eng-ops

We have API access to both ZenHub and GitHub:
https://github.com/ZenHubIO/API
https://developer.github.com/v3/issues/

If we start storing and modeling Issues and their lifecycles, can we start answering nuanced questions about our workflows and productivity?

Issue-specific questions:

• How long did it take to close this issue?
• What type of issue was it? e.g. Eng Sanity, Feature, Support, etc (based on label)
• What Milestones was it a part of?
• How long did it take to go from "New Issue" to "In Progress"? From "Ready to do" to "Closed"? (or any other two pipelines)

Aggregate questions:

• On average, how long does a "1", or "2", or "5" take?
• How long do issues stay as "Ready to do", on average?
• Where do we spend the most eng time? e.g. Support, Feature, Bug, etc
• Which areas (e.g. Bug, etc) have the most issues created for them?
• How long does the average "Bug" take to resolve?

Questions about individual engineers:

• How many points does each person average per week?
• What's the breakdown of each person's tasks (e.g. Bug, Support, etc)
• Can we highlight times when someone has too much/too little assigned to them?

Team questions:

• Could the team "do more"? Do we have the capacity to resolve more issues/week?
• How much does our productivity vary each week?
• Can we automate standups? e.g. Slack us each a message beforehand with our recent updates, etc

Running

You can run this the same way you'd run any django application, or by using ./run.sh in the project directory. Make sure that you have defined a value for the environment variable ENG_OPS_DJANGO_SECRET_KEY.

Things to model

• Issue
• Pipeline
• Label
• User
• Milestone
• Estimate ?
• PRs
• Comments on PRs/Issues

These relationships are fluid – an Issue might enter/leave a Pipeline multiple times, and the timing around that is important. Its Estimates and Assignees may change, and we need to know that.

Modeling option: Issues -> PipelineStates (state: started: ended:?)

Potential roadmap

• V0: Build nuanced definition of Issue that only stores current snapshot into a Postgres DB, visualize in RJMetrics
• V0.1: Build Slack integration for pre-standups (What closed in last 24, what's in each Pipeline)
• V0.2: Model PRs/Comments
• V0.3: Improve Slack integration to include Comments and PRs.
• V1: Build and track nuanced PipelineStates over time

Punt til mid quarter:

• V1.1: Assess tracking nuanced Label/User/Milestone/Estimate/etc changes over time
• V2: Support for individual engineer queries