Properly parsing and structuring your data is an important first step in building an efficient and effective observability solution using the Elastic Stack. Effectively indexing and structuring data into Elasticsearch is critical for establishing efficient search criteria and effective results. Logstash filters and ingest pipelines make processing unstructured data easier by providing a set of common processors to efficiently parse, transform, and index that data into the desired structure.

In this webinar, we will explore concepts from the all-new Elastic Observability Engineer course, including how to process and structure data using a variety of common processors. Our expert instructors will demonstrate various solutions and built-in features that convert, enrich, process, and structure different types of fields from unstructured data. In addition, we will show how to create your own pipeline of processors for transformations that are not possible using the prebuilt processors.

Attend the live webinar to receive access to the Observability Fundamentals course - free of charge. Your course will be sent after the webinar.

Highlights:

Introduce common ingest processors to parse unstructured data into structured data
Discuss best practices for dissecting, converting, and enriching your fields
Explore different scenarios that require either a built-in processor or a pipeline of processors for certain types of unstructured data

Additional Resources:

Training: Elastic Observability Engineer
Blogs:
- Should I use Logstash or Elasticsearch ingest nodes?
- How to ingest data into Elasticsearch Service
- Using Logstash to split data and send it to multiple outputs
Want to try it for yourself? Take some of these features for a spin with a free trial of our Elasticsearch Service

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ORCHESTRATION

Building a Firm Wide Single Task List

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