- Legacy APM Server Reference:
- Overview
- Get started
- Set up
- How-to guides
- Configure
- Secure
- Monitor
- API
- Explore data in Elasticsearch
- Exported fields
- APM Application Metrics fields
- APM Error fields
- APM Profile fields
- APM Sourcemap fields
- APM Span fields
- APM Span Metrics fields
- APM Transaction fields
- APM Transaction Metrics fields
- APM Transaction Metrics fields
- Beat fields
- Cloud provider metadata fields
- Docker fields
- ECS fields
- Host fields
- Kubernetes fields
- Process fields
- System Metrics fields
- Troubleshoot
- Upgrade
- Release notes
- APM Server version 7.15
- APM Server version 7.14
- APM Server version 7.13
- APM Server version 7.12
- APM Server version 7.11
- APM Server version 7.10
- APM Server version 7.9
- APM Server version 7.8
- APM Server version 7.7
- APM Server version 7.6
- APM Server version 7.5
- APM Server version 7.4
- APM Server version 7.3
- APM Server version 7.2
- APM Server version 7.1
- APM Server version 7.0
- APM Server version 6.8
- APM Server version 6.7
- APM Server version 6.6
- APM Server version 6.5
- APM Server version 6.4
- APM Server version 6.3
- APM Server version 6.2
- APM Server version 6.1
- APM integration (Elastic Agent)
Manage storage
editManage storage
editElastic Agent uses data streams to store time series data across multiple indices. Index templates are used to configure the backing indices of data streams as they are created. Each data stream ships with a customizable index lifecycle policy that automates data retention as your indices grow and age. Use ingest pipelines to process and enrich APM documents before indexing them.
The storage and sizing guide attempts to define a "typical" storage reference for Elastic APM, and there are additional settings you can tweak to reduce storage, or to tune data ingestion in Elasticsearch.
In addition, the Applications UI makes it easy to visualize your APM data usage with storage explorer. Storage explorer allows you to analyze the storage footprint of each of your services to see which are producing large amounts of data—so you can better reduce the data you’re collecting or forecast and prepare for future storage needs.