Practical Full ELK Stack: Elasticsearch, Kibana and Logstash
Practical Full ELK Stack: Elasticsearch, Kibana and Logstash, available at $44.99, has an average rating of 4.1, with 86 lectures, based on 18 reviews, and has 180 subscribers.
You will learn about Learning how to deploy Elasticsearch and Kibana in various environment platforms Administering and managing Elasticsearch and Kibana Developing programs for Elasticsearch and Kibana Building data visualization with Kibana Collecting data using Logstash and Beat Implementing high availability for Elasticsearch and Kibana This course is ideal for individuals who are Developers or IT Administators or Web Developers or Anyone who wants to learn Elasticsearch and Kibana It is particularly useful for Developers or IT Administators or Web Developers or Anyone who wants to learn Elasticsearch and Kibana.
Enroll now: Practical Full ELK Stack: Elasticsearch, Kibana and Logstash
Summary
Title: Practical Full ELK Stack: Elasticsearch, Kibana and Logstash
Price: $44.99
Average Rating: 4.1
Number of Lectures: 86
Number of Published Lectures: 86
Number of Curriculum Items: 86
Number of Published Curriculum Objects: 86
Original Price: $24.99
Quality Status: approved
Status: Live
What You Will Learn
- Learning how to deploy Elasticsearch and Kibana in various environment platforms
- Administering and managing Elasticsearch and Kibana
- Developing programs for Elasticsearch and Kibana
- Building data visualization with Kibana
- Collecting data using Logstash and Beat
- Implementing high availability for Elasticsearch and Kibana
Who Should Attend
- Developers
- IT Administators
- Web Developers
- Anyone who wants to learn Elasticsearch and Kibana
Target Audiences
- Developers
- IT Administators
- Web Developers
- Anyone who wants to learn Elasticsearch and Kibana
Welcome to Full ELK Stack Bootcamp!
This bootcamp is designed for any developer and IT admin who want to deploy Elasticsearch, Kibana and Logstash, and develop application based Elasticsearch.
This bootcamp focuses deploying and developing for ELK stack. The bootcamp consists of the following topics:
-
Installing Elasticsearch and Kibana on Windows, Linux and macOS
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Accessing Elasticsearch REST API
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Elasticsearch Document REST API Development
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Collecting Data with Logstash
-
Data Visualization with Kibana
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Collecting Data with Beats
-
High Availability (HA) for Elasticsearch and Kibana
Firstly, we learn how to install Elasticsearch and Kibana on Windows, Linux and macOS so you will have experiences on various platform for installation process.
Next, we learn a basic Elasticsearch REST API. This is an important thing to understand how to access Elasticsearch server from REST API requests.
We also learn how to collect data from file and database using Logstash. Another method to collect data is using Beats. We use Beat services such as Filebeat, Winlogbeat, Metricbeat, Packetbeat, Heartbeat and Auditbeat on Windows Server and Ubuntu Server.
Elasticsearch provides API SDK in order to build applications with Elasticsearch as database. Elasticsearch could be NoSQL database. In this bootcamp, we build application using PHP, ASP.NET Core, Node.js and Python.
After collected data, we can visualize the data using Kibana. We explore some charts and create dashboard on Kibana.
Last, we deploy Elasticsearch and Kibana for high availability scenario. For demo, we use three Elasticsearch servers and two Kibana servers. We also implement a load balancer using Nginx.
