leapar leapar

docker ps -a
docker images
docker build -t tag --no-cache
docker run -i -t tag /bin/bash
docker cp containerid:/path localpath
docker save imageid > local.tar
docker load < local.tar
docker rm containerid
docker rmi imageid

客户端发送http请求，后端进行多个服务器转发。本例转发了3个服务器。

var https = require('https');
var httpProxy = require('http-proxy');
var http = require('http');

httpProxy.createProxyServer({
  target: 'https://app.datadoghq.com',
  agent: https.globalAgent,

metric:tag

http://localhost:4242/api/search/lookup?m=system.disk.in_use{uid=1}

http://localhost:4242/api/search/lookup?m=*{uid=1}

http://localhost:4242/api/query?start=1h-ago&m=sum:rate:system.disk.in_use{uid=1}

查询时间序列 http://app.datadoghq.com/api/v1/query?application_key=583f593e51279d513a6bf830c4ab50e6b28ce273&api_key=2961a4b138138ebf3ab35ec7575b6730&query=system.cpu.idle{*}by{host}&from=1487556595&to=1487656595

https://app.datadoghq.com/api/v1/query?application_key=583f593e51279d513a6bf830c4ab50e6b28ce273&api_key=2961a4b138138ebf3ab35ec7575b6730&query=avg:system.cpu.user{*}%20by%20{host},%20avg:apache.net.bytes{*}%20%2B%20100&from=1487556595&to=1487656595

主机的tag https://app.datadoghq.com/api/v1/tags/hosts?application_key=583f593e51279d513a6bf830c4ab50e6b28ce273&api_key=2961a4b138138ebf3ab35ec7575b6730

同事的内部分享, 个人觉得可以分享给大家，我很久前自己有个人部署和学习了解过zookeeper，但没太认真研究和思考，我知道，有机会，肯定还需要进一步学习zookeeper的

序言
目录规划
安装步骤 3.1 下载和解压 3.3 日志格式 3.4 配置文件 3.5 部署Zookeeper Server服务标识
启动和关闭

Spiceworks https://www.spiceworks.com

http://demo.accord5.com/trellis/admin.php?section=manage&act=settings&code=find&group=ticket

import _hashlib

def _reset_sys_path():
    # Clear generic sys.path[0]
    import sys, os
    resources = "/opt/datadog-agent-o/Datadog Agent.app/Contents/Resources/"
    while sys.path[0] == resources:
        del sys.path[0]

 [Software: ncurses] I | 2017-03-24T17:54:19+08:00 | Dirtied the cache
         [Software: zlib] I | 2017-03-24T17:54:19+08:00 | Building because `preparation' dirtied the cache
       [NetFetcher: zlib] I | 2017-03-24T17:54:19+08:00 | Cleaning project directory `/var/cache/omnibus/src/zlib'
       [NetFetcher: zlib] I | 2017-03-24T17:54:19+08:00 | Extracting `/var/cache/omnibus/cache/zlib-1.2.8.tar.gz' to `/var/cache/omnibus/src/zlib'
          [Builder: zlib] I | 2017-03-24T17:54:19+08:00 | Starting build
          [Builder: zlib] I | 2017-03-24T17:54:19+08:00 | Writing license file from https://gist.githubusercontent.com/remh/77877aa00b45c1ebc152/raw/372a65de9f4c4ed376771b8d2d0943da83064726/zlib.license to /opt/datadog-agent/licenses/zlib/zlib.license
          [Builder: zlib] I | 2017-03-24T17:54:22+08:00 | Adding License: 'https://gist.githubusercontent.com/remh/77877aa00b45c1ebc152/raw/372a65de9f4c4ed376771b8d2d0943da83064726/zlib.license': 2.4888s
          [Builder: zlib] I | 2017-03-24T17:5

	一、引言
	本文记录了困扰团队两周的HBase随机宕机事件的解决方案，并回顾了JVM GC调优基础知识，供各位参考。
	欢迎转载，请注明出处：
	http://blog.csdn.net/u010967382/article/details/42394031
	二、实验环境
	16台虚拟机，每台4G内存，1核CPU，400G硬盘
	Ubuntu 14.04 LTS (GNU/Linux 3.13.0-29-generic x86_64)
	CDH5.2.0套装（包括相应版本的Hadoop，HIVE，Hbase，Mahout，Sqoop，Zookeeper等）
	Java 1.7.0_60 64-Bit Server
	三、异常现场