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Elasticsearch Setup Apple MacBook Pro M1

Apple MacBook Pro M1, 32 GB, Ventura 13.2

Documentation based on comments in this Github Elasticsearch issue.

Install Homebrew

/usr/bin/wg-quick: line 32: resolvconf: command not found

This issue is caused while using the Wireguard in Ubuntu as the installation doesn't come with resolvconf or openresolv

Problem

sid@sid:~$ sudo wg-quick up /etc/wireguard/abc.conf
[sudo] password for sid: 
[#] ip link add abc type wireguard
[#] wg setconf abc /dev/fd/63

Vagrant and VMWare Tech Preview 21H1 on Apple M1 Pro

UPDATE November 20, 2022: VMWare Fusion 13

VMWare Fusion 13 is now released. Read Vagrant and VMWare Fusion 13 Player on Apple M1 Pro for the latest.

Summary

This document summarizes notes taken while to make the VMWare Tech preview work on Apple M1 Pro, it originated

NOTE: Guide to net/http timeouts
Also, here are some Transport settings you might want.

Although not explicitly stated, DNS resolution appears to be taken into consideration as part of the overall http.Client.Timeout setting. If you need to set your own DNS timeout, then it seems https://github.com/miekg/dns is a popular solution.

Additionally, it's important to realise how golang resolves hostnames to IPs (i.e. DNS resolution):
https://golang.org/pkg/net/#hdr-Name_Resolution

System

Debian 10 Buster headless

Chromium dependencies

Shared Libraries needed

$ sudo apt install libnss3 libatk1.0-0 libatk-bridge2.0-0 libcups2 libgbm1 libasound2 libpangocairo-1.0-0 libxss1 libgtk-3-0

Install nvm

Local user

在elasticsearch域的同一vpc下开一台ec2机器，安装nginx
准备ssl证书
配置nginx如下

server {
    listen 443 ssl http2;
    server_name $host;
    rewrite ^/$ https://$host/_plugin/kibana redirect;

    ssl_certificate /path/to/fullchain.pem;

	import os
	import base64
	import streamlit as st
	from openai import OpenAI

	# 设置环境变量和OpenAI客户端
	token = os.environ["GITHUB_TOKEN"]
	endpoint = "https://models.inference.ai.azure.com"
	model_name = st.sidebar.selectbox("选择模型:", ["gpt-4o", "gpt-4o-mini"])

	#!pip install torch
	#!pip install transformers
	#!pip install scikit-learn
	#!pip install numpy
	import json
	from sklearn.model_selection import train_test_split
	import random
	from datetime import datetime
	from transformers import BertTokenizer, BertModel
	import torch

	<?php

	namespace App\Support;

	class Currency
	{
	/**
	* Required base currency
	*
	* @var null

	#!/usr/bin/env bash
	echo=echo
	for cmd in echo /bin/echo; do
	$cmd >/dev/null 2>&1 \|\| continue

	if ! $cmd -e "" \| grep -qE '^-e'; then
	echo=$cmd
	break
	fi
	done