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1
Wie	man	aus	langweiligen	

Logdateien	Gold	gewinnen	
kann
2
About me
• Klaus	Bild	
• Senior	System	Architect

• IBM	Connections/Sametime/TDI	
• Monitoring/Log	Management	
• Infrastructure	(Cloud,	Docker…)	
• Blog:	http://kbild.ch	
• http://linkedin.com/in/kbild	
• https://www.xing.com/profile/Klaus_Bild
3
Logdatei
Eine	Logdatei	(auch	Ereignisprotokolldatei;	englisch	log	file)	enthält	das	automatisch	
geführte	Protokoll	aller	oder	bestimmter	Aktionen	von	Prozessen	auf	einem	
Computersystem.	Die	korrekte	Bezeichnung	dafür	ist	deshalb	Protokolldatei.	
Wichtige	Anwendungen	finden	sich	vor	allem	bei	der	Prozesskontrolle	und	
Automatisierung.	Prinzipiell	werden	alle	Aktionen	mitgeschrieben,	die	für	eine	spätere	
Untersuchung	(Audit)	erforderlich	sind	oder	sein	könnten.	Der	Flugschreiber	in	
Flugzeugen	ist	ein	Beispiel	für	kontinuierliche	Protokollierung,	die	jedoch	selten	
ausgewertet	wird,	zum	Beispiel	nach	einem	Unfall.	
Im	Bereich	der	Datenbanken	bezeichnet	Logfile	die	Protokolldatei,	in	der	Änderungen	
an	der	Datenbank	von	korrekt	abgeschlossenen	Transaktionen	(per	Commit	
abgeschlossen)	festgehalten	werden,	um	im	Fall	eines	Fehlers	(z.	B.	Systemabsturz)	den	
aktuellen	Datenbestand	wiederherstellen	zu	können.	
https://de.wikipedia.org/wiki/Logdatei
4
When do you consult logs?
Never:	
• You	are	not	an	admin	or	developer	
If	something	went	wrong	

(and	a	user	reported	it):	
• What	happened?	
• Where?	
• When?	
• Why?
5
But…
Multi-tier	systems:	
• Multiple	servers	
• Multiple	applications	
• Multiple	databases	
• Multiple	systems	
• …
6
Log Sources
Applications	/	APIs	
• Requests	
• Error	handling	
• Successes	
• Failed	attempts	
• Privilege	changes	
• Object	manipulation
Appliances	
• Routers	
• Switches	
• Firewalls
Databases	
• Queries	
• Errors
Infrastructure	
• Servers	
• Containers	
• Web	servers	
• Load	balancers	
• Paas	/	IaaS
Front	End	
• Log-ins	
• Form

completions	
• Important	click

events
Tools	
• Configuration

Automation	
• Analytics	tools	
• Alerting	tools	
• Chat	tools
Sensors	
• IoT	
• Industrie	4.0	
• Home	

automation
7
Log	examples:	
• [01988:00243-3598456576]	18.01.2016	08:49:35			Opened	session	for	WGMob01/WGC/CH	(Release	9.0.1FP4)	
• [41732479.416668]	[INT_2_VYATTA-default-D]IN=bond1	OUT=bond1.2036	MAC=00:00:5e:00:01:01:00:08:e3:ff:fd:90:08:00	
SRC=95.26.112.172	DST=81.95.156.246	LEN=106	TOS=0x00	PREC=0x00	TTL=55	ID=27102	PROTO=ICMP	TYPE=3	CODE=3	
[SRC=81.95.156.246	DST=95.26.112.172	LEN=78	TOS=0x08	PREC=0x20	TTL=235	ID=62876	DF	PROTO=UDP	SPT=15798	DPT=53	
LEN=58	]		
• 220.160.156.109	-	-	[18/Jan/2016:01:54:22	-0600]	"POST	/saveNewSubmit.do	HTTP/1.1"	200	6687	"http://
www.logfilesarecool.net/createSubmit.do?submitId=4418324"	"Mozilla/5.0	(Windows	NT	6.1;	Trident/7.0;	MATP;	rv:11.0)	like	
Gecko”	
• [1/18/16	8:46:05:061	CET]	000001b6	IndexBuilderQ	I	com.ibm.connections.search.admin.index.impl.IndexBuilderQueue	build	
CLFRW0285I:	Search	is	starting	to	build	the	index	for	wikis.
Booooring
Logs
8
Visualization of Logs = Gold
9
Visualization of Logs
Gives	you:	
• Operational	Visibility

