Elastic Stack Logging
The Elastic Stack can be used to tackle almost any use case, but one of the most popular is log analytics. This instructor-led course provides a strong foundation for getting started with the Elastic Stack — specifically Elasticsearch, Kibana, Logstash, and Filebeat — for the purpose of collecting and analyzing log data. It covers how to deploy and manage the Elastic Stack, as well as how to use your deployment to develop powerful search and analytics solutions. You will learn to use Filebeat to ship log data to an ingest pipeline or Logstash, so it can be processed and structured before being indexed. You will then explore the analytical power of Elasticsearch before visualizing your log data, and the insights they hold, within Kibana. After completing this course, you will be able to make sense of your log data via exploration and analysis within the Elastic Stack.
Duration: 48 hours
- Classroom - 3 Days | 8 hours per day
- Virtual - 4 Days | 6 hours per day
Software Developers, Software Engineers, Data Architects, System Administrators, DevOps
No prior knowledge of the Elastic Stack required
Course outlines: All lessons include a hands-on lab.
1. Logging fundamentals
2. Elasticsearch for time series data
Learn how the diﬀerent components of the Elastic Stack (Elasticsearch, Kibana, Beats, and Logstash) can work together to allow you to make sense of log data.
Learn the basics of Elasticsearch and how it can be optimized for time series data, such as log data
3. Shipping log data
Understand how to use Filebeat to ship data to Elasticsearch, how to use Filebeat modules to automatically process the data, and how to create relevant dashboards for your diﬀerent logs.
4. Structuring data
Understand how to use ingest pipelines and/or Logstash to take unstructured logs and turn them into structured data.
5. Processing data
Understand how to use ingest pipelines and/or Logstash to process log data for optimal storage.
6. Monitoring the Elastic Stack
Learn how you can make sure that Filebeat, Logstash, and Elasticsearch are up and running so you do not experience any down time while analyzing your logs.
7. Kibana for time series data
Learn how to use Kibana to build your own visualizations and dashboards on your log data.
8. Observability apps
Learn how to use the built-in Kibana apps to analyze logging, infrastructure, and uptime data.
9. Machine learning and alerting on observability data
Learn how to detect anomalies in your data and also how to configure alerts using Elastic Stack machine learning and alerting.
Học trực tuyến
Học tại Hồ Chí Minh
Học tại Hà Nội