Building and Scaling a Platform with Project-as-a-Service

2026-06-11 · Source: InfoQ · Field: Technology & Digital — Cloud Computing & IT Infrastructure, Software Development & Engineering, Platform Engineering · Depth: Intermediate, extended

Summary

The Dutch Tax Authority (Belastingdienst) evolved its platform strategy from total developer autonomy to a "Project-as-a-Service" (PaaS) model. Initially, in 2017, they built an OpenShift proof of concept, aiming for developers to manage the entire lifecycle. By 2019, this led to high cognitive load and knowledge fragmentation ("Wild West") for newer teams, with 99+ DevOps teams solving similar problems differently. They shifted to an enablement-over-support philosophy, introducing an open-source PaaS operator that allows teams to create complete Kubernetes environments with a single YAML file, including namespaces, RBAC, and resource quotas. This automation-first approach, combined with a "Golden Path" of standardized guidance, Communities of Practice, Container User Groups, Containerization Days, and Accelerator Hackathons, aims to reduce cognitive load and increase standardization. The platform currently supports over 80 teams and 160 applications across 78 OpenShift clusters with 900+ worker nodes, and plans include deeper Backstage integration and AI-driven ChatOps for support.

Key takeaway

For Platform Engineers or DevOps Leads struggling with scaling developer onboarding and inconsistent environments, you should prioritize shifting from pure support to an enablement model. Implement an automated "Project-as-a-Service" (PaaS) solution to standardize environment provisioning and reduce developer cognitive load. Foster knowledge sharing through communities and hands-on programs like hackathons, ensuring your "golden path" makes the right way the easiest way. Consider AI integration for streamlining repetitive support tasks.

Key insights

Shifting from full developer autonomy to a "paved road" with Project-as-a-Service reduces cognitive load and increases standardization for platform adoption.

Principles

• Enablement over support builds self-sufficient teams.
• Standardization is crucial for platform adoption at scale.
• A platform is an ecosystem of infrastructure and enablement.

Method

Implement a Project-as-a-Service operator for automated environment provisioning via YAML, supported by a "Golden Path" of guidance, Communities of Practice, and AI-driven ChatOps.

In practice

• Automate environment creation using a PaaS operator.
• Conduct Accelerator Hackathons for rapid app onboarding.
• Implement AI-driven auto-answers for ChatOps support.

Topics

• Platform Engineering
• DevOps
• Kubernetes
• Project-as-a-Service
• Developer Enablement
• AI Integration

Code references

• belastingdienst/opr-paas

Best for: CTO, VP of Engineering/Data, AI Architect, DevOps Engineer, Software Engineer, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by InfoQ.