Transforming Logistics: Hosting the Future of Data in Container Terminals

The amount of data available globally is rising at a rapid rate. According to a Forbes Report, it’s predicted that 181 zettabytes of data will have been created by 2025 – the equivalent of 354 billion iPhone 17s with 512 gigabytes of storage. This would require every human on Earth to own 44 iPhones, making Apple the most valuable company in history. While Steve Jobs would likely be delighted, the challenge lies in processing this massive flood of data – and this is where Artificial Intelligence (AI) takes the lead. Viewed through an operational lens, cloud-based data storage and on-premises hosting represent the digital factories that keep our intelligent machinery running – one scalable and shared, the other locally controlled and purpose-built. Choosing between these infrastructures defines how efficiently organizations can feed, train, and deploy AI systems. 

The IT Backbone of Digital Terminals

Within AI, Machine Learning (ML) refers to algorithms that improve their performance by learning from data rather than relying on predefined rules. These models enable the processing of vast and heterogeneous datasets by identifying patterns, generating predictions, and supporting automated decision-making. In the context of container terminals, the ability to derive optimized, data-driven recommendations in real time is critical. A single barge arrival, for example, triggers a cascade of interdependent operational decisions regarding berth allocation, equipment scheduling, and yard capacity management. Fast and well-founded decisions are therefore essential to maintain efficiency and service reliability in such complex environments.  

Container terminals rely on highly available, secure, and efficient IT systems to coordinate container flows between ship, rail, and truck. When it comes to hosting these critical systems, operators face a strategic choice: invest in on-premises infrastructure or leverage cloud-based data storage? Both approaches offer clear advantages and trade-offs. The question: Is local computing still up-to-date in the world of digital terminals? In this article, we’ll shine light on key contrasts. 

Availability and Deployment Speed 

Cloud systems do not have to be set up for individual operators; they are ready for immediate use. On-premises deployment can sometimes stretch into months, involving procurement, hardware installation, and network configuration, in addition to internal compliance, regulatory, and governance alignment. Meanwhile, cloud providers can reuse existing infrastructure, container orchestration frameworks, and automated deployment pipelines to accelerate provisioning. Take a cloud-based service like Apple iCloud, for example: When you decide to subscribe to iCloud, no one needs to deploy a dedicated system for you. The service is simply available, and thanks to the scalable infrastructure, you can seamlessly use the same platform that millions of others are already using. Moreover, Apple performs numerous updates every day without you even noticing – there’s no downtime.  

The in-house approach demands stakeholder coordination, facility preparation, and rigorous planning, causing delays that cloud models often avoid. As a result, terminals seeking rapid availability should consider cloud computing due to its operational readiness and scalability. 

Scalability: Adapting to Dynamic Demand 

Many terminal operators often assess their infrastructure requirements based on current workloads. In an on-premises setting, hardware can be dimensioned according to steady, predictable demand, which may result in efficient resource utilization in stable environments.  However, the strategic advantage of cloud-based data storage lies in its flexibility: Cloud computing can instantly allocate additional capacity to accommodate demand fluctuations. This includes scenarios such as seasonal traffic peaks. To achieve a similar level of scalability with on-premises infrastructure, the local infrastructure would require a far greater amount of space, servers, and racks. 

Data Sovereignty and Security 

Security and compliance remain crucial considerations, given their role as part of critical infrastructure. On-premises systems provide operators with direct control over sensitive operational data and allow for strict, customized security policies. This can be particularly important in workflows involving customs, freight documentation, or port authority interfaces, where accountability, confidentiality, and data integrity are critical requirements in inter-organizational processes. But although on-premises offers maximum control, major cloud providers offer extensive certifications (ISO 27001, SOC reports, GDPR-aligned services) and advanced security mechanisms. This reduces the compliance burden for terminals without large in-house IT teams. At the same time, hybrid models are emerging as a pragmatic bridge: highly sensitive or mission-critical workloads remain on-premises, while scalable tasks such as analytics, machine learning, or IoT data ingestion are increasingly outsourced to cloud platforms. 

Future Visions:  

Recent data and market forecasts support the direction toward more adoption of cloud computing, especially driven by AI, digital transformation, and evolving regulatory frameworks: 

The global public cloud market is projected to grow at a compound annual growth rate (CAGR) of ~10-13%, according to research by SNS Insider – possibly even more in domains that integrate artificial intelligence and machine learning. A recent market summary by Grand View Research expects the public cloud market to reach USD 2.3 trillion by ~2032, growing from a base of around USD 700-750 billion today. In Europe, data sovereignty and compliance have become decisive factors for cloud adoption. The European Data Strategy and GAIA-X, an industry-driven initiative aiming to build a secure, transparent, and sovereign data infrastructure based on European values and standards, explicitly emphasize these requirements. Recent studies underline that GAIA-X aims to strengthen Europe’s digital sovereignty by ensuring transparent governance, secure data exchange, and local data residency. 

A prime example of the cloud transformation is underway in Frankfurt. Germany is rapidly cementing its role as one of Europe’s leading data center hubs, with its market having roughly doubled in size over the past five years. With providers like Yondr, Colt DCS, Firstcolo, and Maincubes quickly expanding, many new sites are designed with sovereign cloud or local data residency options, which directly address the data-sovereignty and compliance concerns of European terminal operators, enabling the switch from on-premises to cloud. 

Conclusion: Balancing Trust, Control, and Innovation 

Cloud-based data storage is not a universal solution, as adoption decisions are highly context-dependent and influenced by organizational, operational, and regulatory conditions. Nevertheless, current market dynamics indicate strong momentum toward cloud-based infrastructures. A crucial factor that has not been mentioned so far is trust. While we believe strongly in the advancements of cloud-hosting ourselves, we know that on-premises still remains preferable for certain operators. INFORM’s approach reflects this rationale by supporting clients in evaluating which deployment model fits their needs best.