The context
A deployment manifest is only part of an operating system. Teams also need to understand identity, persistence, recovery and what has actually been tested.
My platform packages cover GitOps, certificates, DNS, load balancing, autoscaling, observability, highly available databases, runtime security and cost governance.
My contribution
Published Kubernetes manifests, Helm charts, Terraform and OpenTofu modules with architecture notes and operations runbooks.
Derived observability packages from a live Fabric and TreeTracker deployment. Isolated-cluster validation covered metrics collection, 15 Grafana dashboards, log ingestion, alert handling and persistence across pod restarts.
Built infrastructure packages spanning AWS, Oracle Cloud and bare-metal Proxmox. Database packages use three-member high-availability topologies.
Engineering decisions
01. Document the validation boundary
Packages record validation evidence alongside remaining production acceptance criteria. A successful local check does not establish production readiness.
02. Start with operating experience
The observability work grew from a running Fabric and TreeTracker stack. Storage, identity and recovery requirements are part of the package.
03. Keep infrastructure reviewable
Declarative configuration and runbooks make the operating assumptions visible to the next person who uses the code.
The outcome
A reusable body of platform engineering work with source, architecture and operating guidance. Readers can inspect both the implementation and the limits of its validation.
Tools & evidence
Validation is package-specific. Isolated-cluster checks are not a claim of production acceptance for every package.