Services · Cloud & DevOps
Infrastructure as a discipline.
Trust is an engineering discipline — and nowhere is that more literal than the platform your product runs on. Mokshify designs and operates cloud architecture across AWS, Azure, Oracle Cloud and Google Cloud, with infrastructure as code and a release pipeline that treats every deploy as a tested, reviewed, reversible event.
What we do
Cloud architecture — AWS, Azure, OCI, GCP
Network design, compute and storage selection, managed data services, secrets and identity — designed for the product you have and the growth you're planning, not a reference diagram. We're deliberately multi-cloud: the right provider is usually decided by your team's experience, your market's regions and your pricing, and the architecture should survive changing that decision.
Infrastructure as code — Terraform
Every environment we build is declared in Terraform: reviewable, repeatable, destroyable. Staging is a plan-apply away from production parity, and "how is this configured?" is a file you can read, not an archaeology project.
Containers and Kubernetes
Workloads run in Docker containers; Kubernetes enters when service count, scaling granularity or multi-environment operations justify it. We are equally comfortable telling you Kubernetes is premature — the lightest platform that works wins.
CI/CD — GitHub Actions with an AI review gate
Our pipeline standard on every project: tests and static checks on each merge, an AI review pass over the change, then staged rollout with health checks and instant rollback. The deploy terminal in our homepage film isn't decoration — it's our actual release sequence: build ✓ · tests passed · ai review ✓ · cloud sync ✓ · api live.
Observability and operations
Uptime, latency and error budgets on dashboards; alerts that mean something; logs you can query. The systems we run for clients report 99.98% uptime — a number we publish because we measure it.
Engagement shapes
- Foundation build — a new product's platform: accounts, networks, IaC, pipeline, monitoring. Usually inside an MVP Sprint.
- Audit and rescue — an existing setup that's fragile, expensive or opaque: we audit, stabilise, then improve in stages while it keeps serving users.
- Embedded platform engineering — ongoing DevOps capacity inside your team through the Dedicated Team model.
Proof, not promises
Every product in our portfolio — FinCalix, Medico Diagnostics, Terravion Properties, SkillForceHub — runs on this platform architecture: containers, IaC, pipelines with AI review, PostgreSQL and Redis, Nginx at the gateway.
Common questions
Which cloud should my product run on?
Usually the one your team, regions and pricing favour — architecture matters more than the logo. We design with portability in mind: Terraform, containers, managed Postgres.
Do I need Kubernetes?
Not always. It earns its complexity with many services and fine-grained scaling. Early products often do better on simpler container platforms with a clean migration path — we'll say so.
What does your CI/CD look like?
GitHub Actions: tests + static checks + AI review per merge, staged rollouts, health checks, instant rollback. Nothing is deployed by hand.
Can you take over an existing setup?
Yes — audit first (architecture, cost, security, releases), stabilise, then improve in stages without downtime.
How do you control cloud costs?
Right-sizing from measurements, bounded autoscaling, storage lifecycle rules, cache-first design, and per-service cost visibility so anomalies surface in days.
Cloud bill scary? Deploys scarier?
Send us a description of your current setup — or the product you're about to build. We'll reply within 24 hours with an honest first step.
Related: SaaS Development · AI Product Development · Our process · Client work