> TECHNICAL MANUALS // 10 CHAPTERS
10 Cloud Cost Engineering Manuals
Production-ready technical runbooks from Karpenter JIT provisioning to Spot GPU serving and bare-metal colocation.
Chapter 1: The Modern FinOps Operating Model & Governance
FinOps 3-phase lifecycle (Inform, Optimize, Operate), cross-functional RACI governance, and CPAC unit economics mandate.
Chapter 2: Unit Economics & Tagging Governance with FOCUS 1.0
FOCUS 1.0 open billing schema, mandatory 5-key tagging taxonomy, AWS SCP enforcement, and untagged resource remediation.
Chapter 3: High-Density Kubernetes & Karpenter Autoscaling
Just-in-Time (JIT) node provisioning, Graviton ARM64 adoption, Spot consolidation, and bin-packing efficiency.
Chapter 4: Spot Preemptible GPU Orchestration & vLLM Serving
2-minute Spot termination handling, vLLM PagedAttention, speculative decoding, and multi-region GPU fallback.
Chapter 5: Storage Tiering, Lifecycle Governance & EBS Rightsizing
Object storage lifecycle cascades, S3 Intelligent-Tiering, incomplete multipart abort, and EBS gp2 to gp3 online migration.
Chapter 6: Network Egress Optimization, NAT Gateways & Cross-AZ Avoidance
Bypassing NAT Gateway fees with VPC Endpoints, topology-aware routing, and global CDN origin shielding.
Chapter 7: Database Rightsizing, Connection Pooling & Read-Replica Governance
Transaction-level PgBouncer pooling, pg_stat_statements query optimization, and serverless ACU scaling ceilings.
Chapter 8: Observability Cost Governance, Log Sampling & Metric Explosion
Preventing metric label explosion, in-flight OpenTelemetry Collector log filtering, and CloudWatch retention limits.
Chapter 9: Commitment Discounts, Savings Plans & Reserved Instances
Compute Savings Plans vs EC2 Savings Plans vs RIs, the 75-80% coverage curve, and upfront cash optimization.
Chapter 10: Cloud Repatriation, Colocation & Bare-Metal Breakeven
Mathematical breakeven analysis for colocation, the hybrid Egress Shield pattern, and platform engineering overhead.
The TinyCTO Cloud Economics & FinOps Architecture Canon ('The Cloud Bill Bible') establishes an operational engineering discipline for cloud financial governance. Built upon the FinOps Foundation FOCUS 1.0 open specification, the canon details 18 production cloud architectures across 6 archetypes, 24 cloud waste typologies with detection queries and CLI remediation playbooks, a deterministic sizing wizard engine with itemized Bill-of-Materials calculations, 10 deep bilingual engineering manuals, and a 26-tool comparison matrix.
Cloud Economics Manuals Technical FAQs
What is the recommended reading sequence across the 10 FinOps manuals?
Start with Chapter 1 (Operating Model) and Chapter 2 (Unit Economics & Tagging) to establish foundational governance. Then dive into specific domain optimizations: Chapter 3 (Compute/Karpenter), Chapter 4 (Spot GPUs), Chapter 5 (Storage Lifecycle), Chapter 6 (Network Egress), Chapter 7 (Databases), and Chapter 8 (Observability). Conclude with executive strategy in Chapter 9 (Commitment Discounts) and Chapter 10 (Cloud Repatriation).
How do the manuals handle code examples and CLI commands?
Every manual provides production-ready, copy-pasteable configuration files: Terraform/OpenTofu HCL, Kubernetes YAML manifests, AWS CLI commands, PgBouncer configurations, and OpenTelemetry Collector pipelines, accompanied by mathematical formulas and architecture flowcharts.
Are the techniques in the manuals applicable to GCP and Azure as well as AWS?
Yes. While AWS terminology is often used as a baseline, every chapter covers equivalent multi-cloud abstractions (e.g. GKE Autopilot, Azure Container Apps, Cloud Storage lifecycle rules, and Azure Savings Plans) standardized per FOCUS 1.0.
What maturity level (Crawl, Walk, Run) is required before implementing Chapter 4 (Spot GPUs)?
Spot GPU orchestration is classified as a 'Run' maturity practice. Teams should have mastered basic container autoscaling and automated monitoring ('Walk') before deploying production workloads onto preemptible GPU fleets.
How does Chapter 8 address high-cardinality metric explosion in Prometheus and Datadog?
Chapter 8 codifies the Golden Rule of Metric Cardinality: never inject user IDs, UUIDs, or IP addresses into metric tags. It demonstrates OpenTelemetry Collector processors that filter out healthcheck spam and drop cardinality before metrics are shipped to SaaS vendors.
Can the FinOps manuals be consumed by autonomous AI agents?
Yes. All manuals support dynamic content negotiation via `?format=md` and `Accept: text/markdown`, returning unrendered, dense Markdown optimized for LLM agent ingestion and automated reasoning.