Logstash Training Online

17 Lesson

30 Hours

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Logstash Training helps learners master log data processing using the Logstash platform. Understand real-time data ingestion, log parsing, pipeline configuration, and seamless integration with Elasticsearch and Kibana. Gain hands-on skills to optimize data workflows, improve operational visibility, and streamline log management processes. Prepare to advance your career in data engineering, observability, and system monitoring with practical Logstash expertise.

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Overview

Prerequisites

Basic Linux command line knowledge
Understanding of log types and formats (JSON, syslog, plain text)
Familiarity with the ELK Stack (Elasticsearch, Logstash, Kibana)
Basic scripting skills (especially JSON and regular expressions)
Networking basics (TCP/UDP, ports, protocols)

Optional but helpful

Experience with Elasticsearch and Kibana
Familiarity with YAML and config files
Knowledge of Beats (e.g., Filebeat) for log shipping

What You Will Learn

1. Introduction to Logstash and ELK Stack

2. Installing and setting up Logstash

3. Understanding Logstash architecture (Input → Filter → Output)

4. Creating and configuring pipelines

5. Using input plugins (File, Beats, Syslog, Kafka, etc.)

6. Applying filter plugins (grok, mutate, json, date, etc.)

7. Using output plugins (Elasticsearch, stdout, file, etc.)

8. Parsing structured and unstructured logs

9. Testing and debugging pipelines

10. Performance tuning and best practices

11. Integrating with Beats and Elasticsearch

12. Real-world use cases and hands-on examples

Key Features

24 X 7 Lifetime Support & Access
Small Batches Upto 10 Participants
Experienced & Professional Trainers
1 On 1 Training Option Available
Instructor Led Training : 30 Hrs
Flexible Schedule

Course Curriculum

Lesson 1 - Introduction to Elastic Stack & Use Cases

1. What is the Elastic Stack (ELK / Elastic Stack)

2. Components: Elasticsearch, Logstash, Kibana, Beats

3. Architecture and data flow

4. Common use cases: centralized logging, security monitoring, observability

Lesson 2 - Installation & Setup

1. System requirements (Java, memory, OS prerequisites)

2. Installing Elasticsearch, Logstash, Kibana

3. Basic configuration / starting services

4. Verifying installation and connectivity

Lesson 3 - Elasticsearch Fundamentals (Context)

1. Cluster, node, shard, replica concepts

2. Index management: creating, deleting, mapping

3. JSON document structure, indexing, retrieving

4. Query DSL: search, filters, aggregations

5. Monitoring cluster health and APIs

Lesson 4 - Core Logstash Concepts

1. Logstash’s role and internal architecture

2. Event data model (fields, metadata)

3. Pipeline flow: Input → Filter → Output

4. Plugin categories overview (input, filter, output)

Lesson 5 - Input Plugins & Data Ingestion

1. File input, Beats input, syslog, TCP / UDP, HTTP, Kafka, etc.

2. Configuration options (paths, ports, codecs)

3. Handling multiple input sources

Lesson 6 - Filter Plugins & Transformations

1. Parsing unstructured logs: grok, dissect

2. Data transformation: mutate, rename, remove, split

3. Working with JSON: json filter

4. Date handling: date filter

5. Key-value parsing: kv, csv

6. Enrichment filters: geoip, translate

7. Conditionals & control flow

Lesson 7 - Output Plugins

1. Sending to Elasticsearch

2. Writing to files or stdout

3. Other outputs (e.g. Kafka, database sinks)

4. Template management and index naming strategies

Lesson 8 - Pipeline Management & Advanced Features

1. Multiple pipelines (pipeline configs)

2. Queueing (in‑memory vs persistent queues)

3. Dead letter queues and error handling

4. Pipeline to pipeline communication

5. Conditional routing of events

Lesson 9 - Performance, Scaling & Tuning

1. JVM tuning, heap settings

2. Batch size, worker threads, pipeline throughput

3. Resource considerations (CPU, memory, I/O)

4. Monitoring metrics and bottleneck identification

Lesson 10 - Monitoring & Troubleshooting

1. Logstash monitoring APIs and metrics

2. Debugging logstash configs (e.g. using –config.test_and_exit)

3. Logging and error logs

4. Common failures and how to fix them

Lesson 11 - Integrations with Beats & Agents

1. Filebeat, Metricbeat, Auditbeat, etc.

2. Modules in Beats

3. Using Beats to ship logs to Logstash

4. When to use Beats vs Logstash directly

Lesson 12 - Security, Authentication & TLS

1. TLS/SSL setup for secure communication

2. User authentication and authorization

3. Role-based access control

4. Secure pipeline configurations

Lesson 13 - Working with Logstash Modules

1. What Logstash modules are and when to use them

2. Prepackaged configurations and dashboards

3. Enabling, configuring, overriding module settings

4. Elasticsearch & Kibana setup when using modules

Lesson 14 - Use Cases & Hands-on Projects

1. Real-world log ingestion pipelines (e.g., web logs, application logs)

2. End-to-end project: log → parse → index → visualize

3. Case studies of centralized logging, security logging

Lesson 15 - Production Best Practices & Maintenance

1. Rolling upgrades and version compatibility

2. Backup / restore strategies

3. Log retention, index lifecycle management

4. High availability, redundancy, failover

Lesson 16 - Visualization & Analytics (Kibana)

1. Using Kibana to search, filter, and explore data

2. Creating visualizations (histograms, maps, charts)

3. Building dashboards

4. Alerts and reporting

Lesson 17 - Capstone Project / Final Assignment

1. Designing a full logging pipeline for a sample environment

2. Load simulation, parsing, indexing, dashboarding

3. Performance testing and troubleshooting

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Course Fees

Online Class Room Program

US $ 799.00

100% Money Back Guarantee

Duration : 30 Hrs
Plus Self Paced

Classes Starting From

Fast Track Batch 07 Jul 2026
Weekday Batch 13 Jul 2026
Weekend Batch 11 Jul 2026

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Flexible Training Schedule Options
Industry Experienced Trainers
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Logstash Certification

After completing the Logstash Training and hands-on practical exercises, learners will receive a Course Completion Certificate from igmGuru. This certification validates your expertise in building and managing data pipelines, parsing and transforming log data, integrating with Elasticsearch and Kibana, and automating log ingestion workflows using Logstash.

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Logstash Training Online