Platform engineering01
Make the right path the easiest path.
Kubernetes foundations, GitOps delivery, policy boundaries and developer-facing infrastructure primitives.
Senior Infrastructure Engineer · Germany
Andrey Lesnikov
Infrastructure
that runs itself.
Cloud-native platforms, governed AI infrastructure and resilient systems — designed to stay calm when production gets loud.
Control plane
one plane · three loops
LOOP 01 · REHEARSALapproved
- Change
- Model
- Rehearse
- Gate
- Verify
LOOP 02 · RUNTIMErouted
- Request
- Policy
- Route
- Serve
- Observe
LOOP 03 · HEALINGrecovered
- Detect
- Diagnose
- Act
- Verify
01
Engineering principle
Complexity belongs behind the interface.
The platform can be sophisticated underneath. The experience should still feel calm, legible and predictable — for developers, operators and the business.
AI infrastructure02
Govern every request, not just the model.
Routing, identity, MCP policy, inference, observability and cost evidence as one execution plane.
Reliability systems03
Restore should be proved, not assumed.
Recovery Contract — protect, validate, restore, and prove with a binary PROVED / UNPROVED verdict.
02
Selected systems
Eight repositories. Eight different kinds of proof.
Platform systems across AI infrastructure, control planes, reliability, and GitOps — each verified in CI on kind, minikube, or Compose labs.
01 / Architecture Rehearsal
Test the architecture
before production does.
Deterministic failure rehearsal for architectural assumptions, policy gates and evidence chains.
View case ↗REHEARSAL / 04approved
argo-presync · netpol-cut
BLOCK
02 / TwinOps Control Plane
Treat industrial twins
like infrastructure.
GitOps control plane for industrial digital twins — compose, detect drift, reconcile, replay incidents.
View case ↗TWINOPS / CONTROLsynced
kit streamlive
gitopssynced
03 / AI Runtime Platform
Every AI request
passes through policy.
OpenAI-compatible gateway, MCP governance, KServe/vLLM, KEDA, OIDC, Redis and OpenTelemetry.
View case ↗AI RUNTIME / GATEpolicy on
identityoidc
e2e21.5s
verdictallow
Govern private AI as a platform product.
Policy, identity, audit, intent, MCP, FinOps and SLOs as one operating model.
View case ↗Detect. Recover. Verify. Then trust.
Failure injection, bounded remediation loops and chaos-driven platform validation.
View case ↗Argo CD vs Flux as an operating model duel.
Side by side on kind, with an N=3 CI benchmark of ready, self-heal and recovery times.
View case ↗Don't count CVEs — predict where they can reach.
SBOM, VEX, runtime presence and exposure into ALLOW / WARN / QUARANTINE / BLOCK — incomplete inventory stays UNKNOWN.
View case ↗Restore proved before the incident.
PROTECT → VALIDATE → RESTORE → PROVE on kind with binary PROVED / UNPROVED and fail-closed recovery-point skew.
View case ↗Recognition
Cloud Native Rockstars 2026
Professional recognition is useful when it points back to real systems, real constraints and work that holds up under scrutiny.
Open proof page ↗
Available for meaningful infrastructure conversations