AI Cost Accounting and Chargeback Models
How to implement cost tracking, allocation, and chargeback models for AI workloads including token-based billing, GPU hour accounting, and …
Cost-Management
AI Gateway
A centralized proxy layer that routes, governs, monitors, and optimizes requests to LLM providers, serving as the control plane for …
AWS Cloud Governance for AI Workloads
Practical guide for implementing cloud governance on AWS for AI and ML workloads, covering Organizations, SCPs, tagging, cost management, …
AWS vs Azure Governance Tools
Comparison of AWS and Azure governance capabilities for AI workloads, covering organization management, policy enforcement, cost control, …
Cloud Governance
The framework of policies, processes, and controls that organizations use to manage cloud resources, ensure compliance, control costs, and …
Earned Value Management (EVM)
A project performance measurement technique that integrates scope, schedule, and cost metrics to assess project health.
Enterprise Cloud Governance Framework
A comprehensive framework for governing cloud environments that host AI workloads, covering organizational structure, policy enforcement, …
Managing Test Environments for AI Systems
Test environment strategies for AI: local dev with mocked models, staging with real models, Docker Compose for local AI stacks, cost …
Rate Limiting Patterns for AI Applications
Implementing effective rate limiting for AI-powered applications. Token-based limits, adaptive throttling, queue management, and fair …
Token Optimization Patterns for LLM Applications
Strategies for reducing token usage without sacrificing output quality. Prompt compression, context pruning, output formatting, and cost …
Budgeting an AI Project - What It Really Costs
A practical cost breakdown for enterprise AI projects - from prototype to production - covering model inference, infrastructure, data, …