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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.

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

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  • 20 episodes
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  • Avg 23 min
  • English

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  • Tuesday · 9 min

    Built 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

  • October 6 · 46 min

    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

  • September 22 · 57 min

    "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/

  • September 9 · 35 min

    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/

  • August 25 · 1 hr

    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/

  • August 11 · 7 min

    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/

  • July 28 · 11 min

    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/

  • July 7 · 12 min

    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

  • June 23 · 12 min

    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/

  • June 9 · 13 min

    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/

  • June 2 · 13 min

    The Mainframe Skills Gap: Closing It Without COBOL

    What is the mainframe skills gap, and how can enterprises close it without hiring more COBOL programmers? VirtualZ Computing CTO Vince Re tackles one of the most pressing problems in enterprise IT: the COBOL, JCL, and REXX experts who keep IBM Z mainframes running are retiring faster than they can be replaced, and few new engineers are trained on those technologies. The mainframes still process core banking, insurance, and government workloads — but the people who understand them are aging out. Vince Re argues the fix isn't finding more mainframe specialists. It's making deep mainframe expertise optional for the integration layer, so the cloud-native and DevOps engineers enterprises already employ can work with mainframe data directly — without learning COBOL or REXX. In this episode of Skyward Data, the podcast from VirtualZ Computing: - What the mainframe skills gap is, why it's accelerating, and what it costs enterprises that don't plan for it - Why hiring against a shrinking COBOL and REXX talent pool is a losing strategy - How cloud and DevOps teams can own mainframe data integration using skills they already have - The economics of leveraging abundant cloud-native talent instead of rare, expensive mainframe specialists - How to build a mainframe data strategy that scales with your existing team One practical answer is VirtualZ's no-code approach: PropelZ moves and replicates IBM Z mainframe data to the cloud — proven at 56,000 records per second — with no code and no homegrown pipelines, so teams integrate mainframe data without deep z/OS expertise. 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 skills gap, COBOL skills shortage, IBM Z, z/OS, mainframe modernization, DevOps, cloud-native, IT talent shortage, no-code data integration, hybrid cloud. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/

  • May 26 · 12 min

    App Store Economics for Mainframe Integration Software

    What if enterprise integration software were priced like a smartphone app store — pick the specific capabilities you need and skip the ones you don't? VirtualZ Computing CTO Vince Re explains how VirtualZ applies that model to mainframe integration, letting enterprises choose individual connectors and capabilities instead of buying a large suite and using a fraction of it. Vince Re contrasts the traditional "buy everything, use some of it" enterprise software model with a modular, app-store approach: granular selection, pay for what you use, and combine specialized components into exactly the integration you need. He explains why modular architecture also lets a vendor ship new capabilities faster than monolithic, all-in-one development. In this episode of Skyward Data, the podcast from VirtualZ Computing: - How app-store-style pricing changes enterprise software buying — paying for a handful of capabilities instead of dozens - Examples of modular components working together, such as the Splunk connector, the data-movement multiplexer, and cloud storage - Why modular architecture accelerates innovation compared with monolithic platforms - The advantages of granular selection: lower cost, faster implementation, and flexibility to change later - How customers assemble custom mainframe integration by combining specialized capabilities This modular philosophy runs through VirtualZ Computing's no-code portfolio for enterprise mainframe data: PropelZ (moving and replicating IBM Z data to the cloud, proven at 56,000 records per second), Lozen (live in-place data access), FlowZ (cloud storage for backup and archive), and Zaac (cloud and SAN as native z/OS storage) — four products you deploy and combine, with no code and no homegrown pipelines, rather than one suite you buy whole. Topics: enterprise software pricing, modular architecture, mainframe integration, IBM Z, z/OS, connectors, no-code data integration, software procurement, hybrid cloud. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/

