The cloud mirage: Why legacy applications in IaaS are holding you back

For many organizations, the answer is no. The promise of cloud—where supply and demand are always in alignment, where costs are optimized, where innovation moves at the speed of business—is still frustratingly out of reach.

And the culprit? A legacy application portfolio that was built for another era. Even when running in an IaaS (Infrastructure as a Service) environment, these applications drag down performance, inflate costs, and limit agility. Here’s how:

1. You’re not actually optimizing resources

One of the biggest promises of cloud computing is dynamic scalability—the ability to scale up when demand is high and scale down when it’s low, ensuring that resources (and costs) are always right-sized. But legacy applications, even when running on virtual machines in the cloud, weren’t designed to scale elastically. They expect fixed infrastructure, which means:

• You’re still overprovisioning resources to meet peak demand, leaving expensive cloud capacity underutilized most of the time.
• You can’t truly take advantage of serverless or containerized models, which maximize efficiency and minimize waste.
• Your carbon footprint stays unnecessarily high because you’re not optimizing compute power based on actual usage.

Simply put, without modernizing application architectures, cloud remains just another costly data center—only now, it’s someone else’s hardware.

2. You’re paying for a bloated, legacy skillset

When your applications are still rooted in decades-old architectures, you need people who understand those architectures—and that’s expensive.

• You’re forced to keep teams with expertise in aging programming languages (COBOL, PowerBuilder, classic .NET, etc.) and old-school database technologies.
• Your cloud engineers must work around monolithic architectures, instead of leveraging modern cloud-native approaches like microservices, event-driven systems, and managed services.
• Recruiting and retaining talent becomes an uphill battle, because new developers want to work with Kubernetes, serverless, AI-driven development—not legacy systems duct-taped to VMs.

The result? High costs, slow hiring, and a growing tech debt that stifles innovation.

3. You’re stuck in the slow lane for innovation

The rapid evolution of Generative AI, intelligent automation, and hyper-personalized user experiences is changing the way companies engage with customers and employees. But if your applications are still tightly coupled, running on outdated codebases, and dependent on legacy integrations, adding these modern capabilities is a nightmare.

• AI-powered features like natural language interfaces, real-time recommendations, and automated workflows require modular, API-first architectures. If your apps don’t support that, you’re stuck watching competitors pass you by.
• Rapid experimentation and iteration become impossible when making even minor updates requires navigating a web of interdependencies.
• Cloud-native DevOps and CI/CD practices don’t fully apply when your core applications still require manual updates, downtime windows, and rigid release cycles.

If you’re trying to embed AI, improve user experiences, or speed up innovation cycles, legacy application constraints will slow you down at every step.

4. Your data is stranded on digital islands

Data-driven decision-making is only as good as the data you can access. But many legacy applications were built long before modern data-sharing principles came into play. They:

• Store critical information in siloed databases that don’t integrate well with cloud-based analytics tools.
• Lack real-time data streaming capabilities, making it difficult to unify and analyze data across the enterprise.
• Are locked into old licensing models, preventing organizations from shifting to scalable cloud-based data lakes, warehouses, and AI-driven analytics platforms.

That means your company is still making fragmented decisions based on incomplete data, rather than leveraging the full power of cloud-scale analytics, AI-driven insights, and automated decision-making.

Breaking free: The case for modernization

If your organization has simply lifted-and-shifted legacy applications to the cloud, you’re not truly unlocking the value of cloud. The path forward requires modernizing application portfolios, including:

• Refactoring monolithic apps into cloud-native architectures (microservices, serverless, and API-driven models).
• Replatforming legacy workloads onto managed cloud services that handle scalability and optimization automatically.
• Retiring obsolete applications and consolidating redundant systems to reduce complexity.
• Reimagining how applications deliver value, leveraging AI, automation, and intelligent user experiences.

The bottom line

Cloud isn’t just about moving workloads—it’s about unlocking business agility, efficiency, and innovation. If your legacy applications are still forcing you to overprovision resources, maintain outdated skillsets, slow down innovation, and fragment your data strategy, then you haven’t truly completed your cloud journey.

It’s time to move beyond just being “in the cloud” to actually leveraging the cloud—and that starts with application modernization.

Sogeti has helped hundreds of clients modernize their application portfolios. With our best-in-class accelerators and tools, our broad base of skillsets across the software technology landscape, our depth in AI-Amplified Agile Quality Engineering and automation, and our strong alliances across all major Hyperscalers, we are ready to help jumpstart your modernization journey.