What we do
The disciplines and practices we bring across engagements. We are deliberately specialist - Kubernetes-native platform engineering, observability, reliability, and the infrastructure underneath production AI inference - rather than a generalist consultancy.
Capabilities describe what we do. To see how we work with you (durations, structures, deliverables), see our engagement formats.
Core capabilities
Each has its own page covering our approach, typical workstreams, and results.
Platform Engineering
Internal Developer Platforms, GitOps operating models, self-service infrastructure, and the operating model that lets a platform team scale without becoming the bottleneck.
Read more →Kubernetes
Enterprise EKS and GKE estates: architecture, multi-cluster governance, security hardening, autoscaling, and the operational disciplines that keep large estates reliable.
Read more →Observability
Telemetry architecture, SLO frameworks, alerting redesign, and observability cost optimisation - stack-agnostic across commercial and open-source platforms.
Read more →Infrastructure as Code
Terraform and Terragrunt at enterprise scale: module design, state management, PR-driven workflows, drift detection, and keyless authentication.
Read more →Supporting capabilities
Disciplines we bring across engagements but do not sell as standalone offerings. Each shows up as a workstream within Assessment, Transformation, Reliability Engineering, or AI Platform engagements.
CI/CD & GitOps
Pipeline design, GitOps operating models, Kubernetes-backed ephemeral runners, and deployment automation. Migration from legacy CI to modern platforms.
Cloud Platforms
AWS and GCP delivery experience. Landing zones, account vending, cost optimisation, and multi-cloud strategy where it makes sense - not for its own sake.
Security & Compliance
Admission-time policy enforcement (OPA, Kyverno), secrets management, identity and access controls, and regulated environments including PCI-DSS.
AI Inference Platform
Production-ready Kubernetes foundations for inference workloads - GPU governance, deployment patterns, latency-aware reliability, and cost attribution.
Engagement details →Developer Experience
Golden paths, self-service workflows, opinionated infrastructure modules, and the patterns that reduce friction between application teams and the platform.
Cost Optimisation & FinOps
Workload right-sizing, spot instance consolidation, observability cost reduction, and unit economics for platform spend - delivered as part of broader engagements.
Not sure where to start?
If you're trying to match a capability to a way of buying, our engagement formats are the place to look. Or just get in touch.