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Automation workflow

Turn repeat website maintenance into structured workflows.

Recipes turn the maintenance your team repeats into runs that are configured once, ask before anything disruptive, and log every step under the right client.

Works with the providers your maintenance already touches Amazon Route 53 Bento Bunny.net Cloudflare DigitalOcean endoflife.date Gandi GitHub GitLab Ionos Laravel Cloud Laravel Forge Mailgun Namecheap Oh Dear OVHcloud Ploi Porkbun Vultr
The real problem

Manual maintenance is hard to scale safely.

The same tasks repeat across every client project, and every manual run invites drift, skipped steps and missing proof. Three chores became buttons.

The checklist that became a button.

The update procedure lived in a doc titled FINAL-v3, and every developer ran it slightly differently. As a recipe, it runs in the same order with the same checks on every client server.

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The reboot that asked first.

Sunday-night reboots used to be one person, one terminal and crossed fingers. Now the run applies the updates, then stops at the disruptive part: 2 machines want a reboot, confirm? The click happened Monday at 09:10, in daylight, and the log shows exactly what followed.

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The monitors that create themselves.

A new client domain went live on Thursday, and the monitor-creation recipe gave it checks without anyone filing a task. When the site moved behind a CDN, the real-IP sync kept the monitors pointed at the true server. Monitoring stopped lagging behind the work.

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The value

Repeatability is the feature.

Same task, same run, every client.

A recipe is configured once: the scope, the schedule, the steps that must ask first. Then every client server gets the same maintenance in the same order, whether the run is started by the senior who wrote it or the hire who joined on Monday.

Proof instead of memory.

Maintenance work leaves proof instead of disappearing into terminals. Every run keeps its step timeline, its logs and its confirmations on the client project, so reviews, retainers and postmortems read the record instead of asking around.

The recipes

Start from recipes, not from scratch.

The recipes cover the work agencies repeat most: server updates, pending reboots, CVE remediation, monitor creation and real-IP sync. Run them by hand, put them on a daily schedule, or let events trigger them, as your plan allows.

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Proof

What a run leaves behind.

Automations you can read: what ran, what asked, what changed.

The recipe collection
Curated maintenance recipes: Ubuntu updates, kernel reboot checks, CVE remediation, monitor creation and real-IP sync.
Runs scoped to the project
Every run targets the project, provider or server it belongs to, and its result lands on the same page.
Confirmations where it matters
Disruptive steps stop and ask, at a sane hour.
Logs and step timelines
Every run keeps its steps, timings and output, attached to the client project it touched.
Manual, scheduled or event-driven
Run recipes by hand, on daily schedules, or from events, as your plan allows.
The shift

Manual checklist versus automation run

Before

A developer follows a checklist and remembers to report what happened.

With Unolia

The workflow records steps, confirmations, logs and status in the project.

Before

Every client site gets a slightly different maintenance process.

With Unolia

Recipes make one baseline that still keeps human review where it matters.

Before

Disruptive actions run from silent background scripts, or not at all.

With Unolia

Disruptive steps wait for a click from a human, at a sane hour.

Make recurring maintenance inspectable.

One repeat task, turned into a run your team configures once and trusts after.

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