White Park

Services

DevOps, SRE, Cloud & AI Engineering

Five disciplines, one senior team — from a first product version through production infrastructure and the pager that comes with it.

01

MVP

Web & Mobile

Product engineering for teams shipping a first version — web and mobile applications built to hold up under real users, not just a demo.

What this covers

  • Product scoping and technical architecture from a blank slate
  • Web application development (React / Next.js)
  • Mobile application development (React Native, and native where needed)
  • API and backend design built to extend past the first release
  • Authentication, payments and third-party integrations
  • Design handoff to production-ready UI

What you get

  • A production-deployed web and/or mobile application
  • Documented architecture and a codebase ready for an in-house team
  • A CI/CD pipeline for ongoing releases

Who it's for

Founders and product teams building a first version who need it to work under real users, not just survive a demo.

Stack

Next.js · React Native · TypeScript · PostgreSQL · Node.js

02

Scaling

DevOps & Platform Engineering

Infrastructure, CI/CD and internal tooling that let a small team ship fast without breaking things. We build the platform underneath the product.

What this covers

  • CI/CD pipeline design and automation
  • Containerization and Kubernetes orchestration
  • Internal developer tooling and self-service platforms
  • Infrastructure as code (Terraform)
  • Environment and release management — staging, canary, blue-green
  • Secrets management and access control

What you get

  • A CI/CD pipeline from commit to production
  • Infrastructure defined and version-controlled as code
  • Runbooks for common operational tasks

Who it's for

Teams past their first deploy who are shipping often enough that manual releases and infrastructure drift have started to hurt.

Stack

Kubernetes · Docker · Terraform · GitHub Actions · ArgoCD

03

Cloud

Cloud Infrastructure

Architecture and provisioning across AWS, GCP and Azure — networking, compute, storage and cost, designed to be reproducible and owned in code.

What this covers

  • Cloud architecture design across AWS, GCP and Azure
  • VPC, networking and IAM design
  • Compute and storage provisioning, right-sized for actual load
  • Cost optimization and usage auditing
  • Multi-region and disaster-recovery setup
  • Migration off a single provider or off bare metal

What you get

  • Reproducible infrastructure-as-code modules
  • Documented network and access architecture
  • A cost baseline and optimization plan

Who it's for

Product teams whose cloud footprint or bill has outgrown ad-hoc console changes.

Stack

AWS · GCP · Azure · Terraform · Kubernetes

04

AI

AI & GPU Infrastructure

Applied AI systems and the GPU infrastructure they run on — model serving and inference pipelines, and the training and orchestration layer beneath them.

What this covers

  • Model serving and inference pipeline design
  • GPU cluster provisioning and orchestration
  • Training pipeline setup and orchestration
  • LLM application and RAG pipeline engineering
  • Cost and latency optimization for inference at scale
  • Vector database and embedding infrastructure

What you get

  • A deployed inference/serving pipeline
  • GPU infrastructure provisioned and orchestrated as code
  • Monitoring for latency, cost and model performance

Who it's for

Teams shipping an AI feature or product who need the infrastructure underneath it to be reliable and cost-aware, not a notebook running in production.

Stack

PyTorch · vLLM · Kubernetes · NVIDIA GPUs · Terraform

05

Reliability

Observability · SRE · Support

Monitoring, alerting and incident response for systems already in production. We keep what's built running, and improve it under real load.

What this covers

  • Monitoring and alerting setup — metrics, logs, traces
  • On-call rotation design and incident response process
  • SLO/SLA definition and error-budget tracking
  • Postmortems and reliability improvement roadmaps
  • Load testing and capacity planning
  • Production support and pager coverage

What you get

  • A monitoring and alerting stack tuned to real failure modes
  • Documented incident response runbooks
  • An ongoing production support arrangement

Who it's for

Teams with something already in production who need fewer surprises and faster recovery when something breaks.

Stack

Prometheus · Grafana · OpenTelemetry · PagerDuty · Datadog

See it in production — the WorkStack case study.

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