Cloud Cost Optimization — Cut Your Infrastructure Bill Without Cutting Capability
You are spending $5,000/month on cloud infrastructure and you are not sure what half of it does. Sound familiar? Most cloud bills are 30-50% higher than they need to be due to over-provisioned instances, forgotten resources, missing reserved capacity, and architectures that were never optimized for cost. We audit your cloud spend, identify savings, and implement changes that reduce your bill while maintaining or improving performance.
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Where Cloud Money Goes to Waste
Cloud cost waste follows predictable patterns across every company we audit:
Over-provisioned compute (25-40% of waste): Instances sized for peak load that runs at 20% utilization most of the time. An m5.2xlarge ($280/month) running at 15% CPU average should be an m7g.large ($59/month) with auto-scaling for the rare peaks. Multiply this by every instance in your account.
Forgotten resources (15-25% of waste): Unattached EBS volumes from terminated instances ($0.10/GB/month adds up). Elastic IPs not associated with running instances ($3.60/month each since the 2024 pricing change). Old snapshots, unused load balancers, idle NAT gateways, and development environments that were never shut down.
Missing commitments (15-20% of waste): Stable workloads running on on-demand pricing instead of Savings Plans or Reserved Instances. A 1-year Savings Plan saves 30-40%. A 3-year commitment saves 50-60%. If you have workloads that have been running for 6+ months without interruption, you are overpaying.
Data transfer (10-15% of waste): Cross-AZ data transfer ($0.01/GB each way), NAT Gateway processing ($0.045/GB), and internet egress add up silently. VPC endpoints for S3 and ECR eliminate NAT costs for image pulls and object access. Keeping traffic within the same AZ where possible reduces cross-AZ charges.
Architecture inefficiency (variable): Running a dedicated RDS instance when Aurora Serverless would auto-scale with demand. Using Lambda for always-on workloads when a Fargate service is cheaper. Storing infrequently accessed data in S3 Standard instead of S3 Intelligent-Tiering. These require architectural changes but often provide the largest savings.
Our Cost Optimization Process
Cost Audit: We analyze your cloud bill using Cost Explorer, detailed billing reports, and resource-level cost allocation. We identify the top cost drivers by service, region, and tag. We correlate costs with resource utilization data from CloudWatch to find the gap between what you pay for and what you use.
Quick Wins (week 1): We implement immediate savings: terminate unused resources, resize over-provisioned instances, delete unattached volumes and old snapshots, add S3 lifecycle policies, and configure auto-scaling for non-production environments. These changes are low-risk and typically save 15-25% of the monthly bill.
Commitments (week 2): Based on your stable workload profile, we recommend Savings Plans or Reserved Instances with specific term and payment options. We calculate the break-even point and risk for each commitment. We never recommend 3-year commitments for workloads that might change — 1-year plans with flexibility are the safer default.
Architecture Changes (weeks 3-4): We implement deeper optimizations: migrating to Graviton instances (20% cheaper, often faster), moving to Aurora Serverless for variable-load databases, adding caching layers to reduce database instance requirements, configuring spot instances for fault-tolerant workloads, and restructuring data transfer paths to minimize cross-AZ and NAT charges.
Ongoing Monitoring: We set up AWS Budgets with alerts on spending anomalies, configure Infracost in your Terraform pipeline for cost-aware infrastructure changes, and create a monthly cost dashboard that tracks spending trends by service and team. Cost optimization is not a one-time project — it is an ongoing practice.
What You Get
A comprehensive cloud cost optimization engagement:
- Cost audit — service-by-service analysis with waste identification and savings estimates
- Quick-win implementation — unused resources cleaned, instances right-sized, lifecycle policies added
- Commitment recommendations — Savings Plan or RI analysis with break-even calculations
- Architecture optimization — Graviton migration, spot instances, caching, and transfer reduction
- Cost monitoring — budgets, anomaly alerts, and monthly cost dashboards
- Infracost integration — cost impact on every infrastructure PR
- Savings report — documented before/after monthly costs with projected annual savings
- Tag-based allocation — per-team and per-service cost visibility
Why Anubiz Engineering
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