Cloud Infrastructure

Cloud that gets cheaper as it gets bigger.

Migration, landing zones, and platform engineering across AWS, Azure, and GCP — built so your teams ship faster and your finance team stops being surprised.

300+

Workloads migrated

38%

Avg. spend reduction

99.99%

Platform availability

15 min

Median recovery time

Why estates go wrong

Three ways a cloud programme quietly stops paying for itself

None of these show up in the first quarter. All of them are expensive to unwind once the estate is live.

The bill grows faster than the business

Lift-and-shift moves a workload sized for a datacentre refresh cycle onto hardware you now rent by the hour. Nothing is wrong, and everything is expensive.

  • No unit-cost metric, so growth looks like success
  • Idle non-production running nights and weekends
  • Commitments bought against last year's shape

Governance arrives after the workloads

Accounts get created ad hoc, tags are optional, and identity sprawls. Retro-fitting boundaries onto a live estate costs several times what it costs to lay them first.

  • Cost cannot be attributed to a team
  • Blast radius spans unrelated systems
  • Audit evidence assembled by hand each cycle

Nobody owns reliability

The platform works until it doesn't, and then the people who know why have left. Availability targets exist in a slide but nothing gates a release against them.

  • Alerts tuned to noise, so they are muted
  • Runbooks describe a system two versions old
  • Recovery rehearsed for the first time during an incident

Capabilities

From first landing zone to steady state

Whether you are moving your first workload or trying to regain control of an estate that grew faster than its governance.

Migration & modernisation

Portfolio assessment, wave planning, and execution — rehost where it is sensible, refactor where it pays for itself, retire what nobody has opened in two years.

  • Dependency mapping
  • Wave-based cutover
  • Rollback per wave

Landing zones

Multi-account foundations with identity, network segmentation, logging, and guardrails in place before the first production workload arrives.

  • Account vending
  • Policy guardrails
  • Central log archive

Kubernetes platforms

An internal platform your product teams can self-serve, with the operational burden owned by the platform rather than by every squad.

  • Golden paths
  • Progressive delivery
  • Multi-tenant isolation

Infrastructure as code

Terraform or Bicep modules under review, tested in CI, and versioned — so environments are reproducible and drift is a build failure, not a mystery.

  • Module library
  • Policy as code
  • Drift detection

FinOps & cost control

Showback by team, commitment planning, and rightsizing that survives the quarter — cost engineering, not a one-off spreadsheet exercise.

  • Unit-cost metrics
  • Commitment strategy
  • Anomaly alerting

Reliability engineering

Service level objectives agreed with the business, error budgets that actually gate releases, and game-days that rehearse the failure before it happens.

  • SLO definition
  • Chaos exercises
  • Runbook automation

Platform anatomy

What a landing zone actually contains

Four layers, built in this order. Skipping straight to workloads is the single most common reason an estate needs rescuing eighteen months later.

Foundation

Account topology

Organisation units mapped to your business, with account vending automated.

Identity and access

Central IdP federation, least-privilege roles and a tested break-glass path.

Network fabric

Segmented VPCs, private connectivity and controlled, logged egress.

Log archive

Immutable central logging with retention set by your audit obligation.

Guardrails

Policy as code

Service control policies and OPA rules enforced in the pipeline, not in a wiki.

Tagging standard

Cost-allocation tags mandatory at creation, so attribution works from day one.

Baseline security

Encryption defaults, public-access blocks and CIS benchmarks applied per account.

Drift detection

Out-of-band change surfaces as a build failure rather than a surprise.

Delivery platform

Golden paths

Paved routes to production a product team can self-serve without a ticket.

GitOps pipeline

Argo CD or Flux reconciling declared state, with progressive delivery built in.

Module library

Reviewed, versioned Terraform or Bicep modules tested in CI before publication.

Environment parity

Ephemeral preview environments built from the same modules as production.

Operations

Observability

OpenTelemetry traces, metrics and logs correlated behind one query surface.

SLOs and error budgets

Targets agreed with the business, with budget burn gating releases.

