1.
Michael Kehoe
Senior Site Reliability Engineer
LinkedIn
Using SaltStack to Auto Triage and
Remediate Production Systems

2.
Topics
• $ whoami
• Salt @ LinkedIn
• LinkedIn’s auto remediation story
• Nurse
• Salt API
• Auto-remediation Salt Modules
• How to get started

3.
$ whoami

4.
Salt @ LinkedIn
• 11-14k minions per master
• Up to 8.5 events/ second per master
• Deployment system heavily utilizes Salt
• 5 dedicated SRE’s work on LinkedIn’s Salt infrastructure
• Number of SRE’s who also contribute

5.
Alert Growth vs NOC Engineers
LinkedIn’s Auto-remediation Story
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Num of Alerts
Num of Engineers

6.
The problem
LinkedIn’s Auto-remediation Story
• Growing number of high priority alerts vs Engineers to watch
• Complicated ITR’s (runbooks) took time for NOC engineers to
execute and escalate
• SRE’s would forget to run diagnostic tooling during outages
• Longer MTTR == Bad experience for members

7.
Building the Solution
LinkedIn’s Auto-Remediation Story
• LinkedIn needed a workflow engine
• Requirements
• Take automated actions against applications/ hosts
• Perform the run book automatically
• Appropriate auditing
• Scalable

8.
What’s already out there
Autoremediation
• StackStorm
• fbar
• SaltStack
Started building an in-house solution in Mid-2014

9.
Nurse
Image: freeflaticons.com

10.
Nurse
• ‘Event based’ system
• Built on top of LinkedIn’s existing monitoring infrastructure
• Allows for manual execution via Web UI
• Allows for other systems to plug-in via REST API
• Built in rules-engine
• Allows for complicated checks/ branching
• Global environment awareness
• Scalable!

11.
Nurse

12.
Nurse

13.
The basics
Salt REST API
• RESTful interface to SALT
• Allows for external-authentication
• PAM
• LDAP
• Your own plugin…
• Built on top of CherryPy

14.
Interface
Salt REST API
• /login - Log in to receive a session token
• /logout - Remove or invalidate sessions
• /minions – Working directly with minions
• /jobs - Getting lists of previously run jobs or getting the return from a single job
• /run - Run commands without normal session handling
• /events - Expose the Salt event bus
• /hook - A generic web hook entry point that fires an event on Salt's event bus
• /keys – Wrapper around key management
• /ws - Open a WebSocket connection to Salt's event bus
• /stats - Return a dump of statistics collected from the CherryPy server
https://docs.saltstack.com/en/latest/ref/netapi/all/salt.netapi.rest_cherrypy.html

15.
Configuration
Salt REST API
external_auth:
ldap:
headless-nurse:
- '*':
- test.*
- nurse.*
- '@jobs'
https://docs.saltstack.com/en/latest/ref/netapi/all/salt.netapi.rest_cherrypy.html
/etc/salt/master.d/salt-api.conf

16.
Configuration
Salt REST API
rest_cherrypy:
port: 8888
ssl_crt: /etc/salt/pki/api/salt-api.crt
ssl_key: /etc/salt/pki/api/salt-api.key
https://docs.saltstack.com/en/latest/ref/netapi/all/salt.netapi.rest_cherrypy.html
/etc/salt/master.d/salt-api.conf

17.
Configuration
Salt REST API
auth.ldap.basedn: 'dc=example,dc=com'
auth.ldap.binddn: ’readonly-ldap@example'
auth.ldap.bindpw: ’password'
auth.ldap.filter: sAMAccountName={{ username }}
auth.ldap.server: ldap.example.com
auth.ldap.tls: True
auth.ldap.persontype: 'person'
auth.ldap.groupclass: 'group'
auth.ldap.groupou: 'Users’
https://docs.saltstack.com/en/latest/topics/eauth/index.html
/etc/salt/master.d/salt-api.conf

18.
Code Interfaces
Salt REST API
• There is a Python interface to the Salt API – pepper
• Provides basic wrapper around REST API
• https://github.com/saltstack/pepper/
• See https://github.com/SUSE/salt-netapi-client for JAVA
bindings

19.
Python Code example
Salt REST API
from pepper.libpepper import Pepper
api = Pepper('https://salt.example.com:8888')
api.login('saltdev', 'saltdev', ’ldap')
# Run simple function
api.low([{'client': 'local', 'tgt': '*', 'fun': 'test.ping'}])
# Execute a runner function
api.runner('jobs.lookup_jid', jid=12345)

20.
Goals
Auto-remediation Salt Modules
• Auto-triage issues
• Reduce context-switching
• Run labor intensive tasks automatically
• Gather data while engineer is logging in after escalation
• Auto-remediate issues
• Let the engineer sleep
• Faster MTTR

21.
Implementation
Auto-remediation Salt Modules
• Auto-triage issues
• Identify abusive clients
• Collect & analyses thread/ heap dumps
• Parse & summarize log files

22.
Implementation
Auto-remediation Salt Modules
• Auto-remediate issues
• Restart/ OOR applications
• Scale-up applications
• Blocking abusive clients
• Update A/ B experiment definitions
• Otherwise escalate…

23.
Implementation
Auto-remediation Salt Modules
• Plenty of Salt modules/ runners already out there
• Over 300 modules are available in Salt core
• Modules to take remediate & notify
• Write your own
• Make sure you test!

24.
Success
LinkedIn’s Auto-remediation Story
• 854k actions taken
• 100% of service health check alerts are on boarded
• ~37k man hours have now been automated
• Now automating ~1100 hours/ week

25.
Success
LinkedIn’s Auto-remediation Story
0
5
10
15
20
25
30
0
5000
10000
15000
20000
25000
30000
35000
40000
2010 2011 2012 2013 2014 2015 2016 2017
Num of Alerts
Num of Engineers

26.
Some lessons learnt
How to get started
• Need to make decision on how you architecture YOUR ‘event
bus’
• Use external monitoring to trigger Salt via API
• Use reactors/ beacons internally within Salt’s event bus
• See ‘Thorium’ documentation for Salt’s new reactor engine
• Auditing is important!
• Need to know what/ who triggered actions

27.
Some lessons learnt
How to get started
• Reporting is important!
• Need to know how often automated actions are being taken
• Find failure hotspots
• Leverage event-bus or returners
• Safety first
• Don’t give yourself too much rope…

28.
Conclusion
• Think carefully about your ‘Event-Driven-Automation’
architecture
• The sky is the limit with Salt…don’t limit yourself
• Again…safety first

29.
Questions?
29
Thank You