def submit_errors_metric(lambda_context):
"""Increment aws.lambda.enhanced.errors by 1
"""
if not are_enhanced_metrics_enabled():
return
lambda_metric(
"{}.errors".format(ENHANCED_METRICS_NAMESPACE_PREFIX),
1,
tags=get_enhanced_metrics_tags(lambda_context),
)
def submit_enhanced_metric(metric_name, lambda_context):
"""Submits the enhanced metric with the given name
Args:
metric_name (str): metric name w/o enhanced prefix i.e. "invocations" or "errors"
lambda_context (dict): Lambda context dict passed to the function by AWS
"""
if not are_enhanced_metrics_enabled():
logger.debug(
"Not submitting enhanced metric %s because enhanced metrics are disabled",
metric_name,
)
return
tags = get_enhanced_metrics_tags(lambda_context)
metric_name = "aws.lambda.enhanced." + metric_name
# Enhanced metrics always use an async submission method, (eg logs or extension).
lambda_metric(metric_name, 1, timestamp=None, tags=tags, force_async=True)
def submit_enhanced_metric(metric_name, lambda_context):
"""Submits the enhanced metric with the given name
Args:
metric_name (str): metric name w/o enhanced prefix i.e. "invocations" or "errors"
lambda_context (dict): Lambda context dict passed to the function by AWS
"""
if not are_enhanced_metrics_enabled():
logger.debug(
"Not submitting enhanced metric %s because enhanced metrics are disabled",
metric_name,
)
return
# Enhanced metrics are always written to logs
write_metric_point_to_stdout(
"{}.{}".format(ENHANCED_METRICS_NAMESPACE_PREFIX, metric_name),
1,
tags=get_enhanced_metrics_tags(lambda_context),
)