Skyward Data

By VirtualZBusiness Technology

Skyward Data episodes

October 20Built Today, for Today: Why Enterprises Are Choosing a New Standard for Data Sharing
Most enterprise data sharing tools were designed in the 1980s and 1990s, before TCP/IP was common and before the public cloud existed. In this episode of Skyward Data, Jeanne Glass, founder and CEO of VirtualZ Computing, explains why those tools can't keep up with today's demands, and why customers, outsourcers, systems integrators, and software providers are turning to PropelZ as the new standard for enterprise data sharing.
Every business unit wants data for analytics, reporting, cloud, and AI. Partners and service providers need data feeds to run the platforms the business just bought. Software providers are waiting on their customers' data to go live. With legacy managed file transfer, ETL, and CDC tools, every one of those feeds has to be designed, built, and maintained by hand, with hop after hop between systems.
Jeanne shares how VirtualZ co-founder and CTO Vince Re explains why the older tools struggle today. Vince is the original author of CA Top Secret, drove the vision behind most of what became Broadcom's mainframe portfolio, and was elected to the kernel.org team for his Linux-on-mainframe work.
In this episode:
Why data sharing tools from the 1980s and '90s don't scale to today's cloud, analytics, AI, and partner requirements

Design, build, maintain vs. install and run: what "built today, for today" means

How PropelZ, VirtualZ's patented enterprise data sharing technology, works: multiplatform (IBM Z, IBM i, Linux, UNIX, Windows, on premises or any cloud), any input to any output, one hop, filtering at the source, and no custom code

Why a Fortune 500 retailer, its systems integrator, and its outsourcer, who already owned every legacy tool, each tested PropelZ and chose it: transfers that took 12 to 14 hours finished in 2 to 4 hours

Sustained throughput of around 56,000 records per second, including 60.9 million records in 18 minutes

How Zafin, an AI banking platform provider, runs PropelZ on Linux to take in mainframe data from its bank customers

