Sisällön tarjoaa Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute. Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.

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Actionable Data in the DevSecOps Pipeline

31:58
 
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Manage episode 376839607 series 3018913
Sisällön tarjoaa Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute. Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.

In this podcast from the Carnegie Mellon University Software Engineering Institute, Bill Nichols and Julie Cohen talk with Suzanne Miller about how automation within DevSecOps product-development pipelines provides new opportunities for program managers (PMs) to confidently make decisions with the help of readily available data.

As in commercial companies, DoD PMs are accountable for the overall cost, schedule, and performance of a program. The PM’s job is even more complex in large programs with multiple software-development pipelines where cost, schedule, performance, and risk for the products of each pipeline must be considered when making decisions, as well as the interrelationships among products developed on different pipelines. Nichols and Cohen discuss how PMs can collect and transform unprocessed DevSecOps development data into useful program-management information that can guide decisions they must make during program execution. The ability to continuously monitor, analyze, and provide actionable data to the PM from tools in multiple interconnected pipelines of pipelines can help keep the overall program on track.

  continue reading

408 jaksoa

iconJaa
 
Manage episode 376839607 series 3018913
Sisällön tarjoaa Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute. Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.

In this podcast from the Carnegie Mellon University Software Engineering Institute, Bill Nichols and Julie Cohen talk with Suzanne Miller about how automation within DevSecOps product-development pipelines provides new opportunities for program managers (PMs) to confidently make decisions with the help of readily available data.

As in commercial companies, DoD PMs are accountable for the overall cost, schedule, and performance of a program. The PM’s job is even more complex in large programs with multiple software-development pipelines where cost, schedule, performance, and risk for the products of each pipeline must be considered when making decisions, as well as the interrelationships among products developed on different pipelines. Nichols and Cohen discuss how PMs can collect and transform unprocessed DevSecOps development data into useful program-management information that can guide decisions they must make during program execution. The ability to continuously monitor, analyze, and provide actionable data to the PM from tools in multiple interconnected pipelines of pipelines can help keep the overall program on track.

  continue reading

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