Why do we need Insights Inference?

Insights Inference is KPI (Key Performance Indicator) based interface to provide instance of KPIs across various Vectors. It uses Apache Spark as job scheduler and executor, and Elasticsearch for data.

It is advantageous to get real time observations for each DevOps vector. Also, time series graph could be tracked across each individual vector on the basis of Day/Month/Quarter/Year, resulting in accuracy, and efficiency.

Insights tab with options panel

What's new in Insights with Insights Inference?

A separate tab to show Observations for each DevOps Vector.
Textual Inferences on the performance (Good or Bad).
The observations are classified into Positive, Negative & Neutral
Interpretation of various graphs across various vectors.
Provide information about data at various levels.
Capability to report progress on a Weekly, Monthly and Daily basis.
Configured Spark Jobs are executed on pre-configured intervals for each KPI.
Capability to use existing SDLC Data for applying ML Models.
Capability of a platform to create mathematical formulas for DevOps Metrics.
Spark Jobs store the result in pre- configured ES Indexes.
The User Interface makes call to a service to display the data in the necessary format.
Minimal Engineering effort is needed to add a new KPI, and report the same – No UI Change is needed.

Current/Default supported KPIs

KPI Name	DevOps Vector	Mathematical Function
Average Build Time	BUILD	AVERAGE
Total Number of Builds	BUILD	COUNT
Number of Successful Builds	BUILD	COUNT
Number of Failed Builds	BUILD	COUNT
Maximum Build Time	BUILD	MINMAX
Minimum Build Time	BUILD	MINMAX
Average Complexity	CODEQUALITY	AVERAGE
Average Duplicated Blocks	CODEQUALITY	AVERAGE
Number of Quality Passed Blocks	CODEQUALITY	COUNT
Number of Quality Failed Blocks	CODEQUALITY	COUNT
Average Code Coverage	CODEQUALITY	AVERAGE
Number of Successful Sonar Executions	CODEQUALITY	COUNT
Number of Failed Sonar Executions	CODEQUALITY	COUNT
Average Duration of Successful Deployments	DEPLOYMENT	AVERAGE
Total Failed Deployments	DEPLOYMENT	COUNT
Total Successful Deployments	DEPLOYMENT	COUNT
Maximum Deployment Time	DEPLOYMENT	MINMAX
Minimum Deployment Time	DEPLOYMENT	MINMAX
Number of Defects	DEFECTS	COUNT
Number of Closed Defects	DEFECTS	COUNT
Number of Open Defects	DEFECTS	COUNT
Average Defect Duration	DEFECTS	AVERAGE
User with most Commits	DEVELOPMENT	COUNT

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