Glossary · Automation fundamentals, platforms and components
Scalability
German: Skalierbarkeit
In systems and software engineering, scalability is the ability of a system to handle growing workloads, such as more devices, data, users or production lines, by adding resources, without redesign and with acceptable performance.
- Automation components
In one sentence
Scalability is a system's ability to handle more devices, data or lines by adding resources, without redesign and with acceptable performance.
Example
The data platform was designed for one plant with 5,000 tags and was later extended to four plants and 80,000 tags by adding servers.
How it applies
- Engineering: Scalability is a Nonfunctional requirement. Controller families with compatible CPUs, modular I/O, networks with reserve bandwidth and data architectures that partition load all support it.
- Planning: Define the expected growth in numbers: devices, tags, update rates, users. Test against these numbers, since Latency and cycle times often degrade before a system actually fails.
- Documentation: System descriptions should state the tested limits (maximum number of nodes, tags or clients) and what happens beyond them. Marketing claims such as "fully scalable" need concrete, verifiable figures.
Scalability vs. scaling
Scalability is a system property: how well it grows. Scaling in automation usually means converting a raw signal to engineering units, a different concept with a similar name.