Automation

I can’t count the times I dropped .terraform-version in a new Terraform repo. tfenv read it, fetched the right binary, and switched. When a new Terraform release broke a plan at the worst possible moment, tfenv use put the old one back and I went on with my day. That command has never once asked me to think hard thoughts.

For a long time, my definition of a successful software release was pretty simple: the tests passed, the binaries built, and the checksums matched. Ship it! That still sounds reasonable, but there is a gap hiding between we built some bytes and users downloaded the bytes we intended to publish.

I’ve written many nearly identical Python Dockerfiles. Pick a base image, install dependencies, add a non-root user, find the right console script, and do it again when the next MCP server shows up. That’s a lot of container housekeeping for a tool that might only tell an agent what time it is.

The discourse on platform engineering Twitter and Reddit has been pretty consistent for months now: Terraform is dead, HCL is dead, the entire Infrastructure as Code stack is about to get vaporized by autonomous agents that translate intent directly into cloud provider API calls. The 24-month clock is ticking. Pack up your .tfstate and go home. Another DEAD DEAD DEAD narrative emerges.

Here’s a question I got asked recently: If a skill can already call a REST API using Bash, why bother with MCP? The surface-level answer is “MCP is cleaner.” That’s not wrong, but it undersells what’s actually different - and I think it’s a genuinely useful distinction to understand if you’re serious about building reliable agent workflows. Also, common-sense needs a resurgence given the massive amount of all old things are DEAD when new thing comes out clickbait that is proliferating on LinkedIn.

Let me paint you a picture. It’s 2025. You’ve discovered that you can describe a feature in plain English and an LLM will just… build it. The dopamine hit rivals or even eclipses social media. You feel as if you’re shipping things in an afternoon that used to take a week. You’re not reading diffs. You’re not understanding the internals. You’re just vibing - and it feels amazing.

Sometimes, especially if you aren’t a developer by trade, you can get stuck on something small that will find you banging your forehead on your desk (figuratively, of course). Most of the time, it is easy enough to find an answer online or even from ChatGPT. Other times, you may not be so lucky. The other day, I fell victim to a TWE or time wasting event that I thought was worth writing about. Fasten your seatbelt!

For many moons, importing existing infrastructure (that is to say, infrastructure running outside of Terraform state), has not been a trivial task. Historically, Terraform did not generate any configuration. You would have to write the infrastructure-as-code in a manner that reflects how it was deployed. Then, to make matters not easier, you would fetch the ‘ol shovel and dig out the unique resource identifiers to feed through the command line. Handling a single resource in this manner is pretty simple. Wrangling 20+ resources like this is not. Last month, Terraform v1.5.0 was released, offering the ability to use import blocks. Let’s test this new feature on my favorite infrastructure provider, Alkira.

I recently wrote a blog about generating Terraform with ChatGPT. In that experiment, I was using GPT-3.5. It didn’t take much to trip up the galactic AI in many of the experiments I did with Terraform and beyond. According to OpenAI GPT-4 soars past its predecessor in its advanced reasoning capabilities. Let’s use this model to build code in Python and Go. How will the super titan fair in the Sysadmin arena? Let’s take on some tedious backend work head-on with the biggest brain around and see what happens.

Usually, when it comes to technology, my grandmother doesn’t know much because she doesn’t care. What is the cloud? How to install a new browser on her laptop? What is 2FA? I might be speaking French to her as I discuss these things. Yet, she knows what ChatGPT is. This shows the vast amount of publicity, hype, and polarization that has ensued since November 2022. I tend to avoid AI fear-mongering and focus more on, how could a tool like this help enhance my daily grind? Can ChatGPT write Terraform as elegantly as a poem written from the perspective of Samuel L. Jackson in Pulp Fiction? Let’s take it for a spin on AWS using infrastructure-as-code.

Blowing out cloud spend is an easy thing to do. This McKinsey Report notes that 80% of enterprises consider managing cloud spend a challenge. I recently presented at the Cloud Security Alliance in Kansas City and had the opportunity to network with some tremendous DevOps and Security professionals. One excellent side conversation somehow transitioned to a deep discussion on better ways to understand cost implications in the era of infrastructure-as-code. Shouldn’t cost be someone else’s problem?

Optional attributes for object type constraints is almost here! I’ve been waiting for this feature to come along for a while. I have tested it extensively in -alpha, and I can confidently confirm that it is a game changer. This feature is long in the making, being discussed as far back as this thread in 2018. Today, it is now in beta, so the official release could be any day now. Let’s demonstrate how this is useful and build some common AWS infrastructure.