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Hadoop,	Fluentd	cluster	monitoring	
with	Prometheus	and	Grafana
2016/08/26
Wataru	Yukawa(@wyukawa)
#promcon2016
Who	am	I?
• Data	Engineer	at	LINE
• LINE	makes	a	messaging	application	of	the	
same	name,	in	addition	to	other	related	
services
• It	is	the	most	popular	messaging	platform	in	
Japan
LINE
Who	am	I?
• First	time	to	Germany!
• Maintain	an	on-premises	log	analysis	platform	
on	top	of	Hadoop/Hive/Fluentd.
• Unofficial Prometheus Evangelist in Japan
– Organized	meetup	in	Tokyo	on	June	14,	2016	
(more	than	100	attendences)
– http://developers.linecorp.com/blog/?p=3908
Agenda
• Background	of	LINE’s	development	
environment
• Promgen introduction
• hadoop/fluentd cluster	monitoring	with	
Prometheus	and	Grafana
Before Prometheus
• I	have	experience	with other monitoring	tools	like	
Ganglia,	Nagios
• I	found	Prometheus
– Monitoring	and	alerting	are	unified
– There	is	a	query	feature	that	allows	ad-hoc	queries
• max	disk	usage:	max	by	(instance)	(100	-
(node_filesystem_free{...}	/	node_filesystem_size{...})	*	100)
• I	want	to	use	Prometheus
• How	do	we	adjust	Prometheus	to	our	
environment?
LINE’s	development	environment
• We rarely use cloud service like AWS because we
are under on-premises environment
– host information doesn’t change frequently
• That’s	why	currently	we	don’t	use	any	service	
discovery	system	(like	Consul)
– Therefore,	we	need	to	use	static	configuration	for	
Prometheus
• We	wanted	to	manage	servers	through	a	browser
• So,	we	created	a	tool	to	manage	server	list	called	
promgen (https://github.com/line/promgen)
Agenda
• Background	of	LINE’s	development	
environment
• Promgen introduction
• hadoop/fluentd cluster	monitoring	with	
Prometheus	and	Grafana
About	promgen
• Simple	web	app	written	in	ruby	which
– Generates	server list/rules	and	reloads(POST	/-
/reload)	Prometheus
– Controls	alert	management
Promgen data model
Service
Project
Project
Project
Farm
Farm
Farm
Host
Host
Host
Host
Host
Host
Host
Host
Host
service	of	promgen
This	service	has	3	projects(blog-admin,	blog-batch,	blog-web)
project	of	promgen
alert	
notification
exporters
hosts
Host	screen
Exporter	of	promgen
Job name becomes Prometheus	label
prometheus.yaml
rule_files:
- "/tmp/prom.rule"
scrape_configs:
- job_name:	'dummy'
file_sd_configs:
- files:
- "/tmp/prom.json"
Promgen
update
update
Promgen	doesn’t change prometheus.yaml	directly,
but	instead	updates	prom.rule/prom.json.
User	should	run	Promgen and	Prometheus	on	the	same	machine.
prom.json	example
[
{
"targets":[
"blog.admin1.localhost:9100”,
"blog.admin2.localhost:9100”,
...
],
"labels":{
"service":"blog",
"project":"blog-admin",
"farm":"blog-admin-RELEASE",
"job":"node"
}
},
...
]
service/project/farm/job	become	Prometheus	labels
We use this Prometheus labels in	Grafana Templates
How	to	use	labels	in	templating
• Templating	is	useful	because	dashboard	can	
be	reused
• Labels	correspond	to	templates	in	Grafana
• In	this	example,	we	use	the	farm	label
Prometheus	and	Grafana
• Prometheus	pulls	metrics	from	exporters
• Grafana’s datasouce is	Prometheus
• Prometheus and Grafana are a	perfect
combination
• I really appreciate Grafana’s Prometheus	
plugin
PrometheusExporters Grafana
About	promgen
• Simple	web	app	written	in	ruby	which
– Generates	server list/rule	and	reload(POST	/-
/reload)	prometheus
– Controls	alert	management
Alertmanager
• Alertmanager is powerful because users can
avoid a	flood	of	alert	notifications
• Deduplication	and	silences are useful
• Alertmanager can avoid alert fatigue
• We want to manage	alert	notification	rules	and	
settings easily
– for	example,	we	want	to	add HipChat room and Mail
address through browser.
