Optimize
- Latest Dynatrace
- Explanation
- 3-min read
- Published May 26, 2026
Once you know where your consumption is going, optimization is about two questions: how much data do you really need to send and keep, and how efficiently are you querying it?
Optimization is the closing loop of cost management: once you can see and attribute spend, you can reduce it. Two levers drive DPS cost down:
- Send and keep less data.
- Query your data more efficiently with DQL, dashboards, workflows.
This page points to the best-practice guides that answer those questions for each Dynatrace capability.
If you don't know yet which telemetry signals or queries are driving your cost, start with the usage dashboards: An overview dashboard shows your consumption of all capabilities, and drill-down dashboards for traces, logs, and Full-Stack consumption give specific optimization suggestions: queries missing a scan limit, hosts that could downgrade their monitoring mode, and more.
For the full set of viewing surfaces, see View. Then come back here for the best-practice fixes.
Overview
The cards below link to capability-specific best-practice guides to help you achieve the following use cases:
- Cut log volume by tuning ingest pipelines, sampling, and retention.
- Reduce metric cardinality and trim span metrics.
- Right-size retention per data type to match compliance and operational needs.
- Detect and tune expensive DQL queries before they accumulate cost.
- Optimize dashboards and notebooks to reduce repeat query volume.
Looking for real-world examples? The Dynatrace community examples repository is an open space where practitioners share configurations across Dynatrace apps and capabilities.
Optimize host monitoring costs
Optimize telemetry costs
Logs
Metrics
Traces
Retention
How long you keep data is part of what you pay for. Use this reference to understand defaults and the configurable ranges per data type.
