Cloud Strategy & Infrastructure

Cloud Strategy & Infrastructure

AWS migration, platform consolidation, and cloud cost optimization.

Stop Paying for Resources You Don’t Need

Your cloud bill is steadily increasing, but are you getting proportional value? Most companies overspend on cloud infrastructure by 30-50% through oversized resources, idle instances, inefficient architecture, and expensive observability tools.

I help you optimize your cloud strategy, improve governance, and significantly reduce spending—without compromising performance, security, or reliability.

Proven Cost Reduction Track Record

ShareASale Platform Optimization

AWS Infrastructure:

  • 25% cost reduction through right-sizing and architectural improvements
  • Maintained 99.95%+ uptime during optimization
  • Zero customer impact from changes
  • $20,000+ monthly savings sustained over years

DataDog Observability:

  • 50% cost reduction through log filtering and sampling strategies
  • Improved signal-to-noise ratio (fewer alerts, more actionable)
  • Better incident response despite reduced data volume
  • Custom metrics for business-critical monitoring

Method: Data-driven analysis, incremental changes, continuous measurement—not “slash and hope.”

Service Offerings

1. Cloud Cost Optimization Assessment

Situation: Your cloud bill is steadily increasing, and you’re not sure why. You suspect you’re overspending but don’t know where to cut costs.

Our Solution: Deep-dive analysis of your cloud usage and spending using tools like AWS Trusted Advisor, AWS Cost Explorer, and third-party platforms.

We Identify:

  • Oversized Resources — Instances running at <20% utilization
  • Idle Resources — Development/test environments running 24/7
  • Inefficient Storage — Unoptimized data storage and backup strategies
  • Network Waste — Unnecessary data transfer costs
  • Reserved Instance Gaps — Missing savings opportunities
  • Zombie Resources — Forgotten instances and services
  • Architectural Inefficiencies — Better architectures for less cost

Deliverable: Prioritized list of actionable recommendations with:

  • Expected cost savings per recommendation
  • Implementation effort and risk assessment
  • Quick wins (<1 week) vs. long-term improvements
  • Business impact analysis

Typical Results: 20-40% cost reduction identified, with 10-15% achievable in first 30 days.

2. Observability & Logging Strategy

Situation: You’re paying a fortune for observability and logging tools (DataDog, Splunk, New Relic), but you’re not getting the insights you need. Your logs are noisy, and your alerts are not actionable.

Our Solution: Cost-effective observability strategy that improves signal while reducing cost.

We Implement:

  • Log Filtering — Eliminate noisy logs that don’t inform decisions
  • Sampling Strategies — Collect representative data without 100% ingestion
  • Metric Optimization — Track what matters, not everything possible
  • Alert Tuning — Reduce false positives, improve actionability
  • Custom Dashboards — Business-relevant metrics, not vanity metrics
  • Cost Attribution — Understand who/what drives observability costs

Proven Results:

  • 50% DataDog cost reduction at ShareASale
  • Faster incident detection despite reduced data volume
  • More actionable alerts (less noise)
  • Better business metric visibility

Philosophy: You don’t need to log everything—you need to log the right things. More data ≠ better insights.

3. Edge Computing & Modern Architecture

Situation: You’re paying for global infrastructure you might not need, or your latency isn’t meeting user expectations despite high costs.

Our Solution: Evaluate edge computing alternatives for cost and performance optimization.

Edge Opportunities:

  • Cloudflare Workers — Global deployment with near-zero latency
  • Edge Caching — Reduce origin load and costs
  • Edge Compute — Run logic close to users without traditional servers
  • Serverless at Edge — Pay only for actual usage
  • Static Asset Optimization — CDN and edge delivery strategies

Recent Experience: Built production RAG applications on Cloudflare Workers:

  • Broad model selection with Workers AI
  • Sub-100ms global latency
  • 90%+ cost reduction vs. traditional cloud deployment
  • Scales automatically without manual intervention

When Edge Makes Sense:

  • Global user base with latency requirements
  • Read-heavy workloads (caching opportunities)
  • Static or semi-static content
  • APIs with predictable patterns
  • AI features that can run on smaller models

4. AI & LLM Cost Optimization

Situation: You’re building AI features but costs are unpredictable and growing faster than value delivered.

Our Solution: Practical strategies for controlling LLM and AI infrastructure costs based on recent production experience.