• That’s why we implement webhook in promgen
Rule	control	screen
HipChat and Mail
• User	can	set	HipChat	room	and	mail	address	
to	receive	alert
How	to	notify	alert
• Promgen has	webhook feature	to	send	alert	to	
both HipChat	and	Mail
• If alert occurs, user can receive alert through
Alertmanager, Promgen
Prometheus Alertmanager Promgen
HipChat
Mail
Agenda
• Background	of	LINE’s	development	
environment
• Promgen introduction
• hadoop/fluentd cluster	monitoring	with	
Prometheus	and	Grafana
Log analysis platform
• Access	logs	are	sent	to	HDFS	by	fluentd.	There	
are	more	than	400	Fluentd processes	and
150kmsg/sec	during	peak	times.
• Fluentd	is	an	OSS	log	collector	like	logstash,	
flume	written	in	ruby
• Our	Hadoop	cluster	is	medium-sized,	
consisting	of	40	units.
MRv2/Tez/HDFS
Hive
HDP2.4.0
access	
logaccess	
log
access	
log
Monitoring of	hadoop/hive	cluster
• Developers	normally	use	jmx_exporter to	monitor	java	
middleware
• But	I	wanted	to	create exporter,	so	I	implemented	
namenode/resourcemanager/jstat exporter	
• namenode_exporter uses	http://namenode:50070/jmx
• resourcemanager_exporter uses		
http://resourcemanager:8088/ws/v1/cluster/metrics
• jstat_exporter uses	jstat command
– Honestly,	current	jstat_exporter implementation	is	not	so	
good because	when	Prometheus	pulls	metrics,	jstat
command	is	always	executed
– cache	may	be	necessary
Namenode FilesTotal monitoring	by	
using	namenode_exporter
NameNode Down!
Alerts are also Prometheus metrics	so	Grafana can	show	alerts	as	
annotations
Resoucemanager job	monitoring	by	
using	resourcemanager_exporter
Hiveserver2 jvm monitoring	by	using	
jstat_exporter
https://issues.apache.org/jira/browse/HIVE-13374
Fluentd buffer	monitoring
• Fluentd has	buffer	mechanism	to	retry	if	
destination	is	unstable
• fluent-plugin-prometheus enables	buffer	
monitoring
• fluent-plugin-prometheus is		fluentd	plugin	
and	use	Prometheus	Ruby	client
access log count
• fluent-plugin-prometheus enables	us	to	count	
access	log	but	we	need	sampling	because	of	
high	cpu usage
• One	fluentd process	can‘t	handle	high	traffic
HTTP status count
Although 4xx/5xx	is	not	0,	it	may	become	0	
because	of	sampling. So we will switch to Flink.
HTTP status percentage
sum(rate(accesslog_counts{tag="..."}[1m]))	by	(status,	job)	/	
ignoring(status)	group_left
sum(rate(accesslog_counts{tag="..."}[1m]))	by	(job)
fluentd_exporter
• Fluentd is	often	required	to	execute	in	multi	
process	because	of	GVL
• I	implemented	fluentd_expoter to	monitor	
fluentd cpu usage per process
• fluentd_exporter can	handle	multiple	fluentd
processes
My	feeling
• Prometheus’s	query	language	is	really	powerful
– sum(rate(accesslog_counts{tag="..."}[1m]))	by	(status,	
job)	/	ignoring(status)	group_left
sum(rate(accesslog_counts{tag="..."}[1m]))	by	(job)
• Prometheus	and	Grafana are	a	perfect	
combination
• We created promgen to improve host
management and alert notification settings
References
• http://developers.linecorp.com/blog/?p=3908
• https://github.com/line/promgen
• http://www.fluentd.org/
• https://github.com/wyukawa/hadoop_exporter
• https://github.com/wyukawa/jstat_exporter
• https://github.com/wyukawa/fluentd_exporter
• https://github.com/kazegusuri/fluent-plugin-
prometheus

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