Software Engineer's Guide to DevOps

Aug 13, 20190 likes59 views

The document is a guide to DevOps for software engineers that discusses topics like continuous integration, containers, orchestration, infrastructure as code, and how DevOps can help create a smooth path from development to operations. It provides an overview of many DevOps practices and tools that engineers can use such as Docker, configuration management tools, orchestration tools like Kubernetes, and documenting infrastructure as code. The overall message is that DevOps aims to break down silos between development and operations teams.

A SOFTWARE ENGINEER’S
GUIDE TO DEVOPS
LAURIE BARTH

LAURIE BARTH
SOFTWARE ENGINEER
@laurieontech

@laurieontech
DEVOPS EXISTS
TO CREATE A SMOOTH PATH
FROM DEVELOPMENT
THROUGH OPERATIONS

@laurieontech
CI/CD
CONTINUOUS INTEGRATION
CONTINUOUS DELIVERY

@laurieontech
WHAT IT TAKES TO
DEPLOY AN APP

@laurieontech
Alice Goldfuss
THE CONTAINER
OPERATORS MANUAL

@laurieontech
WHAT ABOUT YOUR
APPLICATION?

@laurieontech
CONFIGURATION
MANAGEMENT TOOLS

@laurieontech
IDEMPOTENT
4 x 1 = 4
4 x 1 x 1 = 4
4 x 1 x 1 x 1 = 4
4 x 1 x 1 x 1 x 1 = 4
4 x 1 x 1 x 1 x 1 x 1 = 4

@laurieontech
MULTIPLE APPS
WORKING TOGETHER

@laurieontech
WHAT ABOUT YOUR
TARGET STATE?

@laurieontech
awsgeek.com/pages/AWS-Periodic-Table.html

@laurieontech
DEVOPS SHOULD
MATTER TO DEVELOPERS

@laurieontech
UNDERSTANDING RELEVANT
INFORMATION AND IMPACTS

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Slides for the session delivered at Devoxx UK 2025 - Londo. Discover how to seamlessly integrate AI LLM models into your website using cutting-edge techniques like new client-side APIs and cloud services. Learn how to execute AI models in the front-end without incurring cloud fees by leveraging Chrome's Gemini Nano model using the window.ai inference API, or utilizing WebNN, WebGPU, and WebAssembly for open-source models. This session dives into API integration, token management, secure prompting, and practical demos to get you started with AI on the web. Unlock the power of AI on the web while having fun along the way!

ICDCC 2025: Securing Agentic AI - Eryk Budi Pratama.pdfEryk Budi Pratama

Title: Securing Agentic AI: Infrastructure Strategies for the Brains Behind the Bots As AI systems evolve toward greater autonomy, the emergence of Agentic AI—AI that can reason, plan, recall, and interact with external tools—presents both transformative potential and critical security risks. This presentation explores: > What Agentic AI is and how it operates (perceives → reasons → acts) > Real-world enterprise use cases: enterprise co-pilots, DevOps automation, multi-agent orchestration, and decision-making support > Key risks based on the OWASP Agentic AI Threat Model, including memory poisoning, tool misuse, privilege compromise, cascading hallucinations, and rogue agents > Infrastructure challenges unique to Agentic AI: unbounded tool access, AI identity spoofing, untraceable decision logic, persistent memory surfaces, and human-in-the-loop fatigue > Reference architectures for single-agent and multi-agent systems > Mitigation strategies aligned with the OWASP Agentic AI Security Playbooks, covering: reasoning traceability, memory protection, secure tool execution, RBAC, HITL protection, and multi-agent trust enforcement > Future-proofing infrastructure with observability, agent isolation, Zero Trust, and agent-specific threat modeling in the SDLC > Call to action: enforce memory hygiene, integrate red teaming, apply Zero Trust principles, and proactively govern AI behavior Presented at the Indonesia Cloud & Datacenter Convention (IDCDC) 2025, this session offers actionable guidance for building secure and trustworthy infrastructure to support the next generation of autonomous, tool-using AI agents.