Getting Started with LogStash
Getting Started with LogStash
Use Of Data Log Analysis >https://callistaenterprise.se/assets/presentationer/cadec-2015-elk.pdf
Start Video Webinar (1hr) :https://www.elastic.co/products/logstash
What is the difference between Logstash and Beats?edit
Beats are lightweight data shippers that you install as agents on your servers to send specific types of operational data to Elasticsearch. Beats have a small footprint and use fewer system resources than Logstash.
Logstash has a larger footprint, but provides a broad array of input, filter, and output plugins for collecting, enriching, and transforming data from a variety of sources.
For more information, see theLogstash Introductionand theBeats Overview.
Data Sources
Brief Architecture LogStash : Inputs
Filters
Data Output
Resselient : Recover Easy from failure and maintian queue for processing
Dynamic PipeLines
Input from Port Beat (Datsource)
What are we sending in Input
What is a PipeLine:https://medium.com/the-data-experience/building-a-data-pipeline-from-scratch-32b712cfb1db
2 Queues available in Logstash
Messages that are Undeliverable or cant be processed
Dead Letter Queue to handle and save and Handle Exception
Setting Up
- Create Data and setup in Beats to send data
- in Config Stage setup set input and Map Filter and Clean Data and then send the data to Elastic Search
3) Send all data to ElasticSearch and Check data in Kibana
Link:Documentation of Imp Files Inside inside the Logstash installation
Searchhttps://comparisons.financesonline.com/microsoft-power-bi-vs-elasticsearch
Serialization and Deserialization
Using Codec to transform Json to Redis Events
Encoding
Decoding
Line Codec is Default
Grok Filter to Filter after Parsing
Faster and Better Algorithm
Swiss Army Knife For Filtering
Example of Mutate Filter
Enrich data
Adding New Data to existing one
Custom Translation Mapping : Resolve Product Code but can be used in Querirs in Ealastic Search as well
