Field Notes From the Architecture & FinOps Trenches.
Practical, principal-authored engineering playbooks on running AWS, high-throughput streaming pipelines, Data Vault 2.0 lakehouses, and Agentic AI systems at lower unit cost. Written from real enterprise engagements - zero marketing filler.
Ingesting 20.5 Billion Daily Records at 1/10th Spark Cost: PyArrow Zero-Copy Streaming & Hybrid Data Vault 2.0
How we replaced OOM-prone JVM clusters with a stateful C++/PyArrow micro-batch Parquet engine (~300,000 rec/sec under 80 MB RAM) and automated Raw/Business Vaults to Kimball star schemas with dbt.
Read the Architectural Playbook AI/ML · Bedrock · FinOpsAI/ML Cost Optimization on AWS: Where the GPU and Token Money Really Goes
Training, inference, Amazon Bedrock token loops, and the surprisingly large "everything else". A practical playbook for cutting ML and LLM spend without slowing engineering velocity.
Read the Playbook Kubernetes · Amazon EKSKubernetes Cost Optimization: Closing the Request Gap on Amazon EKS
Your EKS bill is an EC2 and EBS/NAT bill in disguise. How to right-size resource requests, pack nodes tightly, buy compute commitments wisely, and stop paying for idle cluster slack.
Read the Playbook Karpenter · Spot · GravitonKarpenter Cost Optimization: NodePools That Actually Save Money
Karpenter is only as cheap as its NodePool and PodDisruptionBudget configuration. Consolidation windows, Spot diversification, Graviton4 mixing, and the anti-patterns we keep fixing.
Read the PlaybookWant These Patterns Applied to Your AWS Bill or Data Platform?
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