Release Go/No-Go
Enable Continuous Monitoring for Continuous Release Readiness
Release Go/No-Go Challenges
With DevOps and Agile practices, most organizations are making more frequent releases than ever. However, they still encounter challenges in taking release Go/No-Go decisions:
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Disjointed Data
Organizations are unable to unify data from different tools to get a single indicator of whether or not to go ahead with a release.
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Lack of Contextual Insights
There’s a lot of manual analysis required as different stakeholders try to make sense of the disjointed data in their context.
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Project Risk Scoring
Organizations are unable to find a balance between standardization and flexibility to manage exceptions and rules and score projects across different parameters.
Expedite Release Go-No/Go Decisions
Gathr helps you automate data collection from different tools in your delivery cycle to quickly analyze various performance metrics and ensure secure and compliant releases:
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Data Collection
Collect data from tools like Jira, SonarQube, TestRail, etc., with out-of-the-box connectors for quick correlation and simplify risk assessment across projects.
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Management Summary
Get a quick overview of all projects with their average risk scores and identify how many projects are approved, at risk, or blocked.
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Project Summary
Drill to project details like their code coverage, the number of defects across projects, their distribution by severity, and their breakdown by different stages of the release cycle.
Simplify Defect and Test Suite Analysis
Detect and resolve bugs and vulnerabilities quickly for a better user experience and assess your test scope and quality gates for high-quality releases.
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Incident Traceability
Quickly trace defects to their builds and commit ID, identify which builds have a higher portion of blockers and critical issues, who worked on it, and more.
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Test Suite Analysis
Analyze test cases and their automation status to identify areas of improvement. You can search and visually analyze test suites across different projects in a few simple clicks.
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Risk Score Configuration
Define risk score as a function of defects, code coverage, test coverage, etc., using the Formula Engine, which simplifies computations with excel-like formulas.
Solution Highlights
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Ready-to-use solution requiring minimal configuration
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Out-of-the-box connectors to gather and analyze data from multiple tools
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Ready dashboards and templates to visualize data
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Python and Machine Learning support for predictive analysis
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Highly flexible; change formulas and add new tools without coding
Solution Benefits
Release Go/No-Go solution helps teams expedite their release lifecycle with dashboards providing actionable insights suited for different stakeholders as per their context.
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