thanks for the post. I always found this site a good place to start[0] and a review of the various approaches[1] (disclaimer: I took part in writing that one)
There's an infrastructure engineer, or engineers that support DevOps operations. But DevOps by definition was about Devs doing more Ops, having an engineer 'do it for you' never made sense. 'DevOps engineer' was an unfortunate rebranding of infra engineers to maintain the status quo.
What would it take to create a runtime that bridges programming language ecosystems? A runtime that lets us import libraries from any language and use them idiomatically (as much as possible) with a straight forward DX? (check out the url for a simple example)
Hey friends! I recently published a blog post discussing common infrastructure reorganization models that companies adopt and why they often fail. After interviewing dozens of engineering leaders and infrastructure teams over the past two years, I've noticed companies tend to evolve their infrastructure orgs into a few canonical forms with distinct tradeoffs.
The post covers:
- 4 primary infrastructure org models
- Reasons companies consolidate into centralized platform teams or decompose them
- Tradeoffs, failure modes and pitfalls when reorg-ing infrastructure
- A new approach porposal for leveraging cloud intelligence to empower developers
Rather than continually rearranging org boundaries and responsibilities, I argue that we need to shift the focus to tools that bring the benefits of platform orgs into infrastructure orgs.
Would love to hear what you think! What infrastructure org structures have you seen succeed or struggle?
That's what we do with Klotho [0], annotations are only used to close behavioral gaps that are not available in application code. (I'm one of the founders)
"The primary reason to introduce a new example is when the LLM is incorrectly identifying technology as ABSTRACT vs not, missing connections, or even missing resources entirely. However, we don’t have unlimited tokens for every example we might need. An optimization we came up with here is Dynamic Examples using pre-filtering. Instead of providing examples that would generalize to everything, we focus the examples on what we can guess is in the queries.
We extract a list of technologies using word lists, which is easier than extracting their intents, and if we don’t find many matches, we assume that more ABSTRACT resources are present. Once extracted, we can then create a custom prompt by selecting specific examples to the technologies mentioned in the query and a set of bedrock examples including baseline rules for the different actions that expand language understanding."
[0] https://infrastructurefromcode.com/ [1] https://klo.dev/state-of-infrastructure-from-code-2023/