Best Practices for Global Capability Centers (GCCs): Managing Cloud Costs and Optimizing Infrastructure Spend

The Trials and Tribulations of Global Capability Centers in 2025

Even with booming emerging technologies such as AI and AR/VR, Global Capability Centers (GCCs) are continuing to grow. According to one study from LinkedIn, “The market size of GCCs [in 2024] expanded to $64.6 billion, with ambitions to grow this figure to $105 billion by 2030.” GCCs are constantly finding new use cases, scaling in different ways, and adding new users, leading to exponential growth in cloud costs and usage.

In 2025, container platforms such as Kubernetes continue to gain traction and are being used by more and more Global Capability Centers. The nature of Kubernetes allows for rapid autoscaling services and allows developers to make faster deployments. With faster build times and automatic scaling of key infrastructure come ever-increasing cloud costs. Managing cloud costs and resource utilization in real-time becomes more and more challenging.

Attributing costs to different teams, business units, and product lines becomes more critical as your team grows and GCCs add on more and more business units. New services and functions lead to more cloud utilization across numerous teams and departments and can cause a headache when trying to understand where your resources, time, and money are being spent. In 2025, cloud cost management and real-time optimization of resources will become more and more commonplace amongst every Global Capability Center.

So, without further ado, let’s investigate some of the upcoming trends in cloud cost management and best practices for GCCs to start paying attention to.

Current Cloud Cost Trends

Cloud costs can easily spike in numerous ways. Every GCC runs into scaling concerns and often needs to be able to manage multiple cloud providers and ever-changing pricing models. Here are just a few popular trends shaping cloud cost management in 2025:

• Usage-Based Pricing Gains Popularity: More cloud providers and GCCs are adopting granular usage-based pricing models, making it more difficult for GCCs to track consumption, and overall spend, and manage finances in real time to avoid surprise bills.

• Multi-Cloud and Hybrid Cloud Strategies Grow: Companies are leveraging resources and services from all major cloud providers, using different parts of AWS, Azure, and GCP to optimize performance in real-time and avoid vendor lock-in. However, managing resources across multiple platforms introduces complexity around managing costs and understanding usage.

• AI-Driven Cost Increases and Optimization Opportunities: Increased adoption of machine learning and the rise in GenAI leads to even faster scaling of cloud costs. On the flip side, AI and ML in the cloud are also being used to help users analyze cloud usage patterns and recommend cost-saving measures before they hurt your bottom line.

The Evolution of FinOps

FinOps (short for Financial Operations) has become the gold standard practice for efficiently managing cloud spend. FinOps is a methodology that brings financial accountability to DevOps teams. As FinOps adoption has increased collaboration and accountability across teams, it has now evolved into an essential practice for GCCs that are looking to continuously optimize cloud expenses.

Key Principles of FinOps

• Tight Collaboration Between Finance and Engineering Teams: Cloud cost management is no longer just a responsibility of the finance or DevOps team. Cross-functional collaboration ensures that costs are considered at every stage of development and that teams take more ownership over their cloud costs and usage.

• Real-Time Cloud Cost Monitoring: Global Capability Centers need to be adopting real-time dashboards and automated alerts ASAP. Higher visibility and actionable anomaly detection help prevent unexpected cost surges and help teams resolve incidents faster.

• Unit Economics and Cost Allocation: Businesses are shifting towards detailed cost allocation models that track spend at the most granular levels – tracking dollars spent per feature, per customer, or per business unit. Unit economics shows the overall efficiency of your GCC and can help guide resource allocation in the future.

• Automation and Control: Automated policies and controls are being implemented to optimize cloud resources in real time. Shutting down idle instances, rightsizing VMs and containers, and enforcing budget limits can help teams maintain operational efficiency in the cloud without any extra effort.

Also read: Top FinOps Tools to Consider in 2025

GCC Considerations for Cloud Cost Management

Unlike traditional businesses, GCCs face unique cloud cost challenges due to their common rapid-scaling, multi-tenant architectures. Many GCCs run into high storage and compute demands, and many of these processes can never be downsized again. So, it’s important that you consider the following when managing cloud spend for a high-growth business:

• Cost Allocation and Shared Infrastructure: Global Capability Centers are continuously serving multiple customers from a shared infrastructure, sometimes even across multiple clouds. Intelligent tagging strategies and cost allocation tools like Amnic ensure that cloud costs are allocated correctly to different cloud resources, customers, and/or product lines. Accurate cost allocation leads to more efficient investments into your cloud environments and brings more transparency to financial teams as to how the company is performing against budgets and financial forecasts.

