Logstash
| Typically Used By | Organizations with existing ELK stack; Complex processing needs |
| Description | A server-side data processing pipeline that ingests, transforms, and enriches data from multiple sources before forwarding to LogScale. |
| Official Vendor Documentation | https://www.elastic.co/docs/reference/logstash/ |
| Setup Difficulty | 5 (Advanced) |
| Useful for | DevOps , DevOps |
| Primary Use Case | Log transform & enrich |
| Scenarios not Recommended | Resource-constrained environments; Simple logging needs |
| Data Volume Handling | High |
| Authentication Method | Token-based |
| Fault Tolerance | Medium |
| Additional Tools Required | None |
Logstash is a free and open-source data processing pipeline from Elastic that ingests data from multiple sources simultaneously, transforms it, and sends it to various destinations. As part of the Elastic Stack (ELK), Logstash provides a powerful plugin architecture with over 200 plugins for inputs, filters, and outputs, enabling sophisticated data collection, parsing, enrichment, and routing. Organizations already using Logstash in their infrastructure can easily add Falcon LogScale Collector as an output destination without replacing existing pipelines, enabling gradual migration, hybrid architectures, or multi-destination log routing. Logstash's rich filtering capabilities, including grok parsing, field manipulation, and data enrichment, make it ideal for complex log processing requirements before forwarding to LogScale.
Logstash ingest flowThe following diagram shows how Logstash log data flows through Log Collector's ingestion pipeline, highlighting specific parser types applied to the log data before data is compressed, stored in the repository, and indexed for searching: