Post on 06-May-2015
description
transcript
IRM Summit 2014
Customer Intelligence: Using the ELK stack (Elasticsearch,
Logstash and Kibana) to analyse
ForgeRock OpenAM audit data
warren.strange@forgerock.com
IRM Summit 2014
Make pretty pictures for the boss
3IRM Summit 2014
Coincidence?
OpenDJ, OpenIDM, OpenAM produce copious amounts of audit data
Analysis of that data is left as an exercise for the reader
Many great SIEM tools
Desire for an Open Source solution for data analysis
What is the ELK stack?
Elasticsearch: “No SQL” database
Logstash: Log collection and transformation
Kibana: Data visualizer for Elasticsearch
Yes, but what does ELK do?
Collect, analyse and visualize data Any kind of dataGithub (8 Million repos), Soundcloud (30M users), The Guardian (40M documents)
Answer questions:● Where are my users coming from?● What is the traffic in North America vs.
Europe?● Why do I see an employee logging in from
Canada?
Elasticsearch
● NoSQL, REST/json, document oriented, schemaless, “Big data” full text search engine
● Apache 2.0 license ● Sweet spot is rapid full text search / ad hoc queries ● Not a replacement for an RDBMS
● Not transactional, not ACID, etc.
● Built on Apache Lucene project
Logstash
● Swiss army knife of log collection, transformation and forwarding
● JRuby based● Large footprint :-(● lumberjack
● go based collector that feeds into logstash ● Very lightweight, small footprint
Kibana
Logstash flow
Input sourcefiles, database, syslog, etc.
Filtersgrep, regex, geoIP, ...
Outputelasticsearch, file, db, syslog
“Plugin” based architecture. Add new plugins for input, output and filters
Logstash example
Input sourcefile: amAccess.*type: amAccess
FiltersMap IP address to GEO location
Outputelasticsearch:9100
Read from OpenAM access logs
Add Geo Location data
Write the result to Elasticsearch
input {
file {
type => amAccess
path => "/logs/am/log/amAuthentication.*"
}
}
Input section
Wildcards can be used
Data is tagged with a type. Use this to classify & search by type
filter { if [type] == "amAccess" { csv { columns => [time,Data,LoginID,ContextID, IPAddr, LogLevel, Domain, LoggedBy, MessageID, ModuleName, NameID,
HostName] separator => " " } date { match => ["time", "yyyy-MM-dd HH:mm:ss"] } geoip { database => "/usr/share/GeoIP/GeoIP.dat" source => ["IPAddr"] } }}
Filter apply to type
Parse the dataas csv
Normalize the date to a common format
Enrich the record with GEO location
output { stdout { codec => rubydebug } elasticsearch { host => localhost }}
Output
Send the data to Elasticsearch and the stdout
ELK Demo Environment
OpenAM OpenDJ OpenIDM
logstash
elasticsearch:9100
Apache:80/443 +Policy Agent
Log Files
Kibana
Marketing Genius?
Where to hold the next ForgeRock Summit: Europe, USA, or Canada?
Asks you to find out pronto:● What country are customers visiting the ForgeRock website from?● How are they authenticating (forgerock account, or federated?)
The next IRM summit location:
We have beer!Bring your toque!
Next StepsDelivery Models
Cloud or Appliance?Interested in collaborating?
Share logstash config, kibana reports, etc.Puppet/Chef/Ansible/Docker installers?