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使用govanityurls让私有代码仓库中的go包支持go get

定制Go Package的Go Get导入路径》一文中我们讲到了通过使用govanityurls服务,我们可以定制go package的go get导入路径。不过,govanityurls的用途还不止这些,它还可以让你的私有代码仓库中的go package支持go get。

众所周知,开源的Go package一般分布在github、bitbucket等站点,但商业组织内部闭源的Go package则不一定都托管在像github这样的代码管理服务站点上,虽然使用github private repository服务的组织和个人正在日益增多(国内用户可能会用到码云git.oschina.net、code.csdn.net等)。很多企业或组织会自己搭建私有代码仓库(一般使用git)来满足组织内部的代码版本管理需求,而目前市面上主流且成熟的支持本地搭建的代码管理软件包括gitlabbitbucket等。那么如何让go get支持从这些私有代码仓库中获取go package呢?本文将来回答这个问题。

很多人会问:为什么要让私有仓库中的go package支持go get呢?直接git clone不就行了么?用过go get的gopher们都清楚:go get可以自动分析go package的依赖,并帮助自动下载相关依赖。虽然go get下载依赖有各种局限,但没有go get的帮助,手工去下载各种依赖会更加“痛苦”。好了,接下来我们将用一个具体的例子来演示一下go get是如何一步步的支持从私有代码仓库下载Go包的。

我所在的开发团队使用的代码仓库就是在阿里云ECS上自行搭建的,使用的是Atlassian出品的bitbucket。虽然bitbucket在在线服务市场占有率可能不及github,但在线下自建代码仓库方面,bitbucket也是不可小觑的重量级选手。

不过bitbucket如何安装不是这里的重点,bitbucket的安装方法参考其官网manual即可。安装后的bitbucket 仓库中的Project foo的repository bar的clone地址样式如下:

http://bitbucket_ip:bitbucket_port/scm/foo/bar.git

注意:我们的bitbucket仓库没有启用https,auth的方式采用的是普通的user和password方式(bitbucket支持客户端SSH key方式访问repository)。除此之外,我们并没有为bitbucket仓库绑定域名。

一、尝试go get“裸库”

我们以foo这个在demo project下的go repository为例,这个repository的clone地址为:http://10.11.12.13:31990/scm/demo/foo.git,于是我们先来尝试一下直接go get这个未经任何“修饰”的“裸库”(由于没有使用https,因此我们在go get的命令行参数中增加了-insecure选项):

# go get -insecure -v 10.11.12.13:31990/scm/demo/foo.git
# cd .; git ls-remote git://10.11.12.13:31990/scm/demo/foo
fatal: protocol error: bad line length character: HTTP
# cd .; git ls-remote https://10.11.12.13:31990/scm/demo/foo
fatal: unable to access 'https://10.11.12.13:31990/scm/demo/foo/': gnutls_handshake() failed: An unexpected TLS packet was received.
# cd .; git ls-remote http://10.11.12.13:31990/scm/demo/foo
fatal: could not read Username for 'http://10.11.12.13:31990': terminal prompts disabled
# cd .; git ls-remote git+ssh://10.11.12.13:31990/scm/demo/foo
ssh_exchange_identification: Connection closed by remote host
fatal: Could not read from remote repository.

Please make sure you have the correct access rights
and the repository exists.
# cd .; git ls-remote ssh://10.11.12.13:31990/scm/demo/foo
ssh_exchange_identification: Connection closed by remote host
fatal: Could not read from remote repository.

Please make sure you have the correct access rights
and the repository exists.
10.11.12.13:31990/scm/demo/foo.git (download)
root@10.11.12.13's password:

以失败告终!我们来分析一下go get -v输出的日志! 通过日志可以看出go get先后尝试用不同访问方式去获取repository数据,尝试的顺序依次是:git、https、http和git+ssh,结果都无功而返。

  • 对于git方式,我们并未开通bitbucket的git访问服务,失败是必然的;
  • 对于https,我们的bitbucket server同样未予支持;
  • 对于http方式,日志提示:” terminal prompts disabled”,即客户端终端的提示被禁了,也就是无法输入user和password;
  • 对于最后一种git+ssh,由于没有ssh登录bitbucket主机的密码也失败了。

在四种访问方式中,http是我们期望的。为了http方式能成功获取数据,我们需要开启termnial prompts(通过GIT_TERMINAL_PROMPT=1),于是我们再次尝试:

# GIT_TERMINAL_PROMPT=1 go get -v -insecure 10.11.12.13:31990/scm/demo/foo.git
# cd .; git ls-remote git://10.11.12.13:31990/scm/demo/foo
fatal: Could not read from remote repository.

Please make sure you have the correct access rights
and the repository exists.
# cd .; git ls-remote https://10.11.12.13:31990/scm/demo/foo
fatal: unable to access 'https://10.11.12.13:31990/scm/demo/foo/': gnutls_handshake() failed: The TLS connection was non-properly terminated.
Username for 'http://10.11.12.13:31990': tonybai
Password for 'http://tonybai@10.11.12.13:31990':
10.11.12.13:31990/scm/demo/foo.git (download)
Username for 'http://10.11.12.13:31990': tonybai
Password for 'http://tonybai@10.11.12.13:31990':
package foo/config: unrecognized import path "foo/config" (import path does not begin with hostname)
package foo/routers: unrecognized import path "foo/routers" (import path does not begin with hostname)
github.com/mattes/migrate (download)
package github.com/mattes/migrate/driver/mysql: cannot find package "github.com/mattes/migrate/driver/mysql" in any of:
    /root/.bin/go18/src/github.com/mattes/migrate/driver/mysql (from $GOROOT)
    /root/go/src/github.com/mattes/migrate/driver/mysql (from $GOPATH)

我们看到这次go get在尝试http访问repository时,我们有机会输入user和password了,go get也成功了!至于下面的“unrecognized import path” error那是由于repository在GOPATH下的位置变更导致的。我们查看一下已经下载到本地的foo repository:

# tree -L 1 10.11.12.13\:31990/scm/demo/foo.git/
10.11.12.13:31990/scm/demo/foo.git/
├── foo.json
├── foo.yaml
├── conf
├── config
├── controllers
├── Dockerfile
├── errors
├── front-static
├── index
├── main.go
├── Makefile
├── migrations
├── models
├── README
├── routers
├── service
├── static
├── tests
├── topic
├── utils
├── vendor
├── views
└── websocket
17 directories, 6 files

虽然go get成功了, 但对于gopher来讲,foo下package的导入路径变成了:

import 10.11.12.13:31990/scm/demo/foo.git/some-package

这种格式、这种长度的导入路径是无法接受的。那我们该如何解决呢?

