Elastic Search Training

Introduction to Elastic Search

Understand the basics of Elastic Search, its architecture, and how it fits into the ELK stack (Elasticsearch, Logstash, and Kibana). Learn about its role in search and analytics.

Setting Up Elastic Search

Learn how to install and configure Elastic Search on various platforms. Understand cluster setup, node configuration, and initial indexing.

Data Indexing and Mapping

Explore how to index and map data in Elastic Search. Study the creation of indices, types, and mappings, and how to optimize data storage and retrieval.

Search and Querying

Discover how to perform searches and queries in Elastic Search. Learn about different query types, including full-text search, structured search, and complex queries.

Aggregation and Analytics

Study aggregation features in Elastic Search for data analysis. Learn how to perform statistical, histogram, and bucket aggregations to extract insights from your data.

Performance Tuning

Learn techniques for optimizing Elastic Search performance. Understand indexing strategies, query optimization, and resource management for efficient search operations.

Integration with Other Tools

Explore how Elastic Search integrates with other tools and platforms. Learn about Logstash for data ingestion, Kibana for visualization, and various APIs for custom integrations.

Security and Access Control

Understand security features in Elastic Search. Learn about user authentication, role-based access control, and securing data in transit and at rest.

Monitoring and Maintenance

Discover best practices for monitoring and maintaining Elastic Search clusters. Learn how to use monitoring tools, manage cluster health, and handle backups and recovery.

Case Studies and Practical Applications

Engage with case studies and practical exercises to apply Elastic Search concepts. Work on real-world scenarios to build and manage search solutions effectively.

Advanced Features and Customization

Explore advanced features and customization options in Elastic Search. Learn about plugins, custom analyzers, and scripting to extend the functionality of your search engine.

Elasticsearch Syllabus

1. Introduction to Elasticsearch

  • What is Elasticsearch?
  • Use Cases and Benefits
  • Core Concepts
  • Index, Document, Type
  • Node, Cluster, Shard, Replica
  • Document CRUD Operations

2. Querying Elasticsearch

  • Basic Search Queries
  • Full-Text Search
  • Filtering, Aggregations, Sorting
  • Query DSL (Domain-Specific Language)

3. Mapping and Analysis

  • Mapping Types
  • Analysis and Analyzers
  • Mapping Customization

4. Scaling Elasticsearch

  • Horizontal Scaling
  • Cluster Setup and Configuration
  • Sharding and Replication Strategies

5. Advanced Search Features

  • Geo-Spatial Search
  • Highlighting
  • Fuzzy Queries, Wildcard Queries

6. Elasticsearch APIs

  • RESTful API Basics
  • CRUD Operations Using APIs
  • Bulk API

7. Elasticsearch Security

  • Authentication and Authorization
  • User Roles and Permissions

8. Monitoring and Administration

  • Cluster Health Monitoring
  • Performance Tuning
  • Backup and Restore Strategies

9. Integration with Other Systems

  • Logstash and Beats for Data Ingestion
  • Kibana for Visualization and Monitoring

10. Elasticsearch in Production

  • Best Practices
  • Troubleshooting Common Issues

11. Advanced Querying

  • Query Performance Optimization
  • Complex Nested Queries
  • Scripted Queries and Filters
  • Function Score Query for Custom Relevance Scoring

12. Aggregations

  • Metrics Aggregations (sum, min, max, avg)
  • Bucket Aggregations (terms, date histograms, ranges)
  • Pipeline Aggregations for Advanced Metrics

13. Mapping and Analysis

  • Custom Analyzers and Tokenizers
  • Multi-Fields and Dynamic Templates
  • Index-Time and Search-Time Boosting

14. Index Management

  • Index Settings and Mappings Management
  • Index Aliases and Index Templates
  • Index Lifecycle Management (ILM)

15. Data Modeling

  • Parent-Child Relationships
  • Join Datatype for Denormalization
  • Handling Hierarchical Data

16. Scalability and Resilience

  • Cross-Cluster Search
  • Shard Allocation Awareness
  • Circuit Breakers and Thread Pools

17. Security

  • SSL/TLS Configuration
  • Role-Based Access Control (RBAC)
  • Audit Logging and Compliance Features

18. Monitoring and Performance Tuning

  • Performance Metrics and Monitoring APIs
  • Hot-Warm-Cold Architecture
  • JVM Tuning and Heap Management

19. Data Ingestion

  • Using Logstash for Complex Data Pipelines
  • Beats for Lightweight Data Shippers
  • Ingest Node for Elasticsearch Data Transformation

20. Advanced Scripting

  • Inline and Stored Scripts
  • Scripting Languages
  • Security Considerations and Limitations

Training

Basic Level Training

Duration : 1 Month

Advanced Level Training

Duration : 1 Month

Project Level Training

Duration : 1 Month

Total Training Period

Duration : 3 Months

Course Mode :

Available Online / Offline

Course Fees :

Please contact the office for details

Placement Benefit Services

Provide 100% job-oriented training
Develop multiple skill sets
Assist in project completion
Build ATS-friendly resumes
Add relevant experience to profiles
Build and enhance online profiles
Supply manpower to consultants
Supply manpower to companies
Prepare candidates for interviews
Add candidates to job groups
Send candidates to interviews
Provide job references
Assign candidates to contract jobs
Select candidates for internal projects

Note

100% Job Assurance Only
Daily online batches for employees
New course batches start every Monday