How Lozen, FlowZ, and Zaac bring the same built-today approach to data on IBM Z
Learn more and see customer and partner validation: https://virtualzcomputing.com/evidence-validation/
Schedule a briefing: https://calendly.com/jeanne-glass-virtualzcomputing
10 min
October 06 Give Cloud Apps Live Access to Mainframe VSAM Data — Without Copying It
Every plan to use mainframe data in the cloud starts the same way: "first, make a copy."
In this Skyward Data episode, VirtualZ Computing Founder & CEO Jeanne Glass and Co-Founder & CTO Vince Re — the original author of CA Top Secret — explain how to give cloud, distributed, and AI applications live, real-time read and write access to mainframe VSAM data without moving or copying it, using VirtualZ Lozen.
Why does every mainframe-to-cloud project reach for a copy first?
Because mainframe data is complex — VSAM, EBCDIC, mainframe-specific formats — so the reflex is to extract it, transform it, and replicate it to a data lake, warehouse, or database. But every copy is a duplicate to store, secure, and govern; a pipeline to build and maintain; and a source of drift from the live system of record.
Vince shares how one financial-services company spent two years trying to make a change-data-capture (CDC) model work in production before giving up. Lozen takes the copy out of the middle. The data never leaves z/OS. Applications running in AWS, Azure, Google Cloud, or any distributed environment read and write VSAM, QSAM, sequential files, PDS, and GDG data using standard file-system calls — the mainframe presented as a standard NFS network drive, with no proprietary API and no application rewrite.
Because there's only one copy of the data, you get real-time integrity on reads and writes: no stale data, no cross-platform locking, no reconciling updates back to the mainframe. Existing RACF, ACF2, and Top Secret security still governs every access — even from a remote cloud app — and the work is zIIP-eligible to contain MIPS.
Jeanne and Vince also cover a problem most teams miss: because mainframe data is shared data, moving one application off the mainframe usually forces you to move ten others that share its files. Lozen ends that — modernize one app and leave its data where it is. And they draw an honest line between live access and replication: use Lozen for real-time, file-system read/write access where the mainframe stays authoritative; use PropelZ (VirtualZ's no-code replication product) for SQL/relational access, tools like Tableau or Snowflake, or heavy AI query offload. Most large mainframe sites need both.
In this episode:
• Why "just make a copy" is the reflex for mainframe data — and what it really costs
• How Lozen gives cloud and distributed apps live read/write access to mainframe VSAM data with no movement
• Real-time data integrity for reads and writes, with no locking or reconciliation headaches
• How existing RACF/ACF2/Top Secret security is preserved and how Lozen is zIIP-eligible
• The shared-data problem: modernize one app without moving the ten that share its files
• Live access vs. replication — when to use Lozen and when to use PropelZ
If you're a mainframe architect, data platform leader, application modernization or migration lead, or an AI and analytics owner getting IBM Z data into the cloud, this conversation is for you.
See Lozen in action — including the AWS PartnerCast featuring Lozen with Rocket Enterprise Server and AWS services — and explore more at https://virtualzcomputing.com/lozen. Skyward Data is the podcast from
VirtualZ Computing — the first woman-founded, woman-led, and Native American-founded and -led mainframe software provider. VirtualZ's no-code, install-and-run portfolio (PropelZ, FlowZ, Lozen, and Zaac) connects IBM Z mainframe data to cloud, AI, and analytics without rewrites, pipelines, or forced migrations.
Learn more: https://virtualzcomputing.com
47 min
September 22 "Just Send Us the File": The Two-Sided Data Sharing Problem Between ISVs and Their Customers, and the One Engine That Solves Both
Why does "just send us the file" take six to eight weeks per extract when an enterprise shares data with its ISV, and what changes when PropelZ from VirtualZ Computing runs on both sides of the feed, whether the data lives on IBM Z, IBM i, Linux, Windows or in a SaaS tenant?
Every ISV runs on data its customers have to send it. Every enterprise sends its data to a long list of ISVs and service providers to get the service it already paid for. Both sides are waiting on the same file: a custom extract program somewhere in the customer's estate, and a one-off intake on the ISV's side that decodes a different layout from every customer. The enterprise isn't getting what it pays for. The ISV isn't delivering what it sold. Neither of them caused it.
In this episode of Skyward Data, the podcast from VirtualZ Computing, founder and CEO Jeanne Glass and co-founder and CTO Vince Re take the file out of the middle:
→ Why "just send us the file" is a two-sided problem nobody has owned, and what it costs: six-to-eight-week extracts, months of backlog, jobs that break when a field changes, and on the mainframe, metered MIPS that raise the licence cost of everything else running
→ Send side: one product replaces tens of hand-built extracts from any system; the layout you already have, a COBOL copybook or a database table definition, is the spec
→ Receive side: one engine decodes every customer's data inside the ISV platform, on any system with a Java environment, and the customer installs nothing
→ Who owns the metadata: the customer declares what it will send, or the ISV publishes what it needs, and PropelZ supports both
→ The hybrid model: the ISV runs PropelZ by default; the customer runs it on its own side to filter before sending and cut the ISV's processing by roughly half
→ On the mainframe: zIIP-eligible so it doesn't drive the MIPS bill, or run on Linux, Windows or Linux on IBM Z, with round trips back to VSAM when you need them
→ Incremental every ten minutes without turning on CDC or journaling, and inventories of thousands of files run in parallel
→ How a top-tier global bank asked its banking platform ISV to use PropelZ, and the ISV built it into its platform as a container with no mainframe in its estate
→ A proof of concept of close to 10,000 datasets: Friday to Monday on the incumbent tool, a couple of hours on PropelZ
PropelZ is VirtualZ Computing's patented, no-code data movement and decoding platform for IBM Z, IBM i, Linux, Windows, UNIX, VSE, VM and any Java-enabled environment. It reads VSAM, sequential, Db2, IMS, IDMS, copybook-described EBCDIC, database and delimited data in place, transforms it in flight, and delivers it in one hop to more than 100 JDBC targets and native connectors including Snowflake, Databricks, Splunk, Power BI, Vertex AI and SageMaker, at 56,000 records per second, mainframe to cloud.
Topics: ISV data sharing, enterprise data sharing, customer onboarding, data extraction, IBM Z, z/OS, zIIP, IBM i, Linux, COBOL copybook, VSAM, Db2, SaaS data, data integration, PropelZ, VirtualZ Computing
Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/
58 min
September 09PropelZ Multiplexer: Moving a Million Mainframe Data Sets from z/OS to the Cloud in Parallel
How do you move a million mainframe data sets from IBM z/OS to the cloud without a multi-year project? VirtualZ Computing Executive Chairman Marc Sokol and CTO Vince Re walk through the PropelZ Multiplexer — the component that turns a list of 100,000 or 1,000,000 files into a single, self-managing job.
Moving mainframe data isn't the hard part. PropelZ does that at 56,000 records per second, mainframe to cloud. The timeline balloons because someone has to account for every data set, submit every transfer, and verify every result. The Multiplexer takes that manual effort off the plate: hand it the inventory and a parallelism ceiling, and it schedules every PropelZ transfer, monitors resource utilization minute by minute, and floats the number of parallel tasks up and down to match what your system, network, and target can actually absorb.
In this episode of Skyward Data, the podcast from VirtualZ Computing:
Why a data movement project measured in data sets, not terabytes, quietly becomes a multi-month or multi-year effort

