Visibility from Code to Cloud - How pipeline analytics changes how we think about SDLC
summary
Claim: collecting logs and metrics from Spinnaker, Artifactory, Hashi Vault and test/orchestration tools and correlating them yields actionable visibility from plan to prod. The work is: ingest telemetry, metrize logs, build dashboards per persona and correlate across tools to measure lead time, deployment frequency, MTTA/MTTR and surface unplanned work and cost of downtime. Three concrete use cases are operate, measure and audit; the payoff is faster remediation, continuous reduction of technical debt and stronger supply‑chain security.
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chapters (18)
- 0:00Introduction and welcome
- 1:05Speaker background and role
- 2:09What is pipeline analytics?
- 3:58Software delivery chain as an application
- 5:46Why pipeline analytics matters
- 9:04Security risks in delivery chains
- 11:36Outcomes of pipeline analytics
- 13:46Building pipeline analytics step-by-step
- 16:15Operate use case explained
- 17:41Measure use case and KPIs
- 18:45Flow framework and technical debt
- 20:30Flow velocity and load metrics
- 21:55Incident metrics and downtime costs
- 22:59Audit use case for security
- 26:10Implementing with Splunk
- 27:13Stakeholders and dashboards
- 29:18Code to Cloud visibility summary
- 30:02Closing and Q&A
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