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I know there are a lot of tools focused on root cause analysis after things break. Cool, but that’s not what’s wearing me down. What actually hurts is the constant context switching while trying to understand how a system fits together, what depends on what, and what changed recently.
As systems grow, this feels like it gets exponentially harder. Add logs and now you’ve created a million new events to reason about. Add another database and suddenly you’re dealing with subnet constraints or a DB choice that’s expensive as hell, and no one noticed until later. Everyone knows their slice, but the full picture lives nowhere, so bit rot just keeps creeping in.
This feels even worse now that AI agents are pushing large amounts of code and config changes quickly. Things move faster, but shared understanding falls behind even faster.
I’m honestly stuck on how people handle this well in practice. For folks dealing with real production systems, what’s actually helped? Diagrams, docs, tribal knowledge, tooling, something else? Where does it break down?
One thing that became painfully clear over time is that most outages, security issues, and compliance fire drills don’t come from a lack of tools. They come from missing context. People don’t know what’s running, how things connect, or what changed recently, especially once systems sprawl across clouds, repos, and teams.
That’s why I’m building OpsCompanion.
The goal is simple: keep a live, shared picture of what’s actually running and how it fits together.
OpsCompanion helps engineers:
See a live, visual map of services, infrastructure, and dependencies
Answer “what changed?” without digging through five tools, Slack threads, or outdated docs
Preserve operational context so the next person on call isn’t starting from zero
This isn’t about adding more logs or alerts, or slapping AI on top of existing dashboards. It’s about capturing the mental model experienced operators carry in their heads and keeping it shared and up to date.
It’s still early, and there are rough edges. I’ve opened it up to a small group of engineers who work close to production so I can get honest feedback. If it’s useful, great. If not, I genuinely want to understand why and what would make it better.
You can try it here: https://opscompanion.ai/?utm_source=hn&utm_medium=show_hn&ut...
I’ll be around in the comments. Happy to answer technical questions, hear skepticism, get a bit roasted, or talk about what actually breaks in real systems.