Uncover the hidden value of your CI/CD pipeline and discover how Gerrit DevOps Analytics helps to accelerate your development and quickly adapt to an ever-changing market. GerritForge has published one year ago the Gerrit Analytics for the Gerrit Code Review project, showing live metrics on where the project is going, the key contributors and the most active repositories. Learn how to expand the scope of the Data & Insights to the rest of the CI/CD Pipeline, including the Git traffic, system utilization and the relationships inside and across Teams. All of that is possible by just reusing what Gerrit Code Review provides and is often left behind. See a real use-case based on a real-life scenario that can be taken home and applied to your CI/CD Pipeline.

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Gerrit DevOps Analytics
Uncover the hidden value of your CI/CD Pipeline
Luca Milanesio
luca@gerritforge.com
Cesare San Martino
cesare@gerritforge.com

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About GerritForge
Founded in the
UK
HQ in London Committed to
OpenSource

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Gerrit DevOps Analytics
§ There’s a lot value in your DevOps pipeline
§ Information collected from Git, Jenkins, Jira, you
name it
§ Discover and publish meaningful KPI to make
intelligent decisions about
§ People
§ Projects
§ Infrastructure
§ Lower the Risk of a software release leveraging
insights on historical data

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Continuous Delivery
Analytics Dimensions
People Reviews Projects Commits System Metrics

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BigData to the rescue
§ Collect all review events
§ Collect all logs
§ Channel them to a central store
§ Crunch and Crunch continuously
§ Never delete
§ Process, inspect and learn

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GDA Components
The main components of GDA are:
§ GDA Event Collector (Plugin)
This allows for data to be extracted, anonymized and sent
over to the next phase.
§ GDA ELT Engine
This is hosted in the cloud by GerritForge or on-premises
and functions as data mart and processing for all
development related data
§ GDA Dashboard(s)
These are provided by GF according to the customer
needs. Some dashboards are already available (for people
and projects). Others will be built on purpose.

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A real-life use-case
Scenario:
§ TOP5 most valued Tech companies in the world
§ Upgrade software release
§ Change of hardware infrastructure

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A real-life use-case
Questions to be answered:
Q1: Can the new system manage the current
production load?
Q2: What’s the X-Factor of production to reach the
breaking point?
Q3: What’s the risk of my release roll-out?

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A real-life use-case
DevOps Analytics Way:
§ Leverage the data we have
§ Uncover the patterns of production load
§ Allow best use of resources with
minimal risk

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Continuous Delivery Analytics
DEMO

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Wants to know more?
gerritforge.com/devops