CUDly

CUDly - Multi-Cloud Commitment & Usage Discount Manager

CUDly is a comprehensive CLI tool for managing cloud cost commitments across AWS, Azure, and GCP. It helps organizations optimize cloud spending by automating the discovery, analysis, and purchase of multiple Reserved Instances, Savings Plans, and Committed Use Discounts by running a single command.

Key Features

• Multi-Cloud Support - Unified interface for AWS (production), Azure (experimental), and GCP (experimental)
• Intelligent Recommendations - Fetches and analyzes commitment recommendations from cloud provider APIs
• Safe Purchase Automation - Execute purchases with built-in safety controls (dry-run by default)
• Flexible Coverage Control - Purchase only a percentage of recommendations for gradual adoption
• CSV Workflow - Generate recommendations, review offline, then execute purchases
• Advanced Filtering - Filter by region, instance type, engine, and account
• Comprehensive Reporting - Detailed cost estimates, savings calculations, and audit trails

Supported Cloud Providers & Services

AWS Services (Production Ready)

Service	Commitment Type	Description
Amazon RDS	Reserved Instances	MySQL, PostgreSQL, MariaDB, Oracle, SQL Server, Aurora
Amazon ElastiCache	Reserved Nodes	Redis, Memcached
Amazon EC2	Reserved Instances	All instance families
Amazon OpenSearch	Reserved Instances	Search domain instances
Amazon Redshift	Reserved Nodes	DC2 and RA3 node types
Amazon MemoryDB	Reserved Nodes	Memory-optimized nodes
Savings Plans	Hourly Commitments	Compute, EC2 Instance, SageMaker, Database

Azure Services (Experimental)

Service	Commitment Type
Azure SQL Database	Reserved Capacity
Azure Virtual Machines	Reserved Instances
Azure Cache for Redis	Reserved Capacity
Azure Cosmos DB	Reserved Capacity
Azure Cognitive Search	Reserved Capacity

GCP Services (Experimental)

Service	Commitment Type
Compute Engine	Committed Use Discounts
Cloud SQL	Committed Use Discounts
Memorystore	Committed Use Discounts
Cloud Storage	Committed Use Discounts

Installation

From Source

git clone https://github.com/LeanerCloud/CUDly.git
cd CUDly
go build -o cudly cmd/*.go

Using Go Install

go install github.com/LeanerCloud/CUDly/cmd@latest

Quick Start

1. Get Recommendations (Dry Run)

# Get RDS recommendations with default settings (3-year, no-upfront, 80% coverage)
./cudly --services rds

# Get recommendations for multiple services
./cudly --services rds,elasticache,ec2

# Get recommendations for all supported services
./cudly --all-services

2. Review and Refine

# Apply filters to narrow down recommendations
./cudly --services rds \
  --include-regions us-east-1,eu-west-1 \
  --exclude-instance-types db.t2.micro \
  --coverage 50

3. Execute Purchases

# Purchase from generated CSV (requires explicit --purchase flag)
./cudly --input-csv cudly-dryrun-*.csv --purchase

# Skip confirmation prompt
./cudly --input-csv cudly-dryrun-*.csv --purchase --yes

Command Reference

Service Selection

Flag	Description	Default
-s, --services	Comma-separated service list (rds,elasticache,ec2,opensearch,redshift,memorydb,savingsplans)	rds
--all-services	Process all supported services	false

Purchase Configuration

Flag	Description	Default
-p, --payment	Payment option: all-upfront, partial-upfront, no-upfront	no-upfront
-t, --term	Term in years: 1 or 3	3
-c, --coverage	Coverage percentage (0-100)	80
--max-instances	Maximum instances to purchase (0 = unlimited)	0
--override-count	Override recommended count with specific value	0

Execution Control

Flag	Description	Default
--purchase	Execute actual purchases (dry-run by default)	false
--yes	Skip confirmation prompts	false
-i, --input-csv	Input CSV file with recommendations	-
-o, --output	Output CSV file path	auto-generated

Filtering

Flag	Description
--include-regions	Only include these regions
--exclude-regions	Exclude these regions
--include-instance-types	Only include these instance types
--exclude-instance-types	Exclude these instance types
--include-engines	Only include these database engines
--exclude-engines	Exclude these database engines
--include-accounts	Only include these account names
--exclude-accounts	Exclude these account names
--include-extended-support	Include instances on extended support engine versions (see below)
--include-sp-types	Only include these Savings Plan types (Compute, EC2Instance, SageMaker, Database)
--exclude-sp-types	Exclude these Savings Plan types

Extended Support Filtering

By default, CUDly excludes instances running on database engine versions that are in AWS Extended Support. This is because Extended Support incurs additional per-vCPU-hour charges that may offset RI savings.

For example, MySQL 5.7 and PostgreSQL 11 are in Extended Support. Instances running these versions are automatically excluded from RI recommendations.

