Spencer Wilson spencerwilson

Two kinds of samplers

Consider two broad goals in sampling:

These can be treated separately. Doing so may yield a simpler and more flexible conceptual foundation for sampling.

Define a balancer to be a sampler that does the following: For each input trace,

This doc compares the capabilities of popular telemetry sampling systems. The dimensions that are compared:

Temporal resolution: The time range that the limiting occurs on. E.g., limit the number of...

Degree of limiting: In a steady state with spans created at a rate R span/s that is greater than the desired limit,

	/**
	* @typedef Point
	* A pair of numbers suitable for plotting.
	*/

	/**
	* @param {Array.<number>} arr
	* n observations of a continuous random variable (RV).
	* @returns {Array.<Point>}
	* The empirical probabilities of the given observed values of the RV.

	#!/usr/bin/env python

	import numpy as np
	import pandas as pd
	from sklearn import svm

	FILE_NAME = 'mosteller-wallace-federalist-papers.csv'
	STOP_WORDS = ['a', 'an']

	# Rows are samples, cols are [...word_count, AUTHOR, CODE_NUMER].

	# configuration file /etc/nginx/nginx.conf:
	#Elastic Beanstalk Nginx Configuration File

	load_module /home/ec2-user/otel_ngx_module.so;

	user nginx;
	error_log /var/log/nginx/error.log warn;
	pid /var/run/nginx.pid;
	worker_processes auto;
	worker_rlimit_nofile 200000;

	import { Context, SpanAttributes } from '@opentelemetry/api';
	import {
	ReadableSpan,
	Span,
	SpanProcessor,
	} from '@opentelemetry/sdk-trace-base';

	/**
	* Intercepts `onEnd` to modify a finished Span's attributes.
	* Otherwise delegates completely to a child SpanProcessor.