Managed engineering services
Build, operate, and improve your cloud-native platform.
Practical engineering support for Kubernetes, cloud infrastructure, CI/CD, observability and SRE, from the same engineers who design our technical assessments.
Services
What we help with
Scoped to your environment. We tell you plainly what we would change and why.
Kubernetes platform operations
Day-2 operation of production clusters, on cloud or on-premises.
- Cluster health and capacity reviews
- Namespace, RBAC and quota design
- Add-on management (ingress, DNS, storage, certificates)
- Runbooks for your on-call team
Cluster upgrades & lifecycle
Planned, rehearsed upgrades instead of risky jumps across versions.
- Version and API deprecation assessment
- Upgrade rehearsal in a staging cluster
- Node pool rotation and rollback plans
- Post-upgrade validation
Infrastructure as Code
Reproducible infrastructure with Terraform, Terragrunt and Ansible.
- Module structure and state strategy
- Import of existing infrastructure
- Policy checks in the plan stage
- Safe refactoring of live environments
CI/CD & GitOps
Delivery pipelines teams trust, from commit to production.
- GitHub Actions, GitLab CI and Jenkins
- Argo CD or Flux for cluster delivery
- Progressive delivery and automated rollback
- Supply-chain controls for images
SRE, monitoring & incident response
Observability that leads to action, and a calm incident process.
- Prometheus, Grafana, Loki and VictoriaMetrics
- SLIs, SLOs and burn-rate alerting
- Alert noise reduction
- Incident review and follow-up practice
Performance & reliability improvements
Targeted work on the problems costing you incidents or money.
- Right-sizing requests and limits
- Autoscaling design (HPA, cluster autoscaling)
- Resilience to node and zone failures
- Cost visibility for shared clusters
GPU infrastructure & self-hosted LLMs
Run models on infrastructure you control.
- GPU node pools and device plugins
- Model serving and inference autoscaling
- Model rollout and version management
- Capacity and cost planning for inference
AI-assisted operational workflows
Practical use of AI in operations, with engineers in control.
- AI-assisted incident triage and summaries
- Runbook automation with human approval
- Guardrails for tools with cluster access
- Evaluation of results before adoption
Engagement models
Work with us the way that fits
Scope, deliverables and support hours are agreed in writing before work starts.
Consulting & one-time implementation
A defined piece of work: a design review, a migration or a new capability, delivered and handed over.
Project-based engineering
A scoped project with milestones, such as a platform build, CI/CD rework or observability rollout.
Ongoing managed support
Continuing operational support for your platform, with scope and hours agreed up front.
Platform health checks
A structured review of a cluster or platform with prioritised, practical recommendations.
Start a conversation
Tell us about your platform
A few details help us prepare a useful first call. We will reply by email to arrange it.
- A short scoping call to understand goals and constraints.
- A written proposal with scope, approach and estimate.
- Work starts only once you have agreed the proposal.