Cost Optimization Strategies:

  • Model Selection — Right-size models for use cases (GPT-4o vs. GPT-4o-mini vs. open source)
  • Prompt Engineering — Reduce token usage while improving results
  • Caching Strategies — Avoid redundant API calls
  • Edge Inference — Run smaller models locally or at edge
  • Batch Processing — Process lower-priority work efficiently
  • Request Throttling — Prevent cost spirals from abuse
  • Quality Monitoring — Ensure cost cuts don’t degrade quality

Recent Portfolio Work:

  • Compared Vercel (OpenAI) vs. Cloudflare Workers (local inference)
  • Built evaluation frameworks to measure quality vs. cost tradeoffs
  • Demonstrated 90%+ cost reduction for suitable use cases

Typical Findings:

  • 30-50% cost reduction through model selection
  • 20-30% reduction through prompt optimization
  • 60-90% reduction through edge inference (where applicable)
  • Unpredictable costs → predictable costs through architecture

5. Cloud Governance & Security

Situation: You’re concerned about the security and compliance of your cloud environment. You need to ensure you’re following best practices and meeting regulatory requirements (ISO 27001, NIST, SOC 2).

Our Solution: Establish robust cloud governance framework aligned with business requirements.

We Implement:

  • Security Policies — IAM best practices, least privilege access
  • Compliance Controls — Automated checks for regulatory requirements
  • Cost Controls — Budgets, alerts, approval workflows
  • Tagging Strategy — Resource organization and cost attribution
  • Automated Enforcement — Policy-as-code, guardrails
  • Audit & Reporting — Visibility for compliance and governance

Compliance Experience:

  • SOC 2 audit support for financial platforms
  • GDPR compliance for tracking systems
  • PCI-DSS for payment processing systems
  • Regular security audits and penetration testing

6. FinOps & Cloud Financial Management

Situation: You want to create a culture of cost-consciousness within your engineering teams. You need to make cloud spending a shared responsibility.

Our Solution: Implement FinOps principles and practices to empower teams.

We Establish:

  • Cost Visibility — Dashboards showing spending by team/service/environment
  • Budget Ownership — Teams own their cloud costs
  • Forecasting — Predictable cost growth tied to business metrics
  • Cost-Aware Development — Engineers understand cost implications
  • Optimization Incentives — Reward teams for cost-conscious decisions
  • Regular Reviews — Monthly cost reviews with actionable insights

Cultural Change:

  • From “not my problem” to shared responsibility
  • From reactive cost management to proactive optimization
  • From annual budget shocks to continuous improvement

Why Choose Me?

Proven Results, Not Promises

I’ve delivered actual cost reductions in production environments:

  • 25% AWS reduction while improving reliability
  • 50% DataDog reduction while improving observability
  • Zero customer impact from optimization initiatives
  • Sustained savings over years, not one-time fixes

Data-Driven Approach

I don’t make recommendations based on hunches:

  • Detailed usage analysis and spending patterns
  • Business impact assessment for every change
  • A/B testing for performance-sensitive optimizations
  • Continuous measurement and adjustment

Holistic Perspective

Cost optimization isn’t just about spending less:

  • Performance — Maintain or improve user experience
  • Reliability — Don’t sacrifice uptime for savings
  • Security — Cost cuts can’t introduce vulnerabilities
  • Developer Experience — Don’t slow down engineering teams
  • Scalability — Solutions that work at current and future scale

Recent Technology Experience

Current with modern cloud patterns:

  • Edge Computing — Cloudflare Workers, edge functions
  • Serverless — Lambda, Workers, event-driven architectures
  • Containers — Docker, ECS (AWS), Kubernetes (learning)
  • Infrastructure as Code — Terraform, CloudFormation
  • Modern Observability — DataDog, CloudWatch, custom metrics

Crisis-Tested

I’ve optimized under pressure:

  • Cost reduction mandates with tight deadlines
  • Performance problems with business impact
  • Scaling issues during traffic spikes
  • Migration deadlines with zero-downtime requirements

Technical Capabilities

Cloud Platforms

AWS (Primary Expertise):

  • EC2, ECS, Lambda (compute)
  • RDS, DynamoDB, DocumentDB (databases)
  • S3, EBS (storage)
  • VPC, CloudFront, Route 53 (networking)
  • CloudWatch, X-Ray (observability)
  • IAM, Secrets Manager, KMS (security)
  • Cost Explorer, Trusted Advisor, Budgets (FinOps)