• Optimizing Storage Costs: As GCCs generate vast amounts of data, cloud storage solutions (such as Amazon S3 buckets) can easily build up over time. Tiered storage systems can help optimize costs by automatically moving infrequently accessed data to lower-cost storage options.

• Network and Data Transfer Cost Management: Many GCCs overlook network egress fees, which can add up quickly when transferring large volumes of data between cloud regions or providers. Optimizing API calls and leveraging CDNs can help reduce these expenses.

• Compute Costs: Compute costs are one of the biggest contributors to cloud costs when services autoscale out of control. Global Capability Centers can easily run into a spike in the usage of compute resources such as EC2, quickly leading to unexpected cloud bills. Tight management of compute resources can drive a massive reduction in cost without actually hindering end-user experiences.   

Continuous Cost Optimization Tips for a GCC

Cloud cost optimization is not a one-time exercise – it requires continuous monitoring and constant refinement. FinOps adoption leads to greater collaboration around the cost optimization practice and leads to a culture of shared ownership. In order to continuously drive cost optimization at your Global Capability Center, here are some proven strategies:

• Implement Autoscaling and Rightsizing: Both overprovisioned and underprovisioned resources lead to wasted spend and negative customer experiences. Autoscaling policies and rightsizing recommendations in a tool like Amnic can help you quickly match compute capacity to real-time demand.

• Leverage Reserved Instances and Savings Plans: For GCCs that run more predictable workloads, Reserved Instances (RIs) and Savings Plans can significantly reduce cloud expenses compared to on-demand pricing.

• Enable Tighter Cost Control and Management Policies: Amnic allows you to set budgets, configure cost alerts, monitor spending patterns, and take fast action to shut down unused resources to prevent overspending. A collaborative environment for cost control and visibility leads to a better understanding of your team’s cloud usage, driving more efficient decisions at every level.

• Regularly Audit and Optimize Cloud Spend: Weekly, monthly, and/or quarterly FinOps reviews can help you identify idle resources, misconfigured instances, and cost spikes, allowing teams to make data-driven decisions. Greater transparency brought through easily-shared Amnic reports and dashboards can make this even easier. 

Also read: Best Practices for SaaS Companies

Examples of Successful GCCs

UNI’s Cloud Cost Observability Overhaul

UNI’s Problem: The massive growth in the credit card industry has led to a massive boom in cloud usage and expenses for FinTech companies like Uni. The industry’s rapid growth and massive scale have been primarily driven by seamless, cloud-technology-driven financial experiences. As Uni’s user base and technology scale, they can incur problematic cloud bills and require a way to intelligently optimize their cloud infrastructure in real-time.

Who They Are: Uni drives innovative FinTech solutions in India, building smooth onboarding processes, personalized offers, and better mobile apps focused on positive customer experiences. The industry has achieved an annual growth rate of 20% over the past 5 years, with credit cards exceeding 78 million in July 2022.

How They Benefit: By using Amnic and continuously driving FinOps practices, Uni has enhanced real-time visibility into cloud spending, enabling data-driven decisions and streamlined cost governance for AWS and Kubernetes. 

What They Did:

• Optimized Amazon CloudWatch: By fine-tuning Amazon CloudWatch configurations, Uni reduced unnecessary monitoring costs while retaining essential performance insights.

• Optimized Instance Type Recommendations for EC2: Leveraging data analytics in Amnic, the Uni team received recommendations for optimal EC2 instance types, ensuring the best performance-to-cost ratio based on Uni workload requirements.

• Rightsized Kubernetes Nods and Pods: A thorough analysis of Kubernetes usage identified opportunities to right-size nodes and pods, aligning resources more closely with actual demand and avoiding over-provisioning. This allowed the engineering team to take action where necessary and proactively use recommendations that enabled them to run a lean cloud infrastructure.

• Achieved 360-Degree Cost Visibility in 24 Hours: Uni was able to leverage Amnic’s full suite of cost optimization and observability features in just one day. With stringent security protocols already in place in the Amnic platform, SOC 2 Type 2 compliance, GDPR, and ISO:27001 certifications were in place out-of-the-box.

Business Outcomes:

• Uni reduced its monthly cloud spend by mitigating overprovisioned resources and trimming unused services, creating a more optimized, predictable cloud environment.

