cost-optimization

Cloud cost optimization reduces AWS and GCP spend by implementing Reserved Instances, Spot Instances, Savings Plans, and right-sizing compute resources. It analyzes utilization data to identify under-provisioned machines and baseline workloads, cutting expenses while maintaining required performance levels.

Optimizing S3 storage tiers lowers cloud spend by moving infrequently accessed data to Standard-IA or Glacier tiers. This strategy targets object storage costs specifically, ensuring data resides in the most cost-effective tier based on access patterns and retention requirements.

Setting up budget alerts and anomaly detection monitors cloud infrastructure costs by establishing automated notifications for unusual spending spikes. It enables governance through showback and chargeback mechanisms, mapping resource consumption directly back to responsible teams.

Preemptible VMs and Spot Instances suit fault-tolerant workloads, not baseline operations. For baseline workloads, Savings Plans and Committed Use Discounts provide predictable pricing. Autoscaling tuning ensures compute resources match demand, maximizing efficiency across varying traffic levels.

CDN configurations reduce network egress charges by caching content closer to end users, minimizing expensive data transfer requests from origin servers. This network efficiency strategy significantly lowers outbound data processing fees across cloud platforms.

Finding underutilized EC2 instances cuts compute expenses by analyzing CPU utilization metrics over a specific period, such as the past 7 days. This analysis identifies machines suitable for right-sizing or termination, immediately reducing wasted infrastructure spend.