Jira metrics Eazybi Cloud functions

This a simple API that captures a public report from Eazybi and do calculations to output the Monte Carlo forecast metrics to be imported to Eazybi source.

The output could be, for example: How many itens the team could deliver in 14 days with 85% cofidence(percentile)?

This is a alternative version to Jira metrics Eazybi that can be deployed to a GCP Cloud Function.

Sample output:

{
    "schema": {
        "fields": [
            {
                "name": "project",
                "type": "string"
            },
            {
                "name": "cycletime 50%",
                "type": "integer"
            },
            {
                "name": "cycletime 85%",
                "type": "integer"
            },
            {
                "name": "cycletime 95%",
                "type": "integer"
            },
            {
                "name": "montecarlo 50%",
                "type": "integer"
            },
            {
                "name": "montecarlo 85%",
                "type": "integer"
            },
            {
                "name": "montecarlo 95%",
                "type": "integer"
            }
        ],
        "primaryKey": [
            "project"
        ],
        "pandas_version": "1.4.0"
    },
    "data": [
        {
            "project": "JP",
            "cycletime 50%": 3,
            "cycletime 85%": 14,
            "cycletime 95%": 29,
            "montecarlo 50%": 18,
            "montecarlo 85%": 12,
            "montecarlo 95%": 9
        }
    ]
}

How to use

Setup an Eazybi public report

Create an Eazybi report to be consumed by this api, example:

• Rows
  • Project dimension, Project hierarchy level
  • Time dimension, Day hierarchy level
  • Issue dimension, Issue hierarchy level
• Columns
  • Measure cycle time (in days)

Your table/data should look like this:

Project	Time	Issue	Cycle time
JP	Aug 25 2022	JP-105	24
JP	Aug 29 2022	JP-110	30

Save the report and make it public with an access token, you will use this info in the request Json body.

Setup a GCP Cloud function

Create a runtime enviroment variable with the name AUTH_BEARER_TOKEN with a secret token of your choice

You should configure the cloud function as usual copying main.py and requirements.txt and define the entrypoint as main

Configure API Eazybi project

Go to your account Source Data tab and add a new source aplication as a Rest:API.

• Your source data URL should be <your_gcp_server_url>/eazybi/<your_secret_name_or_config_filename_without_.yml>
  • Example: https://jira-metrics-eazybi.app/eazybi/jp
• Set request method to POST
• Add to the request body the report details and calculation configuration:

{
    "Account_number": "Eazybi report account number, integer (without quotes)",
    "Report_number": "Eazybi report number, integer (without quotes)",
    "Report_token": "Eazybi report token, string (WITH quotes)",
    "Cycletime": {
        "Percentiles": [
            50,
            85,
            95
        ]
    },
    "Throughput_range": 90,
    "Montecarlo": {
        "Simulations": 10000,
        "Simulation_days": 14,
        "Percentiles": [
            50,
            85,
            95
        ]
    }
}

• Set Authentication parameters as HTTP header
  • Header name Authorization
  • Header value the token created as an eviroment varialbe on your cloud function
• Content type to JSON
• Data path to $.data

How to setup dev enviroment

Setup

python3 -m venv venv
source venv/bin/activate
pip install -r requirements_dev.txt

launch.json is a sample file to be able to debug locally in vscode,add it to your .vscode dir.

To be able to generate http requests Postman vscode extension is recommended.

You can create a enviroment variable creating a .env file.