一种方法就是在bitbucket server端进行配置,通过为私有镜像仓库赋予域名的方式来去除import path中ip、port、不必要的前缀路径:scm/demo以及不必要的repository名中的后缀”.git”。但这种配置方式可能是非常复杂的,且是与你使用的git server软件相关的:bitbucket可能有bitbucket的配置方法,换作gitlab,可能就需要另外一种配置方法了。

另外一种方法就是用govanityurls来屏蔽server端复杂的配置,也屏蔽了与git server软件的相关性。

二、使用govanityurls让私有代码仓库中的go包支持go get

在《定制Go Package的Go Get导入路径》一文中,我们已经详细说明了govanityurls的使用和配置方法,这里就不赘述了,仅给出必要配置。

1、配置和启动govanityurls

这里我们使用pkg.tonybai.com这个域名来作为tonybai.com下面所有go package的导入路径的前缀,以foo package为例,它的导入路径将为”import pkg.tonybai.com/foo”,这样我们的vanity.yaml的配置如下:

/foo:
        repo: http://10.11.12.13:31990/scm/demo/foo.git

启动govanityurls:

$ nohup govanityurls -host pkg.tonybai.com &

2、配置nginx并做域名重指向

在我的环境中,我将govanityurls部署到与bitbucket相同的server上了。在这台主机上,我们配置一下nginx,让govanityurls的服务以80端口呈现:

# cat /etc/nginx/conf.d/default.conf
server {
        listen 80;
        server_name pkg.tonybai.com;

        location / {
                proxy_pass http://10.11.12.13:8080;
                proxy_redirect off;
                proxy_set_header Host $host;
                proxy_set_header X-Real-IP $remote_addr;
                proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        }
}

重启nginx使配置生效:nginx -s reload

3、验证

到目前为止foo这个repo的go get path变成了pkg.tonybai.com/foo了,我们来试着go get一下:

# GIT_TERMINAL_PROMPT=1  go get -insecure -v pkg.tonybai.com/foo
Fetching https://pkg.tonybai.com/foo?go-get=1
Parsing meta tags from https://pkg.tonybai.com/foo?go-get=1 (status code 200)
get "pkg.tonybai.com/foo": found meta tag main.metaImport{Prefix:"pkg.tonybai.com/foo", VCS:"git", RepoRoot:"http://10.11.12.13:31990/scm/demo/foo.git"} at https://pkg.tonybai.com/foo?go-get=1
tonybai.com/foo (download)
Password for 'http://10.11.12.13:31990':

package foo/config: unrecognized import path "foo/config" (import path does not begin with hostname)
package foo/routers: unrecognized import path "foo/routers" (import path does not begin with hostname)
github.com/mattes/migrate (download)
package github.com/mattes/migrate/driver/mysql: cannot find package "github.com/mattes/migrate/driver/mysql" in any of:
    /root/.bin/go18/src/github.com/mattes/migrate/driver/mysql (from $GOROOT)
    /root/go/src/github.com/mattes/migrate/driver/mysql (from $GOPATH)

go get成功!查看一下本地foo的repository情况:

# tree -L 1 go/src/pkg.tonybai.com/foo
go/src/pkg.tonybai.com/foo
├── foo.json
├── foo.yaml
├── conf
├── config
├── controllers
├── Dockerfile
├── errors
├── front-static
├── index
├── main.go
├── Makefile
├── migrations
├── models
├── README
├── routers
├── service
├── static
├── tests
├── topic
├── utils
├── vendor
├── views
└── websocket

17 directories, 6 files

三、小结

  • 通过govanityurls,我们可以很容易让私有代码仓库中的go包支持go get;
  • 对于本身就不支持go get的git server,那govanityurls也是无能为力的。

微博:@tonybai_cn
微信公众号:iamtonybai
github.com: https://github.com/bigwhite

定制Go Package的Go Get导入路径

近期Go team的组员Jaana B. Dogan,网名:rakyll开源了一个小工具:Go Vanity URLs。这个小工具可以帮助你快速为你的Go package定制Go get的导入路径(同样也是package被使用时的import路径)。

说到go package的go get导入路径,我们最常见和常使用的domain name就是github.com了,比如:beego包的go get导入路径就是 go get github.com/astaxie/beego。我们还经常看到一些包,它们的导入路径很特殊,比如:go get golang.org/x/net、go get gopkg.in/yaml.v2等(虽然net、yaml这些包实际的repo也是存在于github.com上的),这些就是定制化的package import path,它们有诸多好处:

  • 可以为package设置canonical import path ,即权威导入路径

    这是在Go 1.4版本中加入的概念。Go package多托管在几个知名的代码管理网站,比如:github.com、bitbucket.org等,这样默认情况下package的import path就是github.com/xxx/package、bitbucket.org/xxx/package等。一旦某个网站关门大吉了,那package代码势必要迁移到其他站点,这样package的import path就要发生改变,这会给package的用户造成诸多不便,比如之前的code.google.com关闭就给广大的gopher带来了很大的“伤害”。canonical import path就可以解决这个问题。package的用户只需要使用package的canonical import path,这样无论package的实际托管网站在哪,对package的用户都不会带来影响。

  • 便于组织和个人对package的管理

    组织和个人可以将其分散托管在不同代码管理网站的package统一聚合到组织的官网名下或个人的域名下,比如:golang.org/x/net、gopkg.in/xxx等。

  • package的import路径可以更短、更简洁

    有些时候,github.com上的go package的import path很长、很深,并不便于查找和书写,通过定制化import path,我们可以使用更短、更简洁的域名来代替github.com仓库下的多级路径。

不过rakyll提供的govanityurls仅能运行于Google的app engine上,这对于国内的Gopher们来说是十分不便的,甚至是不可用的,于是这里fork了rakyll的repo,并做了些许修改,让govanityurls可以运行于普通的vps主机上。

一、govanityurls原理

govanityurls的原理十分简单,它本身就好比一个“导航”服务器。当go get将请求发送给govanityurls时,govanityurls将请求中的repo的真实地址返回给go get,后续go get再从真实的repo地址获取package数据。

img{512x368}

可以看出go get第一步是尝试获取自定义路径的包的真实地址,govanityurls将返回一个类似如下内容的http应答(针对go get tonybai.com/gowechat请求):

