Multi-cloud cost optimization insights for AWS users

Cloud costs can spiral out of control faster than you might expect—especially when managing workloads across multiple cloud providers alongside your AWS infrastructure. While multi-cloud strategies offer flexibility and prevent vendor lock-in, they introduce significant complexity to cost management. The good news? With the right approach, you can achieve transparency and optimization across your entire cloud ecosystem.

What is multi-cloud cost optimization?

Multi-cloud cost optimization involves strategically managing resource allocation, pricing models, and operational workflows across multiple cloud providers to minimize expenses while maintaining performance. For AWS-centric organizations, this means balancing AWS services with other platforms while leveraging AWS-specific tools for granular control.

The challenges are significant:

Cross-platform complexity: Tracking usage and costs across disparate cloud providers requires specialized tools and expertise
Resource fragmentation: Over-provisioning or underutilizing resources in AWS can lead to wasted spend—like paying for idle EC2 instances or oversized EBS volumes
Lack of unified visibility: Without centralized dashboards, identifying cost drivers becomes nearly impossible, especially when each provider speaks their own “billing language”

Why is tracking costs in multi-cloud environments so challenging?

According to industry research, approximately 80% of enterprises now use multiple clouds, making cost optimization increasingly complex. The difficulty stems from several factors:

Disparate billing systems: Each provider has unique pricing models and billing formats—AWS bills look nothing like Azure or GCP invoices
Inconsistent resource tagging: Making it difficult to allocate costs to specific departments or projects—imagine trying to determine which team is responsible for a particular spike in cloud spending
Limited native cross-cloud tools: Most cloud providers’ cost management tools focus on their own ecosystems, creating blind spots in your financial visibility

Think of it like managing multiple bank accounts with different currencies and fee structures—without a unified financial dashboard, you’re left piecing together the complete picture manually.

Essential cost optimization strategies for AWS users in multi-cloud environments

1. Implement rigorous rightsizing across all platforms

Rightsizing—adjusting resource sizes to match workload demands—can reduce costs by 20-50%. For AWS users, tools like AWS Compute Optimizer provide AI-driven recommendations for EC2 instances. Consider:

Analyzing CPU, memory, and storage utilization patterns over time (not just peak usage)
Downsizing over-provisioned resources—that t3.2xlarge instance might only need to be a t3.large
Consolidating workloads where appropriate to reduce the total instance count

For EBS volumes specifically, proper sizing and type selection can significantly reduce costs without sacrificing performance. For example, switching from general-purpose (gp2) to throughput-optimized (st1) volumes for log storage can cut costs by more than half.

2. Leverage AWS-specific discount mechanisms

AWS offers several powerful cost-reduction tools that should be core to your strategy:

Savings Plans: Commit to consistent usage for 1-3 years for discounts of 40-72%—ideal for steady-state workloads
Reserved Instances: For predictable workloads, offering similar savings with more specific resource commitments
Spot Instances: For flexible, interruptible workloads, providing up to 90% savings—perfect for batch processing, testing, and development

While managing these alongside other cloud providers’ discount programs adds complexity, the potential savings make it worthwhile. Consider tools that can track commitment utilization across platforms to maximize your return on investment.

3. Implement unified cost monitoring and governance

Visibility is essential. Consider these approaches:

AWS Cost Explorer + third-party tools: Use AWS’s native tools alongside specialized multi-cloud platforms to fill visibility gaps
Amazon QuickSight + FOCUS: This open-source standard enables unified cost reporting across AWS and other providers, creating a single pane of glass for financial analysis
Specialized FinOps tools for AWS: These AWS-compatible FinOps solutions provide deeper insights than native tools alone, helping you identify cross-platform optimization opportunities

A robust monitoring strategy is like having a financial advisor for your cloud spending—it identifies wasteful patterns before they become costly habits.

4. Optimize storage costs across platforms

Storage often represents a significant portion of cloud spend. Consider:

Lifecycle policies: Automatically transition data to lower-cost tiers based on age and access patterns—for example, moving infrequently accessed S3 data to Glacier storage
Deduplication: Eliminate redundant data across platforms to avoid paying multiple times for the same information
EBS optimization: Use EBS-optimized instances and consider ARM-based instances for better price-performance ratio when running I/O-intensive workloads

Remember that storage optimization isn’t just about the direct storage costs—it also affects your compute efficiency, backup expenses, and data transfer fees.

5. Implement auto-scaling across environments

Dynamic resource allocation based on demand is crucial:

AWS Auto Scaling: Configure for EC2 instances and other services to automatically adjust capacity based on real-time demand
Kubernetes auto-scaling: For container workloads spanning multiple clouds—a particularly effective strategy when you have similar applications running across different providers
Scheduled scaling: For predictable usage patterns (e.g., business hours vs. nights/weekends), reducing capacity during known low-traffic periods

Think of auto-scaling as having an automated resource manager that ensures you’re only paying for what you need, exactly when you need it.

6. Establish FinOps practices and cross-functional collaboration

Cost optimization is not just a technical challenge—it requires organizational alignment:

Form a FinOps team: Include representatives from engineering, finance, and operations to ensure all perspectives are considered
Establish clear ownership: Define who’s responsible for optimizing which resources to avoid the “tragedy of the commons” where nobody takes ownership
Regular cost reviews: Schedule recurring sessions to identify optimization opportunities and hold teams accountable for their cloud spending

The most successful organizations treat cloud costs as a shared responsibility, not just an IT expense.

Is multi-cloud actually cheaper?

The answer depends entirely on your implementation. Multi-cloud can increase costs through:

Additional management overhead and tool investments
Reduced volume discounts with any single provider
Duplicate services and data transfer costs between clouds

However, strategic multi-cloud can reduce costs by:

Leveraging each provider’s strengths (e.g., AWS for compute, GCP for specific committed use discounts on certain workloads)
Improving negotiating leverage with providers
Optimizing workload placement based on pricing models—running the right workload on the right platform

The key is having a deliberate strategy rather than an accidental multi-cloud environment that evolved without planning. Think of it like shopping at different grocery stores for specific deals rather than randomly buying items at whichever store you happen to visit.

Automating multi-cloud cost optimization

Manual optimization quickly becomes unsustainable as environments grow. Consider automation for:

Resource rightsizing recommendations
Unused resource identification and cleanup
Reserved capacity management
Anomaly detection and alerting

Hykell’s automation platform can reduce AWS costs by up to 40% through automated optimization, allowing you to focus resources on managing your multi-cloud strategy more effectively. Automation transforms cost optimization from a periodic project to a continuous process embedded in your operations.

Building your multi-cloud cost optimization roadmap

Start with these practical steps:

Conduct a comprehensive audit across all cloud platforms to identify quick wins and establish your baseline
Implement unified tagging standards to enable accurate cost allocation and cross-platform reporting
Deploy monitoring tools that provide cross-cloud visibility into usage and spending patterns
Establish governance policies for resource provisioning to prevent cost sprawl before it begins
Train teams on cost-aware development and operations to build a culture of cloud financial responsibility

Remember that cost optimization is an ongoing process, not a one-time project. The cloud landscape and your requirements will continue to evolve, requiring regular reassessment of your strategy.

By implementing these strategies while leveraging AWS-specific tools and automation, you can achieve significant cost savings across your multi-cloud environment without compromising performance or flexibility. The result? More budget available for innovation rather than infrastructure maintenance.