Once loved now (arguably) oft-maligned former darling of search Yahoo! (yes, we even left the exclamation point in to be nice) has open sourced its Daytona an application-agnostic framework for automated performance testing and analysis.
Yahoo! software engineers Sapan Panigrahi and Deepesh Mittal explain that the automation, intelligence and control aspects of Daytona that give it clout include:
- Repeatable test execution,
- Standardized reporting
- Built-in profiling support for integrated app performance testing on applications
Performance metrics are aggregated and then presented in a unified user interface.
What differentiates this product?
Its differentiation lies in its ability to aggregate and present aspects of application, system and hardware performance metrics in a comprehensive interface.
Developers, architects and systems engineers can use the framework in an on-premises environment or any public cloud to test:
- Defined services
- Whole applications
- Application components
The firm insists that Yahoo! is committed to being “a good open source citizen” — so Daytona comes on the heels of recent contributions of Screwdriver, Athenz, and TensorFlowOnSpark.
“At Yahoo, Daytona has helped us make applications more robust under load, reduce the latency to serve end-user requests, and reduce capital expenditure on large-scale infrastructure,” detail Panigrahi & Mittal.
Prior to Daytona, Panigrahi & Mittal explain that the teams created multiple, heterogenous performance tools to meet the specific needs of various applications.
“This meant that we often stored test results inconsistently, making it harder to analyse performance in a comprehensive manner. We had a difficult time sharing results and analysing differences in test runs in a standard manner, which could lead to confusion,” note the pair.
With Daytona, Yahoo! is now able to integrate all its load testing tools under a single framework and aggregate test results in one common central repository.
“We are gaining insight into the performance characteristics of many of our applications on a continuous basis. These insights help us optimise our applications which results in better utilisation of our hardware resources and helps improve user experience by reducing the latency to serve end-user requests,” write Panigrahi & Mittal.
Ultimately, Daytona helps us reduce capital expenditure on our large-scale infrastructure and makes our applications more robust under load. Sharing performance results in a common format encourages the use of common optimisation techniques that can be used across many different applications.