<!DOCTYPE html>
<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8"/>
<meta name="go-import" content="tonybai.com/gowechat git https://github.com/bigwhite/gowechat">
<meta name="go-source" content="tonybai.com/gowechat ">
<meta http-equiv="refresh" content="0; url=https://godoc.org/tonybai.com/gowechat">
</head>
<body>
Nothing to see here; <a href="https://godoc.org/tonybai.com/gowechat">see the package on godoc</a>.
</body>
</html>

二、使用govanityurls

关于govanityurls的使用,可以参考其README.md,这里以一个demo来作为govanityurls的使用说明。

1、安装govanityurls

安装方法:

$go get github.com/bigwhite/govanityurls

$govanityurls
govanityurls is a service that allows you to set custom import paths for your go packages

Usage:
     govanityurls -host [HOST_NAME]

  -host string
        custom domain name, e.g. tonybai.com

和rakyll提供的govanityurls不同的是,这里的govanityurls需要外部传入一个host参数(比如:tonybai.com),而在原版中这个host是由google app engine的API提供的。

2、配置vanity.yaml

vanity.yaml中配置了host下的自定义包的路径以及其真实的repo地址:

/gowechat:
        repo: https://github.com/bigwhite/gowechat

上面这个配置中,我们实际上为gowechat这个package定义了tonybai.com/gowechat这个go get路径,其真实的repo存放在github.com/bigwhite/gowechat。当然这个vanity.yaml可以配置N个自定义包路径,也可以定义多级路径,比如:

/gowechat:
        repo: https://github.com/bigwhite/gowechat

/x/experiments:
        repo: https://github.com/bigwhite/experiments

3、配置反向代理

govanityurls默认监听的是8080端口,这主要是考虑到我们通常会使用主域名定制路径,而在主域名下面一般情况下都会有其他一些服务,比如:主页、博客等。通常我们都会用一个反向代理软件做路由分发。我们针对gowechat这个repo定义了一条nginx location规则:

// /etc/nginx/conf.d/default.conf
server {
        listen 80;
        listen 443 ssl;
        server_name tonybai.com;

        ssl_certificate           /etc/nginx/cert.crt;
        ssl_certificate_key       /etc/nginx/cert.key;
        ssl on;

        location /gowechat {
                proxy_pass http://10.11.36.23:8080;
                proxy_redirect off;
                proxy_set_header Host $host;
                proxy_set_header X-Real-IP $remote_addr;
                proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;

                proxy_http_version 1.1;
                proxy_set_header Upgrade $http_upgrade;
                proxy_set_header Connection "upgrade";
        }
}

这里为了方便,我既在80端口提供http服务,也在443端口提供了https服务。这里的10.11.36.23就是我真正部署govanityurls的host(一台thinkcenter PC)。/etc/nginx/cert.key和/etc/nginx/cert.crt可以通过下面命令生成:

sudo openssl req -x509 -nodes -days 365 -newkey rsa:2048 -keyout /etc/nginx/cert.key -out /etc/nginx/cert.crt

CN填tonybai.com

注意:修改两个文件的owner权限,将其owner改为nginx worker process的user,我这里是www-data(chown www-data:www-data /etc/nginx/cert.*)。

4、测试govanityurls

我在我的mac上修改了一下/etc/hosts,添加一条路由:

10.11.36.23 tonybai.com

我们来go get tonybai.com/gowechat:

$go get -v -insecure tonybai.com/gowechat
Fetching https://tonybai.com/gowechat?go-get=1
https fetch failed: Get https://tonybai.com/gowechat?go-get=1: EOF
Fetching http://tonybai.com/gowechat?go-get=1
Parsing meta tags from http://tonybai.com/gowechat?go-get=1 (status code 200)
get "tonybai.com/gowechat": found meta tag main.metaImport{Prefix:"tonybai.com/gowechat", VCS:"git", RepoRoot:"https://github.com/bigwhite/gowechat"} at http://tonybai.com/gowechat?go-get=1
tonybai.com/gowechat (download)
package tonybai.com/gowechat: no buildable Go source files in /Users/tony/Test/GoToolsProjects/src/tonybai.com/gowechat

$ls /Users/tony/Test/GoToolsProjects/src/tonybai.com/gowechat
LICENSE        README.md    mp/        pb/        qy/

我们可以看到tonybai.com/gowechat被成功get到本地,并且import path为tonybai.com/gowechat,其他包可以按照这个定制的gowechat的导入路径import gowechat package了。

上面例子中,我们给go get传入了一个-insecure的参数,这样go get就会通过http协议去访问tonybai.com/gowechat了。我们试试去掉-insecure,不过再次执行前需先将本地的tonybai.com/gowechat包删除掉。

$go get -v tonybai.com/gowechat
Fetching https://tonybai.com/gowechat?go-get=1
https fetch failed: Get https://tonybai.com/gowechat?go-get=1: x509: certificate signed by unknown authority
package tonybai.com/gowechat: unrecognized import path "tonybai.com/gowechat" (https fetch: Get https://tonybai.com/gowechat?go-get=1: x509: certificate signed by unknown authority)

虽然我已经关掉了git的http.sslVerify,但go get的执行过程还是检查了server端证书是未知CA签署的并报错,原来这块的verify是go get自己做的。关于httpskey和证书(.crt)的相关知识,我在《Go和HTTPS》一文中已经做过说明,不是很熟悉的童鞋可以移步那篇文章。

我们来创建CA、创建server端的key(cert.key),并用创建的CA来签署server.crt:

$ openssl genrsa -out rootCA.key 2048
$ openssl req -x509 -new -nodes -key rootCA.key -subj "/CN=*.tonybai.com" -days 5000 -out rootCA.pem
$ openssl genrsa -out cert.key 2048
$ openssl req -new -key cert.key -subj "/CN=tonybai.com" -out cert.csr
$ openssl x509 -req -in cert.csr -CA rootCA.pem -CAkey rootCA.key -CAcreateserial -out cert.crt -days 5000

# ls
cert.crt  cert.csr  cert.key  rootCA.key  rootCA.pem  rootCA.srl

我们将cert.crt和cert.key拷贝到ubuntu的/etc/nginx目录下,重启nginx,让其加载新的cert.crt和cert.key。然后将rootCA.pem拷贝到/etc/ssl/cert目录下,这个目录是ubuntu下存放CA公钥证书的标准路径。在测试go get前,我们先用curl测试一下:

# curl https://tonybai.com/gowechat
<!DOCTYPE html>
<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8"/>
<meta name="go-import" content="tonybai.com/gowechat git https://github.com/bigwhite/gowechat">
<meta name="go-source" content="tonybai.com/gowechat ">
<meta http-equiv="refresh" content="0; url=https://godoc.org/tonybai.com/gowechat">
</head>
<body>
Nothing to see here; <a href="https://godoc.org/tonybai.com/gowechat">see the package on godoc</a>.
</body>
</html>

curl测试通过!