  • May 19 · 11 min

    Unified Mainframe + Cloud Monitoring with PropelZ

    How do you monitor IBM Z mainframe and cloud infrastructure in one place instead of two separate systems? VirtualZ Computing CTO Vince Re explains how PropelZ's console logging connector streams mainframe console messages directly into modern monitoring tools, so operations teams see mainframe, Kubernetes, and cloud alerts in a single unified view rather than treating the mainframe as an isolated silo. Vince Re makes the case for unified operations: instead of choosing between mainframe expertise and cloud-native skills, teams combine them by feeding real-time mainframe console data into the dashboards and alerting tools they already run. The result is faster incident response across the whole environment, because mainframe events sit on the same timeline as everything else. In this episode of Skyward Data, the podcast from VirtualZ Computing: - How streaming mainframe console messages into existing tools creates one cross-platform view of mainframe, Kubernetes, and cloud alerts - Using monitoring stacks teams already know — such as Splunk and Prometheus — instead of mainframe-specific tooling - Why real-time mainframe visibility speeds incident response across hybrid infrastructure - Getting more from existing monitoring investments rather than standing up a separate mainframe system - Building operations that scale as the hybrid environment grows PropelZ streams mainframe console messages, SMF records, and other z/OS data into cloud and monitoring platforms 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 monitoring, hybrid cloud operations, IBM Z, z/OS, console messages, observability, Splunk, Prometheus, Kubernetes, incident response, no-code data integration. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/

  • May 12 · 7 min

    Skip the Copybooks: Automated DB2-to-Snowflake Migration

    Why does moving DB2 mainframe data to platforms like Snowflake still require weeks of manual COBOL copybook creation — and how can you skip that step entirely? VirtualZ Computing CTO Vince Re explains how PropelZ's automatic metadata discovery removes copybook work from database integration, so a DB2-to-Snowflake migration that used to take months can run in minutes. Vince Re breaks down why copybook creation has quietly slowed mainframe database projects for decades, and how self-describing databases change the equation: PropelZ reads the table's own metadata automatically, so you write a SQL query and run the move instead of hand-building copybooks first. That makes deep COBOL expertise optional for database data movement, not a prerequisite. In this episode of Skyward Data, the podcast from VirtualZ Computing: - How automatic metadata discovery replaces weeks of manual copybook engineering for database integration - Why "write a SQL query and run it" is the modern alternative to copybook-first workflows - A real DB2 table migration that went from complex to straightforward - Why manual metadata management is the biggest adoption barrier for mainframe database projects - How the approach scales from a single table migration to billion-row analytics workloads PropelZ moves and replicates IBM Z mainframe data — including DB2 — to cloud data warehouses like Snowflake, Databricks, Redshift, and BigQuery 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: DB2 migration, mainframe copybooks, metadata discovery, Snowflake, Databricks, IBM Z, z/OS, cloud data warehouse, SQL, no-code data integration, hybrid cloud. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/

  • May 5 · 11 min

    Migrating 200,000+ Mainframe Datasets with PropelZ

    How do you migrate 200,000+ mainframe datasets to the cloud when transferring them one at a time would take months? VirtualZ Computing CTO Vince Re explains how the PropelZ multiplexer turns massive mainframe data migrations from an operational nightmare into an automated, parallel process — moving hundreds of datasets at once instead of queuing them individually. Vince Re walks through inventory-driven migration: PropelZ takes a full inventory of the datasets to move, then runs them in parallel, cutting projects that would take months down to weeks. He explains why enterprises choose intelligent queue management over one-at-a-time transfers for virtual tape library migrations, application modernization, and large-scale cloud moves. In this episode of Skyward Data, the podcast from VirtualZ Computing: - Real performance: 100–200 parallel transfers processing thousands of datasets per hour - Comprehensive status tracking that turns black-box migrations into transparent, monitored processes - Integration with existing automation and help-desk systems - Uses beyond migration: compliance archiving, disaster recovery, and data center consolidation - Why parallel, inventory-driven processing scales where individual file transfers don't The multiplexer is built into PropelZ, VirtualZ's no-code tool for moving and replicating IBM Z mainframe data to the cloud — proven at 56,000 records per second, mainframe to cloud — with no code and no homegrown pipelines. 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). Topics: mainframe data migration, IBM Z, z/OS, virtual tape library, VTL migration, parallel data transfer, application modernization, disaster recovery, no-code data integration, hybrid cloud. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/

