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fix(dsm): set dsm checkpoint for all records in event #643

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c0906a0
set checkpoint for all messages one loop approach
michael-zhao459 Aug 4, 2025
8230b07
fix lint
michael-zhao459 Aug 4, 2025
e2cd3c5
formatting stuff
michael-zhao459 Aug 4, 2025
5cf2059
better approach with indexes
michael-zhao459 Aug 4, 2025
90480bb
changed approach returning early, rename to dd_ctx
michael-zhao459 Aug 5, 2025
6936bba
keep APM record[0] implementation
michael-zhao459 Aug 5, 2025
268c1e5
Keep APM records[0] approach
michael-zhao459 Aug 5, 2025
2f8dfaa
add more batch processing tests
michael-zhao459 Aug 6, 2025
63e41cb
want to keep looping
michael-zhao459 Aug 6, 2025
e5a0903
clean up if statement
michael-zhao459 Aug 6, 2025
103ffa1
structure code based on comment
michael-zhao459 Aug 6, 2025
6c2fbbd
Suggested loop structure
michael-zhao459 Aug 7, 2025
2067363
same structure with kinesis
michael-zhao459 Aug 7, 2025
f2b2dc3
return early
michael-zhao459 Aug 7, 2025
1a1a1d9
suggested refactoring
michael-zhao459 Aug 8, 2025
6bcbd0a
more tests
michael-zhao459 Aug 8, 2025
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229 changes: 125 additions & 104 deletions datadog_lambda/tracing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -248,91 +248,100 @@ def extract_context_from_sqs_or_sns_event_or_context(
except Exception:
logger.debug("Failed extracting context as EventBridge to SQS.")

try:
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if context is extracted from event bridge, we don't set a checkpoint. Is that expected?

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The tracers never inject DSM context in the case of event bridge or step functions. I'm not sure this is the PR to be adding the functionality for these event types

first_record = event.get("Records")[0]
source_arn = first_record.get("eventSourceARN", "")

# logic to deal with SNS => SQS event
if "body" in first_record:
body_str = first_record.get("body")
try:
body = json.loads(body_str)
if body.get("Type", "") == "Notification" and "TopicArn" in body:
logger.debug("Found SNS message inside SQS event")
first_record = get_first_record(create_sns_event(body))
except Exception:
pass

msg_attributes = first_record.get("messageAttributes")
if msg_attributes is None:
sns_record = first_record.get("Sns") or {}
# SNS->SQS event would extract SNS arn without this check
if event_source.equals(EventTypes.SNS):
source_arn = sns_record.get("TopicArn", "")
msg_attributes = sns_record.get("MessageAttributes") or {}
dd_payload = msg_attributes.get("_datadog")
if dd_payload:
# SQS uses dataType and binaryValue/stringValue
# SNS uses Type and Value
dd_json_data = None
dd_json_data_type = dd_payload.get("Type") or dd_payload.get("dataType")
if dd_json_data_type == "Binary":
import base64
context = None
records = (
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Maybe let's have records always be: event.get("Records", []), however, in the loop, we can break early if data streams is disabled.

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if index == 0:
     do apm stuff
     if data streams is enabled:
         break

event.get("Records", [])
if config.data_streams_enabled
else [event.get("Records")[0]]
)
for idx, record in enumerate(records):
try:
source_arn = record.get("eventSourceARN", "")
dsm_data = None
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same as bellow, dsm_data is not specific to data streams here. I would name it same as bellow, dd_ctx, or something like that.


# logic to deal with SNS => SQS event
if "body" in record:
body_str = record.get("body")
try:
body = json.loads(body_str)
if body.get("Type", "") == "Notification" and "TopicArn" in body:
logger.debug("Found SNS message inside SQS event")
record = get_first_record(create_sns_event(body))
except Exception:
pass

msg_attributes = record.get("messageAttributes")
if msg_attributes is None:
sns_record = record.get("Sns") or {}
# SNS->SQS event would extract SNS arn without this check
if event_source.equals(EventTypes.SNS):
source_arn = sns_record.get("TopicArn", "")
msg_attributes = sns_record.get("MessageAttributes") or {}
dd_payload = msg_attributes.get("_datadog")
if dd_payload:
# SQS uses dataType and binaryValue/stringValue
# SNS uses Type and Value
# fmt: off
dd_json_data = None
dd_json_data_type = dd_payload.get("Type") or dd_payload.get("dataType")
if dd_json_data_type == "Binary":
import base64

