Cloud, DevOps & AI Infrastructure Consulting

Practical AWS architecture, automation, reliability, and AI infrastructure guidance backed by hands-on engineering experience.

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Professional Summary

Senior Cloud Platform Engineer with more than 20 years of enterprise infrastructure experience across federal environments, specializing in AWS cloud engineering, DevOps automation, platform reliability, Infrastructure as Code, containerized deployments, CI/CD, observability, and AI infrastructure. Proven ability to modernize complex systems, lead technical teams, strengthen operational resilience, and build secure, production-ready platforms that connect engineering execution with business outcomes.

About the Portfolio

Hands-on cloud, DevOps, and AI platform projects showcasing production deployments, Dockerized architectures, CI/CD automation, observability systems, SaaS-ready application design, Linux operations, AWS cloud engineering, and modern infrastructure workflows.

☁️

AWS & Cloud Infrastructure

Deploying and managing cloud infrastructure in live production-style environments.

⚙️

DevOps & Automation

Building CI/CD pipelines, Dockerized deployments, Nginx reverse proxies, Linux services, and repeatable operational workflows.

🧠

AI-Powered Platforms

Designing AI-driven operational tools, executive dashboards, infrastructure intelligence systems, and SaaS-ready software platforms.

FREE CLOUD & AI READINESS ASSESSMENT

How Ready Is Your Business for the Cloud?

Answer a few practical questions and receive an instant readiness score with focused recommendations for cloud infrastructure, automation, monitoring, security, and AI adoption.

0 of 8 answered

1. Where does your primary application or workload run today?

2. How is infrastructure currently created and changed?

3. How are application deployments handled?

4. How strong is your monitoring and alerting?

5. How are backups and recovery handled?

6. How mature are your security controls?

7. Are containers part of your deployment model?

8. What is your current AI adoption level?

0/100

Your Cloud Readiness Score

Want DemarkoCloud to help implement these recommendations?

Use your assessment as the starting point for a focused cloud, DevOps, or AI consultation.

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DEMARKOCLOUD SERVICES

Turn Readiness Gaps Into an Action Plan

Practical cloud, DevOps, and AI infrastructure services for small businesses, startups, and technical teams that need a stronger foundation without hiring a full-time platform engineering team.

01

Cloud Foundation & Architecture Review

Defined Architecture Review — $995
One defined AWS environment + one primary workload/application. Implementation is quoted separately.

Review the current environment, identify major architecture gaps, and create a focused roadmap for a more reliable, supportable AWS foundation.

Best for: Teams using AWS or moving toward AWS that need clarity before making more infrastructure changes.

Typical scope

  • Current-state cloud review
  • Architecture and operational gap analysis
  • Security, backup, and monitoring observations
  • Prioritized improvement roadmap
Deliverable: Cloud architecture findings + prioritized action plan
02

Terraform & Delivery Automation

Replace repeatable manual infrastructure and deployment work with version-controlled Terraform and practical CI/CD automation.

Best for: Teams relying on console clicks, manual deployments, or undocumented infrastructure changes.

Typical scope

  • Terraform Infrastructure as Code
  • GitHub Actions CI/CD workflows
  • Validation and deployment automation
  • Repeatable environment configuration
Deliverable: Working automation + implementation documentation
03

Cloud Reliability & Operations

Improve visibility, resilience, and operational readiness through monitoring, logging, alerts, backup review, and operational documentation.

Best for: Teams that discover problems from users, lack useful alerts, or are uncertain about recovery readiness.

Typical scope

  • CloudWatch metrics and dashboards
  • Centralized logging and alerting
  • Backup and recovery review
  • Operational runbook recommendations
Deliverable: Reliability improvements + operational readiness plan
04

AI Application Infrastructure

Help move an AI idea or prototype toward a deployable application foundation with APIs, containers, cloud infrastructure, and operational safeguards.

Best for: Teams experimenting with AI APIs, internal assistants, RAG, or AI-enabled applications.

Typical scope

  • AI application deployment architecture
  • Frontend/backend/API integration planning
  • Docker and AWS deployment foundation
  • Monitoring and production-readiness guidance
Deliverable: AI deployment architecture + implementation roadmap

Not Sure Which Service Fits?

Start with the free Cloud & AI Readiness Assessment. Your results will highlight the strongest areas to address first.

Take the Free Assessment
A SIMPLE PATH FORWARD

How DemarkoCloud Works

Start with clarity. DemarkoCloud helps identify the most important cloud, DevOps, reliability, and AI infrastructure gaps before recommending implementation work.

1

Assess

Complete the Cloud & AI Readiness Assessment to identify potential gaps across eight readiness areas: cloud infrastructure, infrastructure automation, CI/CD & delivery, reliability & monitoring, backup & recovery, security, container readiness, and AI readiness.

Free
2

Review

For organizations that need a deeper technical review, DemarkoCloud examines one defined AWS environment and primary workload and documents the most important findings.

$995 Cloud Foundation & Architecture Review
3

Plan

Receive a professional report with readiness scores, prioritized findings, practical recommendations, and a 30/60/90-day action plan.

Clear priorities. Defined next steps.
4

Implement

Implement the recommendations internally, use another provider, or request a separately scoped DemarkoCloud project for Terraform, CI/CD, reliability, or AI application infrastructure.

Implementation quoted separately
Start the Free AssessmentRequest a Consultation

Current Projects

Explore the projects below to view source code, deployment workflows, observability systems, AI-powered platforms, and production-style engineering documentation.

