Platform & reliability assessment
A read of where the platform actually stands — availability, change safety, observability, and cost — and what to do about it first.
Services · Infrastructure
Platform, reliability, and cloud — engineered to hold at scale.
Deep infrastructure work delivered as clear offerings, not as a team on a timesheet: assessments that end in a decision, migrations with a sequence, and reliability someone owns.
01 / What it covers
Four things, and each one is buyable.
Cloud migration
On-prem to cloud and cloud to cloud, across AWS, Azure, and GCP: the target model, the sequence, and the dependencies that decide the order.
SRE & observability
Service levels that mean something, alerts people trust, and the operational practice that keeps them true.
Managed reliability
Reliability run as an ongoing service with named ownership, rather than a project that ends and decays.
02 / Where it usually starts
If any of this sounds familiar.
- The platform can no longer absorb what the business is asking of it.
- A migration started, stalled, and nobody wants to say so out loud.
- There are dashboards and alerts, and no one trusts either.
- Reliability work happens, but nobody owns the outcome.
What you leave with
- An honest current-state read, in language a board can follow
- A target platform model, and the real gap between here and there
- A sequenced plan with dependencies and a first move
- Named owners, and the measures that say whether it is working
03 / How it runs
The same ladder as everything else.
Usually starts with a diagnostic
A diagnostic →A few weeks, fixed scope — enough to know where you stand and what deserves the first move.
Built and led as a 100+ specialist Center of Excellence, with multi-year client relationships and an offering catalog behind it.
04 / Questions
What people ask first.
Do you take the platform over, or work with my team?
With your team. The people who run the platform keep running it — the work is the decision, the target model, and the sequence, made with them rather than around them. For delivery-heavy stretches I bring in trusted specialists and stay accountable for the outcome.
We are mid-migration and stuck. Is it too late?
That is one of the most common places to start. A stalled migration is usually blocked by ownership or an unmapped dependency rather than by technology, and the first job is to say out loud which one it is.
Does our observability need to be in order first?
No. What you cannot see is itself a finding, and an honest one — it tells us where the platform is being run on faith. We work from what exists.
Which clouds do you work with?
AWS, Azure, GCP, and on-prem estates that are moving to one of them. The target model decides the platform, not the other way round.
What if the answer is that we should not migrate?
Then that is the recommendation, with the reasoning and what to do instead. A diagnostic that ends in "don’t" has still saved you the programme.
Also under Services
Advisory →The engagement ladder itself — a working session, a fixed-scope diagnostic, a hands-on transformation, or a retainer. Start wherever the decision is.AI Strategy →Getting AI into the engineering lifecycle: the roles, the workflow, and the measures that turn AI ambition into shipped outcomes.