• Acting quickly on the insights from Amnic led to a 20% reduction in cloud infrastructure expenses in just one month.

• Closer cross-team collaboration sped up cost-related decisions and product feature rollouts, ultimately accelerating new feature delivery without impacting cloud efficiency.

• The entire engineering organization benefited from real-time insights into resource allocation, enabling them to quickly identify performance bottlenecks and optimize environments. This transparency fostered a culture of accountability, where developers could validate whether their deployments aligned with financial goals.

Key Stat: Uni lowered overall cloud infrastructure costs by 20% across all AWS and Kubernetes resources within the first month of implementation.

Jiffy’s 50% Lower Cluster Costs

Jiffy’s Problem: Jiffy is built on AI and no-code technology, requiring massive cloud computing and processing investments. Businesses like Jiffy that provide automation technologies and are built on autoscaling Kubernetes environments can easily run into surging, unpredictable cloud costs. Jiffy needed a way to quickly detect anomalies in their cloud spending, take action around reasonable rightsizing recommendations, and deep-dive into Kubernetes costs at every level.

Who They Are: Jiffy provides a full-stack platform that enables banks, financial services companies, and Fortune 500 organizations to solve large-scale operational and efficiency challenges. Their ready-to-deploy HyperApps help business users improve customer experience and realize the true value of digital transformation and cloud adoption. With Amnic, Jiffy gets greater visibility around the efficiency of their cloud and gives the team a way to control and optimize spending habits before they hurt the bottom line.

How They Benefit: With Amnic’s cloud cost observability platform, Jiffy was able to drive a dramatic decrease in Kubernetes cluster costs, allowing more agile development, greater cost visibility, and improved resource utilization.

What They Did:

• Recommendations for Rightsizing Instances and Pods: Amnic’s platform helped analyze Jiffy.ai's Kubernetes clusters comprehensively, identifying opportunities for right-sizing instances and pods to match workload demands accurately.

• Cluster, Instance, and Node-Level Views: With granular visibility into cluster, instance, workload, and node-level metrics, Amnic was able to pinpoint inefficiencies and areas for optimization effectively. With greater visibility and control, Jiffy was able to improve cluster health, and resource governance, and roll out policy changes without disrupting production.

• Greater Visibility into Kubernetes Utilization: By leveraging the visualizations and recommendations provided by Amnic, Jiffy.ai gained deeper insights into Kubernetes utilization patterns, allowing them to make informed decisions about resource allocation and scaling strategies.

• Enhanced Cloud Cost Reporting and Monitoring for FinOps Teams: With enhanced transparency into cloud operations, Jiffy could closely monitor and receive reports on cloud costs and trends, more closely aligned with specific business objectives so the team could approve new optimization initiatives faster.

Business Outcomes:

• By rightsizing their Kubernetes environment, Jiffy cut cluster costs by 50%. The resultant savings were funneled into research and development of new features.

• Beyond direct cost savings, engineers found it easier to experiment with new services and microservices due to clearer organizational guidelines. This also boosted morale, as teams felt confident that testing new features wouldn’t create hidden or runaway expenses.

Key Stat: Jiffy slashed Kubernetes costs by 50% in three months.

Oftentimes, FinOps and DevOps teams struggle to quickly identify exactly where rogue cloud costs come from and how to take action. Real-time anomaly detection and recommendations tackle this issue, giving you an actionable place to start in seconds. No more digging through multiple accounts and clouds looking at savings plans and reserved instances or finding resource-level opportunities for rightsizing your Kubernetes clusters. 

Staying on Top of Your Cloud Infrastructure Costs

As Global Capability Centers like yours continue to scale throughout 2025, cloud cost management will continue to be a key factor in maintaining profitability and operational efficiency. The rise in FinOps adoption, real-time cost monitoring, and AI-driven tools have made it easier than ever to track and control cloud expenses, even as incurring cloud expenses also becomes easier. So, proactive planning and collaboration across finance, engineering, and product teams is even more essential to keeping costs down while maintaining operational efficiency.

By staying on top of current cloud cost trends, implementing robust FinOps practices, and continuously optimizing infrastructure spend, GCCs can quickly ensure they’re not only keeping costs under control but also driving the right investments across their entire cloud ecosystem.

Don’t hesitate to sign up for a 30-day free trial of Amnic or reach out for a personalized demo to learn how a holistic cloud cost observability platform can help you reduce costs and improve the efficiency of your cloud infrastructure.