Note: This feature requires the --validation-profile flag to specify an AWS profile with permissions to describe RDS instances across all member accounts in your organization.

# Extended support filtering with validation profile
./cudly --services rds --validation-profile my-org-reader-profile

# Include extended support instances (skip filtering)
./cudly --services rds --include-extended-support

This is useful if you plan to upgrade the database version before the RI term ends, or if the Extended Support charges are acceptable for your use case.

Duplicate Purchase Prevention

CUDly automatically checks for Reserved Instances purchased within the last 24 hours and adjusts recommendations to avoid duplicate purchases. This is useful when running the tool multiple times in quick succession or when recovering from partial purchase failures.

For example, if you purchase 5 db.r6g.large RIs and run CUDly again within 24 hours, those 5 instances will be subtracted from the recommendation count to prevent double-purchasing.

Authentication

Flag	Description
--profile	AWS profile to use
--validation-profile	AWS profile for instance type validation

Usage Examples

Example 1: Conservative RDS Adoption

Purchase 50% of 1-year partial-upfront RDS recommendations:

./cudly --services rds \
  --payment partial-upfront \
  --term 1 \
  --coverage 50

Example 2: Multi-Service with Different Coverage

Apply different coverage percentages per service:

./cudly \
  --services rds,elasticache,ec2 \
  --rds-coverage 50 \
  --elasticache-coverage 80 \
  --ec2-coverage 100 \
  --payment no-upfront \
  --term 3

Example 3: Regional Focus

Only process specific regions with instance limits:

./cudly --services ec2 \
  --include-regions us-east-1,us-west-2 \
  --max-instances 50 \
  --payment all-upfront \
  --term 3

Example 4: CSV-Based Workflow

# Step 1: Generate recommendations
./cudly --all-services --output recommendations.csv

# Step 2: Review CSV file externally

# Step 3: Purchase with filters
./cudly \
  --input-csv recommendations.csv \
  --include-regions us-east-1 \
  --exclude-instance-types db.t2.micro,cache.t2.micro \
  --coverage 75 \
  --purchase

Example 5: Exclude Small Instances

./cudly --services rds,elasticache \
  --exclude-instance-types db.t2.micro,db.t2.small,db.t3.micro,cache.t2.micro \
  --payment partial-upfront \
  --term 3

Example 6: Database Savings Plans Only

# Get only Database Savings Plans recommendations
./cudly --services savingsplans \
  --include-sp-types Database \
  --term 1 \
  --coverage 80

Example 7: Exclude SageMaker Savings Plans

# Get all Savings Plans except SageMaker
./cudly --services savingsplans \
  --exclude-sp-types SageMaker \
  --term 3

Coverage Percentage

The coverage percentage controls what portion of recommendations to act on:

Coverage	Description	Use Case
100%	All recommended instances	Maximum savings, stable workloads
75%	Three-quarters of recommendations	Balanced approach
50%	Half of recommendations	Conservative adoption
25%	Quarter of recommendations	Testing/validation
0%	Skip service entirely	Exclude from processing

Safety Features

CUDly includes multiple safety mechanisms to prevent unintended purchases:

1. Dry-run by default - No purchases without explicit --purchase flag
2. Interactive confirmation - Prompts before actual purchases (unless --yes)
3. CSV workflow - Review recommendations before purchasing
4. Coverage control - Purchase only what you need
5. Instance limits - Cap total purchases with --max-instances
6. Duplicate prevention - Checks for existing commitments
7. Instance type validation - Validates against known types
8. Detailed logging - Full audit trail of operations
9. CSV exports - Permanent record of all recommendations and purchases

Cloud Provider Authentication

AWS

CUDly uses the standard AWS SDK credential chain:

1. Environment variables (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY)
2. Shared credentials file (~/.aws/credentials)
3. AWS config file (~/.aws/config)
4. IAM instance role (EC2/ECS)