我们再来看看go get:

# go get tonybai.com/gowechat
package tonybai.com/gowechat: unrecognized import path "tonybai.com/gowechat" (https fetch: Get https://tonybai.com/gowechat?go-get=1: x509: certificate signed by unknown authority)

问题依旧!难道go get无法从/etc/ssl/cert中选取适当的ca证书来做server端的cert.crt的验证么?就着这个问题我在go官方发现了一个类似的issue: #18519 。从中得知,go get仅仅会在不同平台下参考以下几个certificate files:

$GOROOT/src/crypto/x509/root_linux.go

package x509

// Possible certificate files; stop after finding one.
var certFiles = []string{
    "/etc/ssl/certs/ca-certificates.crt",                // Debian/Ubuntu/Gentoo etc.
    "/etc/pki/tls/certs/ca-bundle.crt",                  // Fedora/RHEL 6
    "/etc/ssl/ca-bundle.pem",                            // OpenSUSE
    "/etc/pki/tls/cacert.pem",                           // OpenELEC
    "/etc/pki/ca-trust/extracted/pem/tls-ca-bundle.pem", // CentOS/RHEL 7
}

在ubuntu上,/etc/ssl/certs/ca-certificates.crt是其参考的数字证书。因此要想go get成功,我们需要将我们rootCA.pem加入到/etc/ssl/certs/ca-certificates.crt中去,最简单的方法就是:

$ cat rootCA.pem >> /etc/ssl/certs/ca-certificates.crt

当然,ubuntu也提供了管理根证书的命令update-ca-certificates,可以看其manual学学如何更新/etc/ssl/certs/ca-certificates.crt,这里就不赘述了。

更新后,我们再来go get:

# go get -v tonybai.com/gowechat
Fetching https://tonybai.com/gowechat?go-get=1
Parsing meta tags from https://tonybai.com/gowechat?go-get=1 (status code 200)
get "tonybai.com/gowechat": found meta tag main.metaImport{Prefix:"tonybai.com/gowechat", VCS:"git", RepoRoot:"https://github.com/bigwhite/gowechat"} at https://tonybai.com/gowechat?go-get=1
tonybai.com/gowechat (download)
package tonybai.com/gowechat: no buildable Go source files in /root/go/src/tonybai.com/gowechat

go get成功!

三、小结

  • 使用govanityurls可以十分方便的为你的go package定制go get的导入路径;
  • 一般使用nginx等反向代理放置在govanityurls前端,便于同域名下其他服务的开展;
  • go get默认采用https访问,自签署的ca和server端的证书问题要处理好。如果有条件的话,还是用用letsencrypt等提供的免费证书吧。

微博:@tonybai_cn
微信公众号:iamtonybai
github.com: https://github.com/bigwhite

使用Fluentd和ElasticSearch Stack实现Kubernetes的集群Logging

在本篇文章中,我们继续来说Kubernetes

经过一段时间的探索,我们先后完成了Kubernetes集群搭建DNSDashboardHeapster等插件安装,集群安全配置,搭建作为Persistent Volume的CephRBD,以及服务更新探索和实现工作。现在Kubernetes集群层面的Logging需求逐渐浮上水面了。

随着一些小应用在我们的Kubernetes集群上的部署上线,集群的运行迈上了正轨。但问题随之而来,那就是如何查找和诊断集群自身的问题以及运行于Pod中应用的问题。日志,没错!我们也只能依赖Kubernetes组件以及Pod中应用输出的日志。不过目前我们仅能通过kubectl logs命令或Kubernetes Dashboard来查看Log。在没有cluster level logging的情况下,我们需要分别查看各个Pod的日志,操作繁琐,过程低效。我们迫切地需要为Kubernetes集群搭建一套集群级别的集中日志收集和分析设施。

对于任何基础设施或后端服务系统,日志都是极其重要的。对于受Google内部容器管理系统Borg启发而催生出的Kubernetes项目来说,自然少不了对Logging的支持。在“Logging Overview“中,官方概要介绍了Kubernetes上的几个层次的Logging方案,并给出Cluster-level logging的参考架构:

img{512x368}

Kubernetes还给出了参考实现:
– Logging Backend:Elastic Search stack(包括:Kibana)
– Logging-agent:fluentd

ElasticSearch stack实现的cluster level logging的一个优势在于其对Kubernetes集群中的Pod没有侵入性,Pod无需做任何配合性改动。同时EFK/ELK方案在业内也是相对成熟稳定的。

在本文中,我将为我们的Kubernetes 1.3.7集群安装ElasticSearch、Fluentd和Kibana。由于1.3.7版本略有些old,EFK能否在其上面run起来,我也是心中未知。能否像《生化危机:终章》那样有一个完美的结局,我们还需要一步一步“打怪升级”慢慢看。

一、Kubernetes 1.3.7集群的 “漏网之鱼”

Kubernetes 1.3.7集群是通过kube-up.sh搭建并初始化的。按照K8s官方文档有关elasticsearch logging的介绍,在kubernetes/cluster/ubuntu/config-default.sh中,我也发现了下面几个配置项:

// kubernetes/cluster/ubuntu/config-default.sh
# Optional: Enable node logging.
ENABLE_NODE_LOGGING=false
LOGGING_DESTINATION=${LOGGING_DESTINATION:-elasticsearch}

# Optional: When set to true, Elasticsearch and Kibana will be setup as part of the cluster bring up.
ENABLE_CLUSTER_LOGGING=false
ELASTICSEARCH_LOGGING_REPLICAS=${ELASTICSEARCH_LOGGING_REPLICAS:-1}

显然,当初如果搭建集群伊始时要是知道这些配置的意义,可能那个时候就会将elastic logging集成到集群中了。现在为时已晚,集群上已经跑了很多应用,无法重新通过kube-up.sh中断集群运行并安装elastic logging了。我只能手工进行安装了!

