Filebeat modules, access logs and Elasticsearch storage requirements
Blog post from Elastic
Filebeat modules, introduced by Elastic, simplify the ingestion and analysis of common log formats by providing preconfigured ingest pipelines and Kibana dashboards, which can be customized. This blog post delves into the on-disk storage requirements when indexing data using Filebeat modules, particularly focusing on the Apache2 module. By default, Filebeat modules offer efficient storage, saving around 20% disk space over standard Elasticsearch settings, with potential savings up to 50% through more aggressive tuning. The modules streamline the collection, parsing, and visualization of logs, and come with optimized mappings that minimize space usage without losing functionality. Various techniques to optimize storage include reducing unnecessary fields, enabling more aggressive data compression, and disabling certain flexible search features, each with its own trade-offs. The post highlights that while default settings already improve storage efficiency, further optimizations can be tailored to specific use cases for even greater space savings.
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