##一．安装
# apt-get install libconfuse-dev expat libpcre3-dev libpango1.0-dev libxml2-dev libapr1-dev libexpat-dev libpcre3-dev rrdtool librrds-perl librrd2-dev python-dev
# wget http://nchc.dl.sourceforge.net/project/ganglia/ganglia%20monitoring%20core/3.2.0/ganglia-3.2.0.tar.gz
# tar zxvf ganglia-3.2.0.tar.gz -C ../software/
# ./configure --prefix=/usr/local/ganglia-3.2.0 --with-gmetad --enable-gexec
# make
# make install
##二．配置
# vim gmetad.conf
data_source “cluster-db” node1 node2 //定义集群名称，以及集群中的节点。由于采用multicast模式，每台gmond节点都有本集群内节点服务器的所有监控数据，因此不必把所有节点都列出来。建议写入不低于2个，在node1节点当掉后，会自动找node2节点取数据。启动gmetad时，会进行域名解析的。
data_source “cluster-memcache” 192.168.41.129
rrd_rootdir “/data/ganglia/rrds” //定义rrd数据库的存放路径，gmetad收集到监控数据后，会更新到该目录下对应的rrd数据库中。
case_sensitive_hostnames 1
# /usr/local/ganglia-3.2.0 /gmond -t > /usr/local/ganglia-3.2.0/etc/gmond.conf
# vim gmond.conf
globals {
daemonize = yes //守护进程运行
setuid = yes
user = nobody //运行用户
debug_level = 0 //调式级别
max_udp_msg_len = 1472 //upd包长度
mute = no //哑巴，本节点将不会再广播任何自己收集到的数据到网络上
deaf = no //聋子，本节点将不再接收任何其他节点广播的数据包
allow_extra_data = yes
host_dmax = 0 /*secs */
host_tmax = 20 /*secs */
cleanup_threshold = 300 /*secs /
gexec = no //是否使用gexec
send_metadata_interval = 0 /secs /
}
cluster {
name = “cluster-db” //本节点属于哪个cluster，需要与data_source对应
owner = “xuhh” //谁是该节点的所有者
latlong = “unspecified”
url = “unspecified”
}
host {
location = “node1”
}
udp_send_channel { //udp发送通道
mcast_join = 239.2.11.71 //多播地址，工作在239.2.11.71通道下。如果使用单播模式，则要写host=node1，单播模式下可以配置多个upd_send_channel
port = 8649 //监听端口
ttl = 1
}
udp_recv_channel { //udp接收通道
mcast_join = 239.2.11.71
port = 8649
bind = 239.2.11.71
}
tcp_accept_channel { //tcp接收通道，可以配置多个tcp_accept_channels来共享集群中监控数据
port = 8649 //远端可以通过连接8649端口来得到监控数据
}
modules { //监控模块
module {
name = “core_metrics”
}
module {
name = “cpu_module”
path = “modcpu.so”
}
module {
name = “disk_module”
path = “moddisk.so”
}
module {
name = “load_module”
path = “modload.so”
}
module {
name = “mem_module”
path = “modmem.so”
}
module {
name = “net_module”
path = “modnet.so”
}
module {
name = “proc_module”
path = “modproc.so”
}
module {
name = “sys_module”
path = “modsys.so”
}
}
/ This collection group will cause a heartbeat (or beacon) to be sent every
20 seconds. In the heartbeat is the GMOND_STARTED data which expresses
the age of the running gmond. /
collection_group {
collect_once = yes
time_threshold = 20
metric {
name = “heartbeat”
}
}
/ This collection group will send general info about this host every
1200 secs.
This information doesn’t change between reboots and is only collected
once. /
collection_group {
collect_once = yes
time_threshold = 1200
metric {
name = “cpu_num”
title = “CPU Count”
}
metric {
name = “cpu_speed”
title = “CPU Speed”
}
metric {
name = “mem_total”
title = “Memory Total”
}
/ Should this be here? Swap can be added/removed between reboots. /
metric {
name = “swap_total”
title = “Swap Space Total”
}
metric {
name = “boottime”
title = “Last Boot Time”
}
metric {
name = “machine_type”
title = “Machine Type”
}
metric {
name = “os_name”
title = “Operating System”
}
metric {
name = “os_release”
title = “Operating System Release”
}
metric {
name = “location”
title = “Location”
}
}
/ This collection group will send the status of gexecd for this host
every 300 secs./
/ Unlike 2.5.x the default behavior is to report gexecd OFF. /
collection_group {
collect_once = yes
time_threshold = 300
metric {
name = “gexec”
title = “Gexec Status”
}
}
/ This collection group will collect the CPU status info every 20 secs.
The time threshold is set to 90 seconds. In honesty, this
time_threshold could be set significantly higher to reduce
unneccessary network chatter. /
collection_group {
collect_every = 20
time_threshold = 90
/ CPU status /
metric {
name = “cpu_user”
value_threshold = “1.0”
title = “CPU User”
}
metric {
name = “cpu_system”
value_threshold = “1.0”
title = “CPU System”
}
metric {
name = “cpu_idle”
value_threshold = “5.0”
title = “CPU Idle”
}
metric {
name = “cpu_nice”
value_threshold = “1.0”
title = “CPU Nice”
}
metric {
name = “cpu_aidle”
value_threshold = “5.0”
title = “CPU aidle”
}
metric {
name = “cpu_wio”
value_threshold = “1.0”
title = “CPU wio”
}
/ The next two metrics are optional if you want more detail…
… since they are accounted for in cpu_system.
metric {
name = “cpu_intr”
value_threshold = “1.0”
title = “CPU intr”
}
metric {
name = “cpu_sintr”
value_threshold = “1.0”
title = “CPU sintr”
}
/
}
collection_group {
collect_every = 20
time_threshold = 90
/ Load Averages /
metric {
name = “load_one”
value_threshold = “1.0”
title = “One Minute Load Average”
}
metric {
name = “load_five”
value_threshold = “1.0”
title = “Five Minute Load Average”
}
metric {
name = “load_fifteen”
value_threshold = “1.0”
title = “Fifteen Minute Load Average”
}
}
/ This group collects the number of running and total processes /
collection_group {
collect_every = 80
time_threshold = 950
metric {
name = “proc_run”
value_threshold = “1.0”
title = “Total Running Processes”
}
metric {
name = “proc_total”
value_threshold = “1.0”
title = “Total Processes”
}
}
/ This collection group grabs the volatile memory metrics every 40 secs and
sends them at least every 180 secs. This time_threshold can be increased
significantly to reduce unneeded network traffic. /
collection_group {
collect_every = 40
time_threshold = 180
metric {
name = “mem_free”
value_threshold = “1024.0”
title = “Free Memory”
}
metric {
name = “mem_shared”
value_threshold = “1024.0”
title = “Shared Memory”
}
metric {
name = “mem_buffers”
value_threshold = “1024.0”
title = “Memory Buffers”
}
metric {
name = “mem_cached”
value_threshold = “1024.0”
title = “Cached Memory”
}
metric {
name = “swap_free”
value_threshold = “1024.0”
title = “Free Swap Space”
}
}
collection_group {
collect_every = 40
time_threshold = 300
metric {
name = “bytes_out”
value_threshold = 4096
title = “Bytes Sent”
}
metric {
name = “bytes_in”
value_threshold = 4096
title = “Bytes Received”
}
metric {
name = “pkts_in”
value_threshold = 256
title = “Packets Received”
}
metric {
name = “pkts_out”
value_threshold = 256
title = “Packets Sent”
}
}
/ Different than 2.5.x default since the old config made no sense /
collection_group {
collect_every = 1800
time_threshold = 3600
metric {
name = “disk_total”
value_threshold = 1.0
title = “Total Disk Space”
}
}
collection_group {
collect_every = 40
time_threshold = 180
metric {
name = “disk_free”
value_threshold = 1.0
title = “Disk Space Available”
}
metric {
name = “part_max_used”
value_threshold = 1.0
title = “Maximum Disk Space Used”
}
}
include ("/usr/local/ganglia-3.2.0/etc/conf.d/.conf")
# mkdir –p /data/ganglia/{rrds, dwoo}
# chown –R nobody.nobody /data/ganglia
# chmod –R 777 /data/ganglia/rrds
对于有两张网卡的服务器，服务器之间的监控通信通过内网，需要如下设置组播网关：
# ip route add 239.2.11.71 dev eth0 //eth0是内网卡
客户端：
安装如上所示
# vim gmond.conf
cluster {
name = “cluster-memcache”
owner = “xuhh”
latlong = “unspecified”
url = “unspecified”
}
host {
location = “192.168.41.129”
}
ganglia PHP web Frontend配置：
PHP环境配置省略
# cp -a /usr/local/src/software/ganglia-3.2.0/web/ /var/www/ganglia
# vim /var/www/ganglia/conf.php
$gmetad_root = "/data/ganglia";
##三．监控图表
ganglia分布式监控系统简介
集成ganglia分布式监控系统步骤
本文转自：ganglia分布式监控系统 | 运维生存时间 + http://www.ttlsa.com/ganglia/ganglia-monitor-system/