二、镜像准备

1.3.7源码中kubernetes/cluster/addons/fluentd-elasticsearch下的manifest已经比较old了,我们直接使用kubernetes最新源码中的manifest文件

k8s.io/kubernetes/cluster/addons/fluentd-elasticsearch$ ls *.yaml
es-controller.yaml  es-service.yaml  fluentd-es-ds.yaml  kibana-controller.yaml  kibana-service.yaml

分析这些yaml,我们需要三个镜像:

 gcr.io/google_containers/fluentd-elasticsearch:1.22
 gcr.io/google_containers/elasticsearch:v2.4.1-1
 gcr.io/google_containers/kibana:v4.6.1-1

显然镜像都在墙外。由于生产环境下的Docker引擎并没有配置加速器代理,因此我们需要手工下载一下这三个镜像。我采用的方法是通过另外一台配置了加速器的机器上的Docker引擎将三个image下载,并重新打tag,上传到我在hub.docker.com上的账号下,以elasticsearch:v2.4.1-1为例:

# docker pull  gcr.io/google_containers/elasticsearch:v2.4.1-1
# docker tag gcr.io/google_containers/elasticsearch:v2.4.1-1 bigwhite/elasticsearch:v2.4.1-1
# docker push bigwhite/elasticsearch:v2.4.1-1

下面是我们在后续安装过程中真正要使用到的镜像:

bigwhite/fluentd-elasticsearch:1.22
bigwhite/elasticsearch:v2.4.1-1
bigwhite/kibana:v4.6.1-1

三、启动fluentd

fluentd是以DaemonSet的形式跑在K8s集群上的,这样k8s可以保证每个k8s cluster node上都会启动一个fluentd(注意:将image改为上述镜像地址,如果你配置了加速器,那自然就不必了)。

# kubectl create -f fluentd-es-ds.yaml --record
daemonset "fluentd-es-v1.22" created

查看daemonset中的Pod的启动情况,我们发现:

kube-system                  fluentd-es-v1.22-as3s5                  0/1       CrashLoopBackOff   2          43s       172.16.99.6    10.47.136.60
kube-system                  fluentd-es-v1.22-qz193                  0/1       CrashLoopBackOff   2          43s       172.16.57.7    10.46.181.146

fluentd Pod启动失败,fluentd的日志可以通过/var/log/fluentd.log查看:

# tail -100f /var/log/fluentd.log

2017-03-02 02:27:01 +0000 [info]: reading config file path="/etc/td-agent/td-agent.conf"
2017-03-02 02:27:01 +0000 [info]: starting fluentd-0.12.31
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-mixin-config-placeholders' version '0.4.0'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-mixin-plaintextformatter' version '0.2.6'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-docker_metadata_filter' version '0.1.3'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-elasticsearch' version '1.5.0'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-kafka' version '0.4.1'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-kubernetes_metadata_filter' version '0.24.0'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-mongo' version '0.7.16'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-rewrite-tag-filter' version '1.5.5'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-s3' version '0.8.0'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-scribe' version '0.10.14'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-td' version '0.10.29'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-td-monitoring' version '0.2.2'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-webhdfs' version '0.4.2'
2017-03-02 02:27:01 +0000 [info]: gem 'fluentd' version '0.12.31'
2017-03-02 02:27:01 +0000 [info]: adding match pattern="fluent.**" type="null"
2017-03-02 02:27:01 +0000 [info]: adding filter pattern="kubernetes.**" type="kubernetes_metadata"
2017-03-02 02:27:02 +0000 [error]: config error file="/etc/td-agent/td-agent.conf" error="Invalid Kubernetes API v1 endpoint https://192.168.3.1:443/api: 401 Unauthorized"
2017-03-02 02:27:02 +0000 [info]: process finished code=256
2017-03-02 02:27:02 +0000 [warn]: process died within 1 second. exit.

从上述日志中的error来看:fluentd访问apiserver secure port(443)出错了:Unauthorized! 通过分析 cluster/addons/fluentd-elasticsearch/fluentd-es-image/build.sh和td-agent.conf,我们发现是fluentd image中的fluent-plugin-kubernetes_metadata_filter要去访问API Server以获取一些kubernetes的metadata信息。不过未做任何特殊配置的fluent-plugin-kubernetes_metadata_filter,我猜测它使用的是kubernetes为Pod传入的环境变量:KUBERNETES_SERVICE_HOST和KUBERNETES_SERVICE_PORT来得到API Server的访问信息的。但API Server在secure port上是开启了安全身份验证机制的,fluentd直接访问必然是失败的。

我们找到了fluent-plugin-kubernetes_metadata_filter项目在github.com上的主页,在这个页面上我们看到了fluent-plugin-kubernetes_metadata_filter支持的其他配置,包括:ca_file、client_cert、client_key等,显然这些字眼非常眼熟。我们需要修改一下fluentd image中td-agent.conf的配置,为fluent-plugin-kubernetes_metadata_filter增加一些配置项,比如:

// td-agent.conf
... ...
<filter kubernetes.**>
  type kubernetes_metadata
  ca_file /srv/kubernetes/ca.crt
  client_cert /srv/kubernetes/kubecfg.crt
  client_key /srv/kubernetes/kubecfg.key
</filter>
... ...

这里我不想重新制作image,那么怎么办呢?Kubernetes提供了ConfigMap这一强大的武器,我们可以将新版td-agent.conf制作成kubernetes的configmap资源,并挂载到fluentd pod的相应位置以替换image中默认的td-agent.conf。

需要注意两点:
* 在基于td-agent.conf创建configmap资源之前,需要将td-agent.conf中的注释行都删掉,否则生成的configmap的内容可能不正确;
* fluentd pod将创建在kube-system下,因此configmap资源也需要创建在kube-system namespace下面,否则kubectl create无法找到对应的configmap。

# kubectl create configmap td-agent-config --from-file=./td-agent.conf -n kube-system
configmap "td-agent-config" created

# kubectl get configmaps -n kube-system
NAME              DATA      AGE
td-agent-config   1         9s

# kubectl get configmaps td-agent-config -o yaml
apiVersion: v1
data:
  td-agent.conf: |
    <match fluent.**>
      type null
    </match>

