One definition, everywhere
The .sklp/ folder describes development, CI, publishing and deployment. You never rewrite the same project for the next step.
Every stack · Every source
Simple or complex. If it runs, Skalpai sees it.
Demo: logs from every project reach the console, a trace reveals the slow request, an alert fires on the error rate, usage is tracked, and an issue opens with the context attached.
Your stack, as it is
Your stack, your machines, one console.
Node, Go, Rust, Python or Bun: add an SDK or an OTLP exporter, and logs, traces and metrics land in the same place. Your virtual machines, Kubernetes clusters and public endpoints report their state there too. Sentinel checks from the outside that every service responds.
Demo: Node, Go, Rust, Python or Bun, with PHP and Java coming soon, across websites, APIs, virtual machines and Kubernetes clusters. Skalpai receives the same logs, traces and metrics from each and shows them in one place.
$ sklp
From code to production, without gluing a toolchain together.
The .sklp/ folder follows your project from your laptop to your machines. sklp starts the local environment, runs CI, builds and publishes images, then deploys from Git. The same definition serves every step, and Skalpai then shows you what is actually running.
Demo: sklp runs CI, then builds, scans and publishes the images. The node's image watch spots the new tag, reconciles the Space from Git and rolls it out, keeping the old image for rollback.
Every application in its own space
Your services run isolated in a Space, with no privileged daemon. An ordinary Linux machine is enough to start.
Git says what should run
Each machine reads the desired state, deploys the right version and keeps the previous one so you can roll back when needed.
Backups that are actually verified
Backups are restored regularly and the result is dated. You know which ones will really work.
Who it's for
Stay in control of your machines without spending your days watching them.
Freelancers, product teams, studios and agencies running several apps for several clients, teams leaving a PaaS without wanting to rebuild an entire platform. One system to learn, whether you are one person or ten.
The boundaries
- You bring the Linux machines. Skalpai does not sell infrastructure and promises neither autoscaling nor multi-region.
- A Space fits on one machine. Applications spread across several machines remain Kubernetes territory, which Skalpai can also monitor.
- The console can monitor on its own. With sklp, it also links what runs to its deployment and the commit that produced it.