Cloud & DevOpsStatus: Lab & Infrastructure ProjectTimeline: 2024

Cloud Infrastructure & CI/CD Deployment Labs

Containerized environments, automated testing workflows, and Terraform infrastructure experiments

Source Code Repository✓ Automated end-to-end pipeline build and test verification in under 3 minutes.

TECHNOLOGY STACK

DockerDocker ComposeGitHub ActionsTerraform (Labs)LinuxNginx

SYSTEM DESIGN & RUNTIME SIMULATION

Interactive Architecture & Pipeline Inspector

INTERACTIVE SYSTEM ARCHITECTURE STUDIO

Klinik Voice Intake & Triage Pipeline

Real-time stateful voice agent architecture with deterministic clinical triage routing

PATTERN: Async WebSockets + LangGraph State Machine

Sub-850ms audio-to-triage turnaround with zero hallucinated diagnoses

SYSTEM EXECUTION PIPELINE (TAP ANY NODE TO INSPECT)

STEP 0118ms

Audio Ingest Stream

Client Microphone Feed

WebSocket / 16kHz PCM

STEP 02240ms

Speech-to-Text Pipeline

Whisper Transcription Core

gRPC Streaming

STEP 03320ms

LangGraph State Machine

Clinical Decision Graph

Python / Async Graph Loop

STEP 048ms

Pydantic Schema Guard

Deterministic Validation

Zod / Pydantic V2

STEP 0565ms

EMR & Dispatch Gateway

Clinical Record Persistence

HTTPS / REST FHIR

STEP 01 OF 05WebSocket / 16kHz PCM

Audio Ingest Stream

Role: Client Microphone Feed

ARCHITECTURAL ROLE & BEHAVIOR

Captures spoken patient audio chunks in real-time over bi-directional duplex WebSockets with voice activity detection (VAD).

ESTIMATED LATENCY: 18ms•TRANSPORT: WebSocket / 16kHz PCM

THE CORE PROBLEM

Discrepancies between local development environments and cloud hosting lead to deployment failures and unrepeatable configurations.

WHAT I BUILT & DELIVERED

Built multi-stage Dockerized environments for backend services, automated test runners with GitHub Actions, and authored declarative Terraform configurations for reproducible cloud resource provisioning.

MY SPECIFIC ROLE & CONTRIBUTION

Wrote multi-stage Dockerfiles optimizing image layer caching, designed CI/CD workflows running automated linting and tests on PR merges, and configured reverse proxies with Nginx.

Architectural Breakdown

1Multi-stage Docker builds reducing final container sizes from 1.2GB down to 140MB
2GitHub Actions workflow matrix executing unit tests across Node.js versions
3Nginx reverse proxy configuration handling SSL termination and rate limiting
4Terraform lab manifests provisioning modular cloud VPCs, subnets, and storage buckets

Key Engineering Decisions & Rationale

Multi-stage Docker caching

Separating build dependencies from runtime environments trimmed deployment bandwidth and closed security attack vectors.

Challenges & Trade-offs

•Documented as an active learning lab to demonstrate infrastructure-as-code principles without claiming multi-region enterprise Kubernetes production ownership.

What I Learned

✓Immutable infrastructure practices eliminate 'works on my machine' debugging cycles.
✓Clear healthcheck endpoints are mandatory for orchestrators to handle rolling zero-downtime restarts.

Interested in similar architecture for your team?

Let's evaluate your current requirements and engineering constraints.

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