    <source>
      type tail
      path /var/log/containers/*.log
      pos_file /var/log/es-containers.log.pos
      time_format %Y-%m-%dT%H:%M:%S.%NZ
      tag kubernetes.*
      format json
      read_from_head true
    </source>
... ...

fluentd-es-ds.yaml也要随之做一些改动,主要是增加两个mount: 一个是mount 上面的configmap td-agent-config,另外一个就是mount hostpath:/srv/kubernetes以获取到相关client端的数字证书:

  spec:
      containers:
      - name: fluentd-es
        image: bigwhite/fluentd-elasticsearch:1.22
        command:
          - '/bin/sh'
          - '-c'
          - '/usr/sbin/td-agent 2>&1 >> /var/log/fluentd.log'
        resources:
          limits:
            memory: 200Mi
          #requests:
            #cpu: 100m
            #memory: 200Mi
        volumeMounts:
        - name: varlog
          mountPath: /var/log
        - name: varlibdockercontainers
          mountPath: /var/lib/docker/containers
          readOnly: true
        - name: td-agent-config
          mountPath: /etc/td-agent
        - name: tls-files
          mountPath: /srv/kubernetes
      terminationGracePeriodSeconds: 30
      volumes:
      - name: varlog
        hostPath:
          path: /var/log
      - name: varlibdockercontainers
        hostPath:
          path: /var/lib/docker/containers
      - name: td-agent-config
        configMap:
          name: td-agent-config
      - name: tls-files
        hostPath:
          path: /srv/kubernetes

接下来,我们重新创建fluentd ds,步骤不赘述。这回我们的创建成功了:

kube-system                  fluentd-es-v1.22-adsrx                  1/1       Running    0          1s        172.16.99.6    10.47.136.60
kube-system                  fluentd-es-v1.22-rpme3                  1/1       Running    0          1s        172.16.57.7    10.46.181.146

但通过查看/var/log/fluentd.log,我们依然能看到“问题”:

2017-03-02 03:57:58 +0000 [warn]: temporarily failed to flush the buffer. next_retry=2017-03-02 03:57:59 +0000 error_class="Fluent::ElasticsearchOutput::ConnectionFailure" error="Can not reach Elasticsearch cluster ({:host=>\"elasticsearch-logging\", :port=>9200, :scheme=>\"http\"})!" plugin_id="object:3fd99fa857d8"
  2017-03-02 03:57:58 +0000 [warn]: suppressed same stacktrace
2017-03-02 03:58:00 +0000 [warn]: temporarily failed to flush the buffer. next_retry=2017-03-02 03:58:03 +0000 error_class="Fluent::ElasticsearchOutput::ConnectionFailure" error="Can not reach Elasticsearch cluster ({:host=>\"elasticsearch-logging\", :port=>9200, :scheme=>\"http\"})!" plugin_id="object:3fd99fa857d8"
2017-03-02 03:58:00 +0000 [info]: process finished code=9
2017-03-02 03:58:00 +0000 [error]: fluentd main process died unexpectedly. restarting.

由于ElasticSearch logging还未创建,这是连不上elasticsearch所致。

四、启动elasticsearch

启动elasticsearch:

# kubectl create -f es-controller.yaml
replicationcontroller "elasticsearch-logging-v1" created

# kubectl create -f es-service.yaml
service "elasticsearch-logging" created

get pods:

kube-system                  elasticsearch-logging-v1-3bzt6          1/1       Running    0          7s        172.16.57.8    10.46.181.146
kube-system                  elasticsearch-logging-v1-nvbe1          1/1       Running    0          7s        172.16.99.10   10.47.136.60

elastic search logging启动成功后,上述fluentd的fail日志就没有了!

不过elastic search真的运行ok了么?我们查看一下elasticsearch相关Pod日志:

# kubectl logs -f elasticsearch-logging-v1-3bzt6 -n kube-system
F0302 03:59:41.036697       8 elasticsearch_logging_discovery.go:60] kube-system namespace doesn't exist: the server has asked for the client to provide credentials (get namespaces kube-system)
goroutine 1 [running]:
k8s.io/kubernetes/vendor/github.com/golang/glog.stacks(0x19a8100, 0xc400000000, 0xc2, 0x186)
... ...
main.main()
    elasticsearch_logging_discovery.go:60 +0xb53

[2017-03-02 03:59:42,587][INFO ][node                     ] [elasticsearch-logging-v1-3bzt6] version[2.4.1], pid[16], build[c67dc32/2016-09-27T18:57:55Z]
[2017-03-02 03:59:42,588][INFO ][node                     ] [elasticsearch-logging-v1-3bzt6] initializing ...
[2017-03-02 03:59:44,396][INFO ][plugins                  ] [elasticsearch-logging-v1-3bzt6] modules [reindex, lang-expression, lang-groovy], plugins [], sites []
... ...
[2017-03-02 03:59:44,441][INFO ][env                      ] [elasticsearch-logging-v1-3bzt6] heap size [1007.3mb], compressed ordinary object pointers [true]
[2017-03-02 03:59:48,355][INFO ][node                     ] [elasticsearch-logging-v1-3bzt6] initialized
[2017-03-02 03:59:48,355][INFO ][node                     ] [elasticsearch-logging-v1-3bzt6] starting ...
[2017-03-02 03:59:48,507][INFO ][transport                ] [elasticsearch-logging-v1-3bzt6] publish_address {172.16.57.8:9300}, bound_addresses {[::]:9300}
[2017-03-02 03:59:48,547][INFO ][discovery                ] [elasticsearch-logging-v1-3bzt6] kubernetes-logging/7_f_M2TKRZWOw4NhBc4EqA
[2017-03-02 04:00:18,552][WARN ][discovery                ] [elasticsearch-logging-v1-3bzt6] waited for 30s and no initial state was set by the discovery
[2017-03-02 04:00:18,562][INFO ][http                     ] [elasticsearch-logging-v1-3bzt6] publish_address {172.16.57.8:9200}, bound_addresses {[::]:9200}
[2017-03-02 04:00:18,562][INFO ][node                     ] [elasticsearch-logging-v1-3bzt6] started
[2017-03-02 04:01:15,754][WARN ][discovery.zen.ping.unicast] [elasticsearch-logging-v1-3bzt6] failed to send ping to [{#zen_unicast_1#}{127.0.0.1}{127.0.0.1:9300}]
SendRequestTransportException[[][127.0.0.1:9300][internal:discovery/zen/unicast]]; nested: NodeNotConnectedException[[][127.0.0.1:9300] Node not connected];
... ...
Caused by: NodeNotConnectedException[[][127.0.0.1:9300] Node not connected]
    at org.elasticsearch.transport.netty.NettyTransport.nodeChannel(NettyTransport.java:1141)
    at org.elasticsearch.transport.netty.NettyTransport.sendRequest(NettyTransport.java:830)
    at org.elasticsearch.transport.TransportService.sendRequest(TransportService.java:329)
    ... 12 more

