Why do most enterprises still archive mainframe SMF records in daily batches when the records are created continuously? VirtualZ Computing CTO Vince Re explains how real-time SMF archiving with PropelZ — VirtualZ's no-code tool for moving IBM Z mainframe data to the cloud — eliminates the data-loss window that batch processing leaves open, and unlocks capabilities batch simply can't deliver.

SMF (System Management Facilities) records are the mainframe's audit, security, and performance log. Batch SMF processing was designed for 1990s constraints — expensive bandwidth and local storage — and Vince Re makes the case that the same approach now creates operational risk: batch transfer failures, delayed audit access, and gaps an attacker or outage can fall into. Streaming SMF data continuously to the cloud closes that gap.

In this episode of Skyward Data, the podcast from VirtualZ Computing:

- How real-time SMF streaming removes batch transfer failures, delayed audit access, and recovery complexity - Capabilities batch can't match: continuous security monitoring, immediate compliance reporting, multi-cloud redundancy - Why cloud economics favor continuous streaming over large scheduled batch transfers - Tamper detection through immediate archiving, cross-platform incident correlation, and faster regulatory response - The shift from SMF archiving as a compliance checkbox to a real-time operational intelligence source

PropelZ writes mainframe SMF data directly to Amazon S3, Azure Blob, and Google Cloud Storage with no code and no homegrown pipelines, and is proven at 56,000 records per second, mainframe to cloud. It's part of VirtualZ Computing's no-code portfolio for enterprise mainframe data, alongside Lozen (live in-place data access), FlowZ (cloud storage for backup and archive), and Zaac (cloud and SAN as native z/OS storage).

Topics: mainframe SMF archiving, IBM Z, z/OS, real-time data streaming, mainframe security monitoring, compliance reporting, audit data, no-code data integration, hybrid cloud.

Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/