# WasteLine by OptimNow | Detect Cloud Waste, Deliver Remediation

Last updated: 2026-05-04

> WasteLine detects orphaned, idle, overprovisioned, and legacy AWS resources, plus AI/ML waste on SageMaker and Bedrock. Read-only, runs inside your environment, results in minutes. No SaaS vendor access to your data.

## Summary

- URL: https://wasteline.optimnow.io/
- Audience: For FinOps, platform engineering, cloud architects, and infrastructure teams.
- Primary action: Book a Free Scan
- Live demo: https://wasteline.vercel.app/
- Publisher: OptimNow

## Product

WasteLine scans your AWS environment for orphaned, idle, and overprovisioned resources, then generates prioritized findings with cost impact and ready-to-execute remediation artifacts. Results in minutes, not weeks.

One tool that detects waste, quantifies the cost, ranks findings by business impact, and delivers CLI scripts, Terraform snippets, and approval workflows your team can apply directly.

## What You Get

- Scan results you can act on, not just read: Every scan produces a prioritized findings table and a ranked remediation plan. Filterable, sortable, export-ready.
- Your executive snapshot at a glance. Total findings, monthly and annualized cost impact, waste broken down by category and account, plus confidence and blast-radius distributions so you know where to focus first.
- Browse, filter, and build your recommended actions. Sort by category, confidence, or blast radius. Pick your quick wins. Each finding includes full detail and remediation scripts. You decide what to act on.
- A ranked queue built from your selections. Each finding you include becomes a prioritized action (P1 to P4) with effort estimate and pre-built remediation script ready to execute.
- One CLI powers the entire flow. Scan, open the dashboard, generate reports. One command each. No agents, no persistent infrastructure, no data leaves your environment.

## Detection Coverage

- Orphaned (9 rules): EBS volumes, Elastic IPs, security groups, AMIs, snapshots, empty S3 buckets, ECR lifecycle, stale multipart uploads, unused secrets
- Idle (8 rules): EC2 instances, load balancers, CloudWatch log groups, NAT gateways, S3 buckets, Lambda functions, DynamoDB tables, Redshift clusters
- Overprovisioned (9 rules): EC2 compute, EBS storage, RDS databases, S3 storage classes and versioning, CloudWatch log retention, DynamoDB provisioning, ECS Fargate scaling, CloudTrail duplicate trails
- Commitment gap (5 rules): Reserved Instance utilization and expiration, Savings Plans coverage and utilization, ElastiCache reserved node coverage
- Schedule blind (2 rules): Non-production EC2 running 24/7, Redshift clusters without pause schedule
- Modernization (7 rules): Older-generation EC2, EBS, and RDS instance types; x86 to Graviton migration for EC2, Lambda, and ECS; RDS extended-support engine versions
- FinOps for AI (9 rules): SageMaker idle notebooks and inference endpoints, stale Studio apps, on-demand training without Spot; Bedrock under-utilized Provisioned Throughput, superseded and orphaned custom models, over-provisioned capacity

## Run From AI Coding Assistants

- Deploy WasteLine from Claude Code, Codex, Cursor, Gemini CLI, or Kiro: Download the starter pack. Paste the bootstrap prompt into your AI coding assistant. It discovers the CLI, proposes the config, and runs your scan - with your approval at every step.
- The AI assistant orchestrates the CLI. It does not run the detection logic. All 49 rules and every remediation script are deterministic and rule-based - the output is identical whether you run the CLI directly or through an assistant.
- Download: https://wasteline.optimnow.io/assets/wasteline-quickstart-vm.zip

## Security and Deployment

- Get/List/Describe only: No write calls. Enforced by AST analysis in CI and runtime SDK guards.
- Zero outbound calls: No telemetry, no phone-home, no license server. Deploy in private subnets with existing NAT or VPC endpoints.
- Results stay in your S3: Static dashboard reads a local JSON file. No server, no shared state, no cross-tenant exposure.
- SHA-256 signed findings: Deterministic scans with manifest hash verification. Safe for CI/CD and change management.

## Pricing

- Free ($0): See what you're wasting. Full scan across all 49 rules, with detailed findings for the 5 most common waste types.
- Professional ($2,500, Per year): All 49 rules fully unlocked with remediation scripts, executive reports, and multi-account scanning.
- Enterprise ($12,500/yr): Continuous, automated cloud waste detection for teams running their own FinOps practice.
- Enterprise+ ($25,000/yr): Everything in Enterprise, plus a dedicated FinOps advisor. 1 day/month of hands-on support.