总结了一下,日志中有两个错误:
- 无法访问到API Server,这个似乎和fluentd最初的问题一样;
- elasticsearch两个节点间互ping失败。

要想找到这两个问题的原因,还得回到源头,去分析elastic search image的组成。

通过cluster/addons/fluentd-elasticsearch/es-image/run.sh文件内容:

/elasticsearch_logging_discovery >> /elasticsearch/config/elasticsearch.yml

chown -R elasticsearch:elasticsearch /data

/bin/su -c /elasticsearch/bin/elasticsearch elasticsearch

我们了解到image中,其实包含了两个程序,一个为/elasticsearch_logging_discovery,该程序执行后生成一个配置文件: /elasticsearch/config/elasticsearch.yml。该配置文件后续被另外一个程序:/elasticsearch/bin/elasticsearch使用。

我们查看一下已经运行的docker中的elasticsearch.yml文件内容:

# docker exec 3cad31f6eb08 cat /elasticsearch/config/elasticsearch.yml
cluster.name: kubernetes-logging

node.name: ${NODE_NAME}
node.master: ${NODE_MASTER}
node.data: ${NODE_DATA}

transport.tcp.port: ${TRANSPORT_PORT}
http.port: ${HTTP_PORT}

path.data: /data

network.host: 0.0.0.0

discovery.zen.minimum_master_nodes: ${MINIMUM_MASTER_NODES}
discovery.zen.ping.multicast.enabled: false

这个结果中缺少了一项:

discovery.zen.ping.unicast.hosts: ["172.30.0.11", "172.30.192.15"]

这也是导致第二个问题的原因。综上,elasticsearch logging的错误其实都是由于/elasticsearch_logging_discovery无法访问API Server导致 /elasticsearch/config/elasticsearch.yml没有被正确生成造成的,我们就来解决这个问题。

我查看了一下/elasticsearch_logging_discovery的源码,elasticsearch_logging_discovery是一个典型通过client-go通过service account访问API Server的程序,很显然这就是我在《在Kubernetes Pod中使用Service Account访问API Server》一文中提到的那个问题:默认的service account不好用。

解决方法:在kube-system namespace下创建一个新的service account资源,并在es-controller.yaml中显式使用该新创建的service account。

创建一个新的serviceaccount在kube-system namespace下:

//serviceaccount.yaml
apiVersion: v1
kind: ServiceAccount
metadata:
  name: k8s-efk

# kubectl create -f serviceaccount.yaml -n kube-system
serviceaccount "k8s-efk" created

# kubectl get serviceaccount -n kube-system
NAME      SECRETS   AGE
default   1         139d
k8s-efk   1         17s

在es-controller.yaml中,使用service account “k8s-efk”:

//es-controller.yaml
... ...
spec:
  replicas: 2
  selector:
    k8s-app: elasticsearch-logging
    version: v1
  template:
    metadata:
      labels:
        k8s-app: elasticsearch-logging
        version: v1
        kubernetes.io/cluster-service: "true"
    spec:
      serviceAccount: k8s-efk
      containers:
... ...

重新创建elasticsearch logging service后,我们再来查看elasticsearch-logging pod的日志:

# kubectl logs -f elasticsearch-logging-v1-dklui -n kube-system
[2017-03-02 08:26:46,500][INFO ][node                     ] [elasticsearch-logging-v1-dklui] version[2.4.1], pid[14], build[c67dc32/2016-09-27T18:57:55Z]
[2017-03-02 08:26:46,504][INFO ][node                     ] [elasticsearch-logging-v1-dklui] initializing ...
[2017-03-02 08:26:47,984][INFO ][plugins                  ] [elasticsearch-logging-v1-dklui] modules [reindex, lang-expression, lang-groovy], plugins [], sites []
[2017-03-02 08:26:48,073][INFO ][env                      ] [elasticsearch-logging-v1-dklui] using [1] data paths, mounts [[/data (/dev/vda1)]], net usable_space [16.9gb], net total_space [39.2gb], spins? [possibly], types [ext4]
[2017-03-02 08:26:48,073][INFO ][env                      ] [elasticsearch-logging-v1-dklui] heap size [1007.3mb], compressed ordinary object pointers [true]
[2017-03-02 08:26:53,241][INFO ][node                     ] [elasticsearch-logging-v1-dklui] initialized
[2017-03-02 08:26:53,241][INFO ][node                     ] [elasticsearch-logging-v1-dklui] starting ...
[2017-03-02 08:26:53,593][INFO ][transport                ] [elasticsearch-logging-v1-dklui] publish_address {172.16.57.8:9300}, bound_addresses {[::]:9300}
[2017-03-02 08:26:53,651][INFO ][discovery                ] [elasticsearch-logging-v1-dklui] kubernetes-logging/Ky_OuYqMRkm_918aHRtuLg
[2017-03-02 08:26:56,736][INFO ][cluster.service          ] [elasticsearch-logging-v1-dklui] new_master {elasticsearch-logging-v1-dklui}{Ky_OuYqMRkm_918aHRtuLg}{172.16.57.8}{172.16.57.8:9300}{master=true}, added {{elasticsearch-logging-v1-vjxm3}{cbzgrfZATyWkHfQYHZhs7Q}{172.16.99.10}{172.16.99.10:9300}{master=true},}, reason: zen-disco-join(elected_as_master, [1] joins received)
[2017-03-02 08:26:56,955][INFO ][http                     ] [elasticsearch-logging-v1-dklui] publish_address {172.16.57.8:9200}, bound_addresses {[::]:9200}
[2017-03-02 08:26:56,956][INFO ][node                     ] [elasticsearch-logging-v1-dklui] started
[2017-03-02 08:26:57,157][INFO ][gateway                  ] [elasticsearch-logging-v1-dklui] recovered [0] indices into cluster_state
[2017-03-02 08:27:05,378][INFO ][cluster.metadata         ] [elasticsearch-logging-v1-dklui] [logstash-2017.03.02] creating index, cause [auto(bulk api)], templates [], shards [5]/[1], mappings []
[2017-03-02 08:27:06,360][INFO ][cluster.metadata         ] [elasticsearch-logging-v1-dklui] [logstash-2017.03.01] creating index, cause [auto(bulk api)], templates [], shards [5]/[1], mappings []
[2017-03-02 08:27:07,163][INFO ][cluster.routing.allocation] [elasticsearch-logging-v1-dklui] Cluster health status changed from [RED] to [YELLOW] (reason: [shards started [[logstash-2017.03.01][3], [logstash-2017.03.01][3]] ...]).
[2017-03-02 08:27:07,354][INFO ][cluster.metadata         ] [elasticsearch-logging-v1-dklui] [logstash-2017.03.02] create_mapping [fluentd]
[2017-03-02 08:27:07,988][INFO ][cluster.metadata         ] [elasticsearch-logging-v1-dklui] [logstash-2017.03.01] create_mapping [fluentd]
[2017-03-02 08:27:09,578][INFO ][cluster.routing.allocation] [elasticsearch-logging-v1-dklui] Cluster health status changed from [YELLOW] to [GREEN] (reason: [shards started [[logstash-2017.03.02][4]] ...]).