Required IAM Permissions

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "CostExplorer",
      "Effect": "Allow",
      "Action": [
        "ce:GetReservationPurchaseRecommendation",
        "ce:GetReservationUtilization",
        "ce:GetReservationCoverage",
        "ce:GetSavingsPlansPurchaseRecommendation"
      ],
      "Resource": "*"
    },
    {
      "Sid": "ReservedInstanceOperations",
      "Effect": "Allow",
      "Action": [
        "rds:DescribeReservedDBInstancesOfferings",
        "rds:DescribeReservedDBInstances",
        "rds:PurchaseReservedDBInstancesOffering",
        "elasticache:DescribeReservedCacheNodesOfferings",
        "elasticache:DescribeReservedCacheNodes",
        "elasticache:PurchaseReservedCacheNodesOffering",
        "ec2:DescribeReservedInstancesOfferings",
        "ec2:DescribeReservedInstances",
        "ec2:PurchaseReservedInstancesOffering",
        "es:DescribeReservedInstanceOfferings",
        "es:DescribeReservedInstances",
        "es:PurchaseReservedInstanceOffering",
        "redshift:DescribeReservedNodeOfferings",
        "redshift:DescribeReservedNodes",
        "redshift:PurchaseReservedNodeOffering",
        "memorydb:DescribeReservedNodesOfferings",
        "memorydb:DescribeReservedNodes",
        "memorydb:PurchaseReservedNodesOffering",
        "savingsplans:DescribeSavingsPlans",
        "savingsplans:CreateSavingsPlan"
      ],
      "Resource": "*"
    },
    {
      "Sid": "RegionDiscovery",
      "Effect": "Allow",
      "Action": [
        "ec2:DescribeRegions",
        "ec2:DescribeInstanceTypeOfferings"
      ],
      "Resource": "*"
    },
    {
      "Sid": "AccountDiscovery",
      "Effect": "Allow",
      "Action": [
        "sts:GetCallerIdentity",
        "organizations:ListAccounts"
      ],
      "Resource": "*"
    }
  ]
}

Azure (Experimental)

Uses Azure SDK DefaultAzureCredential:

1. Azure CLI (az login)
2. Environment variables (AZURE_TENANT_ID, AZURE_CLIENT_ID, AZURE_CLIENT_SECRET)
3. Managed Identity (Azure VM)

GCP (Experimental)

Uses Google Cloud SDK credential chain:

1. Service account JSON (GOOGLE_APPLICATION_CREDENTIALS)
2. Application Default Credentials
3. gcloud CLI authentication

Output Format

CUDly generates CSV files with comprehensive details:

Timestamp,Status,Service,Provider,Account,Region,ResourceType,Count,Term,PaymentOption,UpfrontCost,RecurringCost,TotalCost,EstimatedSavings,PurchaseID

File Naming Convention

• Dry run: cudly-dryrun-YYYYMMDD-HHMMSS.csv
• Purchase: cudly-purchase-YYYYMMDD-HHMMSS.csv

Architecture

CUDly/
├── cmd/                      # CLI entry point and orchestration
├── pkg/                      # Shared multi-cloud packages
│   ├── common/              # Cloud-agnostic types and interfaces
│   └── provider/            # Provider abstraction layer
└── providers/               # Cloud-specific implementations
    ├── aws/                 # AWS provider (production)
    │   ├── services/        # Service clients (RDS, EC2, etc.)
    │   └── recommendations/ # Cost Explorer integration
    ├── azure/               # Azure provider (experimental)
    │   └── services/        # Azure service clients
    └── gcp/                 # GCP provider (experimental)
        └── services/        # GCP service clients

Design Principles

• Interface-driven - All implementations follow defined interfaces for testability
• Multi-cloud abstraction - Unified types and behaviors across providers
• Plugin architecture - Services registered and discovered at runtime
• Safety-first - Multiple layers of protection against unintended purchases

Development

Prerequisites

• Go 1.23 or later
• AWS/Azure/GCP credentials for integration testing

Building

# Build binary
go build -o cudly cmd/*.go

# Run tests
go test ./...

# Run tests with coverage
go test -cover ./...

# Run specific package tests
go test ./providers/aws/...

Project Structure

Directory	Purpose
cmd/	CLI implementation, flag parsing, orchestration
pkg/common/	Cloud-agnostic types (Provider, Service, Commitment)
pkg/provider/	Provider interface, registry, factory
providers/aws/	AWS implementation with 8 service clients
providers/azure/	Azure implementation (experimental)
providers/gcp/	GCP implementation (experimental)

Contributing

Contributions are welcome! Please see CONTRIBUTING.md for guidelines.

Areas for Contribution

• Additional AWS services (Lambda, DynamoDB, etc.)
• Azure and GCP service implementations
• Enhanced reporting and analytics
• Web UI dashboard
• Terraform/CloudFormation integration

License

This project is licensed under the Open Software License 3.0 (OSL-3.0). See the LICENSE file for details.

The OSL-3.0 is an OSI-approved open source license that:

• Allows commercial use, modification, and distribution
• Requires attribution and license preservation
• Includes a patent grant
• Requires derivative works to be licensed under OSL-3.0

Disclaimer

This tool can make actual cloud commitment purchases when used with the --purchase flag.

• Always verify recommendations before purchasing
• Test thoroughly in dry-run mode first
• Start with low coverage percentages
• Use instance limits for safety
• The authors are not responsible for unintended purchases or financial commitments

Support

• Issues: GitHub Issues
• Discussions: GitHub Discussions

Shameless Plug

This tool is brought to you by LeanerCloud. We help companies reduce their cloud costs using a mix of services and tools such as AutoSpotting.

Running at significant scale on AWS and looking for cost optimization help? We can help you avoid committing to suboptimal resources by rightsizing and other optimizations before purchasing commitments. Contact us.