  • April 28 · 10 min

    PropelZ 2.0: What's New in Mainframe Data Integration

    What's new in PropelZ 2.0, and what does the release change for enterprise mainframe data integration? VirtualZ Computing CTO Vince Re walks through the major 2.0 release of PropelZ — VirtualZ's no-code tool for moving and replicating IBM Z mainframe data to the cloud — covering dozens of customer-requested features, including a 60% throughput improvement and native binary data handling. Vince Re explains how real customer problems drove the release: a retailer's binary data requirements, a financial services customer's billion-row processing needs, and a large mainframe outsourcer's enterprise connectivity demands. He shares the technical detail behind each enhancement and how it maps to integration problems enterprises face now. In this episode of Skyward Data, the podcast from VirtualZ Computing: - Custom input/output handlers with variable-length record support and binary data processing - Java method integration delivering a 60% throughput improvement for billion-row workloads - Enhanced incremental processing with minimal-change algorithms that optimize database updates - Software Bill of Materials (SBOM) support for security and supply-chain compliance - Databricks connectivity, SOCKS proxy support, and simplified configuration management PropelZ moves and replicates IBM Z mainframe data to cloud platforms and data warehouses like Snowflake, Databricks, Redshift, and BigQuery 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: PropelZ 2.0, mainframe data integration, IBM Z, z/OS, binary data, SBOM, Databricks, incremental processing, billion-row data, no-code data integration, hybrid cloud. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/

  • April 14 · 40 min

    PropelZ for Linux: Data Movement Beyond the Mainframe

    What happens when mainframe-grade data movement runs anywhere, not just on z/OS? VirtualZ Computing Co-Founder and CTO Vince Re joins Co-Founder Dustin Froyum to introduce PropelZ for Linux — the multi-platform extension of VirtualZ's no-code data movement engine — which takes the same engine proven on IBM Z and runs it anywhere Java runs. Vince Re walks through the architecture: why the core engine translates so cleanly across platforms, where the differences lie, and why they're smaller than you'd expect. He and Dustin also dig into the enterprise security capabilities that matter most — field-level filtering, data masking, SSL/TLS support, and sanitizing sensitive data before it ever reaches its target. In this episode of Skyward Data, the podcast from VirtualZ Computing: - PropelZ for Linux runs on Linux, Windows, macOS, IBM i, UNIX, and any Java-enabled environment - A 150–200% throughput improvement over existing ETL solutions, out of the box - 26,000 rows per second to cloud-based Postgres — multiple terabytes per hour - Zero-code, fully declarative setup — running in minutes to hours, not months - A cautionary tale: a financial services firm spent two years on a legacy ETL project, abandoned it, then ran PropelZ the next day - The Multiplexer: parallel processing that moves millions of files at once using full available bandwidth PropelZ moves and replicates data with no code and no homegrown pipelines, now across mainframe and distributed platforms alike. It's part of VirtualZ Computing's no-code portfolio for enterprise 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: PropelZ for Linux, ETL alternative, data integration, cloud migration, Postgres, multi-platform data movement, data masking, IBM Z, no-code data integration, hybrid cloud. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/

  • April 7 · 36 min

    460K VSAM Records in 25 Seconds: Rethinking VSAM → PostgreSQL at Enterprise Scale

    What really slows down IBM Z modernization? It's not the application code — it's the data. In this episode of Skyward Data, VirtualZ Co-Founder Dusty Froyum and Marc Sokol (Executive Chairman, former SVP at CA Technologies) break down what actually happens inside enterprise VSAM-to-PostgreSQL migrations, and why the data layer is the hardest part to get right. Drawing on decades in the mainframe world, Marc Sokol explains why so many migration programs stall at the data layer — data dependencies, stale datasets, and heavy ETL or CDC architectures turning a "simple migration" into a complex one. Dusty Froyum outlines how a no-code, direct-access approach simplifies the architecture, reduces operational complexity, and helps teams hit tight migration windows without over-engineering. In this episode of Skyward Data, the podcast from VirtualZ Computing: - Why data, not code, is what delays mainframe modernization - Real results: 460,000 VSAM records moved to PostgreSQL in 25 seconds - 60.9 million records delivered in 18 minutes — roughly 56,000 records per second sustained - The hidden complexity behind migrations that look simple at the outset - How to avoid overbuilt ETL and CDC architectures, and move data incrementally without disruption This direct-access, no-code approach is delivered by PropelZ, VirtualZ's tool for moving and replicating IBM Z mainframe data — including VSAM — to the cloud and to targets like PostgreSQL, with no code and no homegrown pipelines. 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). Topics: IBM Z modernization, VSAM, PostgreSQL, mainframe data migration, ETL alternative, CDC, no-code data integration, incremental data movement, z/OS, hybrid cloud. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/