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Lecture 2: Preparation
Chapter 2: Up and Running
Lecture 1: Introduction
Lecture 2: Installing Elasticsearch on Windows
Lecture 3: Installing Kibana on Windows
Lecture 4: Installing Logstash on Windows
Lecture 5: Installing Elasticsearch on Ubuntu Server
Lecture 6: Installing Kibana on Ubuntu Server
Lecture 7: Installing Logstash on Ubuntu Server
Lecture 8: Installing Elasticsearch on macOS
Lecture 9: Installing Kibana on macOS
Lecture 10: Installing Elasticsearch on Docker Environment
Lecture 11: Installing Kibana on Docker Environment
Lecture 12: Enabling Elasticsearch and Kibana Access from Remote Machines
Chapter 3: Elasticsearch Document REST API
Lecture 1: Introduction
Lecture 2: Hello REST API
Lecture 3: CRUD (Create, Read, Update, Delete) on Elasticsearch Index
Lecture 4: CRUD (Create, Read, Update, Delete) on Elasticsearch Document
Lecture 5: Mapping
Lecture 6: Bulk Indexes and Documents
Lecture 7: Upload Dataset to Elasticsearch via Kibana
Lecture 8: Searching (Queries by Examples)
Lecture 9: Aggregations
Lecture 10: Using SQL Query Statements on Elasticsearch API
Lecture 11: Working with Geopoint Field Type
Chapter 4: Elasticsearch Document REST API Development
Lecture 1: Introduction
Lecture 2: Set up for REST API Users for Elasticsearch Development
Lecture 3: PHP
Lecture 4: Case Study 1: Building Todo Application with PHP and Elasticsearch
Lecture 5: ASP.NET Core
Lecture 6: Node.js
Lecture 7: Python
Chapter 5: Collecting Data with Logstash
Lecture 1: Introduction
Lecture 2: Set up for Logstash Users on Elasticsearch
Lecture 3: Hello Logstash Ingest
Lecture 4: Ingest Data from Files
Lecture 5: Ingest Data from Folder (CSV Files)
Lecture 6: Ingest Data from RDBMS Database (MySQL)
Chapter 6: Data Visualization with Kibana
Lecture 1: Introduction
Lecture 2: Preparing Data
Lecture 3: Build Your First Visual Chart
Lecture 4: Creating Data View from Data Index
Lecture 5: [Visual Library] Lens – Bar Chart
Lecture 6: [Visual Library] Lens – Bar Percentage Chart
Lecture 7: [Visual Library] Lens – Bar Stacked Chart
Lecture 8: [Visual Library] Lens – Line Chart
Lecture 9: [Visual Library] Lens – Area Chart
Lecture 10: [Visual Library] Lens – Pie and Donut Charts
Lecture 11: [Visual Library] Lens – Table
Lecture 12: [Visual Library] Lens – Heat map
Lecture 13: Preparing Data for Map Charts
Lecture 14: [Visual Library] – Lens – Region Map
Lecture 15: [Visual Library] – Maps
Lecture 16: [Visual Library] – Aggregation – Metric
Lecture 17: [Visual Library] – Aggregation – Cloud
Lecture 18: Canvas
Lecture 19: Dashboard
Lecture 20: Sharing Canvas and Dashboard
Chapter 7: Collecting Data with Beats – Practical Projects
Lecture 1: Introduction
Lecture 2: Filebeat Overview
Lecture 3: Setting up Role and User for Filebeat on Elasticsearch
Lecture 4: Installing and Configuring Filebeat on Windows (Windows Server)
Lecture 5: Filebeat on Windows with Web Server IIS Module
Lecture 6: Filebeat on Windows with SQL Server Module
Lecture 7: Filebeat on Windows with MySQL Module
Lecture 8: Installing and Configuring Filebeat on Ubuntu Server
Lecture 9: Filebeat on Ubuntu Server with Nginx Module
Lecture 10: Winlogbeat Overview
Lecture 11: Winlogbeat: Setting up Role and User
Lecture 12: Winlogbeat: Installing and Configuring
Lecture 13: Metricbeat Overview
Lecture 14: Metricbeat: Setting up Role and User
Lecture 15: Metricbeat: Installing and Configuring on Windows Server
Lecture 16: Metricbeat: Installing and Configuring on Ubuntu Server
Lecture 17: Packetbeat: Deploying and Implementing on Ubuntu Server
Lecture 18: Heartbeat: Deploying and Implementing on Ubuntu Server
Lecture 19: Auditbeat: Deploying and Implementing on Ubuntu Server
Chapter 8: High Availability (HA) for Elasticsearch and Kibana
Lecture 1: HA Study Case: 3 Servers for Elasticsearch and 2 Servers for Kibana
Lecture 2: Configuring A Network
Lecture 3: Setting Up Elasticsearch Server – Server 1
Lecture 4: Setting Up Elasticsearch Server – Server 2 and Join An Elasticsearch Cluster
Lecture 5: Setting Up Elasticsearch Server – Server 3 and Join An Elasticsearch Cluster
Lecture 6: Setting Up Nginx Load Balancer for Elasticsearch Server Cluster
Lecture 7: Setting Up Kibana Server – Server 1
Lecture 8: Setting Up Kibana Server – Server 2
Lecture 9: Setting Up Nginx Load Balancer for Kibana Server Cluster
Instructors
-
Agus Kurniawan
Researcher, Trainer, Consultant and Author
Rating Distribution
- 1 stars: 1 votes
- 2 stars: 3 votes
- 3 stars: 3 votes
- 4 stars: 7 votes
- 5 stars: 4 votes
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