Source code for faust.sensors.datadog

"""Monitor using datadog."""
import re

from typing import Any, Dict, List, Optional, Pattern, cast

from mode.utils.objects import cached_property

from faust import web
from faust.exceptions import ImproperlyConfigured
from faust.sensors.monitor import Monitor, TPOffsetMapping
from faust.types import (
    AppT,
    CollectionT,
    EventT,
    Message,
    PendingMessage,
    RecordMetadata,
    StreamT,
    TP,
)
from faust.types.assignor import PartitionAssignorT
from faust.types.transports import ConsumerT, ProducerT

try:
    import datadog
    from datadog.dogstatsd import DogStatsd
except ImportError:  # pragma: no cover
    datadog = None
    class DogStatsD: ...  # noqa

__all__ = ['DatadogMonitor']

# This regular expression is used to generate stream ids in Statsd.
# It converts for example
#    'Stream: <Topic: withdrawals>'
# -> 'Stream_Topic_withdrawals'
#
# See StatsdMonitor._normalize()
RE_NORMALIZE = re.compile(r'[\<\>:\s]+')
RE_NORMALIZE_SUBSTITUTION = '_'


class DatadogStatsClient:
    """Statsd compliant datadog client."""

    def __init__(self,
                 host: str = 'localhost',
                 port: int = 8125,
                 prefix: str = 'faust-app',
                 rate: float = 1.0,
                 **kwargs: Any) -> None:
        self.client = DogStatsd(
            host=host,
            port=port,
            namespace=prefix,
            **kwargs)
        self.rate = rate
        self.sanitize_re = re.compile(r'[^0-9a-zA-Z_]')
        self.re_substitution = '_'

    def gauge(self, metric: str, value: float, labels: Dict = None) -> None:
        self.client.gauge(
            metric,
            value=value,
            tags=self._encode_labels(labels),
            sample_rate=self.rate,
        )

    def increment(self,
                  metric: str,
                  value: float = 1.0,
                  labels: Dict = None) -> None:
        self.client.increment(
            metric,
            value=value,
            tags=self._encode_labels(labels),
            sample_rate=self.rate,
        )

    def incr(self, metric: str, count: int = 1) -> None:
        """Statsd compatibility."""
        self.increment(metric, value=count)

    def decrement(self,
                  metric: str,
                  value: float = 1.0,
                  labels: Dict = None) -> float:
        return self.client.decrement(
            metric,
            value=value,
            tags=self._encode_labels(labels),
            sample_rate=self.rate,
        )

    def decr(self, metric: str, count: float = 1.0) -> None:
        """Statsd compatibility."""
        self.decrement(metric, value=count)

    def timing(self, metric: str, value: float, labels: Dict = None) -> None:
        self.client.timing(
            metric,
            value=value,
            tags=self._encode_labels(labels),
            sample_rate=self.rate,
        )

    def timed(self,
              metric: str = None,
              labels: Dict = None,
              use_ms: bool = None) -> float:
        return self.client.timed(
            metric=metric,
            tags=self._encode_labels(labels),
            sample_rate=self.rate,
            use_ms=use_ms,
        )

    def histogram(self, metric: str, value: float,
                  labels: Dict = None) -> None:
        self.client.histogram(
            metric,
            value=value,
            tags=self._encode_labels(labels),
            sample_rate=self.rate,
        )

    def _encode_labels(self, labels: Optional[Dict]) -> Optional[List[str]]:
        def sanitize(s: str) -> str:
            return self.sanitize_re.sub(self.re_substitution, str(s))

        return [f'{sanitize(k)}:{sanitize(v)}'
                for k, v in labels.items()] if labels else None


