Introduction: Alice is a support engineer at TS foundation, a software development firm. Single sign-on for its apps is one of its features.

ALICES’ DAY TO DAY CHALLENGES: Her job is to assist consumers and fix problems as needed. When she receives a ticket for an issue, the first place she looks is the logs on the assigned servers. She continues to look for comparable terms or keyword matches. Meanwhile, records are changing every minute, making her search increasingly difficult.

How can we assist her?

SOLUTION:

This is when the ELK stack comes into play.

ELK includes elastic search, logstash, and kibana layered together to provide a complete analytics solution.

ElasticSearch helps her to simply search logs, learn about the issue, and handle it more quickly; moreover, she can be proactive by studying the logs to determine if any of those clients are experiencing any troubles or failures.

She may now quickly log into Kibana and search for relevant keywords. She may further narrow down her search by utilizing a timestamp filter. Monitoring single sign-on activity is simple with several display graphs on dashboards.

Goal: Let us assist Alice by introducing her to the ELK stack and assisting her in understanding the basic principles and technology underlying it. This will assist her in studying ELK architecture and various ELK stack implementations in businesses. 

Objectives: After finishing this lesson, you should be able to:

• Introducing the ELK stack. 

• Learn about the ELK stack's architecture. 

• Understand diverse ELK jargon 

• Discover the fundamentals of ElasticSearch, Logstash, and Kibana.

• Recognize the application of the ELK stack

Topics:

• Introduction to ELK stack

• Why ELK?

• Architecture of ELK

• High level overview of 

• 
  

• Elastic Search

• Logstash

• Kibana

GOAL- Alice has learned the fundamentals of the ELK stack. What if she needs to work with fresh sets of inputs? Let's support her using logstash, another component of the ELK stack. This lesson will provide her with a brief introduction to Logstash as well as walk her through the process of installing Logstash and ensuring that everything is operational. After you've learned how to store your first event, you may build a more complicated pipeline: it accepts Apache web logs as input, parses the logs, and sends the processed data to an Elasticsearch cluster. Then you'll learn how to connect several input and output plugins to combine data from various sources.

Objectives: At the end of this lesson, you should be able to:

• Logstash should be installed and running on your computer.

• First, learn to stockpile. 

• Make a more sophisticated pipeline that accepts Apache web logs as input, parses the logs, and uploads the processed data to an Elasticsearch cluster.

• Learn how to connect several input and output plugins to harmonize data from many sources.

Topics:

• Introduction to Logstash

• Installing Logstash

• Configuring a log file

• Stashing your First Event

• Parsing Logs with Logstash

• Stitching together Multiple Input and Output

• Plugins 

• Execution Model

Hands On: 

• Step by step guide to install Logstash on your machine

• Configure the log file

• Stash your first event in Logstash

• Parsing Logs with Logstash

• Installing File Beats and configuring it to work with Logstash

• Configuring Grok Plugin

Goal: Alice has a general grasp of the ELK stack; now she wants to go into each component. Let us assist her in getting started by providing a quick overview of Elastic Search along with a use-case. 

Objectives:  At the end of this module, you should be able to:

• Enable Multi Value tags, Numbers, and Full text

• Retrieve the full details of any employee

• Perform Structured search 

• Learn about full-text search

• Return highlighted search snippets

Topics:

• ElasticSearch Overview

• Installing and running ElasticSearch

• Indexing Documents

• Retrieving a Document

• Searching a Document

Hands On:

• Installing and running ElasticSearch

• Indexing Documents

• Retrieving Full Document

• Retrieving a part of Document

• Checking Document Existence

• Updating a Document

• Deleting a Document

• Searching a Document (Overview)

Goal: Alice seems to be enthusiastic about learning and searching in depth. She wishes to learn more about ElasticSearch. She realized that using the match query was not enough. She must comprehend the data and execute a search query against it. This session teaches her how to index and query your data so she may use word proximity, partial matching, fuzzy matching, and language awareness.

Objectives: At the end of this module, you should be able to:

• Perform Structured Search using Elastic search

• Deploy and understand full text search query

• Know your data with multi field search

• Find associated words

• Understand partial matching query

Topics:

• Structured Search

• Full text Search

• Complicated Search 

• Phrase Search

• Highlighting our Search

• Multi-field Search

• Proximity Matching

• Partial Matching

Hands On:

All of the topics mentioned above are quite hands-on.

Goal: Alice had learnt and done numerous searching queries and was pleased with the results when she became aware of a problem. Her inquiry was unable to eliminate the distinction between singular and plural terms, as well as between tenses. She also had to deal with typos and other issues. Let us assist Alice in resolving her troubles by teaching her how to cope with human language in order to improve her performance.

Objectives: At the end of this lesson, you should be able to:

• Using Normalizing Tokens, remove diacritics such as ', and' so that a search for rôle will also match role and vice versa.

• By stemming each word to its root form in Reducing Words to Their Root Form, you may eliminate the distinction between single and plural—fox versus foxes—or between tenses—jumping versus leopard versus jumps.

• To increase search performance in Stopwords: Performance Versus Precision, remove often used words or stopwords such as the, and, and or.

• Including synonyms so that a query for quick can also match fast, or the UK can match the United Kingdom using Synonyms.

• Using Typos & Misspellings, check for misspellings or other spellings, or match on homophones—words that sound the same, such as their versus there, meat versus meet versus mete.

Topics:

• Getting Started with languages

• Identifying Words

• Normalizing Tokens

• Reducing Words to their Root Form

• Stopwords: Performance versus Precision

• Synonyms

• Typos and Misspellings

Hands On:

Above all topics are hands-on intensive