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Cloud Engineering & DevOps

Infrastructure you stop thinking about.

Platforms that absorb a traffic spike without a war room, rebuild themselves from code after a failure, and cost roughly a third less than the setup they replaced.

99.99% availability across managed environments
Availability across managed platforms
99.99%Availability across managed platforms
Average reduction in cloud spend
38%Average reduction in cloud spend
Median recovery time objective
8 minMedian recovery time objective
Increase in deployment frequency
24xIncrease in deployment frequency

Reference topology

Multi-region
Edge
Global CDNWAF + bot controlEdge functions
Platform
KubernetesService meshAutoscaling pools
Data
Postgres HAObject storageStreaming bus

99.99%

Availability target

<8 min

Recovery time

−38%

Cloud spend

The problem

Nobody knows what half of it does, and nobody wants to turn it off.

The bill grows every quarter. Deployments happen on Thursday nights because that is when someone is free to watch. Disaster recovery is a document that has never been tested. And the one engineer who understands the networking is on holiday.

What it costs you

  • Cloud spend rising with no clear link to usage or revenue
  • Manual deployments that require the same person every time
  • Infrastructure changes made in a console and never recorded
  • A recovery plan that has never actually been rehearsed
  • Environments that cannot be recreated from scratch

What we build

The parts that make it survive production.

Every engagement includes all of this. None of it is an upgrade tier.

Cloud architecture

Landing zones, account structure, network design and workload placement designed for how you actually operate.

Infrastructure as code

Everything in Terraform, reviewed, versioned and reproducible. Console changes get detected and reverted, not tolerated.

Kubernetes platforms

Cluster design, multi-tenancy, autoscaling and a developer experience that does not require every engineer to learn it.

CI/CD

Pipelines with automated testing, progressive delivery and one-command rollback. Deployment stops being an event.

Observability

Metrics, logs and traces unified, with alerts tied to user-facing symptoms rather than to every twitch of CPU.

Cost engineering

Rightsizing, commitment strategy, storage lifecycle and workload scheduling — with the savings attributed and tracked.

Resilience

Failure modes identified, recovery objectives agreed, and recovery actually rehearsed on a schedule rather than assumed.

Migration

Moving off legacy hosting or between clouds in stages, with a rollback path at every step and no big-bang weekend.

Where it pays

Real workloads. Real numbers.

Results are drawn from production engagements and measured against a pre-engagement baseline.

Platform modernisation

A monolith on ageing virtual machines moved to containers with autoscaling and a reproducible environment definition.

Infrastructure cost down 41%, deploys up 24x

Cost recovery

Rightsizing, savings-plan strategy, storage tiering and shutdown schedules for non-production environments.

$1.9M annualised saving in 90 days

Multi-region resilience

Active-active deployment across regions with automated failover and quarterly rehearsed recovery.

Recovery time from 6 hours to 8 minutes

Developer platform

Self-service environments, golden paths and paved-road templates so teams ship without waiting on infrastructure.

Environment provisioning from 3 weeks to 20 minutes

Compliance-ready landing zone

Account structure, guardrails and policy as code aligned to HIPAA and SOC 2 from the first deployment.

Audit findings reduced to zero

AI workload platform

GPU scheduling, model serving, inference caching and cost attribution per team and per workload.

Inference cost per request down 61%

How it runs

From first conversation to running system.

  1. 01Stage 1

    Assess

    Architecture review, cost analysis, resilience testing and a security posture check. You get findings ranked by risk and by dollars.

    2 weeks

  2. 02Stage 2

    Codify

    Existing infrastructure captured in code, environments made reproducible, and drift detection turned on before anything is changed.

    3–6 weeks

  3. 03Stage 3

    Improve

    Migration, platform build, pipeline automation and cost work, sequenced so each step stands alone and can be stopped.

    6–16 weeks

  4. 04Stage 4

    Operate or hand over

    We run it, or we train your team and step back. Both paths end with your team able to operate the platform.

    Ongoing

Technology

Chosen by evaluation, not by preference.

We build on what fits your constraints and what your team can maintain. Nothing here locks you in.

  • Your repositories, your cloud account, your licence
  • No proprietary runtime you have to keep paying for
  • Documentation written for the engineer who inherits it
See the full stack

Clouds

  • AWS
  • Microsoft Azure
  • Google Cloud
  • Cloudflare
  • On-premises hybrid

Platform

  • Kubernetes
  • Terraform
  • Pulumi
  • Helm
  • Argo CD
  • Crossplane

Observability

  • Datadog
  • Grafana
  • Prometheus
  • OpenTelemetry
  • Loki
  • PagerDuty

Delivery

  • GitHub Actions
  • GitLab CI
  • Docker
  • Vault
  • SOPS
  • Chaos testing

How we price it

Three ways in. A stop point at each one.

Cost optimisation work is often self-funding — we will show you the projected saving before you commit, and several clients have run the first engagement against the savings alone.

Cloud assessment

Fixed price · 2 weeks

Architecture, cost, resilience and security reviewed together, with a ranked plan and a quantified savings estimate.

  • Architecture and security review
  • Detailed cost breakdown and savings model
  • Resilience and recovery testing
  • Prioritised remediation roadmap
Discuss cloud assessment
Most chosen

Platform build

Fixed scope · 8–20 weeks

Landing zone, Kubernetes platform, pipelines and observability — everything in code, everything reproducible.

  • Infrastructure as code across all environments
  • CI/CD with progressive delivery
  • Observability and alerting
  • Disaster recovery design and rehearsal
  • Team enablement and documentation
Discuss platform build

Managed platform

Monthly · 24/7

We operate the platform: on-call, patching, capacity, cost management and continuous improvement against agreed SLOs.

  • 24/7 on-call and incident response
  • Patching and upgrade management
  • Continuous cost optimisation
  • Quarterly resilience exercises
  • SLO reporting
Discuss managed platform

Questions

What buyers ask about cloud engineering

Direct answers, including the ones that are inconvenient for us.

Still deciding?

Send the question to a senior engineer instead of a form. You will get a straight answer, and a no if that is the honest one.

Across our engagements the average is 38%, and the assessment gives you a specific number for your estate before you commit to anything. The biggest wins are usually rightsizing, non-production shutdown schedules, storage lifecycle policy and commitment strategy — rarely anything exotic.

Usually not. Multi-cloud for resilience is expensive and rarely delivers the resilience people imagine; multi-region within one provider handles most of it far more cheaply. Multi-cloud makes sense for specific workload placement, acquisitions or genuine regulatory requirements. We will argue against it when it is being chosen for the wrong reason.

Often no. For a handful of services, managed container platforms or serverless are simpler and cheaper to operate. Kubernetes earns its complexity when you have many teams, many services or genuine portability requirements. We have talked more clients out of it than into it.

In stages, with both environments running in parallel and traffic shifted progressively behind a routing layer. Every step has a rollback path that has been tested. It takes longer than a weekend cutover and it is the reason our migrations do not appear on your incident record.

Yes, and that is the usual arrangement. We bring depth in the areas they have not had time to build and we pair deliberately so it stays with them. Our objective is to make ourselves unnecessary on the operational side.

Then they stay. We build hybrid platforms with consistent tooling across both, so your team is not maintaining two entirely separate operational models. Data residency, latency and sunk hardware cost are all legitimate reasons not to move.

Start the conversation

Bring us the cloud engineering problem you have already tried to solve.

Ninety minutes with our engineers. You leave with a systems map, a shortlist and an honest read on whether this is worth doing at all.

What to expect

  • No pitch deck, no obligation
  • Senior engineers in the room
  • A written plan within five days