Damon Edwards (PagerDuty), John Willis, John Rauser (Cisco Cloud Security) & Patrick Debois
This article has been a game-changer for my organization and our customers, providing a clear and practical understanding of Generative AI (GenAI) and its enterprise adoption. The detailed explanations of GenAI concepts and real-world examples have been invaluable. The article's focus on critical considerations such as cost, security, trust, and adoption has guided our strategic planning and decision-making. For instance, the insights on cost management and security measures helped us implement GenAI solutions more efficiently and securely.
Vladan Atanasijevic, COO, Comtrade Group
While Generative AI (GenAI) is only just emerging as a mature technology, we are not at the first intersection of AI and DevOps. In the drive for automation, people have used big data and machine learning (ML) to improve IT Operations processes, mostly around event correlation, anomaly detection, and causality determination (AIOps), using past inputs to predict future events. Additionally, to improve the training and delivery of machine learning models, we have seen the application of DevOps practices to make continuous delivery of ML pipelines more reliable (MLOps).
GenAI is different from traditional AI in that it is focused on generating something new instead of predicting patterns (e.g., generate a summary, generate new code, generate an answer to a question). Large language models (LLM) such as GPT-4 or Llama are focused on generating text, models like DALL-E or Stable Diffusion on generating images, and vision models such as LLAVA or GPT-vision on converting images to text. This new technology opens up a whole new set of use cases, which were hard to unlock before. During the software delivery life cycle (SDLC), almost any process can be enhanced by this new technology (i.e., using GenAI to achieve better DevOps delivery).
Instead of training specific machine learning models, these new models exhibit emergent behavior that allow them to perform a set of tasks without specifically being taught that task. This speeds up the deployment of new ideas tremendously; one can simply prototype ideas just with text. On the flip side, these models are not always focused on returning reliable answers. To compensate for this, we’ll use other techniques and we will need to put guardrails in place. To make this process more reliable, we can use existing DevOps concepts and apply them to this new technology (i.e., using DevOps to achieve better GenAI delivery).
What's inside
Practical Guidance — Provides practical guidance on using DevOps principles in relation to GenAI.
Deep Dive — Takes a deeper dive into the emerging field of GenAI in enterprises.
Expert Authors — Written by a team of experts in the field who have applied these principles in various industries.
Change Agents — Change agents can come from anywhere on the org chart. These papers directly address how to lead and implement change no matter your role or title.
Pages
21
Publication Date
May 7, 2024
Topics
AI
Formats
epub · pdf
License
Creative Commons BY-NC-SA
About the authors
4 authors
Damon EdwardsPagerDuty (at publication)▼▲
Now: Attestify · as of 2026
Damon Edwards is Senior Director, Product at PagerDuty. Previously, Damon was a cofounder of Rundeck, the makers of the popular open-source runbook automation platform acquired by PagerDuty in 2020. Prior to Rundeck, Damon was the Managing Partner of DTO Solutions, a DevOps and Operations Improvement Consultancy. Damon has spent the past 23 years working with both the technology and business ends of IT Operations. He is noted for being a leader in porting cutting-edge DevOps techniques to large-scale enterprise organizations. Damon is a frequent conference speaker and writer who focuses on DevOps, SRE, and Operations improvement topics. Damon is active in the international DevOps community, co-host of the DevOps Cafe podcast, and a content chair for Gene Kim’s DevOps Enterprise Summit.
John WillisAuthor, Deming’s Journey to Profound Knowledge▼▲
John Willis has worked in the IT management industry for more than 35 years. John is currently working as a Distinguished Researcher at Kosli. He is researching DevOps, DevSecOps, IT risk, modern governance, and audit compliance. Previously he was an Evangelist at Docker Inc., VP of Solutions for Socketplane (sold to Docker) and Enstratius (sold to Dell), and VP of Training & Services at Opscode where he formalized the training, evangelism, and professional services functions at the firm. Willis also founded Gulf Breeze Software, an award winning IBM business partner, which specializes in deploying Tivoli technology for the enterprise. Willis has authored six IBM Redbooks for IBM on enterprise systems management and was the founder and chief architect at Chain Bridge Systems.
John RauserCisco Cloud Security (at publication)▼▲
John Rauser is Director of Software Engineering at Cisco Cloud Security. He works on distributed networking and security systems, connecting and protecting the world’s largest companies with cloud-delivered solutions. John has spent his career working in various roles across the spectrum of IT, from sysadmin to technology manager, network engineer to infosec lead, developer to engineering leader. John is passionate about organizational leadership, new ways of working, and bridging theory with practice. He speaks regularly at local and international conferences and writes for online publications and on his blog.
In 2009 he coined the word devops by organizing the first devopsdays event. He organized conferences all over the world to collect and spread new ideas. As a pioneer he is always on the look out for new ideas to implement and explore. Currently in the media sector where he is guiding broadcasters with the transition to enter into a dialogue with it's audience as a closed feedback loop.
