Cloud & DevOps services
you won't rewrite in eighteen months.
Cloud architecture, Kubernetes platforms, CI/CD, observability, cost governance, and production support. Built as code, documented as code, and operable by your team without us.
Cloud as engineering, not rebranded sysadmin.
Cloud and DevOps decide whether your software is a product or a ceremony. We build infrastructure that's reproducible from code, observable by default, recoverable under pressure, and cheap enough that no one asks you to justify the bill twice a quarter.
Our teams ship across AWS, GCP, and Azure, run Kubernetes at real scale, and treat on-call as a first-class product concern. We document the runbooks, the decision logs, and the cost model so your team can own what we build long after the engagement ends.
Shipped under this discipline.
A sample of projects where this capability was load-bearing. We omit client names by default and share them under NDA when you want to dig into a specific engagement.
Logistics · United KingdomSangfroid Group: connected maritime operations.
Voyage planning, crew, equipment and commercial records in a connected operational platform.
React · TypeScript · FastAPI · PostgreSQL · Google Cloud
Finance · AustraliaPaylink: connected commerce for Australian SMBs.
SMBs get paid, pay bills and reconcile from one app instead of four tools.
Flutter · Flask · PostgreSQL · AWS
Retail · AfricaFrontir: emerging-markets research.
Research clients access representative panels in markets that were previously unreachable.
React · Redux · PHP · Slim
HRLendora: staff rostering and appointments without the spreadsheet.
Staff and appointments are scheduled from one place instead of spreadsheets.
Django · AWS · Python · jQuery
ManufacturingGeopulse: Operations platform.
A web app for operations, built with React, Flask, GCP and Python. Core workflows, records and reporting run through one validated data model that non-technical staff operate day to day.
React · Flask · GCP · Python
RetailOrdermint: E-commerce platform.
A web app for online retail, built with Django, AWS, Python, jQuery and Bootstrap. Catalogue, inventory, checkout and fulfilment run off one backend, so what shoppers see is always what the business can actually sell.
Django · AWS · Python · jQuery
EducationEquivoice: Education platform.
A web app for online learning, built with Wagtail, AWS, Python and AWS SES. Courses, submissions, grading and progress live in one platform that learners return to and instructors run without technical help.
Wagtail · AWS · Python · AWS SES
The work that turns a cloud account into a platform.
Most engagements combine two or three of these. Usually an IaC foundation, a CI/CD platform, and an observability stack together. We scope the mix during discovery.
Cloud architecture and migration.
A cloud foundation you won't have to redo in a year. New-build foundations on AWS, GCP, or Azure, or migrations off a legacy data centre or another cloud, with well-architected reviews, landing zones, network design, security posture, and a clear cost envelope.
Kubernetes platform engineering.
Kubernetes your team can operate, not just stand up. Production-grade clusters on EKS, GKE, AKS, or self-managed, multi-tenant, with GitOps via Argo CD or Flux, service mesh where it earns its keep, and PDBs and HPAs that match traffic.
CI/CD pipelines.
Ship faster and safer, with a pipeline people trust. End-to-end pipelines in GitHub Actions, GitLab CI, CircleCI, or Jenkins, with build caching, test parallelism, ephemeral review environments, progressive delivery, and release notes that aren't fiction.
Observability and SRE.
Know something's wrong before your customers tell you. Metrics, logs, and traces across the stack with Datadog, New Relic, Grafana, or a fully open-source path, with SLOs that map to business outcomes, alerts that fire on signal not noise, and on-call rotations your team can live with.
Cost governance and FinOps.
Cut the cloud bill without cutting reliability. Cost allocation tags, budgets, anomaly alerts, reserved-capacity plans, and right-sizing — we routinely cut 25 to 40% of monthly cloud spend in the first engagement without touching reliability.
Security and compliance.
Pass the audit and sleep at night. IAM design, secrets management, supply-chain controls, vulnerability scanning, and audit trails, configured to match SOC 2, ISO 27001, PCI, or HIPAA with evidence artefacts your auditors will accept.
Scoping cloud & DevOps? Get an engineer's read on your build in 30 minutes — no sales pitch, no decks.
Start a projectThe platform stack we ship with.
Tool choice follows the problem and the team's comfort. The tools our engineers know deeply enough to debug at 3am:
Pick the engagement model
that fits the commitment.
The same cloud & DevOps work ships under any of these three commercial shapes. The difference is in how you hold us accountable and how you scale up or down.
Run AI workloads in your own cloud.
Private model endpoints on Azure, AWS Bedrock or Vertex AI, capacity for open models, and the tracing and cost controls AI workloads need in production.
Explore AI developmentCloud and DevOps questions we hear most.
Can't find what you're looking for? Email hello@cloudini.co and we'll reply within one working day.
We're fluent in AWS, GCP, and Azure. Most of our engineers carry multiple associate or professional certifications. We start from where you are rather than pushing a preferred cloud. Multi-cloud goes in only when it solves a specific problem, not as an end in itself.
Migrations follow a rehost-replatform-refactor framework, applied workload by workload rather than as one big move. We always start with a well-architected review and a dependency map, then migrate in small, reversible increments. Each workload is proven in the new environment before the old one is retired.
Yes. We regularly inherit legacy cloud estates built by previous vendors or in-house teams. The first four weeks are a clean-up. IaC-ify what isn't. Document what is. Kill the orphaned resources. Fix the critical security gaps. Only then do we add new capability.
We only propose Kubernetes when the workload justifies it. Most teams don't need it. When we do use it, we keep the platform boring. Managed control plane (EKS / GKE / AKS), GitOps with Argo CD or Flux, a narrow set of well-understood add-ons, documented runbooks. No artisanal Helm charts that only one engineer understands.
We can set up on-call from day one. PagerDuty or Opsgenie rotation, severity runbooks, escalation paths, post-incident review process. We can also share the on-call load with your team or take it off your hands entirely under a dedicated-team or ODC engagement.
Cloud cost work starts with visibility. Cost allocation tags, service-level attribution, and a baseline. From there we right-size, enable auto-scaling where it helps, shift to spot or savings plans for predictable workloads, and flag waste that's often 20 to 40% of the bill. We set budgets and anomaly alerts so new waste gets caught within days.
Our journey with them has been nothing short of exemplary, far exceeding our initial expectations.
Let's build from here.
Thirty minutes with an engineer who builds. No sales, no drip campaign. If we're the wrong fit we'll tell you and point you somewhere better.