Inspire, develop, and guide a winning organization.
Create visible workflows to achieve well-architected software.
Understand and use meaningful data to measure success.
Integrate and automate quality, security, and compliance into daily work.
Understand the unique values and behaviors of a successful organization.
LLMs and Generative AI in the enterprise.
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Learn how making work visible, value stream management, and flow metrics can affect change in your organization.
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Multiple award-winning CTO, researcher, and bestselling author Gene Kim hosts enterprise technology and business leaders.
In the first part of this two-part episode of The Idealcast, Gene Kim speaks with Dr. Ron Westrum, Emeritus Professor of Sociology at Eastern Michigan University.
In the first episode of Season 2 of The Idealcast, Gene Kim speaks with Admiral John Richardson, who served as Chief of Naval Operations for four years.
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DevOps best practices, case studies, organizational change, ways of working, and the latest thinking affecting business and technology leadership.
Is slowify a real word?
Could right fit help talent discover more meaning and satisfaction at work and help companies find lost productivity?
The values and philosophies that frame the processes, procedures, and practices of DevOps.
This post presents the four key metrics to measure software delivery performance.
June 24, 2020
Adapted from The DevOps Handbook by Gene Kim, Jez Humble, Patrick Debois, and John Willis.
While DevOps practices have been pioneered by the web-scale, Internet “unicorn” companies such as Google, Amazon, Netflix, and Etsy, each of these organizations has, at some point in their history, risked going out of business because of the problems associated with more traditional “horse” organizations: highly dangerous code releases that were prone to catastrophic failure, inability to release features fast enough to beat the competition, compliance concerns, an inability to scale, high levels of distrust between Development and Operations, and so forth.
However, each of these organizations was able to transform their architecture, technical practices, and culture to create the amazing outcomes that we associate with DevOps. As Dr. Branden Williams, an information security executive, quipped, “Let there be no more talk of DevOps unicorns or horses but only thoroughbreds and horses heading to the glue factory.”
DevOps principles and practices are compatible with Agile, with many observing that DevOps is a logical continuation of the Agile journey that started in 2001. Agile often serves as an effective enabler of DevOps, because of its focus on small teams continually delivering high quality code to customers.
Many DevOps practices emerge if we continue to manage our work beyond the goal of “potentially shippable code” at the end of each iteration, extending it to having our code always in a deployable state, with developers checking into trunk daily, and that we demonstrate our features in production-like environments.
Many view DevOps as a backlash to ITIL or ITSM (IT Service Management), which was originally published in 1989. ITIL has broadly influenced multiple generations of Ops practitioners, including one of the co-authors, and is an ever-evolving library of practices intended to codify the processes and practices that underpin world-class IT Operations, spanning service strategy, design, and support.
DevOps practices can be made compatible with ITIL process. However, to support the shorter lead times and higher deployment frequencies associated with DevOps, many areas of the ITIL processes become fully automated, solving many problems associated with the configuration and release management processes (e.g., keeping the configuration management database and definitive software libraries up to date). And because DevOps requires fast detection and recovery when service incidents occur, the ITIL disciplines of service design, incident, and problem management remain as relevant as ever.
The absence of traditional controls (e.g., segregation of duty, change approval processes, manual security reviews at the end of the project) may dismay information security and compliance professionals.
However, that doesn’t mean that DevOps organizations don’t have effective controls. Instead of security and compliance activities only being performed at the end of the project, controls are integrated into every stage of daily work in the software development life cycle, resulting in better quality, security, and compliance outcomes.
Many misinterpret DevOps as the complete elimination of the IT Operations function. However, this is rarely the case. While the nature of IT Operations work may change, it remains as important as ever. IT Operations collaborates far earlier in the software life cycle with Development, who continues to work with IT Operations long after the code has been deployed into production.
Instead of IT Operations doing manual work that comes from work tickets, it enables developer productivity through APIs and self-serviced platforms that create environments, test and deploy code, monitor and display production telemetry, and so forth. By doing this, IT Operations become more like Development (as do QA and Infosec), engaged in product development, where the product is the platform that developers use to safely, quickly, and securely test, deploy, and run their IT services in production.
While many of the DevOps patterns shown in this book require automation, DevOps also requires cultural norms and an architecture that allows for the shared goals to be achieved throughout the IT value stream. This goes far beyond just automation. As Christopher Little, a technology executive and one of the earliest chroniclers of DevOps, wrote, “DevOps isn’t about automation, just as astronomy isn’t about telescopes.”
Although many DevOps success stories take place in organizations using software such as the LAMP stack (Linux, Apache, MySQL, PHP), achieving DevOps outcomes is independent of the technology being used. Successes have been achieved with applications written in Microsoft.NET, COBOL, and mainframe assembly code, as well as with SAP and even embedded systems (e.g., HP LaserJet firmware).
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