CLOUD PLATFORM CASE STUDY

NorthStar Terraform Platform

Production-style AWS cloud platform engineered with Terraform and automated through GitHub Actions. NorthStar demonstrates secure networking, private compute, application delivery, Infrastructure as Code, CI/CD automation, monitoring, observability, and repeatable infrastructure lifecycle management across 61 AWS resources and eight engineering phases.

AWS Terraform GitHub Actions CI/CD CloudWatch Infrastructure as Code
View Case Study View Repo
FLAGSHIP PROJECT

OpsIntel

AI-powered Executive Infrastructure Intelligence Platform designed to transform operational infrastructure data into executive-level insights, readiness scoring, governance visibility, commercialization intelligence, and strategic decision support. Built with a modular SaaS-ready architecture supporting multi-tenant and future white-label deployment models.

AI SaaS Executive Intelligence Next.js TypeScript White-Label
View Repo

AI InfraWatch

Enterprise-style AI infrastructure observability platform demonstrating real-time telemetry, operational metrics dashboards, infrastructure topology monitoring, deployment history tracking, CI/CD pipeline visualization, AI incident analysis, Dockerized services, AWS EC2 deployment, Nginx reverse proxy integration, and GitHub Actions CI/CD automation.

AI Observability Docker AWS EC2 Nginx CI/CD
View Repo

AI Support Ticket Triage Platform

Production-style AI support ticket triage platform demonstrating Dockerized frontend and backend services, Docker Compose orchestration, AWS EC2 deployment, Nginx reverse proxy, GitHub Actions CI/CD, automated health validation, and rollback workflow support.

AI Docker AWS EC2 Nginx CI/CD
View Repo

Automated CI/CD Deployment Pipeline

Production-style CI/CD deployment pipeline demonstrating GitHub Actions automation, Dockerized application deployment, AWS EC2 hosting, Nginx reverse proxy configuration, deployment scripting, health validation, and security group hardening.

GitHub Actions Docker AWS EC2 Nginx CI/CD
View Repo

Dockerized AWS Web App

Production-style containerized web deployment demonstrating Docker, Docker Compose, Nginx reverse proxy, AWS EC2 hosting, Linux server administration, and security group hardening.

AWS Docker Nginx Compose Linux
View Repo

Cloud Resume Project

Production-style cloud deployment project demonstrating EC2 hosting, Nginx, HTTPS, GitHub Actions CI/CD, Docker, Amazon ECR, and ECS Fargate.

AWS Nginx CI/CD Docker ECS
View Repo
ENTERPRISE AI PORTFOLIO

Enterprise Retrieval-Augmented Generation

A progressive Enterprise RAG engineering portfolio demonstrating document ingestion, semantic retrieval, hybrid search, conversational memory, source attribution, production architecture, security, observability, and scalable AI platform design.

3Completed RAG Systems
1Production System in Progress
EnterpriseArchitecture Focus
End-to-EndRAG Engineering
COMPLETED

Mini RAG #1 — End-to-End RAG

Built a complete Retrieval-Augmented Generation pipeline that loads enterprise documents, divides content into chunks, creates vector embeddings, stores them in a vector database, retrieves relevant context, constructs grounded prompts, and generates source-supported answers.

PythonChromaDBEmbeddings Vector SearchFLAN-T5Source Attribution

Core capabilities

  • Document loading and chunking
  • Vector embedding generation
  • Semantic similarity search
  • Top-K context retrieval
  • Grounded answer generation
  • Source citation and attribution
COMPLETED

Mini RAG #2 — Enterprise Retrieval

Expanded the foundational pipeline into an enterprise retrieval system supporting multiple documents, metadata-aware search, department filtering, hybrid retrieval, result merging, re-ranking, retrieval evaluation, and production-style source attribution.

Hybrid SearchMetadata FilteringRe-ranking Keyword SearchRetrieval EvaluationTop-K

Core capabilities

  • Multi-document ingestion
  • Document and department metadata
  • Vector and keyword retrieval
  • Hybrid result merging
  • Enterprise re-ranking
  • Retrieval quality evaluation
COMPLETED

Mini RAG #3 — Conversational RAG

Engineered a conversational RAG architecture with session management, short-term and long-term memory, history-aware query processing, memory-aware retrieval, prompt orchestration, conversation windowing, and summarization.

Conversation MemorySession ManagementQuery Rewriting Memory RetrievalSummarizationOrchestration

Core capabilities

  • Conversation session management
  • History-aware query processing
  • Memory-aware document retrieval
  • Short-term memory windowing
  • Long-term memory summarization
  • Scalable memory orchestration
IN PROGRESS

Enterprise RAG #4 — Production RAG Systems

Extending the RAG portfolio into production engineering with secure deployment architecture, API services, containerization, monitoring, evaluation, reliability, access control, governance, operational support, and scalable enterprise infrastructure.

Production ArchitectureSecurityMonitoring DeploymentReliabilityGovernance

Production focus

  • Secure RAG service deployment
  • Application and retrieval monitoring
  • Production evaluation pipelines
  • Access control and data governance
  • Reliability and failure handling
  • Scalable operational architecture
START A CONVERSATION

Request a DemarkoCloud Consultation

Tell me a little about your environment and the problem you are trying to solve. This request does not create a paid engagement. It starts a conversation so we can determine whether DemarkoCloud is a good fit.

Tell DemarkoCloud About Your Project

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Having trouble opening the request? Email DemarkoCloud directly at dmrk_little@yahoo.com.

Get in Touch

Contact me for collaboration, cloud engineering, DevOps opportunities, AI infrastructure projects, or SaaS platform development.

Email: dmrk_little@yahoo.com

LinkedIn: https://linkedin.com/in/demarkol