Page Comparison

KPI Name / Definition

Representation

Tool

Maturity Levels

KPI Calculation

On Hover

Remarks

Deployment Frequency

measures how often code is deployed to production

Line chart

• Y- Axis - Count

• X- Axis - Months

• Aggregation Method - Sum

• Positive trend indication - Increase

Agile Project Management

• Build Tools

M1: 1

M2: 2-3

M3: 4-5

M4: 6-7

M5: >=8

It is calculated as No. of deployments done on a environment in a month

• It is calculated as a 'Count'. Higher the count during a month, more valuable it is for the Business or a Project

• Maturity of the KPI is calculated based on the latest value

Month - <<Count>> 

Change Failure Rate

measures the proportion of builds (changes) that have failed for whatever reason over a given period of time

Line Graph with single-select filter

• Y- Axis - Percentage

• X- Axis - Weeks

• Aggregation Method - Average

• Positive trend indication - Decrease

Build

• Jenkins

• Bamboo

• Azure Pipelines

• Teamcity

M1: >60% 

M2: 45-60%,

M3: 30-45%,

M4: 15-30%,

M5: <15%

Total no. of failed Builds/Total number of Builds

• It is calculated as a ‘Percentage’. Lower the percentage, better is the ‘Quality’

• Maturity of the KPI is calculated based on the average of last 5 values that corresponds with the maturity scale

*If the KPI data is not available for last 5 weeks, the Maturity level will not be shown

Date Range: <<Percentage>>

Total number of Changes: <<Value>>

Failed Changes: <<Value>>

1. Multiple jobs can be configured for the same project

Lead time for changes

gauges the speed of software delivery by measuring the duration between a code change and its deployment in production. It provides visibility into the efficiency and effectiveness of the development process.

Line Graph with single-select filter

• Y- Axis - Days

• X- Axis - Weeks

• Aggregation Method - Average

• Positive trend indication - Decrease

JIRA

Repos

M1: >3 Months 

M2: 1-3 Months,

M3: <1 Month,

M4: < 1 week,

M5: < 1 Day

Date Range: <<Lead time in Days>>

Mean time to Recover (MTTR)

is a metric that measures the average time taken to recover from production incidents. It is calculated based on the production incident tickets raised during a certain period of time.

Line Graph

• Y- Axis - Hours

• X- Axis - Weeks

• Aggregation Method - N/A

• Positive trend indication - Decrease

JIRA

M1: >1 Week 

M2: 1 day - 1 week,

M3: 12-24 Hours,

M4: 1-12 Hours,

M5: < 1 Hour

• Mean time to recover will be based on the Production incident tickets raised during a certain period of time

• For all the production incident tickets raised during a time period, the time between start date and closed date of the incident ticket will be calculated

• Then the average of all such tickets will be shown

• There will be 3 configurations

  • Issue type to identify Production incidents

  • One field that will allow user to setup either label or custom field

  • DOD field for field for kpi for tracking fixing of production incident, among list of dod status
    whichever is reached first will be taking as completion time.

• Fields on Overlay

  • Issue ID

  • Issue Type

  • Issue Description

  • Created Date

  • Closed Date

  • Time to Recover (Hrs)