Gain	end-to-end	visibility	across	your	operations	and	break	down	silos	across	your	infrastructure	
• Search	and	Investigation

Find	and	fix	problems,	correlate	events	across	multiple	data	sources	and	automatically	detect	
patterns	across	massive	sets	of	data	
• Proactive	Monitoring

Monitor	systems	in	real	time	to	identify	issues,	problems	and	attacks	before	they	impact	your	
customers,	services	and	revenues	
• Business	Insights

Make	better-informed	business	decisions	by	understanding	trends,	patterns	and	gaining	
operational	intelligence	from	machine	data
10
Visualization of Logs
The	Solution	-	ELK	Stack
}
11
The ELK stack
Elastic	Search:	
• Lucene	based	search	engine	(Java	Stack)	
• Distributed	capability	
• REST	API	over	HTTP	
• Data	share	using	JSON	format	
Logstash:	
• Ruby	Agent	application	
• Agent	to	collect	log	data	in	numerous	input	formats	
• Filters	can	be	applied	
• Many	Output	formats	supported	
Kibana:	
• Flexible	analytics	and	visualization	platform
12
WebGate environment
Agents/Shipper Broker
Filebeat
Filter/Indexer
Search/StorageWeb	Interface/
Visualizer
Docker	containers
13
Logstash
Input:	
• beats,	couchdb_changes,	drupal_dblog,	elasticsearch,	exec,	eventlog,	file,	
ganglia,	gelf,	generator,	graphite,	github,	heartbeat,	heroku,	http,	http_poller,	irc,	
imap,	jdbc,	jmx,	kafka,	log4j,	lumberjack,	meetup,	pipe,	puppet_facter,	relp,	rss,	
rackspace,	rabbitmq,	redis,	snmptrap,	stdin,	sqlite,	s3,	sqs,	stomp,	syslog,	tcp,	
twitter,	unix,	udp,	varnishlog,	wmi,	websocket,	xmpp,	zenoss,	zeromq	
Output:	
• boundary,	circonus,	csv,	cloudwatch,	datadog,	datadog_metrics,	email,	
elasticsearch,	elasticsearch_java,	exec,	file,	google_bigquery,	
google_cloud_storage,	ganglia,	gelf,	graphtastic,	graphite,	hipchat,	http,	irc,	
influxdb,	juggernaut,	jira,	kafka,	lumberjack,	librato,	loggly,	mongodb,	
metriccatcher,	nagios,	null,	nagios_nsca,	opentsdb,	pagerduty,	pipe,	riemann,	
redmine,	rackspace,	rabbitmq,	redis,	riak,	s3,	sqs,	stomp,	statsd,	solr_http,	sns,	
syslog,	stdout,	tcp,	udp,	webhdfs,	websocket,	xmpp,	zabbix,	zeromq
14
Logstash
Filter:	
• aggregate,	alter,	anonymize,	collate,	csv,	cidr,	clone,	cipher,	checksum,	date,	
de_dot,	dns,	drop,	elasticsearch,	extractnumbers,	environment,	elapsed,	
fingerprint,	geoip,	grok,	i18n,	json,	json_encode,	kv,	mutate,	metrics,	multiline,	
metaevent,	prune,	punct,	ruby,	range,	syslog_pri,	sleep,	split,	throttle,	translate,	
uuid,	urldecode,	useragent,	xml,	zeromq
Log	Entry/Message
84.74.43.46	-	-	[15/Mar/2016:08:41:00	+0100]	"GET	/files/basic/api/myfilesync/feed?page=1&pageSize=500&includeConflict=true	HTTP/1.1"	200	1323	"-"	"IBM-LC-
IBM	Connections	sync/1602.3033.1103	(Mac	OS	X	10.10.5)"
Document
Field	1