dd_json_data = dd_payload.get("binaryValue") or dd_payload.get("Value")
if dd_json_data:
dd_json_data = base64.b64decode(dd_json_data)
elif dd_json_data_type == "String":
dd_json_data = dd_payload.get("stringValue") or dd_payload.get("Value")
# fmt: on
else:
logger.debug(
"Datadog Lambda Python only supports extracting trace"
"context from String or Binary SQS/SNS message attributes"
)

dd_json_data = dd_payload.get("binaryValue") or dd_payload.get("Value")
if dd_json_data:
dd_json_data = base64.b64decode(dd_json_data)
elif dd_json_data_type == "String":
dd_json_data = dd_payload.get("stringValue") or dd_payload.get("Value")
dd_data = json.loads(dd_json_data)

if is_step_function_event(dd_data):
try:
return extract_context_from_step_functions(dd_data, None)
except Exception:
logger.debug(
"Failed to extract Step Functions context from SQS/SNS event."
)
if idx == 0:
context = propagator.extract(dd_data)
dsm_data = dd_data
else:
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in this else, dsm_data is not set. Is that an issue?

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@michael-zhao459 michael-zhao459 Aug 5, 2025 •
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Not an issue. I checked in dd-trace-py and DSM never injects context into attributes.AWSTraceHeader, we can just set a checkpoint with None

logger.debug(
"Datadog Lambda Python only supports extracting trace"
"context from String or Binary SQS/SNS message attributes"
)
# Handle case where trace context is injected into attributes.AWSTraceHeader
# example:Root=1-654321ab-000000001234567890abcdef;Parent=0123456789abcdef;Sampled=1
attrs = event.get("Records")[0].get("attributes")
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here, it's accessing records[0] again. I would put this whole section in an else if idx == 0 (line 315)

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Suggested change
attrs = event.get("Records")[0].get("attributes")
attrs = record.get("attributes")

if attrs:
x_ray_header = attrs.get("AWSTraceHeader")
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maybe put this logic in the extract_context I suggested above. The extract_context can take an argument: extract_from_xray?

(extract_context is probably not a great name, I let you find a better one)

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Hmm. I might be misinterpreting but I'm not sure we should have one function return both a Context() object and the return of a json.loads(). I ended up splitting the x-ray extractor into another helper, let me know what you think

if x_ray_header:
x_ray_context = parse_xray_header(x_ray_header)
trace_id_parts = x_ray_context.get("trace_id", "").split("-")
if len(trace_id_parts) > 2 and trace_id_parts[2].startswith(
DD_TRACE_JAVA_TRACE_ID_PADDING
):
# If it starts with eight 0's padding,
# then this AWSTraceHeader contains Datadog injected trace context
logger.debug(
"Found dd-trace injected trace context from AWSTraceHeader"
)
if idx == 0:
context = Context(
trace_id=int(trace_id_parts[2][8:], 16),
span_id=int(x_ray_context["parent_id"], 16),
sampling_priority=float(x_ray_context["sampled"]),
)
except Exception as e:
logger.debug("The trace extractor returned with error %s", e)

if dd_json_data:
dd_data = json.loads(dd_json_data)
# Set DSM checkpoint once per record
_dsm_set_checkpoint(dsm_data, event_type, source_arn)

