SDLC & Cloud Architecture
Modern software delivery on Azure and AWS — from clean architecture patterns to cloud-native microservices, Infrastructure as Code, and GitOps workflows that ship with confidence.
Modern Cloud SDLC
A continuous loop of planning, building, securing, deploying, and monitoring — all automated and observable.
Plan
Azure Boards, Jira, threat modelling, architecture review
Code
Feature branches, PR reviews, SAST in IDE, pre-commit hooks
Build
Docker multi-stage builds, versioned artifacts, SBOM generation
Test
Unit, integration, DAST, performance, chaos engineering
Release
Semantic versioning, changelogs, release notes automation
Deploy
Blue/green, canary, GitOps with ArgoCD/Flux, zero-downtime
Operate
SRE practices, runbooks, incident response, on-call rotation
Monitor
Azure Monitor, Datadog, distributed tracing, cost observability
Azure Cloud Services
Azure is my primary cloud platform. I architect solutions using a combination of PaaS services, containers, and serverless — always choosing the right service for the job, not the most complex one.
Managed Kubernetes for container orchestration at scale
Serverless compute for event-driven microservices
Enterprise messaging for decoupled async communication
Globally distributed multi-model NoSQL database
Centralized secrets, keys, and certificate management
Gateway for publishing, securing, and versioning APIs
AWS Cloud Services
AWS architecture experience spanning container orchestration, serverless functions, event-driven messaging, and managed data services — with a focus on cost-optimized, resilient patterns.
Elastic Kubernetes Service for managed container workloads
Serverless functions triggered by events and HTTP requests
Fully managed message queuing and pub/sub notifications
Single-digit millisecond NoSQL with on-demand scaling
REST and WebSocket API management at scale
Lifecycle management for secrets, credentials, and API keys
Terraform & Bicep
Infrastructure as Code is the practice of managing and provisioning cloud infrastructure through version-controlled definition files — not manual clicks. Every resource, network rule, and policy lives in Git.
Terraform
Multi-cloud, provider-agnostic. Use for Azure + AWS environments. HCL syntax, state management, modules.
Bicep
Azure-native IaC. Cleaner syntax than ARM templates, first-class Azure integration and type safety.
Use Terraform Workspaces + remote state in Azure Storage Account with state locking via Azure Blob leases. Store Terraform plans as artifacts and apply only reviewed plans — never run terraform apply directly in CI without a plan review step.
GitOps with ArgoCD & Flux
GitOps is the practice of using Git as the single source of truth for both application code and infrastructure. The cluster continuously reconciles its actual state to match the desired state declared in Git.
Developer pushes to Git
A developer merges a PR with updated Kubernetes manifests or Helm chart values into the deployment repo.
GitOps Operator detects drift
ArgoCD or Flux continuously polls (or receives webhooks) and detects that the cluster state differs from Git.
Automated reconciliation
The operator applies the diff to the cluster. No humans SSH into the cluster. All changes are auditable via Git history.
Drift detection & alerting
Any manual change to the cluster is immediately detected as drift. Alerts are sent and drift is automatically corrected.
Cloud Architecture Patterns
Microservices
Decompose applications into independently deployable services. Each service owns its data, exposes an API, and can be scaled independently. Use bounded contexts from DDD.
Serverless First
Prefer managed serverless services (Azure Functions, AWS Lambda) for event-driven, bursty workloads. Pay-per-execution with zero infrastructure management overhead.
CQRS + Event Sourcing
Separate reads from writes. Store state changes as immutable events. Replay events to reconstruct state. Use Azure Service Bus or Kafka as the event backbone.
Strangler Fig
Incrementally migrate legacy monoliths to microservices using the Strangler Fig pattern. Route traffic gradually from the old system to the new using Azure API Management or AWS API Gateway.
BFF Pattern
Backend For Frontend — create dedicated API aggregation layers for each client type (web, mobile, third-party). Reduces over-fetching and simplifies mobile client code (key for React Native and MAUI apps).
Chaos Engineering
Deliberately inject failures to test resilience. Use Azure Chaos Studio or AWS FIS. Start with hypothesis-based experiments in staging before applying to production.