aws-cost-management

Terraform module to automate AWS Savings Plans purchases. Maintain target coverage, spread financial risk, and save on Compute and Database costs — on autopilot.

Free AWS cost monitoring for personal accounts. View daily spending from terminal without expensive Cost Explorer API. Perfect for personal accounts. Haskell/Nix

Deadweight identifies where your AWS spend is being wasted by uncovering unused, idle, and forgotten resources that continue to cost you money.

This package provides a Strands-native “cost guard” layer for AI agents, focused on controlling and attributing LLM and tool spend within Strands-based workflows. It enforces budgets and policies at run time while emitting persistent, OpenTelemetry-style metrics so teams can monitor and optimize cost across tenants, strands, and workflows.

The AWS Billing Monitor is an automated solution that tracks AWS spending and alerts your team when costs change significantly. After experiencing billing incidents that weren't caught by existing monitoring solutions, this system was created to provide proactive cost oversight.

AWS CLI and CloudShell toolkit for auditing resources and potential costs across all AWS regions.

Open-source AWS cost analysis and recommendation engine built around AWS Cost and Usage Report (CUR) data. Identify practical cost-optimization opportunities using a deterministic, rules-based recommendation engine. It is designed to be self-hosted, transparent, and easy to run locally with Docker

Read-only AWS cost optimization and FinOps audit CLI (Python/boto3). Finds idle EC2/EBS/RDS, orphaned snapshots, unused Elastic IPs and Savings Plan gaps. Prioritized savings report, safe for production.

Automatically analyzes AWS CloudFormation templates and identifies unused or over-provisioned resources to optimize costs.

📚 Hands-on AWS Cost Management workshop — cost usage governance. Bilingual EN+VI. AWS First Cloud Journey series.

Enterprise-grade FinOps framework for AWS & GCP. Automates Cost of Revenue (COR) forecasting, multi-cloud unit economics, and strategic variance analysis using Python and Prophet modeling.

Optimized Reddit-scale cloud spend by building a Unit Economics model. Managed a 48% spend increase while driving an 8.4% efficiency gain ($13.69 to $12.54 per 1k DAU). Developed a dual-axis dashboard and a Python automation script to monitor scaling margins and enforce budget guardrails.

AWS技術コンテンツの作成 https://zenn.dev/riadraz

Stop AWS bill surprises: budgets and alerts, cost anomaly detection, tag enforcement, off-hours shutdown of dev/test and S3 lifecycle rules. Terraform modules with GitHub Actions (OIDC).

An AWS CDK (TypeScript) stack that deploys AWS Cost Anomaly Detection monitors with KMS-encrypted SNS alerting and a Lambda filter that suppresses noisy services and reformats alerts into readable email.