How the Multiplexer runs 100 PropelZ transfers in parallel and adapts the count in real time to zIIP utilization, available bandwidth, and target response — opening the throttle overnight and pulling it back during business hours

The customer result: 9,000 mixed disk, tape, and GDG data sets that ran from Friday night to Monday morning on a competitor's product finished in a couple of hours with the PropelZ Multiplexer

Why the 5% rule of thumb — a typical PropelZ operation uses about 5% of one zIIP engine — sets the ceiling and floor for how much parallelism your environment can sustain

How single-pass, direct z/OS-to-target movement on zIIP processors avoids the multi-tier gateway architectures where failures are hard to trace

How per-file status flows to a simple log and the operator console for integration with OPS/MVS, NetView, and other z/OS automation

Using the same technique to split one multi-terabyte table into a hundred parallel operations

Where this shows up: application modernization, virtual tape library relocation, daily partner data feeds, log files from dozens of LPARs, and feeding Databricks and Snowflake for AI and analytics
PropelZ is VirtualZ Computing's no-code tool for extracting and transforming IBM Z mainframe data to any target. It's part of a four-product portfolio alongside Lozen (real-time read-write access to live mainframe data without moving it), FlowZ (mainframe files to cloud object storage), and Zaac (cloud and SAN presented as native z/OS disk and tape).
Topics: PropelZ Multiplexer, mainframe data migration at scale, IBM Z, z/OS, parallel data movement, virtual tape library migration, GDG, VSAM, zIIP offload, mainframe to cloud, mainframe batch window, mainframe modernization, hybrid cloud data integration, Databricks, Snowflake, AI data pipelines.
Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/
36 min
August 25Why ETL and Change Data Capture Break at Mainframe Scale — and What Replaces Them
VirtualZ Computing Executive Chairman Marc Sokol and CTO Vince Re break down how a Fortune 500 retailer moved a 60-million-record VSAM file from z/OS to PostgreSQL in the cloud at a sustained 56,000 records per second — with no staging database, no change data capture, and zero lines of custom code. The same file on their previous solution ran for two days.
VSAM (Virtual Storage Access Method) is the mainframe's core file structure, and getting it into a relational database has traditionally meant one of three things: hand-built ETL scripts that break whenever a copybook changes, a change data capture deployment that demands VSAM logging and RLS, or a staged gateway architecture that reads and writes the same data four times. Vince Re explains why all three break down at enterprise scale — including one customer who spent two years on a CDC approach and never got it working.
In this episode of Skyward Data, the podcast from VirtualZ Computing:
The real benchmark environment — a mid-sized z/OS system, 4K+ record sizes, a shared 10 Gb link, and GCP-hosted PostgreSQL, using no more than 3–5% of available bandwidth