## FAQ

### What is WasteLine?

WasteLine is an AWS cloud waste detection tool by OptimNow. It scans for orphaned, idle, and overprovisioned resources, quantifies cost impact, and generates ready-to-execute remediation artifacts including AWS CLI scripts, Terraform snippets, and OpenOps approval workflows.

### Is WasteLine safe to run in production?

Yes. WasteLine is strictly read-only. It uses only Get, List, and Describe API actions. No write calls, no Delete, Modify, Tag, or Create. Safety is enforced by AST static analysis in CI and runtime SDK guards.

### Does WasteLine send data outside my AWS account?

No. WasteLine runs entirely inside your AWS environment. There is no SaaS backend, no telemetry, no phone-home, and no license validation server. Scan results are stored in an S3 bucket in your account. Zero outbound calls to non-AWS endpoints.

### How much does WasteLine cost?

WasteLine has four tiers: Free at $0 for a full 49-rule scan on a single AWS account with executive reports and remediation artifacts; Professional at $2,500/year for multi-account scanning and drift tracking; Enterprise at $12,500/year for automated Fargate scans, CUR integration, AWS-native recommendation ingestion, and white-label dashboards; and Enterprise+ at $25,000/year for managed FinOps support, monthly reviews, and remediation accountability.

### What types of cloud waste does WasteLine detect?

WasteLine detects 7 categories of waste across 49 rules: orphaned resources (EBS volumes, Elastic IPs, security groups, AMIs, snapshots, S3 buckets, ECR lifecycle, multipart uploads, unused secrets), idle resources (EC2, load balancers, CloudWatch log groups, NAT gateways, S3, Lambda, DynamoDB, Redshift), overprovisioned resources (EC2, EBS, RDS, S3, CloudWatch log retention, DynamoDB, ECS Fargate, CloudTrail), commitment mismatches (Reserved Instances, Savings Plans, ElastiCache reserved nodes), schedule-blind resources (EC2 and Redshift without cost-aware scheduling), modernization opportunities (older-generation EC2, EBS, and RDS; x86-to-Graviton migration for EC2, Lambda, and ECS; RDS extended-support engines), and FinOps for AI (SageMaker idle notebooks and inference endpoints, stale Studio apps, on-demand training without Spot; Bedrock under-utilized Provisioned Throughput, superseded and orphaned custom models, over-provisioned capacity).

### Does WasteLine use AI to detect waste?

No. All 49 detection rules and every remediation script are deterministic and rule-based - no LLM makes detection decisions or generates remediation logic. An optional --ai-narrative flag (off by default) rewrites the executive summary using only anonymized, aggregated stats. Separately, WasteLine ships with a public starter pack that lets you run the CLI from inside Claude Code, Codex, Cursor, Gemini CLI, or Kiro (the AWS IDE). The AI assistant orchestrates the CLI; the detection logic stays deterministic.

### Does WasteLine cover AWS AI/ML workloads?

Yes. WasteLine includes 9 detection rules for SageMaker and Bedrock: idle SageMaker notebooks and inference endpoints, stale Studio apps, on-demand training jobs missing Managed Spot, under-utilized Bedrock Provisioned Throughput, Provisioned Throughput on superseded model versions, stale custom models, over-provisioned capacity, and models with newer family versions available.

### How do I remove WasteLine from my AWS account?

Run aws cloudformation delete-stack to remove all resources created by WasteLine. There is no agent, daemon, or persistent process. The S3 bucket with scan history is retained by default so you keep your data, but can be manually deleted.

## Links

- Landing page: https://wasteline.optimnow.io/
- Live demo (interactive, sample data): https://wasteline.vercel.app/
- Starter pack ZIP (run from AI coding assistants): https://wasteline.optimnow.io/assets/wasteline-quickstart-vm.zip
- LLM index: https://wasteline.optimnow.io/llms.txt
- Sitemap: https://wasteline.optimnow.io/sitemap.xml
- Book a free scan: https://tidycal.com/1r8yjp2/free-cloud-waste-check-wasteline-by-optimnow?utm_source=llm-md&utm_medium=ai-search&utm_campaign=free-scan
- Contact: contact@optimnow.io