Data Processing

We can store and process large volumes of information and perform automated and intelligent analysis of metrics that provide a better view of the efficiency of a project and its development team.

All data processed by Pulzen is fully secured and encrypted at every stage. Data at rest is protected using AES-256 encryption, ensuring the highest level of security for your stored information. We do not store or analyze sensitive business logic or code details—instead, we focus exclusively on extracting and aggregating quantitative metrics. This means your information is used only to provide high-level insights and trends, never exposing confidential or granular details.

Pulzen organizes processed data into three main categories, each focused on a different aspect of the software development lifecycle. All metrics are strictly quantitative—no sensitive content, code, or detailed user actions are ever processed or stored.

VCS (Version Control Systems)

  • Repositories: Aggregate counts of code repositories and their activity. This helps track the growth and usage of your codebase over time, supporting project health and scalability analysis.
  • Teams: Number of teams collaborating on repositories. Understanding the number of active teams provides insight into collaboration and organizational structure.
  • Users: Count of individual contributors. Monitoring the number of users involved helps assess engagement and team size.
  • Commits: Total number of commits, as well as aggregate additions and deletions of code. This metric helps measure development activity and codebase evolution.
  • Pull Requests: Number of pull requests created and processed, including their different statuses and key dates. This provides visibility into code review cycles and team collaboration.
  • Reviews: Count of code reviews performed, measuring both coder and reviewer activity. This helps evaluate code quality processes and team participation in reviews.
  • Workflows / Pipelines: Number of automated workflow or pipeline executions, along with their aggregate statistics. This metric helps assess automation adoption and CI/CD efficiency.
  • Deploys: Count of deployment events. Tracking deployments helps monitor release frequency and delivery practices.
  • Releases: Number of releases or milestones. This metric provides an overview of major delivery points and project progress.

Issue Tracker (Project Management Tools)

  • Issues / Tasks: Total number of issues or tasks tracked in the system. This helps teams understand workload, backlog, and progress.
  • Sprints: Number of sprints or time-boxed periods. Sprint metrics support agile planning and delivery cadence analysis.
  • Users: Number of users involved in the tracker. This shows the level of participation and distribution of work among contributors.
  • Projects: Number of projects tracked. Project counts help organizations monitor portfolio size and resource allocation.
  • Teams: Number of teams managing or working on issues. This metric provides insight into team-based project management and collaboration.

Collaboration & Communication

This section tracks only the volume of user activity and engagement in collaboration platforms. The following metrics are collected per user and date, helping organizations understand communication patterns and team engagement:

  • Team Chat Message Count: Number of messages sent in team channels. Indicates the level of group communication and collaboration.
  • Private Chat Message Count: Number of messages sent in private chats. Reflects direct, one-on-one, or small group interactions.
  • Post Messages: Number of posts made in channels. Shows how often users initiate discussions or share information with the team.
  • Reply Messages: Number of replies to messages. Measures responsiveness and participation in ongoing conversations.
  • Urgent Messages: Number of messages marked as urgent. Highlights the frequency of critical communications that may require immediate attention.
  • Call Count: Number of calls made. Tracks the frequency of voice or video calls for collaboration and quick discussions.
  • Meeting Count: Number of meetings attended or created. Indicates involvement in scheduled team activities, planning, and coordination.
  • Audio Duration In Seconds: Total duration of audio calls (in seconds). Provides insight into the amount of time spent in voice communication.
  • Video Duration In Seconds: Total duration of video calls (in seconds). Measures engagement in video-based collaboration and remote meetings.
  • Screen Share Duration In Seconds: Total duration of screen sharing (in seconds). Reflects collaborative work, presentations, and knowledge sharing during meetings.

GitHub Copilot

  • Seat usage: Measures the number of seats or licenses being used compared to the total available. Useful for evaluating resource utilization efficiency.
  • IDE per user/team: Measures the use of Integrated Development Environments (IDEs) by user or team. Useful for understanding preferences and usage patterns of development tools.
  • Language per user/team: Tracks the programming languages used by each user or team. Useful for identifying which programming languages are being used the most.
  • % Suggestion accepted: Measures the percentage of suggestions accepted by users compared to the total number of suggestions made by Copilot. Indicates the receptivity and efficiency of each suggestion delivered.
  • % Lines accepted: Measures the percentage of lines of code that are accepted or integrated into the developer's code. Helps evaluate the quality and acceptance of the suggestions.
  • % Suggestion by chat: Measures the percentage of suggestions made through GitHub Copilot Chat. Useful for understanding the dynamics of Chat usage.
  • Daily usage of GitHub Copilot: Provides a visual representation of the daily usage of GitHub Copilot. Helps identify peak usage times and patterns over a period of time.