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import json
from datetime import datetime, timedelta
from typing import Any, Dict, Generator, List, Optional
import boto3
from botocore.paginate import PageIterator
from mypy_boto3_xray.client import XRayClient
from mypy_boto3_xray.type_defs import TraceSummaryTypeDef
from pydantic import BaseModel
from retry import retry
class TraceSubsegment(BaseModel):
id: str # noqa: A003 VNE003 # id is a field we can't change
name: str
start_time: float
end_time: float
aws: Optional[dict] = None
subsegments: Optional[List["TraceSubsegment"]] = None
annotations: Optional[Dict[str, Any]] = None
metadata: Optional[Dict[str, Dict[str, Any]]] = None
class TraceDocument(BaseModel):
id: str # noqa: A003 VNE003 # id is a field we can't change
name: str
start_time: float
end_time: float
trace_id: str
parent_id: Optional[str] = None
aws: Dict
origin: str
subsegments: Optional[List[TraceSubsegment]] = None
class TraceFetcher:
default_exclude_seg_name: List = ["Initialization", "Invocation", "Overhead"]
def __init__(
self,
filter_expression: str,
start_date: datetime,
end_date: Optional[datetime] = None,
xray_client: Optional[XRayClient] = None,
exclude_segment_name: Optional[List[str]] = None,
resource_name: Optional[List[str]] = None,
origin: Optional[List[str]] = None,
minimum_traces: int = 1,
):
"""Fetch and expose traces from X-Ray based on parameters
Data is recursively fetched in the following order:
* Trace summaries
* Trace IDs
* Traces
* Segments
* Subsegments
* Nested Subsegments
Parameters
----------
filter_expression : str
AWS X-Ray Filter Expressions
see: https://docs.aws.amazon.com/xray/latest/devguide/xray-console-filters.html
start_date : datetime
Start date range to filter traces
end_date : Optional[datetime], optional
End date range to filter traces, by default 5 minutes past start_date
xray_client : Optional[XRayClient], optional
AWS X-Ray SDK Client, by default boto3.client('xray')
exclude_segment_name : Optional[List[str]], optional
Name of segments to exclude, by default ["Initialization", "Invocation", "Overhead"]
resource_name : Optional[List[str]], optional
Name of resource to filter traces (e.g., function name), by default None
origin : Optional[List[str]], optional
Trace origin name to filter traces, by default ["AWS::Lambda::Function"]
minimum_traces : int
Minimum number of traces to be retrieved before exhausting retry attempts
"""
self.filter_expression = filter_expression
self.start_date = start_date
self.end_date = end_date or self.start_date + timedelta(minutes=5)
self.xray_client = xray_client or boto3.client("xray")
self.trace_documents: Dict[str, TraceDocument] = {}
self.subsegments: List[TraceSubsegment] = []
self.exclude_segment_name = exclude_segment_name or self.default_exclude_seg_name
self.resource_name = resource_name
self.origin = origin or ["AWS::Lambda::Function"]
self.annotations: List[Dict[str, Any]] = []
self.metadata: List[Dict[str, Dict[str, Any]]] = []
self.minimum_traces = minimum_traces
paginator = self.xray_client.get_paginator("get_trace_summaries")
pages = paginator.paginate(
StartTime=self.start_date,
EndTime=self.end_date,
TimeRangeType="Event",
Sampling=False,
FilterExpression=self.filter_expression,
)
trace_ids = self._get_trace_ids(pages)
self.trace_documents = self._get_trace_documents(trace_ids)
self.subsegments = self._get_subsegments()
def get_annotation(self, key: str, value: Optional[any] = None) -> List:
return [
annotation
for annotation in self.annotations
if (value is not None and annotation.get(key) == value) or (value is None and key in annotation)
]
def get_metadata(self, key: str, namespace: str = "") -> List[Dict[str, Any]]:
seen = []
for meta in self.metadata:
metadata = meta.get(namespace, {})
if key in metadata:
seen.append(metadata)
return seen
def get_subsegment(self, name: str) -> List:
return [seg for seg in self.subsegments if seg.name == name]
def _find_nested_subsegments(self, subsegments: List[TraceSubsegment]) -> Generator[TraceSubsegment, None, None]:
"""Recursively yield any subsegment that we might be interested.
