Reference Architecture

A reference stack, adapted to your platform

We start from proven cloud-native patterns, then adapt the stack to your workload, team, and operational maturity — GitOps, Kubernetes, operators, secrets, observability, and dashboards as version-controlled platform logic.

Core delivery pipeline

Source

GitHub

GitOps

Argo CD

Orchestration

Kubernetes

Database

CNPG

Secrets

Sealed Secrets

Observability layer

Collection

Alloy

Metrics

Prometheus

Logs

Loki

Traces

Tempo

Visualisation

Grafana

This architecture enables developers to deploy new services in minutes through self-service scaffolding — not DevOps tickets. Every component is open-source, CNCF-aligned, and deployed through Argo CD. You own everything from day one.

The Assessment

Reference Architecture

We measure platform debt before we build

Before we encode anything, we identify where engineering time disappears: infrastructure friction, deployment bottlenecks, broken environments, missing ownership, and manual recovery work.

8+h

Per engineer per week

Infrastructure Friction

69% of developers lose 8+ hours every week to inefficiencies — broken workflows, manual provisioning, and tool sprawl. That's a full workday gone because there's no proper DevOps automation in place.

Source: State of Developer Experience Report, Atlassian

50+%

Of engineering teams

Deployment Bottleneck

Over half of engineering teams still deploy less than once a week, and when deployments fail, 15% need more than a week to recover. Manual processes and missing automation turn every release into a slow, fragile event.

Source: Google DORA State of DevOps Report 2025

€30k

Per year per engineer

Lost Productivity

Engineers spend 20–30% of their time fighting infrastructure instead of shipping product. For an EU SaaS team, that's roughly €30,000 in lost output per engineer, every year — money that buys nothing.

Source: McKinsey "Why your IT organization should prioritize developer experience"

Investing €40–80k in a Golden Path — automated pipelines, GitOps, isolated preview environments, and self-service workflows — targets the recurring overhead shown above. When platform friction costs every engineer hours each week, even modest reductions can pay back quickly. The assessment shows where the highest-leverage improvements are before implementation begins.

Talk to Engineer

In Practice

Three Operating Positions

Platform patterns we encode

Application Layer Integration

Isolated Preview Environments

Every PR automatically provisions an isolated, production-like environment — frontend, backend, and infrastructure included. Feature Branch = Environment. The team tests before the merge, not after the failure. The client sees the feature working exactly as it will in production before it touches the main branch.

Infrastructure Layer

Atomic Release Management

Frontend, backend, and infrastructure deployed as a single deterministic unit via GitOps. We eliminate the "Staging Queue" for good — every component versioned and promoted together, without manual drift and without the "which version is running where" headache.

Systems Layer

Full-Context Previews

Preview environments that test real business scenarios — not just UI. Our custom Kubernetes operator for Mailgun provisions test domains automatically: DNS records requested from DigitalOcean, Mailgun configured, environment ready. Real email flows tested at no extra cost, no manual setup.

The documentation is the platform itself.

Every architectural decision lives in version-controlled logic — not in someone's head or a PDF that goes stale. When we're done, your team doesn't need us to understand the system. The code explains itself.

Start with a focused platform assessment

Our first engagement is a paid technical assessment. We map your delivery workflow, infrastructure gaps, platform debt, and implementation priorities before anything is built.