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Optimize long-running queries, eliminate bottlenecks, and keep compute costs under control without digging through logs or rewriting SQL by hand. The Performance and Cost Agent helps you identify inefficiencies in your pipelines and resolve them quickly, so your data stays fresh, fast, and within budget.

It improves performance by analyzing query logic, historical execution patterns, and resource usage. This makes it easier to meet data SLAs and ensure products, dashboards, and AI models get the data they need, when they need it.

Using the Performance and Cost Agent

Trigger the agent from any asset flagged as underperforming or from a query known to be slow or expensive. It reviews the SQL, surrounding metadata, and historical performance, then recommends code changes and resource configuration tweaks to improve efficiency.

You’ll see an estimate of time and cost savings before applying changes. Once approved, the agent opens a pull request with its suggested improvements and can continue iterating until performance targets are met.

Key Capabilities

Performance Diagnostics and Optimization

The agent evaluates:

  • Query logic and structure
  • Historical execution time and resource usage
  • Metadata context and lineage

It uses that analysis to identify performance bottlenecks and propose:

  • Code-level SQL optimizations
  • Resource allocation and configuration changes
  • Structural improvements that reduce load or complexity

Cost and SLA Awareness

Each recommendation includes an estimate of:

  • Time saved per run
  • Cost reduction per run or per day
  • Impact on data freshness and downstream data availability

This makes it easier to prioritize which performance issues are worth fixing and why.

Automated Implementation and Iteration

Once recommendations are approved, the agent opens a pull request with the proposed changes. It can continue to iterate based on updated performance feedback until the asset meets defined SLAs or cost targets.

Who It’s For

Built for analytics engineers and data engineers who need to improve pipeline speed, reduce costs, and ensure data products stay fresh and reliable without getting buried in manual query tuning.

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