Rechenzentrum

What is a data center?

A data center encompasses all physical and technical facilities required to operate IT systems reliably: servers, storage systems, network infrastructure, power supply, and cooling. In intralogistics, it forms the foundation for all software-driven processes – from the Warehouse Management System to ERP and TMS through to automation solutions that control conveyor systems or autonomous vehicles. Without a stable IT infrastructure, not only office processes come to a standstill, but also physical material flows within the warehouse.

Operating models at a glance

There are three fundamental models:

• On-premises: The data center is operated in-house. You retain full control and full responsibility for hardware, maintenance, security, and capacity planning.
• Colocation: Your own hardware is housed in an external data center operated by a service provider. The vendor supplies the building, power, and cooling, while you remain responsible for the systems themselves.
• Cloud / Hosting: IT infrastructure is sourced entirely as a service – either as a private cloud, public cloud, or hybrid model. Capacities can be scaled flexibly; however, vendor dependency and data location are relevant decision factors.

Which model is the right fit depends on your own IT expertise, compliance requirements, budget, and availability requirements. There is no universally superior model – this is vendor- and context-dependent.

What matters when making a selection

The following aspects are particularly relevant for logistics operations:

• Availability and redundancy: Warehouse control, order picking, and transport scheduling run in real time. Downtime has an immediate impact on operations. SLAs should clearly define availability targets, recovery time objectives (RTO), and maximum tolerable data loss (RPO).
• Latency: Automation solutions such as conveyor system controls or AMR fleets sometimes place high demands on response times between the control system and the IT backend. On-premises or edge solutions may offer advantages here.
• Security and compliance: Data location, access protection, encryption, and backup concepts must be documented and audit-ready – particularly when customer data or customs-relevant information is processed.
• Scalability: Seasonal peaks, growth, or new locations require flexible capacities. Cloud models facilitate this, but bring ongoing cost dependencies.
• Exit scenarios: When changing the operating model or vendor, it must be clarified how data will be migrated and what dependencies exist.

The data center itself is infrastructure – it is not a substitute for applications such as WMS or TMS, which require their own operations, update, and support processes. This distinction must be consistently taken into account during planning and vendor management.