i.e.	Source	IP
Field	2 Field	3 Field	4 Field	5
Filters
15
Logstash
Example	(HTTP	access	log):	
• 84.74.43.46	-	-	[15/Mar/2016:08:41:00	+0100]	"GET	/files/basic/api/myfilesync/feed?page=1&pageSize=500&includeConflict=true	HTTP/
1.1"	200	1323	"-"	"IBM-LC-IBM	Connections	sync/1602.3033.1103	(Mac	OS	X	10.10.5)"	
	filter	{	
		if	[type]	==	"apache_access"	{	
		grok	{	
				match	=>	

{	"message"	=>	"%{IPORHOST:clientip}	%{USER:ident}	%{USER:auth}	[%{HTTPDATE:timestamp}]	"(?:%{WORD:verb}	%{NOTSPACE:request}(?:	
HTTP/%{NUMBER:httpversion})?|%{DATA:rawrequest})"	%{NUMBER:response}	(?:%{NUMBER:bytes}|-)	%{QS:referrer}	%{QS:agent}	}	
…
clientip	:	
84.74.43.46
timestamp:	

15/Mar/2016:08:41:00	+0100
verb:	

GET
request:	

/files/basic/api/myfilesync/feed?
page=1&pageSize=500&includeConflict=true
httpversion:	

1.1
response:	

200
bytes:	

1323
referrer:	

-
agent:	

"IBM-LC-IBM	Connections	sync/1602.3033.1103	
(Mac	OS	X	10.10.5)"
16
Logstash
Example	(HTTP	access	log):	
• 84.74.43.46	-	-	[15/Mar/2016:08:41:00	+0100]	"GET	/files/basic/api/myfilesync/feed?page=1&pageSize=500&includeConflict=true	HTTP/
1.1"	200	1323	"-"	"IBM-LC-IBM	Connections	sync/1602.3033.1103	(Mac	OS	X	10.10.5)"	
		date	{	
				match	=>	[	"timestamp"	,	"dd/MMM/yyyy:HH:mm:ss	Z"	]	
		}	
				geoip	{	
						source	=>	"clientip"	
						target	=>	"geoip"	
						database	=>	"/etc/logstash/GeoLiteCity.dat"	
						add_field	=>	[	"[geoip][coordinates]",	"%{[geoip][longitude]}"	]	
						add_field	=>	[	"[geoip][coordinates]",	"%{[geoip][latitude]}"		]	
				}	
				useragent	{	
							source	=>	"agent"	
							add_tag	=>	[	"browser"	]	
				}	
		}	
}
timestamp:	

15/Mar/2016:08:41:00	+0100
… geoip.country_code3:	
CHE
geoip.location:	

8.298599999999993,	47.06030000000001
clientip	:	
84.74.43.46
…
agent:	

"IBM-LC-IBM	Connections	sync/1602.3033.1103	
(Mac	OS	X	10.10.5)"
os_name	:	

Mac	OS	X
name	:	

Other
os_major	:	

10
os_minor	:	

10
17
Logstash
18
Visualization of Logs
Gives	you:	
• Operational	Visibility

Gain	end-to-end	visibility	across	your	
operations	and	break	down	silos	across	your	
infrastructure	
• Search	and	Investigation

Find	and	fix	problems,	correlate	events	across	
multiple	data	sources	and	automatically	
detect	patterns	across	massive	sets	of	data	
• Proactive	Monitoring

Monitor	systems	in	real	time	to	identify	
issues,	problems	and	attacks	before	they	
impact	your	customers,	services	and	revenues	
• Business	Insights

Make	better-informed	business	decisions	by	
understanding	trends,	patterns	and	gaining	
operational	intelligence	from	machine	data
• IBM	Solutions	Log	Management	
• Centralized	Log	Management	
• Security	Monitoring	
• Performance	Monitoring	
• Data	Analysis
{
19
Costs
• All	ELK	Stack	products	are	
• Installation	and	configuration:	Couple	of	days
20
Lassen	Sie	uns	
zusammen	Gold	
finden	
Vielen	Dank!

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