interval, self.run_sync)
self.timer.daemon = True
self.timer.start()
def stop(self):
self.sync_started = False
def run_sync(self) -> None:
try:
self.flush()
finally:
if self.sync_started and not self.client.shutdown_flag.is_set():
self.timer = threading.Timer(self.report_interval, self.run_sync)
self.timer.daemon = True
self.timer.start()
def record_evaluation(self, evaluation: Evaluation) -> None:
self.event_processor.enqueue(EvaluationTelemetryEvent(evaluation))
def record_log(self, logger_name: str, severity) -> None:
if self.collect_logs:
self.event_processor.enqueue(LogEvent(logger_name, level=severity))
def flush(self) -> FlushTelemetryEvent:
flush_event = FlushTelemetryEvent()
self.event_processor.enqueue(flush_event)
return flush_event
def flush_and_block(self):
self.flush().block_until_consumed()
def _handle_evaluation(self, evaluationEvent: EvaluationTelemetryEvent) -> None:
if self.report_summaries:
self.evaluation_rollup.record_evaluation(evaluationEvent.evaluation)
if self.collect_example_contexts:
self.example_contexts.add(evaluationEvent.evaluation.context)
if self.collect_context_shapes:
context = evaluationEvent.evaluation.context
if isinstance(context, Context):
self.context_shape_aggregator.push(context)
elif not isinstance(context, str):
self.context_shape_aggregator.push(Context(context))
def _handle_flush(self, flush_event: FlushTelemetryEvent) -> None:
try:
telemetry_events = []
if self.report_summaries:
current_eval_rollup = self.evaluation_rollup
eval_summaries = current_eval_rollup.build_telemetry()
self.evaluation_rollup = EvaluationRollup()
if len(eval_summaries.summaries) > 0:
telemetry_events.append(TelemetryEvent(summaries=eval_summaries))
if self.collect_example_contexts:
current_example_contexts = (
self.example_contexts.get_and_reset_contexts()
)
if current_example_contexts:
telemetry_events.append(
TelemetryEvent(
example_contexts=ExampleContexts(
examples=current_example_contexts
)
)
)
if self.collect_context_shapes:
shapes = self.context_shape_aggregator.flush()
if shapes and len(shapes.shapes) > 0:
telemetry_events.append(TelemetryEvent(context_shapes=shapes))
if self.collect_logs:
loggers = self.log_path_aggregator.flush()
if len(loggers.loggers) > 0:
telemetry_events.append(TelemetryEvent(loggers=loggers))
if telemetry_events:
# TODO retry/log
self.client.post(
"/api/v1/telemetry/",
TelemetryEvents(events=telemetry_events),
)
finally:
flush_event.mark_finished()
def _handle_log(self, log_event: LogEvent) -> None:
self.log_path_aggregator.push(log_event.path, log_event.level)
class HashableProtobufWrapper:
def __init__(self, msg):
self.msg = msg
def __hash__(self):
return hash(self.msg.SerializeToString())
def __eq__(self, other):
return self.msg.SerializeToString() == other.msg.SerializeToString()
class ContextExampleAccumulator(object):
def __init__(self):
self.recently_seen_contexts = set()
self.fingerprint_cache = TTLCache(maxsize=1000, ttl=60 * 5)
def size(self):
return len(self.recently_seen_contexts)
def add(self, context: Context) -> None:
fingerprint = ContextExampleAccumulator.context_fingerprint(context)
if fingerprint and fingerprint not in self.fingerprint_cache:
self.fingerprint_cache[fingerprint] = fingerprint
self.recently_seen_contexts.add(
HashableProtobufWrapper(
ProtoExampleContext(
timestamp=current_time_millis(), contextSet=context.to_proto()
)
)
)
def get_and_reset_contexts(self) -> [ProtoExampleContext]:
contexts_to_return = [item.msg for item in self.recently_seen_contexts]
self.recently_seen_contexts.clear()
return contexts_to_return
@staticmethod
def context_fingerprint(context: Context) -> str:
fingerprint_string = ""
for name, named_context in sorted(context.contexts.items()):
key = named_context.get("key")
if key:
fingerprint_string += f"{name}:{key}::"
return fingerprint_string
class EvaluationRollup(object):
def __init__(self):
self.counts = defaultdict(lambda: 0)
self.recorded_since = current_time_millis()
def record_evaluation(self, evaluation: Evaluation) -> None:
if evaluation.config:
reportable_value = None
try:
reportable_value = HashableProtobufWrapper(
evaluation.deepest_value().reportable_wrapped_value().value
)
except Exception:
pass
self.counts[
(
evaluation.config.key,
evaluation.config.config_type,
evaluation.config.id,
evaluation.config_row_index,
evaluation.value_index,
evaluation.deepest_value().weighted_value_index,
reportable_value,
)
] += 1
def build_telemetry(self):
all_summaries = []
key_groups = self._get_keys_grouped_by_key_and_type()
for key_and_type, all_keys in key_groups.items():
current_counters = []
for current_key_tuple in all_keys:
selected_value = None
if current_key_tuple[6]:
selected_value = current_key_tuple[6].msg
current_counters.append(
ConfigEvaluationCounter(
count=self.counts[current_key_tuple],
config_id=current_key_tuple[2],
config_row_index=current_key_tuple[3],
conditional_value_index=current_key_tuple[4],
weighted_value_index=current_key_tuple[5],
selected_value=selected_value,
)
)
all_summaries.append(
ConfigEvaluationSummary(
key=key_and_type[0], type=key_and_type[1], counters=current_counters
)
)
return ConfigEvaluationSummaries(
start=self.recorded_since,
end=current_time_millis(),
summaries=all_summaries,
)
def _get_keys_grouped_by_key_and_type(self):
grouped_keys = defaultdict(list)
for key in self.counts.keys():
grouped_keys[(key[0], key[1])].append(key)
return grouped_keys
class TelemetryEventProcessor(object):
class TelemetryThread(threading.Thread):
def __init__(self, *args, **kwargs):
self.base_client = kwargs.pop("base_client", None)
super().__init__(*args, **kwargs)
def run(self):
try:
super().run()
except Exception as e:
# Log just the exception name and message without the full traceback
logger.warning(
f"Exception in thread {self.name}: {e.__class__.__name__}: {e}"
)
# Using warning level instead of error+traceback to keep logs cleaner
def __init__(
self,
base_client=None,
evaluation_event_handler=None,
flush_event_handler=None,
log_event_handler=None,
) -> None:
self.base_client = base_client
self.thread = None
self.queue = Queue(10000)
self.evaluation_event_handler = evaluation_event_handler
self.flush_event_handler = flush_event_handler
self.log_event_handler = log_event_handler
def start(self) -> None:
self.thread = TelemetryEventProcessor.TelemetryThread(
target=self.process_queue,
daemon=True,
name="TelemetryEventProcessor",
base_client=self.base_client,
)
self.thread.start()
def enqueue(self, event: BaseTelemetryEvent):
try:
self.queue.put_nowait(event)
except Full:
pass
def process_queue(self):
while not self.base_client.shutdown_flag.is_set():
event = self.queue.get()
try:
if (
event.event_type == BaseTelemetryEvent.Type.EVAL
and self.evaluation_event_handler
):
self.evaluation_event_handler(event)
elif (
event.event_type == BaseTelemetryEvent.Type.FLUSH
and self.flush_event_handler
):
self.flush_event_handler(event)
elif (
event.event_type == BaseTelemetryEvent.Type.LOG
and self.log_event_handler
):
self.log_event_handler(event)
else:
raise ValueError(f"Unknown event type: {event.event_type}")
finally:
self.queue.task_done()