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Log Management Systems
A comparison of message and metric
management solutions
Presenter: Mehdi Hamidi
( @eXtrem0us )
Introduction
What is LOG?
●Combination of Time, Tag and Message
●Indicates State of Applications (?)
●Human and Machine Readable Messages (?)
Level of logs in syslog standard
●From Debug to Panic
●rsyslog, syslog, syslog-ng
●/var/log/syslog /var/log/rsyslog
Importance of logs
●Companies and Businesses
●Even Personal Use!
(Twitter, Sensors,... )
LogAnalyzer: a simple solution :)
LogAnalyzer: a simple solution :)
Importance of Logging Systems
WHAT Actually We NEED?
Collect
Messages
Metrics
●Store
●Visualize
●Alert
Importance of Logging Systems
Heterogeneous Environment
Write our own script for each type of log (?)
Not in an enterprise environment with lots of
devices and services!
●Technical Fragility and dependency to
Individuals
●Strong Dependency to knowledge about
underlying process
Commercial Solutions
Splunk
(500M/Day is Free, then: 5,000,000 $)
●Nagios
Everything is restricted to Nagios Concept
No separation between metrics and messages
No stylish diagrams (in free solution)
Problems in cloud infrastructure
No realtime monitoring
No manipulating messages
(1,995 $ for commercial solution)
●Online Services
Good logging system Specifications
●Have a common interface
●Decouple data sources from data outputs
Prevent mentioned dependencies
No effect of adding new data source/output
Reliability
Persistent Buffering
●Extensibility
High Availability
Load Balancing
Robustness
Lots of OpenSource Bricks (OSB!)
Logging Systems:
● Fluentd
● LogStash
● GrayLog
● Logalice
● Rsyslog
● Scribe
Message Stores:
● ElasticSeach
● Hadoop
● MongoDB
● File
● RDBMS
● Redis
● ...
Visualization
(Dashboards):
● Kibana
● Grafana
● Gaylog-WebUI
● PacketBeat
● Chronograph
● ...
Metric Stores:
● InfluxDB
● Prometheus
● Graphite
● ...
Alerting:
● Kapacitor
● Skyline
● Oculus
● Cabot
Log Nature
Semistructured or Unstructured
Generated Massively
More Written and less Read
(That's why we use NoSQL)
Popular Stacks (metrics): TICK Stack
Popular Stacks (Messages) : ELK Stack
Fluentd VS LogStash
Overview
Fluentd:
Written in Cruby
Used in Google Cloud Platform and Kubernetes
Maintained by Tresure Data
●Logstash:
Written in Jruby
Used in ELK Stack
Maintained by Elastic Co.
➢Both use their own RubyGems Repo
➢Out of the box nature, less dependencies
Configuration
Fluentd:
Each Input is tagged
Logs are routed by tags
Logstash:
All inputs are Gathered and Scattered
Conditional Outputs, No tags
Configuration
Transport and Buffering
Fluentd: built-in
LogStash: bundled Redis
version 5.3: persistent buffering
Full Buffer or Output Exception occurrence
Fluentd:
Exception: streaming
Block input plugin: batch
Drop oldest chunk: monitoring
LogStash:
Retry
Discard
Dead Letter Queuing
High Availability and Load balancing
High Availability and Load balancing
High Availability and Load balancing
High Availability and Load balancing
Memory
Fluentd: 40 M
Logstash: 120 M
(in big clusters matter)
Forwarders
●Fluentd:
 Fluentbit (Written in C)
 Fluentd-Forwarder (Written in Go)
 (all in one)
●LogStash:
 Filebeat
 Metricbeat
 Packetbeat
 Winlogbeat
(beat family: separated component for each
purpose)
Community and Support
Fluentd: Poor
Japanese Blogs
Google Group
Logstash: Rich
Documents
Blogs
IRC
Meetups and Certs
Plugins
Fluentd Plugins Verified
Input/Output 554 44
Filter 90 8
Parser 30 2
Formatter 6 0
Obsolete 8 0
Plugins are maintained more by other people.
Plugins
All Plugins are in a Single GitHub Repo.
LogStash Plugins
Input 52
Filter 46
Output 55
Questions?
Thanks You!
ahamidi66@gmail.com
@eXtrem0us
Resources
http://logz.io/blog/fluentd-logstash
http://docs.fluentd.org/articles/buffer-plugin-overvie
https://prometheus.io/docs/introduction/comparison
http://logz.io/blog/elk-stack-5-0
https://www.youtube.com/watch?v=1ye0-sityBw
https://www.youtube.com/watch?v=0lAHrspviIs&list=PL62pIycqXx-TPwtk4JDd0wMuFAyP0gU1y
https://www.youtube.com/watch?v=mfb0R7azKZc
https://www.youtube.com/watch?v=_BAWi9Zhmic

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