IshaanAdarsh

Google Summer of Code 2023 Final Work Product

Introduction

wuputah

Hydra Performance Microbenchmark

Important: This microbenchmark is not intended to represent any real workload. Compression ratios, and therefore performance, will depend heavily on the specific workload. This is only for the purpose of illustrating a "columnar friendly" contrived workload that showcases the benefits of columnar.

Schema

mbierman

#!/bin/bash
# v 2.1.0
  
syslog=/etc/rsyslog.d/09-externalserver.conf
# this logs notice and above. use *.* log everything. 
filter=*.notice
server=192.168.0.19 # Change the server to the IP of your syslog server.
port=514
hostname=firewalla
valid=$(grep "$server:$port" $syslog 2>/dev/null)

joelonsql

🗺🐘 1000+ PostgreSQL EXTENSIONs

This is a list of URLs to PostgreSQL EXTENSION repos, listed in alphabetical order of parent repo, with active forks listed under each parent.

⭐️ >= 10 stars
⭐️⭐️ >= 100 stars
⭐️⭐️⭐️ >= 1000 stars
Numbers of stars might not be up-to-date.

satrobit

Introduction

If you're reading this, chances are you have some idea of eBPF and XDP. In this article, we'll write an eBPF program that will count and categorize packets based on the destination port.

eBPF

Writing low-level tracing, monitoring, or network programs in Linux is not easy. Through all the layers of the kernel, people have been squeezing every bit of performance they could get.

And that's where eBPF comes in. eBPF is basically an extended and modern variation of BPF which is like a virtual machine inside the Linux kernel. It can execute user-defined programs inside a sandbox in the kernel.

These programs can be executed in various hook points but we will focus on XDP for now.

mashhoodr

addEventListener('fetch', event => {
  event.respondWith(handleRequest(event.request))
})

/**
 * Respond to the request
 * adapted from https://github.com/xiaoyang-liu-cs/workers-proxy
 * @param {Request} request
 */
async function handleRequest(request) {

alexellis

Tutorial - Connect your krustlet to any Kubernetes cluster with inlets

• Provision a cluster on DigitalOcean Kubernetes or AKS

• Prepare your krustlet and get its certificates

• Create a Kubernetes secret for inlets

export TOKEN=$(head -c 16 /dev/urandom |shasum|cut -d- -f1)

carlwgeorge

# https://docs.ansible.com/ansible/latest/modules/dconf_module.html
#
# To determine what dconf keys and values to use, you can run `dconf watch /`
# in a terminal as you make changes in settings or tweaks.  You can also use
# `dconf read <key>` and `dconf write <key> <value>` to experiment with various
# settings.  The dconf-editor application is also useful for exploring various
# keys along with their descriptions.

- hosts: localhost
  tasks:

sbernard31

#define KBUILD_MODNAME "foo"
#include <uapi/linux/bpf.h>
#include <linux/bpf.h>
#include <linux/icmp.h>
#include <linux/if_ether.h>
#include <linux/if_vlan.h>
#include <linux/in.h>
#include <linux/ip.h>
#include <linux/tcp.h>
#include <linux/udp.h>

dannguyen

Demo of Google text-to-speech Wavenet API on a NYT article

Was curious if Google's text-to-speech API might be good enough for generating audio versions of stories on-the-fly. Google has offered traditional computer voices for awhile, but last year made available their premium WaveNet voices, which are trained using audio recorded from human speakers, and are purportedly capable of mimicking natural-sounding inflection and rhythm.

tl;dr results

Pretty good...but I honestly can't tell the difference between the standard voice and the WaveNet version, at least when it comes to intonation and inflection. The first 2 grafs of this NYT story, roughly 85 words/560 characters, took less than 2 seconds to process. The result in both cases is a 37-second second audio file.

• The M