Introducing comparisons—a new feature in continuous profiling that helps you gain deeper insights into application performance by effortlessly contrasting performance metrics over time or between code versions. Quickly identify regressions, optimize application performance, and accelerate development cycles. Empower your team to make data-driven decisions. And with unparalleled visibility, deliver faster, more efficient software.
We’ve also added support for Rust and Ruby applications to our continuous profiling toolkit.
🤔 Here’s how the new comparisons feature works
The comparisons feature enhances our continuous profiling capabilities by adding a Compare toggle to the dashboard. When activated, the dashboard switches to a comparison view mode that displays two time-frame windows (A and B) side by side. This dual view enables you to compare performance metrics between two different periods on the line graph directly.
Continuous profiling comparisons. Assume that, at some point (near 2:33 AM, for example), an event we’re interested in tracking the impact of occurs (e.g., a deployment, surge in traffic). Above, two windows of continuous profiling measurements on the CPU time metrics dimension for the 24 hours before (A) and after (B) that event are compared side by side.
✅ Comparisons key benefits
- Easily contrast performance across time periods. Quickly identify performance changes by viewing two time frames simultaneously.
- Gain enhanced insights through comparative analysis. Dive deeper into your data to uncover trends, anomalies, or regressions.
- Enable data-driven optimization. Use comparative insights to make informed decisions to optimize your applications.
The comparisons feature enriches continuous profiling by providing tools that help you troubleshoot more effectively.
🤯 Here are some possible use cases:
- Version comparisons or feature-impact analysis. With the Deployment toggle, overlay deployment activities on the line graph to contrast the before-and-after effects of code changes or new app versions. This enables you to easily identify performance improvements or regressions.
- Time-based analysis. Compare profiles from different periods to investigate performance fluctuations over time. For example, peak traffic periods versus lulls can be analyzed to optimize resource allocation.
💚 Support for Rust and Ruby applications
We’ve expanded language support by adding continuous profiling for Rust and Ruby applications to current support for Go, Node.js, PHP, and Python. This enables developers working in Rust and Ruby to leverage our profiling tools for enhanced performance monitoring.
💪 Great new capabilities, no additional costs
The new comparisons feature and language support for Ruby and Rust are free of additional costs. These enhancements continue our commitment to providing valuable tools that improve your experience and make your life easier.
🚀 Get started
Our team is excited for you to explore these new features to see how they can benefit your development and optimization processes. For more information, dive into these support resources:
- Comparisons feature documentation
- Continuous profiling for Rust and Ruby
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