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Learning Elastic Stack 6.0

You're reading from  Learning Elastic Stack 6.0

Product type Book
Published in Dec 2017
Publisher Packt
ISBN-13 9781787281868
Pages 434 pages
Edition 1st Edition
Languages
Authors (2):
Pranav Shukla Pranav Shukla
Profile icon Pranav Shukla
Sharath Kumar M N Sharath Kumar M N
Profile icon Sharath Kumar M N
View More author details

Table of Contents (19) Chapters

Title Page
Credits
Disclaimer
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Introducing Elastic Stack Getting Started with Elasticsearch Searching-What is Relevant Analytics with Elasticsearch Analyzing Log Data Building Data Pipelines with Logstash Visualizing data with Kibana Elastic X-Pack Running Elastic Stack in Production Building a Sensor Data Analytics Application Monitoring Server Infrastructure

Logstash architecture


The Logstash event processing pipeline has three stages, they are: Inputs, Filters and Outputs. A Logstash pipeline has two required elements; input, output, and, optionally, filters:

Inputs create events, Filters modify the input events, and Outputs ship them to the destination. Inputs and outputs support codecs which enable you to encode or decode the data as and when it enters or exits the pipeline without having to use a separate filter.

Logstash uses in-memory bounded queues between pipeline stages by default (Input to Filter and Filter to Output) to buffer events. If Logstash terminates unsafely, any events that are stored in memory will be lost. To prevent data loss, you can enable Logstash to persist in-flight events to the disk by making use of persistent queues. 

Note

Persistent queues can be enabled by setting the property queue.type: persisted in the logstash.yml file found under the LOGSTASH_HOME/config folder. logstash.yml is a configuration file containing...

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