Elasticsearch works well when paired with Logstash and Kibana. This trio is known as the ELK Stack. Learn about all of the components and functions.
- [Instructor] Let's take a look now…at how this platform comes together.…First, let's break down the open-source part…known as the elastic stack.…At the bottom of the stack, you have two components…which are focused on getting data into your cluster.…You have Logstash, which has been around for a while,…and is great at ingesting log data…but also has evolved to become a full-fledged ETL platform.…Logstash offers common connectors, transformations,…and outputs, as well as there is an open-source community…building additional connectors and addition transformations…for almost any scenario you may encounter.…
I won't be diving too deep in Logstash in this course,…as the main focus is on Elasticsearch.…However know that if you're running Elasticsearch,…you're most likely going to want Logstash…as a good way to ingest data.…Another platform for getting data into your cluster…is Beats.…This component will help you ingest data in real-time…by looking at transactions occurring in the database…or potentially new data being written to a file…
In this course, join Ben Sullins as he dives into the inner workings of Elasticsearch combined with Kibana. Ben provides an overview of the architecture, and then goes over the different deployment methods, and how to best structure your data. From there, he demonstrates how to query data, and how to work with Kibana to present your insights.
- Reviewing key Elasticsearch concepts
- Running Elasticsearch in the cloud and locally
- Bulk loading data
- Setting up mappings of data types
- Querying data
- Running basic aggregations
- Creating visualizations and dashboards in Kibana