Service Pillar 02 of 06

The platform layer your engineering org actually trusts.

We build production-grade Kubernetes platforms, infrastructure-as-code from day zero, and observability that pages the right team — not everyone. Healthcare, finance, telecom workloads at five-nines targets. No hand-rolled snowflakes.

What we do

The full platform stack — designed, shipped, and operated. Every capability listed below is something we've taken from blank-slate to production for a regulated enterprise.

Kubernetes platform engineering

Multi-cluster federation, GitOps via ArgoCD/Flux, golden-path Helm charts, namespace-as-tenant isolation. Hardened against CIS benchmarks. Kyverno/OPA policy guardrails enforced at admission.

Heavy containerization

Docker → distroless → secure base images. Multi-stage builds, SBOM generation, signed images via Cosign. Build-time vulnerability scanning that fails the pipeline, not the engineer's morale.

Terraform & infrastructure-as-code

Module-based composition, drift detection, state management at scale (Terraform Cloud, Spacelift, or Atlantis). Atlantis-style PR workflows so infra changes get the same review rigor as application code.

CI/CD & release engineering

GitHub Actions, GitLab CI, CircleCI — pipelines built for trunk-based development, progressive delivery, and instant rollback. Canary and blue/green deploys orchestrated by Argo Rollouts or Flagger.

Observability that pages correctly

Prometheus + Grafana + Loki + Tempo (or the Datadog/New Relic equivalent). SLI/SLO definitions tied to business outcomes. Burn-rate alerting so on-call doesn't get woken up by a single retry.

Production reliability engineering

Error budgets, postmortem culture, chaos engineering with Litmus or Gremlin, capacity planning, runbook automation. The operational discipline that turns a fragile system into a calm one.

How an engagement runs

Four phases. No surprises. Every phase ends with a deliverable you can take in-house if you choose to part ways.

PHASE 01

Assess

Two-week deep dive. We read your code, talk to your engineers, audit your infra. Output: a written report on what's working, what's load-bearing-but-fragile, and where the leverage is.

PHASE 02

Design

Reference architecture document, RFC-grade. Tradeoff matrix. Cost projections. Migration path with rollback at every step. Reviewed by your senior engineers before a single line of new code.

PHASE 03

Implement

Embedded engineering. We work in your repos, on your branches, in your standups. Pair-programming with your engineers so the knowledge transfer happens in real time, not in a closing-out doc.

PHASE 04

Operate

30/60/90-day operate-with engagement. Your team takes the pager; we sit shadow-on-call. By day 91 you don't need us — and we leave the runbooks, dashboards, and the team confidence that you don't.

Technologies in our daily kit

Tooling we use in production every week. Not a marketing matrix — these are what's actually running on the engagements we ship.

Kubernetes
Docker
Terraform
Pulumi
ArgoCD
Flux CD
Helm
Kustomize
Istio
Linkerd
Cilium
Prometheus
Grafana
Loki
Tempo
OpenTelemetry
Datadog
PagerDuty
Vault
Cosign
OPA / Kyverno
Falco
Trivy
Crossplane
Backstage

Selected work

Three representative engagements. Names anonymized; outcomes verifiable on request under NDA.

Healthcare HIPAA K8s migration

Lift-and-shift to a HIPAA-compliant K8s platform — Fortune 500 health system

Problem
340 microservices on aging VMs across two data centers. Quarterly audit findings on patch latency. Deploys took 4–8 hours and required ops team weekends. Zero immediate observability into PHI access paths.
Approach
EKS-on-AWS landing zone with Vault-backed secrets, OPA admission policies, audit-log streaming to immutable S3, and Argo Rollouts canary delivery. Phased migration: lowest-risk services first, PHI-touching services with red-team review.
Outcome
Deploy time 4hr → 12min. Audit findings on patch latency cleared in next cycle. Two engineers freed up from manual operations. PHI access auditing now answers compliance queries in seconds, not days.
Finance PCI DSS Multi-region

Real-time fraud platform — Tier-1 payments processor

Problem
Single-region fraud-detection stack hitting capacity ceilings during peak holiday traffic. Failover untested, RTO unknown. Deployments paused for 6 weeks each year for "freeze season."
Approach
Active-active multi-region GKE deployment. Kafka mirror-maker for cross-region event consistency. Chaos engineering practice introduced — quarterly failover drills with executive sign-off. PCI DSS scope re-audited with reduced cardholder-data environment surface.
Outcome
99.99% availability hit four quarters running. Holiday freeze eliminated — last year's peak season included six production deploys. Annual PCI audit time cut from 4 weeks to 9 days.
Telecom 5G Core 10⁹ events/day

OSS observability rebuild — global Tier-1 telecom operator

Problem
Network operations center drowning in alerts — 40,000+/day, ~95% noise. Real outages getting buried. Mean time to detect (MTTD) regressed quarter over quarter for two years.
Approach
SLI/SLO-based alerting layer on top of existing Prometheus/Thanos. ML-driven alert clustering (we'll talk about the model on call). Burn-rate-based pages only. Customer-impact correlation built directly into the alert payload.
Outcome
Pages-per-day 40k → ~80, all actionable. MTTD dropped 67% over two quarters. NOC headcount reallocated from triage toward platform improvements. Three quarters of zero customer-impacting outages.

Need this for your platform?

A 30-minute call, a senior architect, no slides. We'll tell you within the first conversation whether this is something we'd ship well.