The Future of the Mainframe – Innovation Driver or Relic?

A mainframe computer, often referred to as “big iron”, is a powerful computing system used by large organizations for essential tasks such as mass data processing and enterprise resource planning. Although mainframes are smaller than supercomputers, they offer higher computing power compared to other computers classes.

If your data engineers are still manually kicking off jobs, chasing failed transfers, or writing custom scripts to keep pipelines running, you're spending engineering hours on problems automation already solved. Data pipeline automation is the use of scheduled or event-driven workflows to move, transform, and monitor data between systems without manual intervention. It's quickly becoming a baseline expectation rather than a competitive edge. In this article, we break down what data pipeline automation actually involves, which parts of the pipeline it covers, how to implement it step by step, and which platforms enterprise teams are evaluating in 2026.

Mainframe developers working in Visual Studio Code face a frustrating yet often overlooked problem. Once job logs are archived, they vanish from the development environment entirely, forcing teams to context-switch between tools to access the data they need. This article examines the hidden productivity cost of that gap. It introduces LogZ Explorer, a new Beta Systems add-on that bridges Visual Studio Code and Beta LogZ, providing direct access to archived mainframe logs within the developer's existing workspace and eliminating the need to switch environments altogether.