Cloudflare:

  • Workers (edge compute)
  • Vectorize, D1, R2 (edge databases and storage)
  • CDN and caching strategies
  • Workers AI (edge inference)

Experience with Azure & GCP:

  • Familiar with core services and patterns
  • Can evaluate multi-cloud strategies
  • Understand cost differences and tradeoffs

Observability Tools

  • DataDog — Deep expertise, cost optimization
  • AWS CloudWatch — Logs, metrics, alarms
  • Prometheus & Grafana — Open-source alternatives
  • Custom Metrics — Business-relevant instrumentation

Infrastructure as Code

  • Terraform — Multi-cloud infrastructure management
  • CloudFormation — AWS-native IaC
  • Ansible — Configuration management and provisioning

Databases

  • SQL Server — Expert level (17+ years)
  • PostgreSQL — Including pgvector for AI workloads
  • NoSQL — DynamoDB, DocumentDB, appropriate use cases
  • Cost Optimization — Query optimization, index design, right-sizing

Engagement Models

1. Cost Optimization Assessment (Fixed Scope)

Duration: 2-4 weeks
Deliverable: Detailed report with prioritized recommendations

Includes:

  • Comprehensive cloud spending analysis
  • Waste identification and quantification
  • Quick win recommendations (<30 days)
  • Long-term optimization roadmap
  • ROI analysis for each recommendation

Pricing: $5,000 - $15,000 depending on infrastructure complexity

Follow-on: Implementation support available

2. Observability Strategy (Project-Based)

Duration: 3-6 weeks
Deliverable: Optimized observability with reduced costs

Includes:

  • Current observability audit
  • Log filtering and sampling implementation
  • Alert tuning and noise reduction
  • Custom dashboard development
  • Cost tracking and attribution

Pricing: $10,000 - $25,000 depending on tool complexity

3. Cloud Strategy & Architecture (Advisory)

Duration: 1-3 months
Time Commitment: 10-20 hours/month

Services:

  • Architecture review and recommendations
  • Technology evaluation (edge vs. cloud, build vs. buy)
  • Migration planning and support
  • Team enablement and training
  • Ongoing optimization guidance

Pricing: $5,000 - $10,000/month

4. Fractional Cloud Leadership

Duration: 3-12 months
Time Commitment: 10-20 hours/week

Services:

  • Strategic cloud planning and roadmap
  • FinOps program establishment
  • Vendor negotiation support
  • Team mentoring on cloud best practices
  • Governance and compliance framework

Pricing: $8,000 - $15,000/month

Ideal Client Profile

You’re a good fit if:

  • Your cloud bill is $10,000+/month and growing
  • You suspect significant waste but lack time to investigate
  • You need observability improvements without spiraling costs
  • You’re considering edge computing or modern architectures
  • You want data-driven decisions, not opinions
  • You value reliability and performance alongside cost optimization

You might not be a good fit if:

  • Your cloud spending is <$5,000/month (ROI may not justify consulting)
  • You need immediate emergency cost cuts (I optimize systematically, not recklessly)
  • You want someone to just “turn things off” (we assess impact first)
  • You’re looking for multi-cloud migration expertise (I focus on optimization)

How We Work

Assessment Phase (Week 1-2)

  • Gather cloud spending data (Cost Explorer, bills, usage reports)
  • Analyze usage patterns and identify anomalies
  • Interview stakeholders on business requirements and constraints
  • Document current architecture and pain points

Analysis & Recommendations (Week 2-3)

  • Quantify waste and opportunities
  • Prioritize recommendations by impact and effort
  • Create detailed implementation plans
  • Present findings with business case for each recommendation

Implementation Support (Optional)

  • Assist with high-impact quick wins
  • Review implementation of recommendations
  • Monitor results and adjust approach
  • Transfer knowledge to internal teams

Ongoing Optimization (Optional)

  • Monthly cost reviews and optimization
  • Continuous improvement program
  • FinOps culture development
  • Regular architecture reviews

Get Started

Stop overpaying for cloud infrastructure. Let’s identify your optimization opportunities.

Contact: Get in Touch · LinkedIn

Portfolio:

  • 25% AWS cost reduction (ShareASale)
  • 50% DataDog cost reduction (ShareASale)
  • Edge Computing Examples (90%+ cost reduction)

Last Updated: December 2025