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Listen to the sounds of
your application
Maciej Biłas @maciejb softwaremill.com jbison.com

!2
Presented at
J-Day
Lbn.sc

Originally authored by:
Maciej Biłas
Krzysztof Ciesielski
Agenda
•

Monitoring, huh?

•

Introducing Graphite

•

Log analysis – the whys

•

Logstash architecture & use cases

•

Exploring logs with Kibana
Monitoring, huh?
source: codeascraft.com
Types of measurements
Network
Machine
Application
source: codeascraft.com
measurement > prediction
measurement >> prediction
Our stack
Server

Server
App

…

App

Yammer Metrics

Graphite

Logstash
http://graphite/render?
target=server.web1.load&height=800&width=600
Graphite
echo "local.random.diceroll 4 `date +%s`" |
nc graphite-server.your.org 2003
successful.login.attempt 1 1384471287

successful.login.attempt 1 1384471297

successful.login.attempt = 1
Yammer metrics
private final Meter successfulLogins =

metrics.meter(name(LoginHandler.class, "successful"));
!
public void login(String user, String password) {
if (canLogin(user,password)) {
successfulLogins.mark();
// ...
} else {
// ...
}
}
Metrics
Types:

Reporters:

•

Gauges

•

STDOUT

•

Counters

•

CSV

•

Meters

•

SLF4J

•

Histograms

•

JMX

•

Timers

•

Graphite

•

Health Checks

•

Ganglia
Counters, meters…
vs.
Gauges
Aggregation
app00.webservice.requestTime
app01.webservice.requestTime
app02.webservice.requestTime
…
source: codeascraft.com
You can also check out
•

collectd https://collectd.org

•

StatsD https://github.com/etsy/statsd/

•

Riemman http://riemann.io/

•

Twitter’s Ostrich https://github.com/twitter/ostrich

•

Ganglia http://ganglia.sourceforge.net/

•

Dashboards:

http://shopify.github.io/dashing/

https://github.com/obfuscurity/descartes

https://github.com/obfuscurity/dusk
Log aggregation?
Event Sourcing
Tracing and storing all the events
Current app state: replaying the stream
Great for data mining and analysis
Log aggregation

•

Less invasive way to build an “event stream”

•

Logs are data with plenty of value
Log aggregation
Log
source

Log
source

Log
source

Central
storage

Query
engine

Web
view
Logstash
•

Open source
•

Written in JRuby

•

Gathers logs from various inputs

•

Parses and extracts metadata

•

Writes to various outputs
Architecture
Inputs
collectd

graphite

s3

drupal_dblog

heroku

snmptrap
unix

elasticsearch

imap

sqlite
varnishlog

eventlog

irc

sqs
websocket

exec

log4j

stdin
wmi

file

lumberjack

stomp
xmpp

ganglia

pipe

syslog
zenoss

gelf

rabbitmq

tcp
zeromq

gemfire

redis

twitter

generator

relp

udp
Grok
Thin layer on top of a regular expression
2013-11-10 19:41:25.321 [main] INFO
o.a.camel.impl.DefaultCamelContext - Apache Camel 2.11.1
(CamelContext: camel-1) started in 4.450 seconds

time 2013-11-10 19:41:25.321
thread main
loglevel INFO
source o.a.camel.impl.DefaultCamelContext
message Apache Camel 2.11.1 (CamelContext: camel-1) started in 4.450 seconds
Grok
2013-11-10 19:41:25.321 [main] INFO
o.a.camel.impl.DefaultCamelContext - Apache Camel 2.11.1
(CamelContext: camel-1) started in 4.450 seconds

grok {
patterns_dir => “./some-dir“
match => ["message", "%{TIMESTAMP_ISO8601:time} 

[%{DATA:thread}] %{LOGLEVEL:loglevel}

%{DATA:source} - %
{MULTILINE_GREEDYDATA:message}"]
}
Outputs
boundary
circonus
cloudwatch
csv
datadog
datadog_metric
s
elasticsearch
elasticsearch_ht
tp
elasticsearch_ri
ver
email

exec

http

null

sqs

file

irc

opentsdb

statsd

ganglia

jira

pagerduty

stdout

gelf

juggernaut

pipe

stomp

gemfire

librato

rabbitmq

syslog

google_bigquer
y

loggly

redis

tcp

lumberjack

riak

udp

google_cloud_st
orage

metriccatcher

riemann

websocket

graphite

mongodb

s3

xmpp

graphtastic

nagios

sns

zabbix

hipchat

nagios_nsca

solr_http

zeromq
Kibana
Checking app activity
Spotting anomalies
Regular events
How often is a feature used?
Plotting multiple event types
Other tools
•

Splunk

•

Graylog2

•

Fluentd

•

log.io
References
•

Graphite

http://graphite.readthedocs.org/en/latest/

•

Yammer Metrics

http://metrics.codahale.com/

•

Logstash

http://logstash.net/

•

Surfing the event stream by Sam Newman at Geecon

http://www.slideshare.net/spnewman/surfing-the-event-stream

•

Lessons from Building and Scaling LinkedIn by Jay Kreps

http://www.infoq.com/presentations/linkedin-architecture-stack

•

Code as Craft

http://codeascraft.com/
Thank you!
Questions?

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