> ## Documentation Index
> Fetch the complete documentation index at: https://docs.cloudthinker.io/llms.txt
> Use this file to discover all available pages before exploring further.

# CostOps

> Find, prioritize, and track cloud cost savings across AWS, GCP, and Azure with AI-generated recommendations

CostOps continuously analyzes your connected cloud accounts to surface savings opportunities, generate prioritized recommendations, and track the optimizations you implement. Cloud waste — idle instances, unattached volumes, drifting reserved-capacity coverage — accumulates quietly between invoices, so CostOps watches for it continuously instead of waiting for the bill.

## How it works

1. **Discover** — CloudThinker scans your connected AWS, GCP, and Azure accounts to inventory resources, configurations, and spending patterns.
2. **Analyze** — Agents evaluate resource utilization, spending trends, and configuration patterns against cloud-native best practices.
3. **Recommend** — [Alex](/guide/agents/alex) generates prioritized recommendations, each with a dollar savings estimate, an effort level (Low/Medium/High), a risk assessment (Low/Medium/High), and implementation steps.
4. **Implement** — With your [approval](/guide/approval), CloudThinker executes a recommendation or provides a detailed guide for manual execution.
5. **Track** — [Savings tracking](/guide/cost-optimization/savings) measures actual savings against projections after implementation.

Alex leads cost work across clouds; [Kai](/guide/agents/kai) covers Kubernetes efficiency and [Tony](/guide/agents/tony) tunes database spend.

## What you can do

| Capability            | Description                                                                                                               | Learn more                                                  |
| --------------------- | ------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------- |
| Recommendations       | Review AI-generated cost-saving recommendations with savings, effort, and risk for each                                   | [Recommendations](/guide/cost-optimization/recommendations) |
| Cost analytics        | Explore spending trends, forecasts, and attribution across accounts and services                                          | [Analytics](/guide/cost-optimization/analytics)             |
| Resource optimization | Right-size instances, detect idle resources, and analyze utilization                                                      | [Resources](/guide/infrastructure/resources)                |
| Savings tracking      | Track implemented recommendations and measure realized savings against projections                                        | [Savings](/guide/cost-optimization/savings)                 |
| Continuous guardrails | Run scheduled [CloudKeepers](/guide/infrastructure/cloudkeepers) cost checks so waste surfaces as findings, not surprises | [CloudKeepers](/guide/infrastructure/cloudkeepers)          |

## Supported resource types

CostOps analyzes 58+ AWS resource types plus core GCP and Azure services.

| Provider | Area           | Coverage                                                                                                                  |
| -------- | -------------- | ------------------------------------------------------------------------------------------------------------------------- |
| AWS      | Compute        | EC2 (right-sizing, reserved instances, spot), ECS, EKS, Lambda memory tuning, Batch, EMR, App Runner                      |
| AWS      | Storage        | S3 lifecycle and storage classes, EBS (unattached, oversized), EFS throughput, Glacier archiving                          |
| AWS      | Database       | RDS sizing and reserved instances, DynamoDB capacity modes, DocumentDB, Neptune, Redshift, ElastiCache                    |
| AWS      | Networking     | CloudFront caching, ELB/ALB/NLB idle detection, NAT Gateway efficiency, Route 53, API Gateway                             |
| AWS      | Analytics & AI | SageMaker endpoints, notebooks, and training jobs, OpenSearch, Kinesis, Firehose, Glue                                    |
| GCP      | All            | Compute Engine (right-sizing, committed use discounts), Cloud Run, Cloud Functions, Cloud SQL, GKE, Cloud Storage classes |
| Azure    | All            | Virtual Machines, Azure Kubernetes Service, Azure SQL Database, Blob Storage, App Services                                |

## Quick start

Ask Alex for your first cost analysis from any workspace chat:

```text theme={null}
@alex #recommend cost-saving opportunities for production workloads
@alex #dashboard current month spending by service
@alex #report unattached EBS volumes and unused Elastic IPs across all regions
```

Each result includes the underlying data, so you can verify a recommendation before acting on it.

## Get started

<CardGroup cols={2}>
  <Card title="Recommendations" icon="lightbulb" href="/guide/cost-optimization/recommendations">
    Generate, review, implement, and track cost-saving recommendations
  </Card>

  <Card title="Analytics" icon="chart-line" href="/guide/cost-optimization/analytics">
    Understand spending patterns, anomalies, and forecasts
  </Card>

  <Card title="Keepers" icon="radar" href="/guide/infrastructure/cloudkeepers">
    Schedule continuous cost guardrails that surface waste as findings
  </Card>

  <Card title="Savings tracking" icon="chart-pie" href="/guide/cost-optimization/savings">
    Measure realized savings and optimization results over time
  </Card>
</CardGroup>