if is_step_function_event(dd_data):
try:
return extract_context_from_step_functions(dd_data, None)
except Exception:
logger.debug(
"Failed to extract Step Functions context from SQS/SNS event."
)
context = propagator.extract(dd_data)
_dsm_set_checkpoint(dd_data, event_type, source_arn)
return context
else:
# Handle case where trace context is injected into attributes.AWSTraceHeader
# example: Root=1-654321ab-000000001234567890abcdef;Parent=0123456789abcdef;Sampled=1
attrs = event.get("Records")[0].get("attributes")
if attrs:
x_ray_header = attrs.get("AWSTraceHeader")
if x_ray_header:
x_ray_context = parse_xray_header(x_ray_header)
trace_id_parts = x_ray_context.get("trace_id", "").split("-")
if len(trace_id_parts) > 2 and trace_id_parts[2].startswith(
DD_TRACE_JAVA_TRACE_ID_PADDING
):
# If it starts with eight 0's padding,
# then this AWSTraceHeader contains Datadog injected trace context
logger.debug(
"Found dd-trace injected trace context from AWSTraceHeader"
)
return Context(
trace_id=int(trace_id_parts[2][8:], 16),
span_id=int(x_ray_context["parent_id"], 16),
sampling_priority=float(x_ray_context["sampled"]),
)
# Still want to set a DSM checkpoint even if DSM context not propagated
_dsm_set_checkpoint(None, event_type, source_arn)
return extract_context_from_lambda_context(lambda_context)
except Exception as e:
logger.debug("The trace extractor returned with error %s", e)
# Still want to set a DSM checkpoint even if DSM context not propagated
_dsm_set_checkpoint(None, event_type, source_arn)
return extract_context_from_lambda_context(lambda_context)
return context if context else extract_context_from_lambda_context(lambda_context)


def _extract_context_from_eventbridge_sqs_event(event):
Expand Down Expand Up @@ -393,30 +402,42 @@ def extract_context_from_kinesis_event(event, lambda_context):
Set a DSM checkpoint if DSM is enabled and the method for context propagation is supported.
"""
source_arn = ""
try:
record = get_first_record(event)
source_arn = record.get("eventSourceARN", "")
kinesis = record.get("kinesis")
if not kinesis:
return extract_context_from_lambda_context(lambda_context)
data = kinesis.get("data")
if data:
import base64

b64_bytes = data.encode("ascii")
str_bytes = base64.b64decode(b64_bytes)
data_str = str_bytes.decode("ascii")
data_obj = json.loads(data_str)
dd_ctx = data_obj.get("_datadog")
if dd_ctx:
context = propagator.extract(dd_ctx)
_dsm_set_checkpoint(dd_ctx, "kinesis", source_arn)
return context
except Exception as e:
logger.debug("The trace extractor returned with error %s", e)
# Still want to set a DSM checkpoint even if DSM context not propagated
_dsm_set_checkpoint(None, "kinesis", source_arn)
return extract_context_from_lambda_context(lambda_context)
records = (
[get_first_record(event)]
if not config.data_streams_enabled
else event.get("Records")
)
context = None
for idx, record in enumerate(records):
dsm_data = None
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this is not specific to dsm, it's dd_ctx

try:
source_arn = record.get("eventSourceARN", "")
kinesis = record.get("kinesis")
if not kinesis:
context = (
extract_context_from_lambda_context(lambda_context)
if idx == 0
else context
)
_dsm_set_checkpoint(None, "kinesis", source_arn)
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we are setting a checkpoint kinesis if not kinesis, I think the name kinesis is wrong, because this code is a bit confusing.

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@michael-zhao459 michael-zhao459 Aug 5, 2025 •
edited
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hmm. This is deep enough inside the extract function where we believe that the event source is from Kinesis from parsing beforehand. However, all AWS documentation says Kinesis lambda event should have this field. To my understanding, this check is for lambda synchronous invocations with records that match Kinesis, but doesn't actually come from a Kinesis stream. @DataDog/apm-serverless Can you help confirm why this check is here in the first place?

continue
data = kinesis.get("data")
if data:
import base64

b64_bytes = data.encode("ascii")
str_bytes = base64.b64decode(b64_bytes)
data_str = str_bytes.decode("ascii")
data_obj = json.loads(data_str)
dd_ctx = data_obj.get("_datadog")
if dd_ctx:
if idx == 0:
context = propagator.extract(dd_ctx)
dsm_data = dd_ctx
except Exception as e:
logger.debug("The trace extractor returned with error %s", e)
_dsm_set_checkpoint(dsm_data, "kinesis", source_arn)
return context if context else extract_context_from_lambda_context(lambda_context)


def _deterministic_sha256_hash(s: str, part: str) -> int:
Expand Down
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