Engineering Case Studies

Engineering Problem: Enterprise application teams were operating across fragmented legacy hypervisors and isolated container clusters, leading to inconsistent security postures, risky maintenance windows during cluster upgrades, and manual day-2 operational toil.

Architecture Summary: Engineered a multi-cluster Red Hat OpenShift 4 platform integrating OpenShift Virtualization (KubeVirt), automated MachineConfigPool (MCP) rolling upgrade gates, multi-tenant RBAC/SCC/NetworkPolicy isolation, full-stack Prometheus/Loki telemetry, and policy-driven Veeam Kasten K10 backup and disaster recovery.

Engineering Problem: Application teams faced multi-day lead times waiting on manual platform-team tickets for namespace provisioning, quota adjustments, RBAC onboarding, and environment creation—creating friction for developers and repetitive toil for platform engineers.

Architecture Summary: Built an Internal Developer Platform using Port as the developer portal and software catalog, wired to automated GitLab/GitOps workflows and OpenShift APIs. Developers request resources through standardized self-service actions that generate validated Helm/Kustomize configurations reconciled by OpenShift GitOps (Argo CD).

Engineering Problem: Shared staging environments suffer from configuration collisions, broken test states, and slow feedback loops when multiple developers test pull requests simultaneously.

Architecture Summary: Architected an end-to-end delivery platform combining OpenShift Pipelines (Tekton) for serverless CI, OpenShift GitOps (Argo CD) ApplicationSets with the Pull Request Generator for per-PR ephemeral namespaces, and Knative Serving for scale-to-zero microservice execution across SNO staging and HA multi-node production.

Engineering Problem: Hard-coded secrets in CI variables, unsigned container images entering clusters, and fragmented visibility into runtime security posture created critical compliance and supply chain risks.

Architecture Summary: Engineered a defense-in-depth security architecture combining HashiCorp Vault and External Secrets Operator (ESO) for runtime secret injection, Harbor private OCI registry with Trivy/Snyk vulnerability scanning, Sigstore Cosign cryptographic image signing, OPA Gatekeeper admission enforcement, and Wiz CNAPP posture monitoring.

Engineering Problem: On-call SRE teams spend excessive hours triaging repetitive Level-1 Kubernetes incidents—such as CrashLoopBackOff pods, OOMKills, image pull errors, and broken Service selectors—while commercial cloud AI tools raise data-privacy concerns for cluster logs.

Architecture Summary: Engineered an in-cluster Autonomous AI SRE Crew using Python and CrewAI orchestrated over a local GPU-accelerated Ollama LLM stack (MicroK8s + NVIDIA GPU Operator), complemented by the K8sGPT Operator and kubectl-ai for continuous cluster diagnostics and self-healing operations.

Engineering Problem: Rapid cloud adoption across business units created snowflake cloud accounts, inconsistent IAM policies, manual Kubernetes cluster builds, and unoptimized infrastructure spend.

Architecture Summary: Engineered modular, reusable Terraform Infrastructure as Code libraries and idempotent Ansible playbooks to automate multi-cloud landing zones (GCP, Azure, AWS), managed Kubernetes fleets (GKE, AKS, EKS), and bare-metal HA RKE2/kubeadm clusters governed centrally through Rancher and GitOps.

Engineering Problem: Stateful applications and high-throughput microservices suffered from fragmented log/metric visibility during incidents and lacked resilient, cloud-native persistent block/object storage on bare-metal and hybrid Kubernetes clusters.

Architecture Summary: Designed and operated a unified observability stack using Prometheus, Alertmanager, Grafana, and Loki alongside self-healing distributed storage platforms powered by external Ceph clusters (provisioned via Ansible) and SUSE Longhorn cloud-native block storage.