Cloud Infra

Telemedicine Infra on Azure

I built a greenfield Azure environment using Infrastructure as Code with Terraform to support remote patient monitoring. The baseline covered network segmentation, private endpoints, key management, and automated backups.

I then implemented a CI/CD pipeline for the mobile app to streamline releases: automated builds, tests, signing, artifact storage, and gated promotions to the stores. The stack follows HIPAA-aligned practices with RBAC, least privilege, encryption in transit and at rest, and audit logging to protect PHI.

Highlights

Azure landing zone: VNets and subnets, private endpoints, Key Vault, backups
Terraform IaC: reproducible environments and reviewable change history
Mobile CI/CD: build → test → sign → staged release with manual approvals
Security baseline: RBAC and least privilege, TLS everywhere, encrypted storage, audit logs
Observability: core logs and alerts for infrastructure and pipeline health

Technologies & tools

Terraform

Azure

Docker

Nginx

GitLab CI/CD

Data Analytics Platform on AWS

I provisioned compute, networking, and storage on AWS, then deployed a multi-node Kubernetes cluster on EC2. The cluster was tuned for heavy ingestion and processing with horizontal scaling and resource quotas to keep workloads stable during bursts.

Prometheus scraped application and node metrics, while Grafana dashboards provided real-time visibility and SLO tracking. The design emphasized fault isolation, rolling updates, and cost awareness.

Highlights

AWS on EC2: VPC, subnets, security groups, Auto Scaling Groups, load balancing
Kubernetes on VMs: multi-node setup with HPA, taints and tolerations, and quotas
Throughput target: approximately five million data points per day with headroom for bursts
Monitoring: Prometheus metrics with Grafana dashboards and alerting
Reliability: rolling deployments, highly available control plane where applicable, backup and restore runbooks

Technologies & tools

Docker

Kubernetes

AWS

Node.js

RabbitMQ

CRM Cloud Migration to GCP

I planned and executed a provider-to-provider migration of a CRM system to GCP. The new foundation was defined in Terraform for consistent and reviewable changes. Workloads were containerized and deployed to GKE with environment-specific configuration and secrets management.

I set up cluster logging, metrics, and alerting to give the operations team clear visibility. Cutover used a staged data sync and a short maintenance window to minimize downtime.

Highlights

GCP build-out with Terraform: networks, IAM, storage, and managed services
GKE deployment: containerized CRM with configuration and secrets per environment
Observability: GKE logging and metrics plus Prometheus exporters and alerting
Migration playbook: staged data sync, verification steps, and a rollback plan
Security and compliance: service accounts with least privilege, encryption at rest and in transit

Technologies & tools

GCP

Terraform

Kubernetes

GitLab