40 Years of Infrastructure as Code: Ansible → Terraform → Kubernetes → Crossplane → AI Agents @DevOpsToolkit

Uploaded August 2026 | Updated September 2026, 1 hour ago

From Bash scripts to AI agents, this video tells the forty-year history of infrastructure as code as a bedtime story — complete with a weary servant, a kingdom that never stops growing, and a parade of tinkers who each promise to fix everything. Traveling through CFEngine, Puppet, Chef, Ansible, Terraform, Kubernetes, and Crossplane, the story traces how every generation of tooling solved a real problem, only for the kingdom to expand fast enough to swallow the improvement whole.

The real nightmare, it turns out, isn't failure — it's winning, over and over, and still being the one who gets woken up at three in the morning. As AI agents arrive and claim the part of the job that took decades to master, the video asks a quietly unsettling question: if the next generation of tooling no longer needs to be readable by a human, who exactly is it being built for — and who will still be holding the lantern when something breaks?

#InfrastructureAsCode #DevOps #Kubernetes

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▬▬▬▬▬▬ ⏱ Timecodes ⏱ ▬▬▬▬▬▬
00:00 History of Infrastructure-as-Code (IaC)
01:34 Bash
03:21 CFEngine, Puppet & Chef
05:18 Ansible
08:01 Terraform & Pulumi
11:55 Crossplane
17:08 AI Agents
19:02 The Nightmare
20:44 Goodnight

40 Years of Infrastructure as Code: Ansible → Terraform → Kubernetes → Crossplane → AI Agents

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$MCP vs CLI: I Tested Both and Heres What Won MCP (Model Context Protocol) promises standardized tool discovery for AI agents, but it comes with a hidden cost: every tool definition, name, description, and parameter schema gets loaded into your context window on every single turn. Connect to a bloated MCP server with 40 or 50 tools and youve burned tens of thousands of tokens before asking a single question. This video puts MCP to the test against a compelling alternative — using CLIs as the communication channel between your agent and remote servers. Through live demos with Claude Code and a Kubernetes cluster, the video walks through both approaches side by side: querying cluster health and component relationships through an MCP server, then accomplishing the same task using the `dot-ai` CLI with a handful of lightweight skill files. The core insight is that LLMs are already trained on widely-used CLIs like `kubectl`, `gh`, and `aws`, making them zero-cost to use. For custom or internal tools, small skill files can teach the LLM what it needs to know at a fraction of the context cost of MCP schemas. The verdict isnt that one approach always wins — well-designed MCP servers with a small number of high-level tools remain a strong choice for centralized, cross-agent deployments — but when context efficiency matters or youre working with tools the LLM already knows, CLIs are often the smarter path. ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Sponsor: Auth0 🔗 http://a0.to/gav ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ #MCPProtocol #AIAgents #KubernetesCLI Consider joining the channel: https://www.youtube.com/c/devopstoolkit/join ▬▬▬▬▬▬ 🔗 Additional Info 🔗 ▬▬▬▬▬▬ ➡ Transcript and commands: https://devopstoolkit.live/ai/mcp-is-burning-your-tokens-before-you-ask-a-single-question 🔗 DevOps AI Toolkit: https://devopstoolkit.ai ▬▬▬▬▬▬ 💰 Sponsorships 💰 ▬▬▬▬▬▬ If you are interested in sponsoring this channel, please visit https://devopstoolkit.live/sponsor for more information. Alternatively, feel free to contact me over Twitter or LinkedIn (see below). ▬▬▬▬▬▬ 👋 Contact me 👋 ▬▬▬▬▬▬ ➡ BlueSky: https://vfarcic.bsky.social ➡ LinkedIn: https://www.linkedin.com/in/viktorfarcic/ ▬▬▬▬▬▬ 🚀 Other Channels 🚀 ▬▬▬▬▬▬ 🎤 Podcast: https://www.devopsparadox.com/ 💬 Live streams: https://www.youtube.com/c/DevOpsParadox ▬▬▬▬▬▬ ⏱ Timecodes ⏱ ▬▬▬▬▬▬ 00:00 MCP vs. CLI 01:10 Auth0 (sponsor) 02:50 MCP Protocol in Action 07:20 CLI Alternative to MCP 17:23 MCP vs CLI: Which One Wins?$

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