Cloud-native is the easy part. Running it well is not
Nobody is impressed by a Kubernetes cluster any more. The useful questions are what your platform does at 3am, whether a deploy can be reversed in a minute, and why the bill went up last month. We answer those with evidence rather than a diagram.
Platforms that survive growth
Systems rarely fail because the architecture diagram was wrong. They fail because traffic, data volume and team size all tripled, and only the first one was designed for.
Architecture and service boundaries
Greenfield design on AWS or GCP, or a second opinion on what you already run. Service boundaries drawn along how your teams actually work, including the times the right answer is a well-structured monolith.
Containers and orchestration
Kubernetes, managed container services or serverless, chosen for the team that has to keep it alive at 3am rather than for the architecture diagram.
CI/CD and release safety
Pipelines that build, test, scan and deploy without a human in the middle, plus the unglamorous parts: staged rollouts, feature flags and a rollback path that has actually been rehearsed.
Observability and on-call
Logs, metrics, traces and alerts wired to the handful of signals that predict an outage. Dashboards nobody opens are a cost, not a control.
Cost engineering
Right-sizing, autoscaling policy, storage tiering, committed-use planning and spend attribution, reviewed against your real usage so savings are traceable to a decision.
Migration without a big bang
Data centre to cloud, or cloud to cloud, in slices with a working rollback at each step. A migration with no way back is a bet, not a plan.
What good infrastructure buys you
Deploys stop being events
Releases go out on a Tuesday afternoon because rollback is one command and CI has already caught the obvious. The Friday deploy joke stops being a joke.
Incidents get shorter
Not eliminated, shortened. Good tracing turns "the site feels slow" into "this query on this service" in minutes instead of an afternoon.
The bill becomes predictable
Tagged, attributed and reviewed monthly. Cloud spend that surprises you is usually a design problem wearing a finance costume.
Growth stops meaning rewrite
Scaling becomes a capacity conversation and a configuration change, rather than the quarter where the platform team rebuilds everything.
No rebuild by reflex
Assess what's there
Two weeks reading your infrastructure, pipelines, dashboards and incident history. You get a written map of risks, costs and quick wins, useful even if you stop there.
Fix the expensive things first
Sequenced by what costs you money or sleep, not by what is architecturally satisfying. In practice that is usually release safety and alerting before anything else.
Automate and hand over
Everything ends up in code, in your accounts, with runbooks your team can follow. We are happy to stay on call. You should not need us to be.
What we build with
Questions we get asked
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