elasticsearch logging启动运行ok!

五、启动kibana

有了elasticsearch logging的“前车之鉴”,这次我们也把上面新创建的serviceaccount:k8s-efk显式赋值给kibana-controller.yaml:

//kibana-controller.yaml
... ...
spec:
      serviceAccount: k8s-efk
      containers:
      - name: kibana-logging
        image: bigwhite/kibana:v4.6.1-1
        resources:
          # keep request = limit to keep this container in guaranteed class
          limits:
            cpu: 100m
          #requests:
          #  cpu: 100m
        env:
          - name: "ELASTICSEARCH_URL"
            value: "http://elasticsearch-logging:9200"
          - name: "KIBANA_BASE_URL"
            value: "/api/v1/proxy/namespaces/kube-system/services/kibana-logging"
        ports:
        - containerPort: 5601
          name: ui
          protocol: TCP
... ...

启动kibana,并观察pod日志:

# kubectl create -f kibana-controller.yaml
# kubectl create -f kibana-service.yaml
# kubectl logs -f kibana-logging-3604961973-jby53 -n kube-system
ELASTICSEARCH_URL=http://elasticsearch-logging:9200
server.basePath: /api/v1/proxy/namespaces/kube-system/services/kibana-logging
{"type":"log","@timestamp":"2017-03-02T08:30:15Z","tags":["info","optimize"],"pid":6,"message":"Optimizing and caching bundles for kibana and statusPage. This may take a few minutes"}

kibana缓存着实需要一段时间,请耐心等待!可能是几分钟。之后你将会看到如下日志:

# kubectl logs -f kibana-logging-3604961973-jby53 -n kube-system
ELASTICSEARCH_URL=http://elasticsearch-logging:9200
server.basePath: /api/v1/proxy/namespaces/kube-system/services/kibana-logging
{"type":"log","@timestamp":"2017-03-02T08:30:15Z","tags":["info","optimize"],"pid":6,"message":"Optimizing and caching bundles for kibana and statusPage. This may take a few minutes"}
{"type":"log","@timestamp":"2017-03-02T08:40:04Z","tags":["info","optimize"],"pid":6,"message":"Optimization of bundles for kibana and statusPage complete in 588.60 seconds"}
{"type":"log","@timestamp":"2017-03-02T08:40:04Z","tags":["status","plugin:kibana@1.0.0","info"],"pid":6,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-03-02T08:40:05Z","tags":["status","plugin:elasticsearch@1.0.0","info"],"pid":6,"state":"yellow","message":"Status changed from uninitialized to yellow - Waiting for Elasticsearch","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-03-02T08:40:05Z","tags":["status","plugin:kbn_vislib_vis_types@1.0.0","info"],"pid":6,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-03-02T08:40:05Z","tags":["status","plugin:markdown_vis@1.0.0","info"],"pid":6,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-03-02T08:40:05Z","tags":["status","plugin:metric_vis@1.0.0","info"],"pid":6,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-03-02T08:40:06Z","tags":["status","plugin:spyModes@1.0.0","info"],"pid":6,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-03-02T08:40:06Z","tags":["status","plugin:statusPage@1.0.0","info"],"pid":6,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-03-02T08:40:06Z","tags":["status","plugin:table_vis@1.0.0","info"],"pid":6,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-03-02T08:40:06Z","tags":["listening","info"],"pid":6,"message":"Server running at http://0.0.0.0:5601"}
{"type":"log","@timestamp":"2017-03-02T08:40:11Z","tags":["status","plugin:elasticsearch@1.0.0","info"],"pid":6,"state":"yellow","message":"Status changed from yellow to yellow - No existing Kibana index found","prevState":"yellow","prevMsg":"Waiting for Elasticsearch"}
{"type":"log","@timestamp":"2017-03-02T08:40:14Z","tags":["status","plugin:elasticsearch@1.0.0","info"],"pid":6,"state":"green","message":"Status changed from yellow to green - Kibana index ready","prevState":"yellow","prevMsg":"No existing Kibana index found"}

接下来,通过浏览器访问下面地址就可以访问kibana的web页面了,注意:Kinaba的web页面加载也需要一段时间。

https://{API Server external IP}:{API Server secure port}/api/v1/proxy/namespaces/kube-system/services/kibana-logging/app/kibana#/settings/indices/

下面是创建一个index(相当于mysql中的一个database)页面:

img{512x368}

取消“Index contains time-based events”,然后点击“Create”即可创建一个Index。

点击页面上的”Setting” -> “Status”,可以查看当前elasticsearch logging的整体状态,如果一切ok,你将会看到下图这样的页面:

img{512x368}

创建Index后,可以在Discover下看到ElasticSearch logging中汇聚的日志:

img{512x368}

六、小结

以上就是在Kubernetes 1.3.7集群上安装Fluentd和ElasticSearch stack,实现kubernetes cluster level logging的过程。在使用kubeadm安装的Kubernetes 1.5.1环境下安装这些,则基本不会遇到上述这些问题。

另外ElasticSearch logging默认挂载的volume是emptyDir,实验用可以。但要部署在生产环境,必须换成Persistent Volume,比如:CephRBD




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