It excludes any subsegments contained in exclude_segment_name.
Since these are nested, subsegment name might be '## lambda_handler'.
It also populates annotations and metadata nested in subsegments.
Parameters
----------
subsegment : TraceSubsegment
subsegment to traverse
seen : List
list of subsegments to be updated
"""
for seg in subsegments:
if seg.name not in self.exclude_segment_name:
if seg.annotations:
self.annotations.append(seg.annotations)
if seg.metadata:
self.metadata.append(seg.metadata)
yield seg
if seg.subsegments:
# recursively iterate over any arbitrary number of subsegments
yield from self._find_nested_subsegments(seg.subsegments)
def _get_subsegments(self) -> List[TraceSubsegment]:
"""Find subsegments and potentially any nested subsegments
It excludes any subsegments contained in exclude_segment_name.
Since these are top-level, subsegment name might be 'Overhead/Invocation, etc.'.
Returns
-------
List[TraceSubsegment]
List of subsegments
"""
seen = []
for document in self.trace_documents.values():
if document.subsegments:
seen.extend(self._find_nested_subsegments(document.subsegments))
return seen
def _get_trace_ids(self, pages: PageIterator) -> List[str]:
"""Get list of trace IDs found
Parameters
----------
pages : PageIterator
Paginated streaming response from AWS X-Ray
Returns
-------
List[str]
Trace IDs
Raises
------
ValueError
When no traces are available within time range and filter expression
"""
summaries: List[TraceSummaryTypeDef] = [trace["TraceSummaries"] for trace in pages if trace["TraceSummaries"]]
if not summaries:
raise ValueError("Empty response from X-Ray. Repeating...")
trace_ids = [trace["Id"] for trace in summaries[0]] # type: ignore[index] # TypedDict not being recognized
if len(trace_ids) < self.minimum_traces:
raise ValueError(
f"Number of traces found doesn't meet minimum required ({self.minimum_traces}). Repeating...",
)
return trace_ids
def _get_trace_documents(self, trace_ids: List[str]) -> Dict[str, TraceDocument]:
"""Find trace documents available in each trace segment
Returns
-------
Dict[str, TraceDocument]
Trace documents grouped by their ID
"""
traces = self.xray_client.batch_get_traces(TraceIds=trace_ids)
documents: Dict = {}
segments = [seg for trace in traces["Traces"] for seg in trace["Segments"]]
for seg in segments:
trace_document = TraceDocument(**json.loads(seg["Document"]))
if trace_document.origin in self.origin or trace_document.name == self.resource_name:
documents[trace_document.id] = trace_document
return documents
@retry(ValueError, delay=5, jitter=1.5, tries=10)
def get_traces(
filter_expression: str,
start_date: datetime,
end_date: Optional[datetime] = None,
xray_client: Optional[XRayClient] = None,
exclude_segment_name: Optional[List[str]] = None,
resource_name: Optional[List[str]] = None,
origin: Optional[List[str]] = None,
minimum_traces: int = 1,
) -> TraceFetcher:
"""Fetch traces from AWS X-Ray
Parameters
----------
filter_expression : str
AWS X-Ray Filter Expressions
see: https://docs.aws.amazon.com/xray/latest/devguide/xray-console-filters.html
start_date : datetime
Start date range to filter traces
end_date : Optional[datetime], optional
End date range to filter traces, by default 5 minutes past start_date
xray_client : Optional[XRayClient], optional
AWS X-Ray SDK Client, by default boto3.client('xray')
exclude_segment_name : Optional[List[str]], optional
Name of segments to exclude, by default ["Initialization", "Invocation", "Overhead"]
resource_name : Optional[List[str]], optional
Name of resource to filter traces (e.g., function name), by default None
origin : Optional[List[str]], optional
Trace origin name to filter traces, by default ["AWS::Lambda::Function"]
minimum_traces : int
Minimum number of traces to be retrieved before exhausting retry attempts
Returns
-------
TraceFetcher
TraceFetcher instance with trace data available as properties and methods
"""
return TraceFetcher(
filter_expression=filter_expression,
start_date=start_date,
end_date=end_date,
xray_client=xray_client,
exclude_segment_name=exclude_segment_name,
resource_name=resource_name,
origin=origin,
minimum_traces=minimum_traces,
)