Complete Elasticsearch Masterclass with Logstash and Kibana
Learn how to build a search engine and break into big data by mastering Elasticsearch, Kibana and Logstash (ELK stack)
4.56 (8222 reviews)
48 428
students
6 hours
content
Dec 2023
last update
$74.99
regular price
What you will learn
Build and Deploy Elasticsearch clusters from scratch
Build Easy to Advanced search queries using powerful Query DSL
Transform and enrich data with Logstash for seamless processing
Craft interactive dashboards for data visualization using Kibana
Implement a Real-World Project by integrating the complete ELK stack
Install and configure Elasticsearch for Scalable Search Solutions
Perform powerful realtime analytics using the Aggregations DSL
Design and manage Logstash Pipelines for Efficient Data Ingestion
Optimize Elasticsearch Performance and Scale Clusters Effectively
Combine Filters, Queries and Aggregations and understand document relevancy and searching
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Our Verdict
Though this course provides solid foundational knowledge in ELK stack, its age has started to show with inconsistencies in various installations. The extensive focus on Mac use may challenge Windows learners, while the outdated content can lead to confusion as students encounter deprecated features. Still worthwhile for those willing to work around these issues or already familiar with newer versions or related software stacks—otherwise consider a more recent alternative.
What We Liked
- Covers all key concepts of ELK stack, great for beginners
- Instructor's clear explanations and live examples enhance understanding
- Excellent resource for those looking to integrate and practice ELK
- Addresses both conceptual overview and hands-on experience
Potential Drawbacks
- Outdated content, installations mentioned may not align with newer versions
- Limited support for Windows OS installation, may require external resources or knowledge
- Deprecated features or commands in current Elasticsearch version 8
- Lectures lack information on possible errors and their solutions
Related Topics
1245870
udemy ID
08/06/2017
course created date
13/11/2019
course indexed date
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