󰣻 git push origin main — then let automation finish it
󰣨 deploy --affected-only --health-gated
󰄬 build reproducible reviewed · signed · tested
󰄬 deploy atomic affected hosts only
󰄬 verify behavioural settle · probe · confirm
󰣻 rollback automatic previous known-good generation

CI/CD, Containers & Orchestration

Infrastructure That Ships Itself

I don’t just administer servers — I encode the desired state, automate the path from pull request to production, and make failure visible before it becomes user-visible.

What I deliver:

You get:

One Path to Production

A deployment is a chain of decisions, not one action. I make each transition explicit and test the transition rather than assuming the previous stage was successful.

  1. Review — changes are evaluated as source, with the scope of each affected host or service visible.
  2. Build — artifacts are built from locked inputs and the candidate generation is evaluated before activation.
  3. Deploy — only the affected targets change, and hand-edited production state is not part of the path.
  4. Settle — the system gets a bounded window to start services and reconnect dependencies.
  5. Verify — critical services and externally visible endpoints are probed.
  6. Roll back — a failed health gate returns the target to the previous known-good generation.

Automation With Guardrails

Automation should make a narrow, repeatable change without hiding its scope. Every production path gets a deployment record, explicit event gates, and a dry-run or preview where the tooling supports one.

The important property is not automation for its own sake. It is that the same reviewed input produces the same result, and a failed deployment stops rather than continuing through later stages.

Choosing the Smallest Useful System

Not every workload needs Kubernetes. A single NixOS host, a systemd service, or a static binary may be easier to operate than a cluster. I choose the smallest design that preserves the guarantees you need: versioned configuration, tested builds, safe release, and a tested restore.

Need Useful default
Reproducible Linux hosts NixOS flakes and shared modules
Configuration across existing servers Ansible roles or a declarative provider
Application delivery CI pipeline plus immutable container image
Multi-service scheduling systemd, Nomad, or Kubernetes by operational scale
Recovery Encrypted backups with scheduled restore tests

What Comes With the Delivery

I document the path, the trust boundaries, the rollback point, and the failure modes. If another engineer has to take over, the system should be legible from its source and its runbooks.

For the live signals that tell you whether the delivered path is healthy, see Monitoring & Observability. For the security controls and review layers around a deployment, see Security Services.

󰣻 CI/CD Pipelines
󰄬 Configuration as Code
󰋖 Containers & Orchestration
󰀦 Health-Gated Rollback
󰔟 Replace manual production changes with a path you can trust.
Tell me how software reaches production today, where manual steps remain, and what has gone wrong. I'll propose a practical automation design with clear gates and rollback points.
[ REQUEST AUTOMATION REVIEW ]
󰣨 ymrtech@ymrtech | 󰌠 NixOS | 󰍢 UTF-8