Get your detailed reports for Quality Gate meetings

Agile Analytics leverages real production data and supercharges your software operation

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Quality Gates serve as checkpoints or milestones within the software development lifecycle to ensure that specific quality criteria are met before progressing to the next phase. Too often, we see that while the process is implemented, the data that is ‘brought’ to the table is not empirical. We see a lot of HiPPO (Highest Paid Person’s Opinion) behaviour going on in these meetings. We believe we have a solution to that challenge! Stop Guessing; start Measuring!

Sprint Insights

Sprint Insights are powered by Large Language Models and GPT and help teams can gain valuable insights into the distinction between feature development and maintenance/non-feature work. It enhances team autonomy by providing objective measures of the time allocated to each type of work. This knowledge empowers teams to prioritize effectively, optimize resource allocation, and ensure a balanced focus on both feature development and maintenance, ultimately improving productivity and delivery outcomes.

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Leaked Private Keys

Looking for Private Keys in your internal source control system is crucial to ensure that unauthorized access to protected cloud resources is prevented within your organization. Mistakenly committing a private key to the central repository can easily occur, and even if the key is removed from the latest commit, it may still exist in older revisions. By leveraging Agile Analytics' Leaks Finder, you can detect the presence of these keys in previous versions and take appropriate actions to secure your cloud resources. This becomes an essential security compliance metric, ensuring that sensitive information is not inadvertently exposed and safeguarding your organization's data and systems.

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Error Budgets

Setting up the process of Error Budgets empowers your teams by granting them increased autonomy in decision-making regarding feature development and quality aspects. Error Budgets provide a defined threshold of acceptable errors or issues in production. By having this framework in place, teams can determine whether they can focus on full-throttle feature development or if attention needs to be given to addressing quality concerns. This approach allows teams to strike a balance between innovation and maintaining high-quality standards, giving them the flexibility to make informed choices and prioritize their efforts effectively.

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DORA Metrics

The industry standard DORA (DevOps Research and Assessment) metrics offer a valuable framework for measuring productivity and identifying high-performing teams while considering the quality aspects of software delivery. DORA metrics encompass four key metrics: Deployment Frequency, Lead Time for Changes, Mean Time to Recover, and Change Failure Rate.

DORA metrics enable the measurement of team productivity through quantitative indicators like Deployment Frequency and Lead Time for Changes. These metrics allow organizations to track and compare productivity levels, identify bottlenecks, and drive improvement efforts. Additionally, DORA metrics incorporate quality aspects through Mean Time to Recover and Change Failure Rate, ensuring that productivity gains are achieved without compromising software quality. By including these quality metrics, organizations can identify high-performing teams that consistently deliver value while upholding high-quality standards.

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We are ready to assist you with Agile Analytics, a comprehensive product that provides detailed reports for Quality Gate meetings and the Quality gate process. By leveraging real production data, we supercharge your software operation, enabling effective quality management in software development.