IT organizations are increasingly using machine data - including in DevOps practices - to get away from 'vanity metrics' and instead to generate 'metrics that matter'. These metrics provide visibility into the delivery of new application code and the business value of DevOps, to both IT and business stakeholders.
Machine data provides DevOps teams and others - including QA, secops, CxOs and LOB leaders - with meaningful and actionable metrics. This allows stakeholders to monitor, measure, and continuously improve the velocity and quality of code throughout the software lifecycle, from dev/test to customer-facing outcomes and business impact.
In this session Andi Mann, chief technology advocate at Splunk, will share core methodologies, interesting case studies, key success factors and 'gotcha' moments from real-world experience with mining machine data to produce 'metrics that matter' in a DevOps context.