Why single-pass processing beats staged architectures that touch the data four times

How COBOL copybook metadata drives field-level transformation declaratively — packed decimal, binary, floating point, and EBCDIC into relational columns with no code

Why JDBC bulk operations, large batches, and deferred commits outperform per-record HTTP and web services approaches

What VSAM logging actually costs in I/O, journal storage, batch window, and deadlock risk

How the multiplexer processes thousands of files in parallel instead of serially

Running PropelZ on z/OS, on Linux, or anywhere with a Java environment

Licensing that is per platform — not per LPAR, not per MIPS, not by data volume
PropelZ is VirtualZ Computing's no-code tool for extracting and transforming IBM Z mainframe data to any target. It's part of a four-product portfolio alongside Lozen (real-time read-write access to live mainframe data without moving it), FlowZ (mainframe files to cloud object storage), and Zaac (cloud and SAN presented as native z/OS disk and tape).
Topics: VSAM to PostgreSQL migration, mainframe data migration, IBM Z, z/OS, change data capture alternatives, no-code ETL, COBOL copybook transformation, EBCDIC conversion, zIIP offload, VSAM to Db2, mainframe modernization, hybrid cloud data integration, AI data pipelines, Snowflake, Databricks.
Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/
1 hr 1 min
August 11 Building PropelZ: Customer-Driven Mainframe Integration
How does customer-driven development shape an enterprise mainframe data integration product? VirtualZ Computing CTO Vince Re explains how the most important features of PropelZ — VirtualZ's no-code tool for moving and replicating IBM Z mainframe data to the cloud — came directly from real enterprise customer problems rather than internal feature speculation.
Vince Re walks through specific origin stories: how a Microsoft Azure monitoring requirement led to the PropelZ Splunk connector, and how database teams' integration challenges drove automatic JDBC metadata discovery. The throughline is a development philosophy where each capability is built to solve a named customer's production problem first, then becomes a feature that serves an entire market.
In this episode of Skyward Data, the podcast from VirtualZ Computing:
- Why the PropelZ Splunk connector was built from Microsoft's Azure monitoring use case
- How database team challenges produced automatic JDBC metadata discovery
- Customer-first vs. feature-speculation product development, and the trade-offs of each
- Why production-tested integrations outperform theoretically designed features
- How solving one enterprise's mainframe data problem scales to a whole segment
PropelZ is 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). PropelZ is proven at 56,000 records per second, mainframe to cloud.
Topics: mainframe modernization, IBM Z, no-code data integration, ETL alternatives, Splunk integration, JDBC, customer-driven product development, hybrid cloud.
Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/
8 min
July 28 Real-Time SMF Archiving vs. Batch: Mainframe Audit Data
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/
12 min
July 07 Mainframe Cloud Backup with FlowZ: Cheaper, Faster, Off-Site
How cheap and how fast can mainframe-to-cloud backup actually be? VirtualZ Computing CTO Vince Re shows how VirtualZ backs up its own IBM Z mainframe — system backups, source code, and operational logs — by streaming them straight to cloud object storage with FlowZ, VirtualZ's no-code tool for using Amazon S3, Azure Blob, and Google Cloud as mainframe backup and archive storage, for pennies a month.
Vince Re explains exactly how it works: FlowZ makes cloud object storage look like a normal output target to z/OS, so the mainframe writes to the cloud as if it were a local device — with no custom code and nothing running on the cloud side. He also answers the objection everyone raises about cloud backup: isn't the network too slow? It isn't, and he walks through why.
In this episode of Skyward Data, the podcast from VirtualZ Computing:
- How cloud object storage becomes a native mainframe output target with no custom code
- Real numbers on volume backup speeds and compression, mainframe to cloud
- Why network bandwidth is not the bottleneck most teams assume it is
- How the approach scales from a small shop to a site moving terabytes a day
- Replacing fragile, expensive local tape and disk media with cheaper, off-site cloud backup
