[For engineering & platform teams]

Infrastructure your team can run without calling us

Cloud bills that climb every month, deployments that need a specific person on hand, and an outage plan that lives in someone's head. We migrate, automate and harden your infrastructure (on AWS, Azure or GCP) and leave you with pipelines, monitoring and documentation your own engineers can operate.

  • Migration to AWS, Azure or GCP with a rollback plan at every step
  • Terraform, CI/CD and Kubernetes set up as code, not clicks
  • Observability, cost control and disaster recovery you can actually test
[Who this is for]

Who this is for

Teams whose infrastructure has become the bottleneck, too slow to change, too expensive, or too dependent on one person.

  1. Businesses still on-premise or on a single server

    The servers work until they don't. Scaling means buying hardware, backups are untested, and the move to the cloud keeps getting postponed because nobody owns it.

  2. Product teams outrunning their infrastructure

    Deployments are manual or fragile, staging drifts from production, and every release is a small event. You need pipelines and environments that keep up with the team.

  3. Regulated or cost-conscious operators

    You are in the cloud already, but the bill is unexplained, access is too broad, and residency, audit and recovery requirements need to be met and evidenced.

[What we build]

Cloud & DevOps services

Each of these can stand alone. Migrations usually pull in infrastructure as code and observability; cost and security reviews often lead to the rest.

  1. Cloud migration (AWS, Azure, GCP)

    Moving workloads from on-premise, a hosting provider or one cloud to another, with the approach chosen per workload: rehost, replatform onto managed services, or refactor where it pays. It applies when hardware is ageing, capacity is limiting growth, or a region change is needed for data residency.

    • Workload inventory and dependency mapping
    • Landing zone with accounts, networking and identity
    • Migration waves with cutover and rollback plans
    • Data migration and validation
  2. Infrastructure as Code

    Every environment defined in Terraform (or Bicep, CloudFormation or Pulumi where it fits), reviewed in pull requests and applied through a pipeline. It applies when environments drift, nobody can rebuild production from scratch, or changes depend on remembering what was clicked.

    • Terraform modules and remote state
    • Environment parity across dev, staging and production
    • Policy checks and drift detection
    • Secrets in a managed vault, never in code
  3. CI/CD pipelines

    Build, test and deploy automation on GitHub Actions, GitLab CI, Jenkins or Azure DevOps, with the deployment strategy (blue/green, canary, rolling) matched to how much risk each service can carry. It applies whenever releases are manual, slow or frightening.

    • Automated test, lint and security scanning stages
    • Artefact versioning and environment promotion
    • Zero-downtime deployment strategies
    • Rollback that is one command, not a meeting
  4. Containers & Kubernetes

    Containerising applications and running them on managed Kubernetes (EKS, AKS, GKE), or on simpler services such as ECS, Cloud Run or App Service when a full cluster is more than you need. It applies when you run many services, need consistent environments, or want to scale by load rather than by guess.

    • Dockerfiles, image hardening and registries
    • Cluster setup, autoscaling and ingress
    • Helm charts or Kustomize for deployments
    • Honest advice when Kubernetes is overkill
  5. Observability & reliability

    Metrics, logs and traces in one place, alerts tied to service-level objectives you set, and on-call runbooks that say what to do at 3 a.m. It applies once uptime matters to customers or contracts, and is best done before an incident rather than after.

    • Prometheus, Grafana, Datadog, CloudWatch or Azure Monitor
    • SLOs, error budgets and alerts that mean something
    • Distributed tracing with OpenTelemetry
    • Incident runbooks and post-incident review
  6. Security hardening, cost optimisation & disaster recovery

    The three reviews most teams put off: least-privilege IAM and network segmentation, a line-by-line look at where the money goes, and backups and recovery that have actually been rehearsed. It applies to any cloud estate that grew organically.

    • IAM, network and encryption baseline against CIS benchmarks
    • Rightsizing, reserved capacity and waste removal
    • Backup schedules, RPO/RTO targets and tested restores
    • Cross-region failover where it is justified
[Alongside the build]

Also part of the engagement

[Technology stack]

Clouds & tooling

  1. Data residency & regional setup

    Deploying into the regions your regulators or customers require (including UAE and other Middle East regions on AWS, Azure and GCP) with data kept where it must stay.

  2. Cloud account & billing setup

    Organisation structure, account separation, budgets, alerts and tagging so cost is attributable from the first month.

  3. Runbooks & documentation

    Architecture diagrams, operating procedures and on-call guides written for your engineers, not for us.

  4. Managed operations

    Ongoing monitoring, patching and support on a retainer, or a clean handover to your team when they are ready.

AWSMicrosoft AzureGoogle CloudTerraformKubernetes (EKS, AKS, GKE)DockerGitHub ActionsGitLab CIJenkinsPrometheus & Grafana
[Our approach]

How we approach cloud work

  1. Your accounts, your code

    Everything is built in cloud accounts you own and defined in repositories you control. If we disappeared tomorrow, nothing would stop working.

  2. Managed before bespoke

    We reach for the managed service before we build a cluster, and for the simple architecture before the impressive one. Complexity has to earn its place.

  3. Tested, not assumed

    Backups are restored, failover is rehearsed and pipelines are exercised before go-live. A recovery plan that has never run is a guess.

[How it works]

What the engagement looks like

  1. 01

    Discovery & assessment

    We inventory your workloads, dependencies, current spend and compliance constraints, and agree what a good end state looks like.

  2. 02

    Target architecture & plan

    A written architecture, migration waves, tooling choices and a cost range, for the project and for the expected monthly run cost.

  3. 03

    Build & migrate

    Landing zone and pipelines first, then workloads in waves with parallel running, validation and a rollback path at each cutover.

  4. 04

    Operate & hand over

    Dashboards, alerts and runbooks in place, your team trained, and either a retainer or a clean handover.

[You own it]

What you receive at the end

Everything runs in accounts you control from the first commit. Ending an engagement is an access change, not a migration.

  • Infrastructure code in your repository
  • Cloud accounts and environments you own
  • CI/CD pipelines with documentation
  • Monitoring dashboards, alerts and SLOs
  • Disaster recovery plan with test results
  • Handover session with your team
[FAQ]

We’ve got the answers you seek

Anything not covered here? Ask us through the contact form and we’ll answer within a working day.

  • Usually the one your team already knows, or the one your regulators and key vendors favour. All three cover the standard needs well; the differences that matter are regional availability, existing licensing (Microsoft-heavy organisations often lean Azure) and specific managed services. We give you a plain comparison for your situation rather than a default answer.

Tell us what your infrastructure looks like today

Where it runs, what the bill is, what breaks. We'll come back within 24 hours with an honest view of what to move first and what it would take.

Trusted by teams across fintech, e-commerce and SaaS

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