OCI Cost Control: Free Tools Every Developer Should Master

Always Free services that keep working forever:

• •2 Oracle Autonomous Databases (20GB each) with automatic scaling and tuning
• •2 Compute VMs (AMD-based, 1/8 OCPU each) perfect for lightweight applications
• •200GB total Block Volume storage with backup capabilities
• •10GB Object Storage for static content and backups
• •10TB monthly outbound data transfer
• •Flexible load balancer (10Mbps) for high availability

Strategic applications:

• •Development and testing environments (saves $2,000-3,000 annually per team)
• •Monitoring and alerting infrastructure
• •Static website hosting and content delivery
• •Database development instances
• •CI/CD build agents

Cost control strategy:

1. Design compartments around cost responsibility (teams, projects, environments)
2. Implement quota policies to prevent overspending within compartments
3. Set up compartment-specific budgets with appropriate alert thresholds
4. Use compartment inheritance for consistent governance policies

Example compartment structure:

Root Compartment
├── Production
│ ├── Database Services (quota: 20 cores max)
│ ├── Application Services (quota: 50 cores max)
│ └── Network Services (quota: 5 load balancers max)
├── Development
│ ├── Shared Development (quota: 10 cores max)
│ └── Sandbox (quota: 5 cores max)
└── Shared Services
 ├── Monitoring (uses Always Free tier)
 └── CI/CD (quota: 10 cores max)

Strategic applications:

• •Multi-cloud architectures without egress penalties
• •Global content distribution at dramatically lower costs
• •Data backup and disaster recovery across regions
• •Analytics and machine learning data pipelines

Cost comparison for a data-heavy application:

Cost optimization features:

• •Automatic scaling based on workload demands (scale down during low usage)
• •Intelligent storage compression reducing storage costs by 50-70%
• •Self-tuning that improves performance while reducing resource requirements
• •Automated backup optimization with intelligent retention policies

Optimization approach:

1. Monitor actual CPU and memory utilization for existing workloads
2. Right-size instances to match actual usage patterns
3. Use OCI's single-core scaling to eliminate overprovisioning
4. Implement auto-scaling for variable workloads

Cost impact example:

Tiering strategy:

• •Standard Tier: Frequently accessed data (default)
• •Infrequent Access Tier: Data accessed monthly or less (50% cost reduction)
• •Archive Tier: Long-term retention data (80% cost reduction)

Lifecycle policy example:

{
"rules": [
 {
"name":"DataLifecycle",
"status":"Enabled",
"transitions": [
 {
"days": 30,
"storageClass":"InfrequentAccess"
 },
 {
"days": 365,
"storageClass":"Archive"
 }
 ]
 }
 ]
}