FlowZ is part of VirtualZ Computing's no-code portfolio for enterprise mainframe data, alongside PropelZ (moving and replicating mainframe data, proven at 56,000 records per second), Lozen (live in-place data access), and Zaac (cloud and SAN as native z/OS storage). For banks, insurers, retailers, and any enterprise running IBM Z, it's a practical path to durable, low-cost, off-site backup and tape replacement.
Topics: mainframe cloud backup, IBM Z, z/OS, cloud object storage, S3, Azure Blob, Google Cloud, tape replacement, mainframe archive, no-code data integration, hybrid cloud.
Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts
13 min
June 23 Multi-Cloud Mainframe Data with PropelZ: One Pipeline
Can you route the same mainframe dataset to AWS, Google Cloud, Azure, and IBM Cloud at once? VirtualZ Computing CTO Vince Re explains how PropelZ — VirtualZ's no-code tool for moving and replicating IBM Z mainframe data to the cloud — sends a single dataset to multiple cloud platforms simultaneously from one configuration, so enterprises use each provider's strengths instead of locking into one.
Vince Re makes the case for treating multi-cloud as a mainframe data strategy rather than a vendor decision: distributing the same z/OS data across providers for resilience, geographic compliance, and cost flexibility, without building and maintaining a separate integration for each cloud.
In this episode of Skyward Data, the podcast from VirtualZ Computing:
- How to route one mainframe dataset to AWS, Azure, Google Cloud, and IBM Cloud simultaneously from a single PropelZ configuration
- Geographic distribution that optimizes performance while meeting regional compliance requirements
- Cost optimization by matching workloads to the best pricing across providers
- Real applications: cross-continent disaster recovery and per-cloud analytics, such as Google Cloud for analytics, Azure for enterprise integration, and AWS for scale
- Moving from "choosing a cloud" to orchestrating several, without managing separate pipelines
PropelZ writes mainframe 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: multi-cloud mainframe strategy, IBM Z, z/OS, mainframe data replication, AWS, Azure, Google Cloud, IBM Cloud, disaster recovery, no-code data integration, hybrid cloud.
Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/
13 min
June 09 Mainframe Security in Splunk: PropelZ SMF & RACF Feeds
How do you get IBM Z mainframe security data into Splunk without custom development? VirtualZ Computing CTO Vince Re explains how the PropelZ Splunk connector — part of VirtualZ's no-code tool for moving mainframe data to the cloud — streams SMF records, RACF logs, and console messages directly into an existing Splunk SOC, so the system processing your most sensitive data is no longer a blind spot.
Vince Re walks through why most mainframe-to-Splunk integration relies on batch processing and custom work, and how PropelZ delivers real-time streaming into existing Splunk deployments with no custom development, no specialized configuration, and no mainframe-specific expertise required on the security team's side.
In this episode of Skyward Data, the podcast from VirtualZ Computing:
- Why real-time SMF, RACF, and console data beats the batch processing legacy connectors depend on
- Out-of-the-box Splunk integration: structured data formatting and unified timeline correlation with the rest of your SOC
- Threat-detection scenarios this enables: privilege escalation monitoring, lateral movement analysis, and data exfiltration alerts
- Applying behavioral analysis and anomaly detection to mainframe security data alongside distributed systems
- Why integration measured in weeks, not months, matters for security operations
SMF (System Management Facilities) is the mainframe's audit and activity log; RACF is IBM's z/OS access-control and security package. PropelZ feeds both into Splunk 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 security monitoring, Splunk integration, SMF, RACF, IBM Z, z/OS, SOC, SIEM, threat detection, real-time data streaming, no-code data integration, hybrid cloud.
Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/
14 min

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Conversations That Power Smarter Data Strategies for AI, Cloud, and Innovation. Skyward Data brings you exclusive conversations with experts shaping the future of enterprise data. Discover how organizations are transforming data access, storage, and AI integration to fuel faster innovation and smarter decisions.

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