Course · Training · Workshop
DevSecOps with AI
Two hands-on days integrating AI and LLMs into your DevSecOps workflows – from prompt engineering to Prometheus queries and local LLM solutions.
In this two-day workshop, discover how to practically integrate AI and Large Language Models (LLMs) into your DevSecOps processes. From basics to advanced techniques – optimize your workflows with hands-on exercises and real-world application examples.
Trainers
What participants say
The course was highly educational. I discovered many tools and found the integration of these tools with AI into a developer environment extremely fascinating. I learned a lot about cutting-edge topics, which is especially impressive given the rapid evolution of the AI landscape. The knowledge I gained has already helped me improve and accelerate my own processes, significantly enhancing my daily workflow.
Cloud Platform Solution Architect, Helvetia Versicherungen Schweiz
These customers booked courses in the same topic cluster.More customers →
Content
In this workshop, you will learn how to effectively integrate AI technologies, particularly Large Language Models (LLMs), into your work processes. You will become familiar with and practically apply both cloud-based and local LLM solutions. Thanks to hands-on exercises and real-world use cases, you will develop the ability to use AI tools in a targeted and efficient manner. We will start with the basics and then delve into advanced concepts such as prompt engineering and RAG, until you are finally able to implement AI solutions for specific DevSecOps tasks.
Key Concepts:
- Introduction to AI and LLMs: Understanding the fundamentals, current developments, and future perspectives.
- Practical use of LLMs: Learning to implement and use local and cloud-based LLMs.
- Prompt Engineering: Developing skills for efficient and creative interaction with LLMs, as well as techniques for minimizing hallucinations and improving output accuracy.
- DevSecOps Use Cases: Hands-on examples for targeted application of AI in the DevSecOps field.
- AI Tool Landscape: Getting to know and applying various tools such as k8s-gpt, aiac, ollama, and llmstudio.
The actual course content may differ from the above depending on the trainer, delivery, duration and the composition of participants.
Request this course in-house
Request a public date
No suitable public date? Register without obligation — once there is enough interest we schedule a new public date and let you know first.
More about DevSecOps with AI
DevSecOps with AI combines the principles of integrated security throughout the software development lifecycle with the capabilities of modern AI technologies and large language models. LLMs are used to detect vulnerabilities, analyze YAML and infrastructure configurations, automate compliance checks, and assist security teams with alert triage. Established frameworks such as the OWASP Top 10 for LLM Applications and the NIST AI Risk Management Framework provide important guidance for the secure use of AI in production DevSecOps environments.Further resources:
History
DevSecOps emerged as an evolution of the DevOps approach, with the goal of integrating security from the very start of the development process — following the "Shift Left" principle. With the rise of AI and LLMs from 2022 onwards, a new era began: tools such as the OWASP LLM Top 10 and the NIST AI RMF, published in January 2023, created the first standardized frameworks for the secure handling of AI systems in enterprise environments.
Since then, the landscape has evolved rapidly: specialized tools such as k8s-gpt, aiac, and Ollama enable teams to integrate AI directly into their Kubernetes and CI/CD pipelines. In July 2024, NIST extended the framework with a Generative AI Profile (NIST AI 600-1), addressing the specific risks of generative AI and helping organizations govern their AI systems based on risk.