Cost telemetry

Unit-cost dashboards by team and by feature, with anomaly alerting.

Incident practice

Game-days, rehearsed runbooks and a blameless review loop that changes the system.

Every layer below your workloads is delivered as reviewed infrastructure code in your repository. There is no console-clicked configuration we can hold and you cannot rebuild.

Our approach

Three things that decide whether cloud pays off

Assessment

Move the right things, in the right order

The most expensive migration is the one that lifts a badly behaved application into a more expensive place to run it. We profile the portfolio first and are entirely willing to recommend leaving workloads where they are.

  • Application dependency graph built from real traffic, not documentation
  • Per-workload disposition: rehost, replatform, refactor, retire, retain
  • Business case modelled against current run cost, including licensing
  • Migration waves sequenced so the riskiest dependency is proven first

Foundations

Guardrails before workloads

Almost every estate we are asked to rescue skipped the landing zone. Retro-fitting identity boundaries, network segmentation, and tagging onto a live estate costs several times what it costs to do first.

  • Account and subscription topology aligned to your org, not the vendor's demo
  • Centralised identity with least-privilege roles and break-glass procedure
  • Network segmentation and egress control designed for audit
  • Tagging standard enforced by policy, so cost attribution actually works

Operations

Handed over as a running concern

We are not trying to become a permanent dependency. The engagement ends with your team operating the platform, with the runbooks, dashboards, and on-call rotation they need to do it.

  • Observability stack instrumented and alert thresholds tuned against real load
  • Runbooks written from incidents rehearsed in game-days
  • On-call rotation and escalation paths established with your team
  • Optional managed operations if you would rather not staff it

Disposition

Six things you can do with a workload. Only one is 'lift it'.

Every application in the portfolio gets one of these, with the reasoning recorded. The cheapest migration is frequently the one you decide not to run.

Retire

Cheapest win
When it applies
No meaningful usage in the last two quarters
Typical effort
Days
Cost effect
Removes run cost entirely
Risk
Low — reversible from backup

Retain

When it applies
Latency, licensing or regulation makes the move uneconomic
Typical effort
None
Cost effect
Unchanged
Risk
Low — nothing moves

Rehost

When it applies
Stable application, datacentre exit on a deadline
Typical effort
1–3 weeks per wave
Cost effect
Neutral to worse without rightsizing
Risk
Medium — cutover risk

Replatform

When it applies
Managed database or runtime removes most of the toil
Typical effort
3–6 weeks
Cost effect
Meaningful reduction in run cost
Risk
Medium — data migration

Refactor

When it applies
The application is strategic and the architecture is the constraint
Typical effort
One quarter or more
Cost effect
Best long-term unit economics
Risk
High — needs product ownership

Repurchase

When it applies
A commodity SaaS product covers the requirement
Typical effort
Weeks, mostly data and change
Cost effect
Shifts capex to a subscription
Risk
Medium — process change

Delivery

How a cloud engagement runs

Each phase produces something you keep, whether or not you continue to the next one.

  1. 01

    Weeks 1–3

    Discovery and business case

    Portfolio inventory, dependency mapping, and a costed target architecture with a disposition for every workload.

  2. 02

    Weeks 4–7

    Landing zone build

    Accounts, identity, networking, logging, and guardrails delivered as reviewed infrastructure code with a pilot workload running on top.

  3. 03

    Ongoing

    Migration waves

    Workloads move in planned waves, each with a rehearsed cutover and a rollback path. Nothing moves on a Friday.

  4. 04

    Post-migration

    Optimisation

    Rightsizing, commitment purchasing, and architectural changes driven by four to six weeks of real production telemetry rather than estimates.

  5. 05

    Handover

    Operate or transfer

    Your team takes the platform with full documentation and shadowing, or we run it under an SLA. Either way the code and access are yours.

What you get

What lands in your repository and your inbox

Artefacts, not slideware. Everything below is yours to keep and rebuild from, whether or not the engagement continues.

