Elastic Observability Engineer (Pt 1) - Virtual
Instructor-led Virtual Training
|Location||Apr 2020||May 2020||Jun 2020||Jul 2020||Aug 2020|
|US Central Time||
May 18 – May 21||
Jun 15 – Jun 18|
|US Pacific Time||
Jun 1 – Jun 4|
|Central European Summer Time - English||
May 25 – May 28|
|Singapore (SGT) Time - English||
Jun 9 – Jun 12|
|Australian Eastern Standard Time - English||
Jun 9 – Jun 12|
Classes in bold are guaranteed to run!
This is Part 1 of a two-part, instructor-led course series that provides a strong foundation on using the Elastic Stack to implement system observability.
In the two parts of this course, you will learn how to collect logs, metrics, and APM data, and then ship them to a single datastore — Elasticsearch. You will also learn how unified observability data can be made even more actionable through machine learning and alerting, as well as easier to correlate data across different sources. Using Kibana, you will also explore how to visualize your observability data through an intuitive user interface. After completing this course, you will be ready to take Elastic Observability Engineer - Part 2.Topics Covered in Part 1
- Observability fundamentals
- Elasticsearch for time-series data
- Shipping metric data
- Shipping log data
- Application performance monitoring (APM)
- Observability apps
- Structuring data
- Processing data
- Kibana for time series
- Data ingestion architectures
- Monitoring the Elastic Stack
- Machine learning and alerting on observability data
- Stable internet connection
- Mac, Linux, or Windows
- Latest version of Chrome or Firefox (other browsers not supported)
- Disable any ad blockers and restart your browser before class
- Ensure that any VPNs on your laptop are disabled before class
Virtual Classroom Information
Virtual classroom trainings are delivered in four, six or eight-hour sessions of live lectures and lab time, with scheduled breaks throughout the session.
Open a specific offering (listed at the top of the page) to see the hours in which it will be held.
We encourage participants to set up their systems prior to logging into the training environment the first day of the class and logged in 15 minutes prior to the start of class each day.