An overview of Trace (your SDLC data assistant)

Cubyts is your AI Assistant for Proactive SDLC Governance, Cubyts integrates seamlessly with tools teams use (e.g. Jira, GitHub, Figma, Jenkins, etc.) to build their products; the platform enhances the development process with real-time insights, proactive flagging of potential issues, and data-driven decision-making, that ensures superlative Developer, Engineering and Execution excellence.

Trace is the data assistant for Scrum teams, the trace functionality offers the following assistance to the scrum team (primarily: Engineering leaders, Engineering managers and Scrum masters/Project or Program managers):

1. Automatic trace of the journey of code from inception to adoption with several augmented data points for analyzing the impediments in the journey.

2. Automatic mashup of critical data points (and it's relationship with flags) from an artifact or team member standpoint; useful for analyzing contributions, risks, workload, productivity, efficiency of execution and members (who are executing the outcomes).

3. Automatic visibility into the artifacts that deviations from the established compliance standards (configured in flags).

Trace offers the data points in the following categories:

1. Flags: This is an administrative report that enables the users to get a comprehensive view of the discovered drifts (in various sync. cycles) with the resolutions triggered by the user or the platform. 

2. Delivery: This category offers a wide spectrum of trace reports that focuses on the upstream part (planning and definition) of the delivery workflow (e.g. feature progress, issue status and sprint progress).

3. Code: This category offers a wide spectrum of trace reports that focusses on the code workflow (which is triggered after the engineer is handed off specification or user stories), the code workflow offers deep dives on Feature branches, Pull requests, code reviews and an array of aggregates for analysis.

4. Deployment: This category focuses on the behavior of the system after the code is deployed in various environments in an internal/customer landscape.

5. Compliance: This category focusses on exposing SDLC artifacts that deviates from the established compliance regulations (configured in flags).

6. Team: This is an important category, offering a wide spectrum of trace reports with a very deep view of contributions from an individual or the entire team (as a collective).

Conclusion

The data points and insights provided by Trace serve as a valuable data assistant for Scrum teams, enabling them to seamlessly integrate data from multiple tools and gain a comprehensive understanding of the code’s journey from inception to adoption.