magnetikonline

Nginx FastCGI response buffer sizes

By default when Nginx starts receiving a response from a FastCGI backend (such as PHP-FPM) it will buffer the response in memory before delivering it to the client. Any response larger than the set buffer size is saved to a temporary file on disk.

This process is outlined at the Nginx ngx_http_fastcgi_module page manual page.

• Introduction
• Determine actual FastCGI response sizes
• Setting the buffer size
• Verifying results

krakjoe

Easy pthreads Pools

The final solution !!

Since the first version of pthreads, PHP has had the ability to initialize Worker threads for users. Onto those Worker threads are stacked objects of class Stackable for execution concurrently.

The objects stacked onto workers do not have their reference counts changed, pthreads forces the user to maintain the reference counts in userland, for the extremely good reason that this enables the programmer to keep control of memory usage; and so, execute indefinitely.

This is the cause of much heartache for newcomers to pthreads; if you do not maintain references properly you will, definitely, experience segmentation faults.

mattiaslundberg

# Install ARCH Linux with encrypted file-system and UEFI
# The official installation guide (https://wiki.archlinux.org/index.php/Installation_Guide) contains a more verbose description.

# Download the archiso image from https://www.archlinux.org/
# Copy to a usb-drive
dd if=archlinux.img of=/dev/sdX bs=16M && sync # on linux

# Boot from the usb. If the usb fails to boot, make sure that secure boot is disabled in the BIOS configuration.

# Set swedish keymap

denji

Moved to git repository: https://github.com/denji/nginx-tuning

NGINX Tuning For Best Performance

For this configuration you can use web server you like, i decided, because i work mostly with it to use nginx.

Generally, properly configured nginx can handle up to 400K to 500K requests per second (clustered), most what i saw is 50K to 80K (non-clustered) requests per second and 30% CPU load, course, this was 2 x Intel Xeon with HyperThreading enabled, but it can work without problem on slower machines.

You must understand that this config is used in testing environment and not in production so you will need to find a way to implement most of those features best possible for your servers.

anderser

#!/usr/bin/env python

import sys
import argparse
import networkx as nx
import community
from networkx.readwrite import json_graph


def graphmltojson(graphfile, outfile):

krakjoe

Multi-Threading in PHP with pthreads

A Brief Introduction to Multi-Threading in PHP

• Foreword
• Execution
• Sharing
• Synchronization
• Pitfalls

algal

#
# A CORS (Cross-Origin Resouce Sharing) config for nginx
#
# == Purpose
#
# This nginx configuration enables CORS requests in the following way:
# - enables CORS just for origins on a whitelist specified by a regular expression
# - CORS preflight request (OPTIONS) are responded immediately
# - Access-Control-Allow-Credentials=true for GET and POST requests

kiela

root@rizzo ~$ uname -a
FreeBSD rizzo.heimdall.pl 9.1-RELEASE FreeBSD 9.1-RELEASE #0: Wed Mar 13 21:02:32 CET 2013 root@rizzo.heimdall.pl:/sys/amd64/compile/rizzo  amd64
root@rizzo ~$ kldload opensolaris
root@rizzo ~$ kldload zfs
root@rizzo ~$ kldload geom_eli
root@rizzo ~$ gpart destroy -F da0
da0 destroyed
root@rizzo ~$ gpart create -s gpt da0
da0 created
root@rizzo ~$ gpart add -t freebsd-zfs -a 4096 da0

rantav

A few show tricks to find slow queries in mongodb

Enable profiling

First, you have to enable profiling

> db.setProfilingLevel(1)

Now let it run for a while. It collects the slow queries ( > 100ms) into a capped collections, so queries go in and if it's full, old queries go out, so don't be surprised that it's a moving target...