The Multi-Cloud Dilemma: How to Control Costs Without Slowing Down Innovation

Today, enterprise innovation is increasingly powered by hybrid, multi-cloud infrastructures. Nearly 90% of enterprises in the Asia/Pacific region have deployed meaningful workloads on multiple public clouds, with India ahead of the curve.

The country’s IT/ITeS sector – a high-growth industry that contributes over 7.5% to India’s GDP – is at the forefront of multi-cloud adoption. However, as adoption deepened and scaled across the sector, an unexpected paradox began to surface – spiralling multi-cloud costs. In fact, over 70% enterprises reported budget overruns in their organization’s cloud spending.

So, how did an inherently cost-effective model like multi-cloud spiral out of control? Let’s explore.

The Case for Multi-cloud Adoption

To grasp the full impact of rising multi-cloud costs, it’s essential to first understand what drove the IT/ITeS sector to adopt this model at such a rapid pace. Their unique operating models and round-the-clock operations demand infrastructures that are always available and quickly scalable.

Here’re a few strategic advantages that drove IT/ITeS organizations to rapidly embrace the multi-cloud:

• Vendor independence for flexibility, choice and control
• Best-of-breed solutions that align with specific workload needs.
• Compliance to data sovereignty laws, industry standards, and client mandates across multiple geographies.
• Faster go-to-market for new services and products without being constrained by a single cloud environment.

All these factors, along with the critical benefit of avoiding costly outages, help organizations save costs while gaining greater agility and control.

Why Managing Cloud Costs Has Become a Challenge

Despite its clear advantages, multi-cloud presents several challenges for IT/ITeS organizations—cost management being one of the most significant. Managing cloud spending was reported as the top challenge over both security and skills in the Flexera 2024 State of the Cloud Report. For IT/ITeS firms, this hits even harder as small inefficiencies can impact client margins and delay innovation.

IT leaders recognize that the very flexibility that makes multi-cloud attractive also makes it fragmented and difficult to optimize, because:

• Managing multiple contracts, SLAs, and pricing models can be a nightmare for organizations. Cost consolidation remains harder in practice, with majority of organizations not even attempting to unify cloud expenses across providers.
• Fragmented tooling, visibility, and control panels: Each cloud provider comes with its own set of management consoles, APIs, monitoring tools, and dashboards. Gaining centralized view is often a big task. Organizations struggle to monitor usage, track spending, enforce security policies, or detect anomalies across all clouds.
• Cloud sprawl and poor resource hygiene: Idle VMs, unused storage, and abandoned test environments often go untracked across providers
• Overprovisioning driven by fear of latency or downtime leads IT/ITeS teams to allocate more resources than needed as a safety buffer. Reports show that over 35% of cloud spend is wasted on unused resources!

The Hidden Cost of Always-On ITeS Operations

In services environments, it’s not unusual for teams to forget decommissioning resources that were spun up for testing, development, or temporary workloads. Idle virtual machines, unused storage volumes, or containers often run without active workloads.

A classic example – the development team launches a test environment on one cloud platform, while another team does the same on a different platform— no coordination or cleanup. These idle or underused assets continue to incur charges month after month, often without delivering any business value.

Hidden or less-visible charges thrive in multi-cloud environments. Data egress fees or data transfer fees can spike unexpectedly if workloads communicate across clouds. Another common issue is unused reserved instances—organizations may commit to long-term capacity for discounts but fail to fully utilize them.

Resource-intensive AI/ML workloads demand continuous compute power, GPU usage, and data access. In many IT/ITeS environments, these workloads run around the clock for real-time analytics, model training, or inferencing. Global 24/7 operations mean workloads and applications must remain highly available across time zones and client regions, leading to significant cost overruns.

Project teams struggle to accurately forecast spend. Delivery costs overshoot initial estimates, impacting margins. Budget unpredictability leads to delays in R&D or new service launches.

The result: Finance can’t predict. Tech can’t optimize. Leadership can’t scale confidently.

Traditional Cost-Saving Tactics No Longer Work

In an ideal world, multi-cloud environments shouldn’t suffer from cost overruns—what makes the difference is how they’re managed and optimized. Yet, that’s rarely the case.

Many organizations try to replicate their legacy approach in multi-cloud environments. But, the traditional tools and monthly reports aren’t sufficient for a highly dynamic environment.

Why? Because cloud consumption is decentralized — owned by DevOps, product teams, and client delivery units. Meanwhile, finance teams operate on lagging indicators, not real-time usage data.

This is where modern Cloud Optimization strategies play a critical role. More and more organizations are adopting effective frameworks and disciplines to smartly navigate their cloud cost management journeys. They are recognizing the need for real-time visibility and tighter collaborations between different functions like technical, operations and finance for effective cost management.

The IT/ITeS sector, in particular, is leading this shift toward governance-first cloud practices, with adoption accelerating rapidly worldwide.

Shifting to Automation & AI for Cloud Optimization

Automation is the front and center of an effective cost management strategy. Here’s how organizations are leveraging automation to control cloud spend.

• AI/ML-powered right-sizing and anomaly detection play a crucial role in optimizing spend and reducing waste across complex cloud environments. AI/ML also helps detect unusual fluctuations in cloud spend or usage by flagging potential misconfigurations, forgotten workloads, or unauthorized usage.
• Smart tagging ensures better cost visibility by tracking spending at a granular level, identify cost drivers, and allocate expenses accurately. Usage policies can be created to automatically control and govern cloud resource behavior
• Auto-decommissioning detects idle or underutilized assets in dynamic IT/ITeS setups and automatically removes or suspends them, preventing unnecessary charges.

External Expertise: The Missing Piece

With multi-cloud adoption on the rise, IT/ITeS organizations are grappling with greater operational complexity. To manage this effectively, many are now relying on Managed Service Providers (MSPs) for streamlined governance, visibility, and optimization across cloud environments.

For mid-to-large IT/ITeS firms, partnering with MSPs can significantly simplify multi-cloud operations and cost management.

MSPs bring in cross-cloud governance frameworks that standardize policies, access controls, and best practices across cloud platforms. They provide centralized visibility dashboards that consolidate usage, cost, and performance metrics in one place. MSPs also set up tailored usage guardrails and assist with compliance requirements across geographies and clients.

Most importantly, they deliver 24/7 optimization services—right-sizing resources, automating clean-ups, and aligning infrastructure with delivery timelines to drive efficiency and cost savings.

Why CtrlS Cloud Optimize

Building an effective cloud optimization strategy is still a complex challenge. CtrlS’ Cloud Optimize offers practical solutions to address this. Cloud Optimize is designed for cloud-heavy industries like IT/ITeS that want to bring control back to cloud spend.

IT leaders leverage Cloud Optimize to:

• Monitor and analyze cloud consumption in real time
• Automate right-sizing, shutdowns, and scaling
• Consolidate multi-cloud visibility and policy enforcement
• Forecast usage and control cost variability across projects

Whether it’s offshore delivery, global SLAs, or AI experimentation, our focus is on helping you keep cloud costs optimized, transparent, and under control.

Conclusion: Driving Innovation at any Cost

In the IT/ITeS world, managing cloud spend isn’t just about saving a few bucks. It’s about mindfully creating a strategic advantage by optimizing the end-to-end environment and prioritizing what’s most important – delivery assurance, client profitability, and competitive edge.