ELK Stack Certification Training

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ELK is an acronym of Elasticsearch, Logstash, and Kibana. Each of these is nothing, but an open-source project. Multisoft Systems offers ELK Stack Course that provides the learners with deeper insight into the ELK Modules. Our trainers help the candidates in gaining the in-depth knowledge of these open-sources. This training program also explains the best possible methods of using the Elastic Search, Logstash, and Kibana with other products and separately.

There are countless learning benefits associated with this training program. After completing the ELK Stack Certification Training, you will be able to:.

  • Learn the details of the ELK Stack with the several use-cases
  • Discuss the various components of ELK Stack in-depth
  • Install the Stack components in your system
  • Utilization of the Logstash to load the data into the Elastic Search
  • Analyze and evaluate the real-time data with the ELK Stack
Target Audience
  • Full Stack Technical Architects
  • Big Data Analytics Engineers – Elastic Search
  • System Log Analysts
  • Web Analysts
  • Web Administrators

To master the ELK Stack concepts, a candidate must-have the basic understanding of the following:

  • SQL
  • JSON Data Format
  • Restful API

1. Introduction to ELK Stack

  • An overview of ELK Stack
  • Why choose ELK?
  • Architecture of ELK
  • An explanation of Elastic Search
  • Logstash and Kibana

2. Introduction to Logstash

  • A brief explanation of Logstash
  • Installation process
  • Log file configuration
  • Stashing process of the first event
  • Analyzing logs with Logstash
  • Uses of input and output
  • Plugins
  • Execution model

3. Introduction to Elastic Search

  • An overview of Elastic Search
  • Installation and running process
  • Indexing documents list
  • Saving the documents
  • Searching the documents

4. Searching in Depth

  • Organized Search
  • Full-text Search
  • Intricate Search
  • Phrase Search
  • Underlining the Search
  • Multi-field Search
  • Proximity Matching
  • Partial Matching

5. Dealing with Human Languages

  • An introduction to various human languages
  • Identifying Words
  • Controlling Tokens
  • Decreasing Words to their actual Root Form
  • Stop words: Performance versus Precision
  • Synonyms
  • Typographical Errors and Spelling Mistakes

6. Aggregation

  • An insight into concepts
  • A brief introduction to Aggregation
  • Analysis process
  • Filtering Process of the Aggregations and Queries
  • Sorting Multivalue Loads
  • Expected Aggregation
  • Doc Values and Field Data

7. Introduction to Data Modeling

  • Elastic Search versus RDBMS
  • Relationships handling
  • Nested objects
  • Scale Designing

8. Geo-locations

  • Major Geo Points
  • Geo Hashes
  • Geo Aggregations
  • Geo Shapes

9. Introduction to Kibana

  • An overview of Kibana
  • Installation process of Kibana
  • Sample data loading process
  • Discovering the saved data
  • Visualization of the data
  • Working with the Dashboard

10. Discovering the Data in Depth and Dashboard Analysis

  • Set-up of Time Filter
  • Searching of the saved data
  • Filtering by the Field
  • Viewing the document data
  • Viewing the document context
  • Viewing the field statistics
  • Data visualization
  • Dashboard analysis
  • Exploring the live data with the ELK Stack

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