Only one person can deploy
Releases go out over SSH by whoever remembers the order of the commands. That person is a single point of failure for the whole product, and bringing a second engineer up to speed takes a week of shadowing.
DevOps and cloud work means taking an application that merely runs somewhere and making it run predictably: packaged in Docker, deployed from Git by a pipeline instead of by hand, watched by monitoring that alerts someone before customers do, and backed by copies that have actually been restored. We pick projects up at any stage — a hand-managed VPS, a cloud account nobody audits, or nothing yet.
Releases go out over SSH by whoever remembers the order of the commands. That person is a single point of failure for the whole product, and bringing a second engineer up to speed takes a week of shadowing.
A dump lands in a folder on the same machine it came from, and no one has unpacked it since it was set up. Until a restore has been rehearsed you do not have a recovery time, you have a hope.
No metrics, no alerting: a full disk or a crashed container reaches you as a support ticket. Monitoring closes that gap, so an incident starts with a notification instead of an angry email from your biggest account.
Idle instances, snapshots from experiments that ended last year, a database two sizes larger than the load needs. A line-by-line review almost always finds spend that buys nothing, without touching redundancy.
Containers restart, migrations run blind, users see 502s for ten minutes. Health-checked deploys keep the old version serving traffic until the new one answers correctly, and roll back on their own when it does not.
Most teams under twenty people need infrastructure work in bursts, then a few hours a month. Hiring for that means paying a salary for idle capacity, when a retainer from $400 a month covers the same ground.
We look at what runs where, how a release actually goes out, what happens to backups, and what the hosting bill is made of. You get a risk list in priority order and an estimate in hours.
Dockerfiles and Compose for every service, secrets moved into environment variables, dev, staging and production separated. The whole environment comes up with one command on any machine.
A pipeline that builds, tests, migrates and ships. The new version only takes traffic after its health check passes, and rolls back to the previous one automatically if it fails.
Host and application metrics, logs in one place, alerts on disk, memory and error spikes. Backups go to off-host storage, and we restore from them in front of you with a stopwatch running.
You get the access, the repository and a README that rebuilds the environment from zero. One month of warranty is included; a monthly retainer afterwards is optional, not assumed.
We fit the stack to the size of the problem: a two-service product does not need a Kubernetes cluster or the operational cost that comes with one. Complexity goes up only when traffic, team size or a security requirement genuinely calls for it.
Dockerfiles and Compose for the app and its database, a one-command deploy, secrets pulled out of the repo, daily backups to off-host storage. Around 20–30 hours. More if there are over three services or data has to move without downtime.
CI/CD with tests and migrations, a staging environment, zero-downtime deploys with automatic rollback, metrics and alerting, backups verified by a real restore, and documentation that rebuilds it all. 50–100 hours, depending on service count and how well the current setup is written down.
A dedicated engineer on retainer: alerts watched, images and dependencies patched, releases shipped, a restore drill every quarter. Hours are agreed up front, and anything past them is billed from $30 an hour.
Prices are indicative and do not constitute a public offer. The final cost, scope and timeline are fixed in a contract or invoice after we have discussed the task.
The clearest example is the CRM we built from scratch for a large HoReCa service company. Twelve-plus modules and 89 database migrations only stay manageable when migrations run inside the deploy pipeline rather than by hand on the server. With RBAC covering 9 roles and 87 permissions, a bad release touches every user at once, so deploys there are health-checked with rollback.
Read the KMD caseSend access, or just describe how a release goes out today. You get a prioritised list of risks and an estimate in hours, with a reply within 2 hours and no obligation.
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