  • March 31 · 51 min

    Modernizing Mainframe Data Access with Progress Software(56 characters.)

    Why does data access — not application code — stall so many enterprise modernization initiatives? In this episode of Skyward Data, the podcast from VirtualZ Computing, VirtualZ joins Progress Software to explore how organizations modernize data access across hybrid environments without disrupting the systems that run their business. Dennis Bennett, Principal Sales Engineer at Progress Software, joins VirtualZ Co-Founder and CTO Vince Re and VirtualZ Co-Founder Dustin Froyum to discuss how trusted enterprise connectivity and modern data movement work together to deliver secure, high-performance data integration. The conversation centers on transforming complex legacy data structures — including mainframe formats like VSAM — into modern, SQL-ready data that can power cloud databases, analytics platforms, and AI initiatives. In this episode of Skyward Data, the podcast from VirtualZ Computing: - Why data access has become the real bottleneck in enterprise modernization - How hybrid architectures support modern analytics without disrupting production systems - The role of high-performance enterprise connectivity in scalable data integration - How legacy mainframe data structures like VSAM are transformed into SQL-ready data - What secure, high-performance integration looks like across a hybrid IT environment On the VirtualZ side, this is powered by PropelZ, VirtualZ's no-code tool for moving and replicating IBM Z mainframe data — including VSAM — to cloud databases and analytics platforms, proven at 56,000 records per second, mainframe to cloud. 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). Topics: enterprise modernization, mainframe data access, VSAM, SQL, Progress Software, hybrid cloud, data integration, cloud databases, no-code data integration, IBM Z. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/

  • March 24 · 6 min

    The 2026 Framework for AI-Ready Enterprise Data

    Why do enterprises struggle to use their own data for AI — even when the data already exists? In this episode of Skyward Data, the podcast from VirtualZ Computing, VirtualZ CEO Jeanne Glass lays out a 2026 framework for activating enterprise data across mainframe and cloud, instantly and safely, so AI initiatives aren't starved of the data they need. Jeanne Glass argues that modernization is no longer a migration project, that integration alone isn't enough, and that the real bottleneck for enterprise AI is reaching mainframe and legacy data without disruption. She outlines how forward-thinking CIOs are building AI-ready hybrid data platforms that make existing data accessible rather than moving and re-platforming everything first. In this episode of Skyward Data, the podcast from VirtualZ Computing: - Why enterprises can't reach their own data — the real constraint on enterprise AI - Why modernization is no longer a one-time migration project - Why data integration on its own doesn't solve the access problem - How CIOs build AI-ready hybrid data platforms without disrupting production systems - What it takes to deliver mainframe and cloud data to AI pipelines safely This is the problem VirtualZ Computing's no-code portfolio is built to solve: PropelZ (moving and replicating IBM Z mainframe data to the cloud, proven at 56,000 records per second), Lozen (live in-place data access), FlowZ (cloud storage for backup and archive), and Zaac (cloud and SAN as native z/OS storage) — making enterprise mainframe data accessible to cloud, analytics, and AI with no code and no homegrown pipelines. Topics: enterprise AI, AI-ready data, mainframe modernization, hybrid data platform, data access, IBM Z, cloud migration, CIO strategy, no-code data integration, hybrid cloud. Listen to more Skyward Data episodes: https://virtualzcomputing.com/podcasts/

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