Somebody on call
Alerts routed to a rota with agreed response times, so a failure wakes an engineer instead of waiting for a customer email.
Infrastructure somebody is watching at three in the morning, model serving included.
Running a website and running a model are different disciplines with the same failure mode: nobody notices until a customer does. We take on both, with alerting that pages a person rather than filling a dashboard nobody opens.
For applications that means architecture on AWS or Google Cloud sized to real traffic, backups restored on a schedule to prove they work, and a deployment pipeline that can roll back inside a minute.
For models it means versioned artefacts, reproducible serving environments, drift and cost monitoring, and a retraining path that passes the same evaluation gate as the original release. A model that degrades quietly is worse than one that fails loudly.
Alerts routed to a rota with agreed response times, so a failure wakes an engineer instead of waiting for a customer email.
Restores tested on a schedule, because an untested backup is an assumption rather than a safeguard.
Compute, storage and inference spend attributed to services and models, reviewed monthly with the things worth switching off named.
Drift, latency and quality tracked per version, with retraining passing the same evaluation gate as the first release.
What runs where, who can reach it, what has no backup, and what would take longest to bring back. The list is always longer than expected.
Infrastructure as code, so rebuilding is a pipeline run rather than an afternoon of one person remembering how it was set up.
Metrics, logs and traces for applications, plus drift, latency and cost for models, with alert thresholds tuned so a page means something.
On-call cover, a monthly reliability and cost review, and a quarterly restore drill run against a real backup rather than a document.
Each phase ends with something you can read and act on. If the evidence says stop, stopping there is a supported outcome rather than an awkward conversation.
Tooling is a decision we make per project, against your constraints and whatever your team already runs. Nothing on this list is a requirement, and we will work inside your existing stack where it holds up.
Yes, and that is most of this work. We start with an inventory and a risk list, fix what is dangerous, then codify the rest so it stops depending on one person's memory.
A response time by severity, a documented escalation path, and runbooks for the failures we can predict. The scope is written into the agreement rather than implied by the word managed.
No. We work inside your own AWS or Google Cloud account under your billing, so you keep ownership, any committed discounts, and the ability to move on.
Tell us where the work sits today and what is holding it up. We will come back with the shape of a first phase, what it would prove, and what running it takes.
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