Skyward Data

VirtualZ

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. Each episode explores how to unlock the full power of your enterprise data—whether it lives on IBM Z, in the cloud, or deep in decades-old tape archives. We dive into real-world stories, bold ideas, and practical strategies for making mainframe and legacy data instantly accessible for AI, analytics, compliance, and modernization. If you're building smarter systems, training better models, or powering transformation with trusted data—Skyward Data is your guide. No fluff. No jargon. Just smart conversations about enterprise data, done right. Learn more at virtualzcomputing.com #AI #Mainframe #EnterpriseData #HybridCloud #DataAccess #SkywardData #VirtualZComputing

  1. Oct 6

    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

    Give Cloud Apps Live Access to Mainframe VSAM Data — Without Copying It
  2. Sep 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/

    "Just Send Us the File": The Two-Sided Data Sharing Problem Between ISVs and Their Customers, and the One Engine That Solves Both
  3. Sep 9

    PropelZ 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/

    PropelZ Multiplexer: Moving a Million Mainframe Data Sets from z/OS to the Cloud in Parallel
  4. Aug 25

    Why 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/

    Why ETL and Change Data Capture Break at Mainframe Scale — and What Replaces Them
  5. Aug 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/

    Building PropelZ: Customer-Driven Mainframe Integration
  6. Jul 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/

    Real-Time SMF Archiving vs. Batch: Mainframe Audit Data
  7. Jul 7

    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

    Mainframe Cloud Backup with FlowZ: Cheaper, Faster, Off-Site
  8. Jun 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/

    Multi-Cloud Mainframe Data with PropelZ: One Pipeline

Ratings & Reviews

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About

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. Each episode explores how to unlock the full power of your enterprise data—whether it lives on IBM Z, in the cloud, or deep in decades-old tape archives. We dive into real-world stories, bold ideas, and practical strategies for making mainframe and legacy data instantly accessible for AI, analytics, compliance, and modernization. If you're building smarter systems, training better models, or powering transformation with trusted data—Skyward Data is your guide. No fluff. No jargon. Just smart conversations about enterprise data, done right. Learn more at virtualzcomputing.com #AI #Mainframe #EnterpriseData #HybridCloud #DataAccess #SkywardData #VirtualZComputing