[docs]class DatadogMonitor(Monitor): """Datadog Faust Sensor. This sensor, records statistics to datadog agents along with computing metrics for the stats server """ host: str port: int prefix: str def __init__(self, host: str = 'localhost', port: int = 8125, prefix: str = 'faust-app', rate: float = 1.0, **kwargs: Any) -> None: self.host = host self.port = port self.prefix = prefix self.rate = rate if datadog is None: raise ImproperlyConfigured( f'{type(self).__name__} requires `pip install datadog`.') super().__init__(**kwargs) def _new_datadog_stats_client(self) -> DatadogStatsClient: return DatadogStatsClient( host=self.host, port=self.port, prefix=self.prefix, rate=self.rate)
[docs] def on_message_in(self, tp: TP, offset: int, message: Message) -> None: """Call before message is delegated to streams.""" super().on_message_in(tp, offset, message) labels = self._format_label(tp) self.client.increment('messages_received', labels=labels) self.client.increment('messages_active', labels=labels) self.client.increment( 'topic_messages_received', labels={'topic': tp.topic}, ) self.client.gauge('read_offset', offset, labels=labels)
[docs] def on_stream_event_in(self, tp: TP, offset: int, stream: StreamT, event: EventT) -> Optional[Dict]: """Call when stream starts processing an event.""" state = super().on_stream_event_in(tp, offset, stream, event) labels = self._format_label(tp, stream) self.client.increment('events', labels=labels) self.client.increment('events_active', labels=labels) return state
[docs] def on_stream_event_out(self, tp: TP, offset: int, stream: StreamT, event: EventT, state: Dict = None) -> None: """Call when stream is done processing an event.""" super().on_stream_event_out(tp, offset, stream, event, state) labels = self._format_label(tp, stream) self.client.decrement('events_active', labels=labels) self.client.timing( 'events_runtime', self.secs_to_ms(self.events_runtime[-1]), labels=labels, )
[docs] def on_message_out(self, tp: TP, offset: int, message: Message) -> None: """Call when message is fully acknowledged and can be committed.""" super().on_message_out(tp, offset, message) self.client.decrement('messages_active', labels=self._format_label(tp))
[docs] def on_table_get(self, table: CollectionT, key: Any) -> None: """Call when value in table is retrieved.""" super().on_table_get(table, key) self.client.increment( 'table_keys_retrieved', labels=self._format_label(table=table), )
[docs] def on_table_set(self, table: CollectionT, key: Any, value: Any) -> None: """Call when new value for key in table is set.""" super().on_table_set(table, key, value) self.client.increment( 'table_keys_updated', labels=self._format_label(table=table), )
[docs] def on_table_del(self, table: CollectionT, key: Any) -> None: """Call when key in a table is deleted.""" super().on_table_del(table, key) self.client.increment( 'table_keys_deleted', labels=self._format_label(table=table), )
[docs] def on_commit_completed(self, consumer: ConsumerT, state: Any) -> None: """Call when consumer commit offset operation completed.""" super().on_commit_completed(consumer, state) self.client.timing( 'commit_latency', self.ms_since(cast(float, state)), )
[docs] def on_send_initiated(self, producer: ProducerT, topic: str, message: PendingMessage, keysize: int, valsize: int) -> Any: """Call when message added to producer buffer.""" self.client.increment( 'topic_messages_sent', labels={'topic': topic}, ) return super().on_send_initiated( producer, topic, message, keysize, valsize)
[docs] def on_send_completed(self, producer: ProducerT, state: Any, metadata: RecordMetadata) -> None: """Call when producer finished sending message.""" super().on_send_completed(producer, state, metadata) self.client.increment('messages_sent') self.client.timing( 'send_latency', self.ms_since(cast(float, state)), )
[docs] def on_send_error(self, producer: ProducerT, exc: BaseException, state: Any) -> None: """Call when producer was unable to publish message.""" super().on_send_error(producer, exc, state) self.client.increment('messages_send_failed') self.client.timing( 'send_latency_for_error', self.ms_since(cast(float, state)), )
[docs] def on_assignment_error(self, assignor: PartitionAssignorT, state: Dict, exc: BaseException) -> None: """Partition assignor did not complete assignor due to error.""" super().on_assignment_error(assignor, state, exc) self.client.increment('assignments_error') self.client.timing( 'assignment_latency', self.ms_since(state['time_start']), )
[docs] def on_assignment_completed(self, assignor: PartitionAssignorT, state: Dict) -> None: """Partition assignor completed assignment.""" super().on_assignment_completed(assignor, state) self.client.increment('assignments_complete') self.client.timing( 'assignment_latency', self.ms_since(state['time_start']), )
[docs] def on_rebalance_start(self, app: AppT) -> Dict: """Cluster rebalance in progress.""" state = super().on_rebalance_start(app) self.client.increment('rebalances') return state
[docs] def on_rebalance_return(self, app: AppT, state: Dict) -> None: """Consumer replied assignment is done to broker.""" super().on_rebalance_return(app, state) self.client.decrement('rebalances') self.client.increment('rebalances_recovering') self.client.timing( 'rebalance_return_latency', self.ms_since(state['time_return']))
[docs] def on_rebalance_end(self, app: AppT, state: Dict) -> None: """Cluster rebalance fully completed (including recovery).""" super().on_rebalance_end(app, state) self.client.decrement('rebalances_recovering') self.client.timing( 'rebalance_end_latency', self.ms_since(state['time_end']))
[docs] def count(self, metric_name: str, count: int = 1) -> None: """Count metric by name.""" super().count(metric_name, count=count) self.client.increment(metric_name, value=count)
[docs] def on_tp_commit(self, tp_offsets: TPOffsetMapping) -> None: """Call when offset in topic partition is committed.""" super().on_tp_commit(tp_offsets) for tp, offset in tp_offsets.items(): self.client.gauge('committed_offset', offset, labels=self._format_label(tp))
[docs] def track_tp_end_offset(self, tp: TP, offset: int) -> None: """Track new topic partition end offset for monitoring lags.""" super().track_tp_end_offset(tp, offset) self.client.gauge('end_offset', offset, labels=self._format_label(tp))
[docs] def on_web_request_end(self, app: AppT, request: web.Request, response: Optional[web.Response], state: Dict, *, view: web.View = None) -> None: """Web server finished working on request.""" super().on_web_request_end(app, request, response, state, view=view) status_code = int(state['status_code']) self.client.increment(f'http_status_code.{status_code}') self.client.timing( 'http_response_latency', self.ms_since(state['time_end']))
def _normalize(self, name: str, *, pattern: Pattern = RE_NORMALIZE, substitution: str = RE_NORMALIZE_SUBSTITUTION) -> str: return pattern.sub(substitution, name) def _format_label(self, tp: Optional[TP] = None, stream: Optional[StreamT] = None, table: Optional[CollectionT] = None) -> Dict: labels = {} if tp is not None: labels.update(self._format_tp_label(tp)) if stream is not None: labels.update(self._format_stream_label(stream)) if table is not None: labels.update(self._format_table_label(table)) return labels def _format_tp_label(self, tp: TP) -> Dict: return {'topic': tp.topic, 'partition': tp.partition} def _format_stream_label(self, stream: StreamT) -> Dict: return {'stream': self._stream_label(stream)} def _stream_label(self, stream: StreamT) -> str: return self._normalize( stream.shortlabel.lstrip('Stream:'), ).strip('_').lower() def _format_table_label(self, table: CollectionT) -> Dict: return {'table': table.name}
[docs] @cached_property def client(self) -> DatadogStatsClient: """Return the datadog client.""" return self._new_datadog_stats_client()