deorder
Joined 9 years ago
Joined 9 years ago
Right now I am using nginx with the image_filter module + caching to do this.
It may not work for VST plugins with certain DRMs though.
Update: I see that bepzi was 1 hour ahead of me. I did not see it when I refreshed the page, only after I replied.
People commit their changes, I (and sometimes another dev) review them and they are pushed to the test environment, from there to staging and then production (with a way to easily roll back). This is all done automatically with out-of-the-box solutions (fluxcd, flagger, kilo, kaniko etc).
At work, Kubernetes is not considered too difficult to manage. Much can be done in a very consistent and complete way unlike Docker. What am I overlooking that makes k8s to be considered snake-oil by so many?
Edit: Forgot to add. I am so happy with k8s that I even run it at home and on my external servers.
Instead of MetalLB I used PureLB, but now I use no LB: https://purelb.gitlab.io/docs/
I use Rook for storage: https://rook.io/
You are absolutely right. A large portion are influencers (I would estimate around 95% of those you see on YouTube and forums) that are full of hype. I think most are not affiliated with Anthropic or any vendor, they are just trying to sell a course, ebook or some "get rich with AI" scheme.
What I appreciate about Claude Code:
- Since it is a terminal/CLI tool it can be run headlessly from cron jobs or scripts. This makes it easy to automate.
- I appreciate the predictable pricing model. A flat monthly fee gives me access to Claude Sonnet and Opus 4 in five-hour sessions each with its own usage limit that resets at the start of a new session. There is a fair use policy of around 50 sessions per month, but I haven’t hit that yet. I deliberately run only one instance at a time as I prefer to use it responsibly unlike some of the "vibe" influencers who seem to push it to the limit.
That's it. Despite being a CLI based tool, Claude Code is remarkably out of the box for what it offers.
That said, no coding agent I have encountered can fully ingest a large inconsistent legacy codebase especially one with mixed architectures that accumulated over years. This limitation is mainly due to context size constraints, but I expect this to improve as context windows grow.