Assessment

  • Application dependency graph built from observed traffic
  • Per-workload disposition with the reasoning recorded
  • Five-year run-cost model including licensing
  • Wave plan sequenced by dependency risk

Build

  • Landing zone as reviewed, versioned infrastructure code
  • Reusable module library published to your registry
  • CI pipelines with policy and security gates
  • Pilot workload running end to end on the platform

Operate

  • Observability dashboards and tuned alert thresholds
  • Runbooks written from rehearsed game-day incidents
  • SLO definitions and error-budget policy
  • On-call rotation and escalation path agreed with your team

Toolchain

What we build on

Managed services wherever they remove work, self-managed only where the control genuinely matters.

Platforms

AWS, Microsoft Azure, and Google Cloud, including regulated-region and sovereign-cloud deployments.

Orchestration

EKS, AKS, GKE, ECS, and serverless runtimes. Argo CD and Flux for GitOps delivery.

Provisioning

Terraform, OpenTofu, Bicep, and Crossplane, with Checkov and OPA enforcing policy in the pipeline.

Observability

OpenTelemetry, Prometheus, Grafana, Datadog, and cloud-native tracing wired in from the first deployment.

Engagement models

Three ways to start

Scope and price are set after the assessment, against your actual estate rather than a headcount guess.

Estate assessment

Fixed fee

Three weeks, quoted up front

A costed, evidence-based read on what you run today and what it should cost.

  • Dependency and disposition analysis
  • Reliability and security posture review
  • Spend model with ranked savings
  • Findings you keep regardless of next steps
Recommended

Platform build

Project

Scoped in phases with exit gates

Landing zone, delivery platform and migration waves, delivered against agreed milestones.

  • Fixed-scope phases you can stop between
  • Infrastructure code in your repository from week one
  • Migration waves with rehearsed rollback
  • Handover with shadowing, not a document drop

Managed platform

Retainer

Monthly, with an agreed SLA

We run the platform under SLA while your team builds on top of it.

  • 24/7 on-call and incident response
  • Continuous cost and rightsizing review
  • Patch, upgrade and compliance cadence
  • Exit plan documented from the first month

Questions

The questions we get asked before signing

If yours is not here, ask it on the assessment call — the answer is usually 'it depends', and the interesting part is what it depends on.

Scope and approach

Will you tell us not to migrate?

Regularly. 'Retain' and 'retire' are two of the six dispositions, and on most portfolios they together cover a meaningful share of the estate. A workload with heavy egress, a latency-bound on-premise dependency, or a licence that reprices in cloud is often cheaper where it is. We would rather say so in week two than have you discover it in year two.

Can you work across more than one cloud?

Yes, and we will push back if the reason is 'avoiding lock-in' rather than a concrete requirement. Genuine multi-cloud drivers — data residency, a customer contract, an acquired estate — are common and worth designing for. Running the same workload twice for insurance is expensive and rarely exercised.

We already migrated and it went badly. Can you help?

That is a large share of the work we do. The assessment is the same, but the disposition set shifts towards replatform and remediation, and the landing zone has to be retro-fitted around live workloads. It costs more than doing it first, and it is entirely recoverable.

Commercials and risk

How do you price migration work?

The assessment is a fixed fee quoted before it starts. Build work is scoped per phase with an exit gate between phases, so you are never committing to the whole programme on day one. Retainers are monthly against a named team and an agreed SLA.

What happens if a cutover fails?

Every wave has a rollback path that has been executed in a staging environment before the production window opens. Nothing moves on a Friday, and no wave proceeds until the previous one is stable. If a rollback is triggered, the wave is re-planned rather than forced.

Do we depend on you afterwards?

Only if you choose to. The platform is infrastructure code in your repository, the runbooks are written for your team, and handover includes shadowing rather than a document drop. The managed option exists because some clients would rather not staff on-call, not because the platform requires us.

Get an honest read on your cloud estate.

A three-week assessment covering architecture, reliability, security posture, and spend — with the findings ranked by what they cost you.